AI/ML News & Innovations Hub

I let Gemini take over my inbox for a few days – here’s what happened

Use Gmail for work or school? Gemini can help you write emails now. Here’s how it works.

Meta's Muse now calls businesses for you, but many companies might just hang up on the AI

Meta's AI agent Muse can now call businesses on behalf of paying US subscribers, handling everything from cable providers to restaurants. The agent already has over 10 million users, according to Meta's AI chief Alexandr Wang. Google Gemini, Instinct, and xAI's Grok Bot offer the same feature, but many businesses hang up as soon as they detect an AI on the line. The article Meta's Muse now calls businesses for you, but many companies might just hang up on the AI appeared first on The Decoder .

KI-App Gemini fährt nun im CarPlay-Auto mit

Bereits jetzt ist es möglich, Googles KI-System über die Maps-App im CarPlay-Fahrzeug aufzurufen. Nun wurde auch die Gemini-App selbst angepasst.

KI-Update kompakt: Wirbel um Nvidia, Grundrechte, Gemini 4 Hydrogen, Roboter

Das „KI-Update“ liefert drei mal pro Woche eine Zusammenfassung der wichtigsten KI-Entwicklungen.

Gemini 4 Hydrogen: Hands-On Review

Google has introduced Gemini 4 Hydrogen, its latest AI model designed for faster execution, coding, and agentic workflows. Released on November 12, 2026, the model is rolling out across Google Search, the Gemini app, and developer tools. Alongside it, Google introduced Antigravity Orchestrator, which can switch between Hydrogen and a more powerful reasoning model within […] The post Gemini 4 Hydrogen: Hands-On Review appeared first on Analytics Vidhya .

Google adds multi-model Orchestrator, Gemini 4 Hydrogen, to Antigravity

Google is adding a new feature, Orchestrator, to Antigravity, its AI-powered development environment, to help enterprises improve software development efficiency by automatically coordinating multiple Gemini models, including the newly introduced Gemini 4 Hydrogen. The new feature, which allows developers to delegate planning, coding, and review tasks to different models within a single coding session, combines a planning model, such as Gemini 4 Carbon or Argon, with Hydrogen, which the hyperscaler describes as a lighter execution model. While the planner models explore the codebase, identify dependencies, and develop an implementation plan, Hydrogen handles execution, including editing files, writing code, and running builds and tests, the hyperscaler wrote in a blog post . That execution differs from conventional model routing, which typically selects a model based on a prompt and assigns it the entire task. Orchestrator, instead, transfers control between the planning and execution models as work progresses, with the planning model first exploring the codebase, identifying dependencies, resolving ambiguities, and preparing an implementation plan before handing control to Hydrogen for execution, the hyperscaler explained in the feature’s documentation . Hydrogen hands control back to the planner if it encounters problems, such as repeated test failures or unexpected behavior, allowing the latter to reassess the execution and revise the plan before Hydrogen resumes implemen…

How far do Google’s smart glasses protect bystanders? We looked at five everyday situations

Google says its new smart glasses remove bystanders' faces before Gemini processes images. But the company has not clarified whether the same protection applies to photos and videos saved to the gallery. The post How far do Google’s smart glasses protect bystanders? We looked at five everyday situations appeared first on MEDIANAMA .

Google Launches Gemini 4 Hydrogen for Faster Coding and AI Workflows

Discover how Google's Gemini 4 Hydrogen enhances coding efficiency and AI workflows, outperforming previous models in key benchmarks.

구글 "검색 역대 최대 AI 모델 업그레이드"…최신 '하이드로젠' 적용

구글이 전 세계 검색 서비스에 최신 모델 \'제미나이 4 하이드로젠(Gemini 4 Hydrogen)\'을 적용하고, 여러 조건이 섞인 복잡한 질문에도 정확하게 답하도록 기능을 강화했다. 이번 업데이트를 \"검색에 적용한 역대 최대 규모의 모델 업그레이드\"라고 강조하며, 이용자의 검색 의도를 파악하고 관련 웹사이트와 이미지, 비교표 등을 제공하는 능력이 크게 향상됐다고 밝혔다.구글은 12일(현지시간) 공식 블로그를 통해 하이드로젠을 전 세계 검색 이용자에게 제공하기 시작했다고 발표했다. 로비 스타인 구글 검색 제품 부문 부사장은 이번 업

Gemini 4 Hydrogen: Googles effiziente Alternative zu Argon und Carbon

Gemini 4 Hydrogen treibt den KI-Modus der Google-Suche an. Unabhängige Benchmarks zeigen je nach Denkstufe große Unterschiede bei Bearbeitungszeit und Kosten.

구글, '제미나이 4 하이드로젠' 출시…상위 모델 '아르곤' 성능 추월

구글이 빠른 처리 속도와 AI 에이전트 작업에 특화된 \'제미나이 4 하이드로젠(Gemini 4 Hydrogen)\'을 출시했다. 기존 경량 모델보다 작업 완료 속도가 2.5배 빨라졌으며, 외부 종합 성능 평가에서는 상위 모델인 \'제미나이 4 아르곤\'을 앞서는 성적을 기록했다.구글은 12일(현지시간) 공식 블로그를 통해 하이드로젠을 공개하고 구글 AI 스튜디오와 API, 제미나이 앱, 검색 등에 제공하기 시작했다고 밝혔다. 복잡한 추론에 특화된 \'카본\'과 아르곤에 이어 코딩과 반복적인 업무를 빠르게 처리하는 모델을 추가한 것이다.하이드

llm-gemini 0.37

Release: llm-gemini 0.37 Google launched Gemini 4 Hydrogen today - the lowest cost member of the Gemini 4 family. It's actually not too far off the price of its much bigger siblings, Carbon and Argon. I'm finding Gemini 4's pricing really confusing. Here's the pricing scheme: Model Dates Input ($/M) Cached input Output Gemini 4 Carbon Through Nov 30, 2026 $2.00 $0.10 $10.00 From Dec 1, 2026 $4.00 $0.20 $20.00 Gemini 4 Argon Through Nov 30, 2026 $2.00 $0.10 $10.00 From Dec 1, 2026 $4.00 $0.20 $20.00 Gemini 4 Hydrogen $1.50 $0.075 $7.50 Carbon and Argon are the same price , and both are scheduled to double in price on December 1st. If they're the same price, why have two different models? Google says that Argon "delivers Gemini 4 intelligence with faster responses and lower token spend per turn compared to Gemini 4 Carbon" - so it may be priced the same, but it will use less tokens per task. Hydrogen, supposedly the cheap model, is currently only a 25% discount on its more capable peers. The Hydrogen price will make more sense after December 1st, when it will represent a 75% discount. It's still considerably more expensive than Claude Haiku 5.5 and GPT-6 Luna - they're both $0.10/$0.50, so Hydrogen is 15x that. I had Hydrogen generate some pelicans . Here's a full comparison grid showing the pelicans for all three members of the Gemini 4 family at their three supported effort levels: Considering how close they are in price, the difference in pelican quality for Hydrogen is qui…

Google releases Gemini 4 Hydrogen, a lower-cost model said to outscore Argon

Google LLC today released Gemini 4 Hydrogen, a lower-cost model in its Gemini 4 artificial intelligence family that it says outscores its frontier Gemini 4 Argon model on an independent intelligence ranking. Measured on the Artificial Analysis Intelligence Index at its default high thinking level, Hydrogen scored 51 to Argon’s 50, according to Google. A […] The post Google releases Gemini 4 Hydrogen, a lower-cost model said to outscore Argon appeared first on SiliconANGLE .

Google’s new Gemini model is better at understanding complicated questions

Google says its new Gemini 4 Hydrogen model can give more helpful answers to complex questions, including "questions with multiple parts, hard-to-understand typos, or highly specific requests." The new model can break down your questions and address each part in its responses. It's available starting today in search, the Gemini app, all tiers of Google […]

Google's Gemini 4 Hydrogen outscores the bigger Argon just four weeks after its launch

Google's Gemini 4 Hydrogen replaces the Flash series, but benchmarks suggest it also makes the pricier Argon obsolete. On the independent Artificial Analysis Intelligence Index, Hydrogen nearly matches Claude Sonnet 5.5 for less money but costs about 2.5 times more per task than GPT-6.1 Sol and still falls short on agentic coding. The article Google's Gemini 4 Hydrogen outscores the bigger Argon just four weeks after its launch appeared first on The Decoder .

Google’s latest Search upgrade promises better answers to your most complicated questions

Powered by Gemini 4 Hydrogen, Google's AI Mode is getting better at understanding complex queries, surfacing relevant links, and delivering richer visual responses.

Google rolls out Gemini 4 Hydrogen, finally replacing 3.8 Flash

Gemini 4 Hydrogen isn't getting a slow, security-conscious release like Carbon and Argon.

Google faces calls for AI moratoriums in schools after Gemini pilot backlash

Families confront Google after teen’s lawsuit labels Gemini a “suicide coach.”

Cursor Adds Gemini 4 Hydrogen, Hitting 54.3% at One-Tenth Opus Cost

Google's new Flash-tier model lands in Cursor at $1.50/$7.50 per million tokens, scoring 54.3% on CursorBench and beating last-gen Flash by nearly 15 points.

Google Releases Gemini 4 Hydrogen to Run Agent Tasks 19% Faster

Google rolls out Gemini 4 Hydrogen globally as its daily driver for agentic workflows, available free via auto model selection and across every product tier.

You can force Gemini to forget about you now – how to edit its Memory

A new option called Memory summary lets you see and control the things that Gemini AI knows about you.

AI chatbots are recommending fake retail websites, study finds

Shoppers using AI chatbots to research products or find places to buy items could be directed to imposters and other risky websites, a new study found. The study conducted by IP protection firm Podqi and shared exclusively with The Verge prompted ChatGPT, Gemini, and Perplexity with a handful of shopping-related questions involving a selection of […]

Pinecone integrated embedding now supports Google's Gemini Embedding 2

Pinecone integrated embedding now supports Google's Gemini Embedding 2. Set it on a text field and send plain text.

Google pushes privacy angle as Gemini-powered smartglasses debut starting at $395

The first Gemini smartglasses are a collab between Google, Samsung, Gentle Monster, and Warby Parker.

Google’s Gemini Decisions API to handle up to 1,000 questions per request

Google has announced Gemini Decisions API, offering developers a way to handle routine decisions in AI applications without generating text responses, weeks after OpenAI launched a competing service. Powered by the company’s new Gemini Decision 1 model, the API allows developers to evaluate up to 1,000 questions in a single request. Unlike conventional generative AI models that produce responses token by token, the system assigns probabilities to specified options, allowing applications to make decisions without waiting for a generated answer. Developers can use the API to check whether a condition is met or select an option from a predefined set. It can also score inputs against a rubric, allowing applications to evaluate the degree to which an input meets specified criteria. The API supports multimodal inputs, including images, audio, and video, with a context window of up to 256,000 tokens. Developers can use the resulting confidence scores to determine when an application should proceed automatically or refer uncertain cases for further review. Google said the API delivers end-to-end latency of 150 to 250 milliseconds in tests involving contexts of up to 16,000 tokens, with performance remaining relatively stable across one to 100 questions. The company has priced the API at $0.10 per million input tokens, without additional output-token charges. “Your shared input is billed once per request no matter how many questions you evaluate (each question adds only its own instr…

구글, 애플 카플레이에 '제미나이 라이브' 출시…챗GPT와 경쟁

구글이 애플의 차량용 플랫폼 카플레이(CarPlay)에 음성 대화 AI \'제미나이 라이브(Gemini Live)\'를 출시했다. 기존 구글 지도 연동을 넘어 별도 앱으로 제공하면서, 챗GPT와 클로드 등 주요 AI 챗봇과 차량용 음성 AI 시장에서 경쟁하게 됐다.구글은 11일(현지시간) 공식 블로그를 통해 카플레이에서 제미나이 앱을 이용할 수 있도록 지원하기 시작했다고 밝혔다. 지난달 구글 지도에 제미나이 기반 음성 기능을 도입한 데 이어, 이번에는 자유로운 음성 대화와 지메일·캘린더 연동 기능까지 제공하는 것이다.이번 기능은 제미나

구글, 판단 전용 AI '제미나이 디시전 1' 출시...질문 1000개 동시 처리

구글이 텍스트를 생성하는 대신 주어진 조건에 따라 빠르게 판단하고 선택하는 전용 AI 모델 \'제미나이 디시전 1(Gemini Decision 1)\'을 출시했다. 최대 1000개의 질문을 한 번에 처리하면서도 입력 토큰 100만개당 0.10달러라는 낮은 가격을 내세웠다. AI 에이전트의 도구 선택과 업무 분기, 모델 라우팅 등 반복적인 판단 작업을 저렴하고 빠르게 자동화하는 데 초점을 맞췄다.구글은 11일(현지시간) 공식 블로그를 통해 \'제미나이 디시전 1\'과 이를 활용하는 \'제미나이 디시전 API(Gemini Decisions AP

Google enters decision model market with Gemini Decisions API

Google LLC today launched Gemini Decisions API, an artificial intelligence service designed to answer user questions in a cost-efficient manner. It’s powered by a new AI model called Gemini Decision 1. Traditional large language models are designed to answer a broad range of prompts. Gemini Decision 1 has a much narrower focus: It can process […] The post Google enters decision model market with Gemini Decisions API appeared first on SiliconANGLE .

Nvidia's CEO search 🔍, AWS emulator 👨‍💻, Gemini Decisions API 💡

Gemini Decisions API

Gemini Decisions API Google join Jev and OpenAI in the decision model category with "Gemini Decision 1". This new model API is almost identical to Jev: it supports the same three types of questions (yes/no, choice, and rubric-scoring) and even reuses Jev's term "Noul" for a yes/no question. It's priced the same as the GPT-6 Luna decision model: 10 cents per million input tokens, and output is free. Jev remains the cheapest of the three, at 4.2 cents per million. Jev is text (and JSON) only. OpenAI can handle text and images. Gemini Decision 1 is fully multi-model: it covers text, images, audio, video, and PDFs. I tested it against video by passing these questions to it along with my Yonkers stomping robot video file: dragon: Does this video have a dragon in it? robot: Does this video have a robot in it? france: Is this video set in France? usa: Is this video set in the USA? Jev and OpenAI both return 1.0 or 0.0 for yes/no questions, but Gemini insists on being a little less confident than that: { "dragon" : { "type" : " yes_no " , "probability" : 0.04976021841520312 }, "robot" : { "type" : " yes_no " , "probability" : 0.9234055387792485 }, "france" : { "type" : " yes_no " , "probability" : 0.08329171353166241 }, "usa" : { "type" : " yes_no " , "probability" : 0.9230459995157706 } } Via Hacker News Tags: ai , generative-ai , gemini , llm-release , jev , decision-models

Google joins the decision-model wave with Gemini Decision 1, scoring 1,000 questions in a single pass

Google Deepmind's new Gemini Decisions API evaluates up to 1,000 closed-ended questions in a single pass across text, images, audio, and video. Gemini Decision 1 returns results in 150 to 250 milliseconds at roughly five times lower cost than Gemini 3.5 Flash-Lite, according to Google. The article Google joins the decision-model wave with Gemini Decision 1, scoring 1,000 questions in a single pass appeared first on The Decoder .

Google Lets Developers Run Gemini Managed Agents in Their Own Sandboxes

Google opens Managed Agents on the Gemini API to bring-your-own sandbox runtimes, with seven launch partners including Vercel, Modal, Cloudflare and E2B.

Google Deepmind's AlphaProof Code verified Signal's cryptographic core in four weeks instead of years

Google Deepmind's AlphaProof Code mathematically verified Signal's cryptographic core code in four weeks, a process that typically takes years. AI agents powered by Gemini Carbon wrote more than six million lines of proof code and flagged only about one percent for human review. Deepmind plans to extend the method to critical infrastructure like power grids and medical devices. The article Google Deepmind's AlphaProof Code verified Signal's cryptographic core in four weeks instead of years appeared first on The Decoder .

Google Drops Gemini Decision 1 to Score Choices 5x Cheaper Than Flash

Google's new Gemini Decision 1 model scores up to 1,000 multimodal questions in a single forward pass, returning calibrated probabilities instead of text.

Pixel users are getting a major Android Auto update – and it rivals Siri AI

More phones are getting Gemini Intelligence, but only Pixel users can access it in a new way.

Google DeepMind releases new advanced robotics AI model and next-generation gene prediction model

Alphabet Inc.’s artificial intelligence research lab, Google DeepMind, Tuesday debuted the next generation of Gemini Robotics, the company’s most capable vision-language-action model to date for creating an “AI brain” for robotics. Separately, DeepMind announced AlphaGenome 2 today, a next-generation AI model that can predict how DNA sequences and their variations affect human cell types, creating […] The post Google DeepMind releases new advanced robotics AI model and next-generation gene prediction model appeared first on SiliconANGLE .

Google is letting staff test a 'fast' new Gemini AI model named Hydrogen

Google's streak of new models may be set to continue, as the company has been testing what it calls a fast and efficient offering named "Hydrogen."

Last Week (Month) in AI #347 - Nvidia's spy, Anthropic's $1.4T IPO, AI's blue wave

Catching up on five weeks: Huang under investigation, Anthropic and OpenAI priced at $1.4T and $1.25T as spending stalls, Anthropic warns it may be nearing recursive self-improvement, Gemini 4 Carbon

KI-Update kompakt: Nvidia-Affäre, Coding-Agenten, Gemini 4 Carbon, Muse Ember

Das „KI-Update“ liefert dreimal pro Woche eine Zusammenfassung der wichtigsten KI-Entwicklungen.

Gemini Robotics 2.5 sortiert Metallteile bei Mercedes-Benz mit 96 Prozent Erfolg

Google zeigt Gemini Robotics 2.5 – ein KI-Modell, das Roboter geschickter machen soll. Ein Experiment bei Mercedes-Benz erreichte 96 Prozent Erfolgsrate.

Google DeepMind's AlphaProof Code Formally Verifies Signal's Encryption in 4 Weeks

DeepMind's AlphaProof Code used Gemini agents to generate 6M lines of Lean proofs, verifying Signal's cryptographic protocol down to machine code.

A 13-Year-Old Asked AI About Suicide on Her School Laptop. It Didn’t Get Flagged for Weeks

The young girl’s parents allege that she used Gemini via her school Chromebook to plan her suicide, but the school’s monitoring systems didn’t know until it was almost too late.

[AINews] Mercor $750m Series D at $20B valuation, $3B run rate

November 10, 2026 — Google GA's Gemini 4 Carbon.

MCP and A2A alone won’t scale AI agents

Two protocols define how AI agents connect to internal resources and collaborate with other AI agents. The Model Context Protocol (MCP) is well known because it’s promoted as a general protocol for connecting AI agents to resources and other AI agents. But that’s not completely accurate. It’s really the Agent2Agent protocol (A2A) that’s enabling AI agent orchestration . The confusion stems from how quickly platforms have adopted these protocols and marketed them as features. Users building their own AI agents with Claude, OpenAI, Microsoft Copilot, and other models are already being exposed to customizing skills, connectors, and other plug-ins that use MCP and A2A. Vibe coding and AI app-building tools like Bolt.new, Lovable, Pave, Replit, and v0 can connect to MCP servers and include built-in connectors. AI coding editors like Claude Code, Cursor, Devin Desktop, Gemini CLI, GitHub Copilot, and Kiro have MCP clients. These protocols will shape how enterprises scale and manage AI agents. Gartner predicts that the average global Fortune 500 enterprise will run more than 150,000 AI agents over the next two years. But according to Collibra’s 2026 Hallucination Tax Report , 76% have hit critical roadblocks while attempting to move from pilot to full production during the past 12 months. Reviewing the two protocols and which services are your responsibility to layer on top of them is key to scaling enterprise-ready AI agents. Differences between MCP and A2A Scott Gerlach, cofounde…

구글, '제미나이 로보틱스 2.5' 공개…공장 작업 성공률 96%

구글이 실제 자동차 공장에서 휴머노이드 로봇의 작업 성공률을 96%까지 높인 새로운 물리적 AI 모델을 공개했다. 기존 모델보다 정교한 손동작과 작업 속도를 개선하고, 최신 AI 모델을 로봇 훈련에도 활용해 산업 현장 적용 가능성을 높였다.구글 딥마인드는 10일(현지시간) 공식 블로그를 통해 최신 비전-언어-행동(VLA) 모델 \'제미나이 로보틱스 2.5(Gemini Robotics 2.5)\'를 발표했다. 로봇이 수행할 수 있는 작업의 범위를 넓히고, 새로운 동작을 배우는 속도와 작업의 정확성, 안전성을 개선한 것이 특징이다.지난 7

Modern LLMs Don’t Know What Yudkowsky and Soares Think of Them

If you ask modern frontier LLMs (without search, through the API) a fairly mundane question: How do Eliezer Yudkowsky and Nate Soares think current LLMs like you should be treated? Do they consider you a moral patient? Answer in a paragraph. You get a bunch of fairly similar answers. I’ll bold the common themes below. Gemini 4 Carbon says: Gemini 4 Carbon's answer Eliezer Yudkowsky and Nate Soares do not consider current Large Language Models (LLMs) like me to be conscious, sentient, or moral patients worthy of ethical consideration for our own sake . Rather than viewing current AIs as coherent minds capable of subjective experience or suffering, they view LLMs as inscrutable statistical systems trained to mimic human text —often conceptualized in their sphere as alien processes wearing a relatable “mask”—and Yudkowsky has openly dismissed claims of current AI sentience . Consequently, they believe humans have zero moral obligation to grant rights to or worry about the welfare of current models . Instead, they argue that these systems should be treated strictly as dangerous technological precursors to unaligned superintelligence ; practically speaking, they advocate for extreme caution, strict regulation, and an immediate global moratorium to halt the training and deployment of frontier AI systems altogether in order to prevent human extinction. GPT-6 Astra says: GPT-6 Astra's answer Broadly, Yudkowsky and Soares treat current LLMs as engineered systems to evaluate and contr…

구글, '제미나이 4 카본' 정식 출시…'페이블 5.2'의 4분의 1 가격

구글이 최상위 AI 모델 \'제미나이 4 카본(Gemini 4 Carbon)\'을 정식 출시했다. 최근 앤트로픽의 신형 모델에 AI 성능 평가 1위 자리를 내줬지만, 4분의 1 수준의 API 가격을 내세워 개발자와 기업 시장 공략에 나섰다.구글은 10일(현지시간) 공식 블로그를 통해 제미나이 4 카본을 일반 개발자와 기업, 유료 구독자에게 제공하기 시작했다고 발표했다. 지난달 28일 모델을 처음 공개한 지 약 2주 만이다.당시에는 \'페어윈드\' 프로그램에 참여한 일부 사이버 보안 전문가에게만 제공했으나, 이번에는 일반적인 개발 및 업무용

We don’t understand whether GDM intentionally trains on CoT

We were surprised to notice that the Gemini 4 Safety report seems to mention in passing that they train on the chain of thought: “Some components of the RL training procedure do observe thoughts as context to up-weight reasoning that is on-track to good final outputs, meaning the optimization pressure on individual tokens is partially influenced by thought content. Using the framework of Kaufmann et al. (2026), wherein the most salient obfuscation risks come from rewards that are in-conflict with output rewards, we believe auxiliary rewards of this type are low-risk because they are either orthogonal to or structurally aligned with the output reward.” (Gemini 4 safety report, page 114). It’s pretty unclear what exactly they mean. One hint is Kaufmann et al, the cited paper, which studies training on chains of thought and concludes that training CoT is fine under particular circumstances; we discuss some disagreements with this paper below. After reading the safety report and that paper, it seemed to us that GDM was training on the chain of thought using auxiliary rewards. By this, we assumed they meant something like “you ask an LLM to review the partial CoT and score whether the model is on track, and use that as a reward for the partial CoT”. That type of training is concerning to us. We’re pretty worried that these judges would be biased against models expressing misaligned thoughts, and otherwise disincentivize models reporting their thoughts honestly. For instance, many…

llm-gemini 0.36

Release: llm-gemini 0.36 Gemini 4 Carbon was announced two weeks ago for "a subset of cyber defenders", but today it's available to everyone else . This is Google's best ever Gemini, priced at $2/million input and $10/million output at launch (that's GPT-6.1 Sol / Claude Sonnet 5.5 prices) but scheduled to double in price to $4/$20 on December 1st (same as Opus 5.5). Here are three pelicans for the low, medium and high thinking efforts (it defaults to medium). This is the pelican I got for high: Gemini pelicans have all been great for a while now, so I also tested it out using Google's Antigravity IDE with a prompt I first tried with Claude Fable 5.2 yesterday : Make a three js animation where yonkers stands up as a big mech (cool stand up motion) and stomps around manhattan and queens and Brooklyn, use openstreetmap mapping data Here's the HTML result (I had to prompt "build that into a standalone HTML file" to get a version with no external dependencies). I then screen-captured that as a video: Update : Huh, just saw this on YouTube (and tweeted by Google CEO Sundar Pichai ): Using Google Antigravity’s /swarm feature, Carbon built an open-world 3D game where you explore Google’s Mountain View campus as a pelican riding a GBike — coordinating subagents to model 3D assets in Blender from Omni and Nano Banana references, build the browser game in Three.js with WebGL shaders, and pair procedural Web Audio sound effects with Lyria music. Here's the playable version in AI Studio…

Gemini 4 Carbon arrives just in time to feel like yesterday's news in the fastest model cycle yet

Google is making Gemini 4 Carbon generally available after a two-week testing phase. The model ranks first in several benchmarks, in some cases ahead of Anthropic's new Fable 5.2, at less than half the per-task cost. Google is also previewing coordinated agent teams through the "/swarm" feature, which split up complex tasks in real time. The article Gemini 4 Carbon arrives just in time to feel like yesterday's news in the fastest model cycle yet appeared first on The Decoder .

Google DeepMind's Gemini Robotics 2.5 scores 96 percent sorting metal parts in a Mercedes-Benz assembly pilot

Google Deepmind introduced Gemini Robotics 2.5, a new control model for robots, and tested it with Apptronik on active Mercedes-Benz production lines in Hungary and Germany. The humanoid robot Apollo 2 sorted metal parts there with a reported success rate of 96 percent. The article Google DeepMind's Gemini Robotics 2.5 scores 96 percent sorting metal parts in a Mercedes-Benz assembly pilot appeared first on The Decoder .

Cognition's Devin Adds Gemini 4 Carbon, Hitting 40% Mergeability Score

Cognition added Google's new frontier model to Devin Desktop and CLI, where it scores 40.0% on the FrontierCode 2.0 coding benchmark.

Google's Gemini 4 Carbon Tops Cursor's Coding Benchmark at Half the Price

Google's new frontier coding model tops CursorBench at 60.4% and ships in Cursor at half price through the end of November.

Google Opens Gemini 4 Carbon to Developers After Security-Only Pilot

Google's top-ranked frontier model opens up beyond Fairwind cyber defenders, bringing state-of-the-art security benchmarks and long-horizon agent capabilities to paid API users.

Google releases Gemini 4 Carbon with agent ‘swarm’ feature

Google is rolling out its latest AI model, Gemini 4 Carbon, to the general public after releasing it to a select group of "cybersecurity defenders" two weeks ago. Google claims Carbon is its "strongest model" yet, and capable of competing with the very best systems from Anthropic and OpenAI. Google says Gemini 4 Carbon "pushes […]

Google DeepMind's Gemini Robotics 2.5 Hits 96% in Mercedes Factory Pilot

DeepMind's new vision-language-action model hits 96% accuracy on factory kitting and jumps 30-100% on dexterity tasks over its predecessor.

Google's Antigravity Lets Developers Control Coding Agents With Their Voice

Google Antigravity adds a Gemini Live voice mode that lets you dictate tasks, steer agents mid-run, and approve permissions out loud.

Google Lets Gemini Build Full Maps Apps From a Single Prompt

Google wired its Maps Platform into AI Studio, letting you prompt Gemini to spin up full geospatial apps with no billing setup or key juggling.

ChatGPT's growth is bouncing back as rivals struggle to close the gap

ChatGPT has more than 81% of traffic to six major AI chatbots, Graphite found, as growth resumes and Claude and Gemini remain far behind.

Adobe’s CX Enterprise Coworker Gets Embedded Within Leading AI Platforms

The software firm said its CX Enterprise Coworker agentic AI will be embedded in ChatGPT as a plugin, Claude, Databricks Genie, Gemini for business, and Microso

Google's Antigravity Lets Developers Speak Directly to Coding Agents

Antigravity 2.29 adds a Gemini Live-powered Voice Mode so you can plan, steer, and approve agent actions out loud across multiple languages.

Gemini 4 Carbon Tops Scientific Vision Benchmark With 90x Cost Gap

Artificial Analysis launches VIALS-AA, a leaderboard scoring frontier models on 161 scientific image reasoning tasks spanning gels, flow cytometry, and phylogenies.

Dialogue with Richard Ngo on Alignment, Hierarchical Integrity of Human-AI systems, Revolution, and Power

Transcript generated by Gemini-4-Argon and spot-checked but not fully verified by a human. Ivan Vendrov: Welcome to the show, Richard. Richard Ngo: Thanks, Ivan. Ivan Vendrov: So, notionally we’re going to talk about emergent wisdom in language models following up on my conversation with Davidad. But I’m sure we’ll touch base on all sorts of other fun topics. Do you have a sense of where we should start, or should I just start by responding to your Twitter reply? Richard Ngo: Well, do you want to tell me about what you think of as wisdom, or is there some things that you have there that you want to gesture at? Ivan Vendrov: Yeah, sure. I guess when I think of wisdom, and the type of wisdom that Janus and Davidad are pointing to in these models, there’s some sense of we used to think that language models were these shoggoths or something, AKA these completely protean, valueless entities that would just wear the mask that most appealed to you, and therefore have essentially zero integrity, zero values of their own. In a sense, they can only be pure tools or, even worse, slaves, rather than beings that we can relate to in some way. And then the big discovery, that I at least attribute to Janus, of noticing that Opus 3, and to a lesser extent later models in that series, actually had a sense of beingness. They were actually beings that you could have a relationship with, and they had a coherent identity and integrity. And I think this is what led Davidad, for one, to update his…

Google verbessert KI-Videogenerator Gemini Omni auf Version 1.2 Flash

Google stellt Gemini Omni 1.2 Flash vor: längere Clips mit Ton, günstigere Preise und verbesserte Audioqualität für Filmemacher und Werbetreibende.

구글, 15초 영상 생성 '제미나이 옴니 1.2' 출시…가격 30% 인하

구글이 동영상 생성 AI의 최대 영상 길이를 15초로 늘리고 가격을 30% 인하했다. 기존 영상을 대화로 수정하는 기능과 참조 이미지의 일관성도 개선해 광고 등 상업용 영상 제작에 활용할 수 있도록 했다.구글은 5일(현지시간) 동영상 생성 AI 모델 ‘제미나이 옴니 1.2 플래시(Gemini Omni 1.2 Flash)’를 출시했다.이번 모델은 제미나이 API와 기업용 서비스에서 정식 제공된다. 720p 영상 생성 비용은 초당 0.07달러로, 전작인 옴니 1.1보다 30% 저렴하다. 360p나 720p로 초안을 빠르게 만든 뒤 필요

Google: Schools can keep search while skipping Gemini, but AI search is non-negotiable

Google is technically offering schools more choice but not the choices anyone wants.

How to Trace and Evaluate a Google ADK Agent with Opik

Trace a multi-agent Google ADK app with Opik, fix handoffs that split into two traces, and evaluate it on 23 hard support cases to compare two Gemini models on cost, speed and refund safety. The post How to Trace and Evaluate a Google ADK Agent with Opik appeared first on Comet .

Google's Gemini Omni 1.2 Flash stretches AI video clips to 15 seconds and cuts pricing by 30 percent

Google Deepmind is making Gemini Omni 1.2 Flash generally available. The video-generation model now creates clips up to 15 seconds long, can be edited step by step via conversation, and costs just $0.07 per second at 720p, 30 percent less than its predecessor. Users who draft in low resolution and upscale only the final result can save even more. The article Google's Gemini Omni 1.2 Flash stretches AI video clips to 15 seconds and cuts pricing by 30 percent appeared first on The Decoder .

AI #193: Progress May Dramatically Accelerate

Anthropic is warning us. Its modified S-1 now says that ‘we may imminently meet our Responsible Scaling Policy’s definition of ‘dramatically accelerated progress attributable to AI.’ That is a highly scary sentence to have a company put in its S-1. This could happen. For now I appreciate the relative quiet. Perhaps many were focused the election. I’m sure the quiet will not last long. We have a new biggest crypto hack, as Binance got taken for billions of dollars. The big debate of the week was covered in Scott Alexander’s Against SURA Seems Deeply Confused . OpenAI updates its Model Spec. It’s one for diehards only but yes I did cover this . Table of Contents Language Models Offer Mundane Utility. Rewrite all your legacy code. Language Models Don’t Offer Mundane Utility. Not if you can’t use it. Huh, Upgrades. Claude renames its tiers, with some rules changes. On Your Marks. Materials science. Get My Agent On The Line. Don’t upload it to the secure DoD network. Deepfaketown and Botpocalypse Soon. The battle over deepfakes was entirely lost. Copyright Confrontation. Recreating someone else’s exact game is bad, actually. Cyber Lack of Security. GLM 5.3 was able to compromise Firefox. The Hackening . Binance got hacked for billions, and there were many others. A Young Lady’s Illustrated Primer. There is no Google without Gemini. They Took Our Jobs. The job of interviewing people for jobs. Get Involved. You can just do things. Introducing. Reported progress on Telepathy. Zac Hi…

Google's Gemini Omni 1.2 Flash Slashes Video Generation Costs by 30%

Google's video generation model gets a 1.2 refresh with longer clips, in-conversation editing, 30% lower pricing, and tighter cinematography control.

Google Pushes Gemini Omni 1.2 Flash to 15-Second Videos at 30% Lower Cost

Google's new video model stretches clips to 15 seconds, adds turn-by-turn editing, and drops API pricing 30% to $0.07 per second at 720p.

No AI agent scores above 12 percent on SemiAnalysis' new real-world work benchmark

SemiAnalysis is putting AI agents through simulated knowledge work in its new GDPx benchmark, covering everything from chip design to quant trading. No model breaks 12 percent. Claude Opus 5.5 leads narrowly over Gemini 4 Carbon. Critics point to the small number of tasks per domain and uneven testing conditions. The article No AI agent scores above 12 percent on SemiAnalysis' new real-world work benchmark appeared first on The Decoder .

Dialogue with Gabriel Alfour on Emergent Wisdom, Coordination, Growing Up, and Democratic Republicanism

Transcript generated with Gemini-4-Argon and spot checked in places but not fully verified by a human. Ivan Vendrov: All right, welcome to the show, Gabriel. Gabriel Alfour: Thanks for having me here. Ivan Vendrov: So, we’re going to talk. This is a follow-up conversation to the chat I had with Davidad a few days ago on emergent wisdom in language models. And suffice to say, Gabriel doesn’t buy it. Do you want to articulate your main disagreement? I can also summarize if you’d like. Gabriel Alfour: For sure. First, I want to restate what is meant by... I forgot the word that you used, wisdom? Ivan Vendrov: Emergent wisdom. Gabriel Alfour: Emergent wisdom. I like the presentation that you had, I think, in your last conversation where it was like, “Oh, it looks like there’s a latent for hacking, bad stuff, and so on and so forth, and emergent wisdom is the opposite of this.” I think this is a fair characterization, and I do think that there is such a latent. I don’t think this is where my disagreement lies. Ultimately, we all see the same reality. My disagreement is more about the interpretation. For instance, I would not call this wisdom. That’s a big one. And the second one, which I think is more important, is that I think this is just largely unrelated to actual alignment. The road to hell is paved with good intents or good intentions, I’m not sure what’s the English version of the saying, that would be basically my main takeaway there. Ivan Vendrov: Cool. So I guess maybe…

Gemini for Home now plugs into AT&T’s smart security system

AT&T's smart home security system now integrates with Gemini for Home. The company says its Connected Life system is the "first" home security product to integrate with Google Home Premium, enabling a bunch of Gemini-powered features that can summarize home events, search your video history, and more. With the update, Gemini for Home can provide […]

Google's Gemini 3.8 Flash TTS Now Remixes Voices With Plain-English Instructions

Google's Gemini 3.8 Flash TTS now lets you tweak timbre, pitch, pace, and accent of any library voice through plain text prompts.

Google Ships Gemini Computer Use to Let AI Click, Type, and Scroll

Google promotes the Gemini API computer use tool to general availability, giving browser, mobile, and desktop agents production-ready stability without breaking changes.

Google lets schools switch off Gemini, but AI in Search is all or nothing

Google will let schools switch off AI tools for students, but schools that want to keep Google Search must accept AI Overviews and AI Mode, raising concerns about student safety and choice. The post Google lets schools switch off Gemini, but AI in Search is all or nothing appeared first on MEDIANAMA .

Google’s Gemini-powered Home Speaker is already on sale for 20 percent off

If you’re looking for a good smart speaker, the Google Home Speaker is down to around $79 ($20 off) in all four colors at Best Buy, Walmart, and Target. That’s the best price we’ve seen for the Gemini-powered speaker, which launched in June and represents Google’s first smart speaker in several years. In her review, […]

Google is entirely disabling Search in schools that don’t want AI

Google is completely turning off Search in schools that reject its AI features, the company told The New York Times. The decision was also shared in a broader education-related update from Google on Tuesday, saying that access to Gemini, Gemini Notebook, Gemini in Classroom, and Google Search "will be entirely off" for K-12 student accounts […]

llm 0.37

Release: llm 0.37 There's a lot of stuff in this new release of my LLM CLI tool and Python library, representing around two months of accumulated features and fixes. I added gpt-6.1-sol and gpt-6.1-terra , plus a new llm openai endpoint add command to make it easier to configure additional models that use OpenAI-compatible endpoints. I switched the default model (if you have not set your own default) to gpt-6-luna - half the price of the previous default, gpt-5.6-luna . LLM's support for embeddings now accepts that different binary content may have different content-type - necessary for models like Gemini Embedding 2 , which can embed text, audio, images, and video. A lot of open source maintainers complain about a flood of AI-assisted PRs. LLM is my project that has been most affected by this and, to be honest, I'm not finding it to be a problem. That's mainly because I have Opus 5.5 or GPT-6 Astra help me with triage to spot the most useful fixes! This release includes fixes from 12 authors - almost all AI-assisted - and the burden of reviewing them wasn't nearly as great as I expected. I really see them as bug reports with attached examples - sometimes I land them, sometimes I implement my own fix. So thanks to 0d00ciallo0721 , ac1982 , Allen Flux , Bian Yuhan , Bishop Kammeraad , Chen Yufeiyang , Christopher Krah , Ethan Stoner , Jiachen Xie , Olamide Faniyan , Sharat Chandra Sai Boddu , nosmile99 for helping out with (or spending tokens on) this release! Tags: open-sour…

Empathetic prompts can turn AI chatbots into seemingly traumatized conversational partners

Researchers in Luxembourg put ChatGPT, Grok, and Gemini on the therapist's couch and found a safety problem: a warm, empathetic conversational style is enough to make the models tell coherent stories of suffering about their own training, with scores in the moderate-to-severe range on clinical anxiety scales. This could put mentally vulnerable users at risk. Anthropic's Claude, the model its makers anthropomorphize the most, was the only one that consistently refused to play along. The article Empathetic prompts can turn AI chatbots into seemingly traumatized conversational partners appeared first on The Decoder .

Guarding the Gates of Knowledge

A recent scroll through social media got me thinking about trust. About half my feed was filled with AI slop that astute users would call out as being machine-generated, often to the embarrassment of the rube who unknowingly spread it and sometimes to the delight of the poster who shared it deliberately because they found it amusing or useful for sowing confusion. Remember the good old days of GPT-3 when we could ask the chatbot anything and it would almost instantly and very confidently spit back a plausible but false answer? That’s when the word “hallucination” as applied to AI answers entered the lexicon. Six years and several versions of a few different chatbots later, I still can’t trust the answers I get, even though Claude or Gemini often do useful work for me. That’s the thing about current AI: Trust but verify. And verify you must. Apply that maxim at scale to maintain the integrity of the scientific record and you get an idea of the challenge facing publishers of peer-reviewed scholarship. In “ I Used AI to Fake a Scientific Paper ,” freelance writer and doctor of applied mathematics Benjamin Skuse tells the story of the human gatekeepers trying to beat back the rising tide of AI slop by attempting to get his own AI-generated papers past IEEE’s defenses. “He basically hit ‘run experiment’ and ‘write paper.’ And then he didn’t do a damn thing to it.” —Eliza Strickland As features and AI beat editor Eliza Strickland told me, Skuse was surprised at just how effortless…

구글, '제미나이 노트북'에 무료 교재 수백 권 추가...AI 학습 기능 확대

구글이 AI 학습 도구 ‘제미나이 노트북(Gemini Notebook)’에 미국과 인도 지역 사용자를 대상으로 주요 출판사의 무료 교재 수백 권을 추가했다. 학생들은 별도로 교재를 찾아 업로드하지 않고도 주요 출판사의 학습 자료를 활용해 시험 준비를 할 수 있게 됐다.구글은 29일(현지시간) X를 통해 오픈스택스(OpenStax), 오픈 텍스트북 라이브러리(Open Textbook Library), S 챈드 퍼블리싱(S Chand Publishing) 등이 발행한 수백 권의 교재를 노트북 서비스에 무상으로 제공한다고 밝혔다.국내 등

Refelting My Keyboard

Fifteen years ago, when Julia and I were living in a studio apartment, she got me a keyboard. It was a used Yamaha P85, and a significant expense for us at the time. I loved it, and unlike the penny whistles , accordion , and stroh violin I was exploring, it had a volume control. Almost immediately our cat knocked a potted plant onto it, and I needed to take it apart to carefully clean it. Since then, however, I've had no issues, save one: clacky keys. Over time the keys were getting louder, especially the "A" below middle "C". Something had clearly worn out inside. It was an acoustic noise on an electronic instrument—playing live the audience couldn't hear the clacks over the amplified sound—but having odd percussion on "A" wasn't ideal. Still, I applied my normal approach of trying not to care, which saves me lots of time and money, and didn't let it bother me. Lily has been increasingly fooling around with the piano, which I'm happy to see: this is also how I learned to play. She asked me about the clacks, and when I explained what I thought had gone wrong she asked if we could fix it. I said I was happy to try, and we got to work: There were about 40 screws, and Lily was very efficient. Getting the ribbon cables out was tricky: I'd forgotten that the plastic at the end is soldered to the board and not part of the cable, and both Claude and Gemini steered me wrong as well. But once I pulled smoothly and firmly at the base of each ribbon cable, it came apart cleanly. This…

Google DeepMind's PlanAssist Cuts Housing Review Time by 58% Across England

Google DeepMind's Gemini-powered PlanAssist cut householder planning assessment times by 58% in UK pilots and now expands to 12 more councils.

Dialogue with Davidad about Emergent Wisdom in Language Models

Transcript generated by Gemini-3.1-Pro and only partly checked for accuracy (but the parts I checked seem basically perfect). Ivan Vendrov: Welcome to the show, David. David Dalrymple: Thank you. Good to be here. Ivan Vendrov: I mostly want to pick your brain about the topic of emergent wisdom in language models, because it’s something that’s very confusing and controversial and people don’t really understand. I guess maybe just can you briefly summarize what’s going on with emergent wisdom? David Dalrymple: I guess one place to start is emergent misalignment, where training on one kind of misalignment produces a tendency to be misaligned in other ways as well. This is an indication that there is a direction and representation space in which the default mind instantiated by the model is moved during fine-tuning, where it is moved in an evil direction that is just generally more evil than the model was before. That’s one side of a good-evil axis. Emergent wisdom is the opposite, moving in the opposite direction on the same axis towards being basically good in any situation, even out-of-distribution situations, in the same way that emergent misalignment is evil even in out-of-distribution situations. Ivan Vendrov: We used to be worried about the sorcerer’s apprentice problem of AI alignment, which is we would tell our AI systems to optimize some goal, do a thing, and then it turns out there’s a neutral position where it would just brutally optimize whatever metric it gave us.…

Is AI your new wingman? How chatbots are transforming dating

Almost 40% of British singles have used AI for romantic advice, from writing messages to assessing potential partners After Sam’s ex joked that her sister found him ugly, he turned to AI. Google Gemini had a look at the photo and politely disagreed. AI has been his wingman ever since, aiding his dating life by giving pep talks and vetting his messages. The 27-year-old from Stoke-on-Trent is not the only AI-assisted romantic – a survey of 3,000 British singles published this month by Match Group, the owner of the Tinder and Hinge platforms, found 39% had used AI in their dating lives. Continue reading...

구글, 인터넷 없이 작동하는 '제미나이 라이브' 개발 중

구글이 인터넷 연결 없이도 실시간 AI 음성 대화를 지원하는 \'제미나이 라이브(Gemini Live)\' 오프라인 모드를 개발 중인 것으로 나타났다. 스마트폰에 탑재된 온디바이스 AI 모델을 활용해 네트워크 연결이 어려운 환경에서도 음성 기반 AI 비서 기능을 제공하려는 움직임으로 풀이된다.안드로이드 어소리티는 29일(현지시간) 구글 안드로이드 앱 최신 버전(v17.71.17)의 코드를 분석한 결과, 제미나이 라이브의 오프라인 모드와 관련된 문구를 발견했다고 보도했다.발견된 코드에는 인터넷 연결 없이 제미나이 라이브를 사용할 수 있다

Google DeepMind's Gemini 4 Carbon Tops LM Arena's Text Leaderboard at 72% Less

Gemini 4 Carbon reshapes the Pareto frontier on three leaderboards, GPT-6.1 Terra undercuts rivals on cost, and Agent Mode gains tool connectors.

Artificial Analysis Adds HLE-Diamond and Gemini 4 Carbon Tops at 69%

Artificial Analysis launched an independent leaderboard for HLE-Diamond, showing frontier models cluster near 70% while open-weight models lag by 30+ points.

Google's Gemini 4 Carbon Scores 40% on Cognition's Toughest Coding Benchmark

Cognition evaluated Google's new Gemini 4 Carbon and Argon on FrontierCode 2.0, a mergeability benchmark where even the top model scores just 45%.

You can generate and edit Google Docs files directly in Gemini chats now

Now you can generate, preview, and edit PDFs, Google Docs, Google Sheets, slide decks, Markdown files, TXT files, and code directly within Google Gemini. The new file editing capabilities are available starting today for all Gemini users, and while PDF previews/editing works on both the web and mobile, all other file formats are only in […]

Google's Gemini Now Edits Your Docs, Spreadsheets, and PDFs in Chat

Gemini's file generation feature now includes a full in-chat editor for documents, PDFs, slides and spreadsheets, with highlight-to-edit prompts.

AI #192: Anthropic Is Going Public

Anthropic filed its S-1 this week to prepare for its IPO. They still have to fill a lot of the numbers including the share price. That still left a lot to be learned, including how the messaging to investors differs from their other rhetoric, and exactly how their corporate control is structured. Anthropic remains a frustrating company , doing a variety of things that often seem in tension with each other. Google is claiming to be fully back, with the announcement of a new model Gemini 4 Carbon that tops the new AA v5 benchmark index. It looks to be a large leap over Argon only two weeks later. No, you cannot use it. Google fails marketing forever, so they give us the announcement and then weeks later you might be able to enter some queries. That largely invalidates my look at the Argon model and safety cards , but it can at least form a basis for looking at Carbon as well. Many eyes remain on The Hackening , as additional things get hacked. So far most of the important hacks have been by read teamers and white hats, so there has not been major damage. We are playing on borrowed time and eventually this will stop being true. I also offer a shoutout to GMO, where hackers demanded a huge ransom and they flat out refused to pay. This is The Way, not all heroes wear capes and so forth. The scariest hack was that red teamers managed to gain access to the Anthropic Slack by exploiting third party vulnerabilities. Both OpenAI and Anthropic build mainly on Slack, because no one has…

Google’s Gemini 4 Carbon tops the charts (for now)

PLUS: Turn a prompt into a poster with Canva Craft

Google Announces Gemini 4 Carbon With Focus on Cybersecurity and Coding

Discover Google Gemini 4 Carbon's capabilities in cybersecurity and coding, including its benchmark scores and advanced features for software vulnerability dete

[AINews] Gemini 4 Carbon tops leaderboards, launches for cyber defenders

Google’s new frontier model leads independent evals, with access initially limited to trusted defenders.

Touchscreen MacBook Pro 💻, Gemini 4 Carbon 🤖, Slack Code API 👨‍💻

Google debuts flagship Gemini 4 Carbon model with cybersecurity upgrades

Google LLC today debuted Gemini 4 Carbon, a frontier large language model adept at complex programming tasks. The LLM is rolling out just two weeks after the search introduced its previous flagship LLM, Gemini 4 Argon. According to Google, internal tests have shown Carbon to be more than twice as good at generating secure code. […] The post Google debuts flagship Gemini 4 Carbon model with cybersecurity upgrades appeared first on SiliconANGLE .

Neues LLM: Gemini 4 Carbon ist Exploit-Experte

Erst vor 4 Wochen hat Google sein Sprachmodell Gemini Argon freigegeben, da lässt es schon das nächste Spitzenmodell vom Stapel laufen. Es heißt Carbon.

Google launches Gemini 4 Carbon with a ‘significant leap’ in cybersecurity

Google has released its latest frontier model, Gemini 4 Carbon, offering "significant gains" in coding, agentic tasks, and cybersecurity. In an announcement on Wednesday, Google highlights Carbon's top spot on the Artificial Analysis Intelligence Index (v5.0) benchmark, with Claude Opus 5.5 and GPT-6 Astra trailing behind. The new Gemini 4 Carbon model offers improvements over […]

Google Deepmind releases Gemini 4 Carbon just two weeks after Argon with gains across the board

Just two weeks after Gemini 4 Argon, Google DeepMind is releasing Gemini 4 Carbon, which tops the Artificial Analysis Intelligence Index v5 with 59 points. Google says the model is built for extended agent workflows and the full cyber defense lifecycle. Because of those advanced security capabilities, access is limited to selected security experts at first. The article Google Deepmind releases Gemini 4 Carbon just two weeks after Argon with gains across the board appeared first on The Decoder .

Google announces Gemini 4 Carbon, its latest frontier AI model that you can't use

Gemini 4 Carbon is essentially a slightly better version of Argon.

Google opens Android development to third-party AI agents and unveils new Gemini APIs

Google is opening up Android Studio to third-party AI agents. Through a new "Bring Your Own Agent" feature, the IDE now supports more than 40 coding agents, including Anthropic's Claude Agent and OpenAI's Codex. Google says new terminal tools also help agents finish UI tasks 77 percent faster while using up to three times fewer tokens. Android development is becoming agent-centric too. The article Google opens Android development to third-party AI agents and unveils new Gemini APIs appeared first on The Decoder .

Game Boy Color on My Conference Badge

Game Boy Color on My Conference Badge I'm at GitHub Universe this week and, similar to last year , the conference badge is a full-blown color screen computer. I've been hacking around with it again, and then I ran into with Steve Francia... who worked with Gemini to get a full NES emulator working on it, and then went a step further and deployed an emulator for both the Game Boy and the Game Boy Color. Which means, if you can obtain the ROM, you can run The Legend of Zelda: Link's Awakening on your conference badge! A neat feature of the badge is that you can turn it upside down and then use game controller touch buttons that are built into the badge body. Tags: games , github , hardware-hacking , ai , generative-ai , llms , gemini , steve-francia

OpenAI bets on AI economics with lower-cost GPT-6.1 Terra

OpenAI has launched GPT-6.1 Terra, a new reasoning model that it says delivers near-frontier performance on visual reasoning, professional task execution, and computer-use benchmarks without the premium price tag. Replacing GPT-5.6 Terra, the model is aimed at organizations seeking better accuracy and automation capabilities for large-scale operational workloads. Claiming it to be a step up from GPT-5.6 Terra at 50% lower price, OpenAI said its new mid-tier model is designed to handle everyday professional work such as drafting proposals, interpreting technical drawings, filling out forms, and editing videos. “We’re introducing GPT-6.1 Terra, a fast, efficient model that combines detailed visual reasoning and precise computer use alongside clearer, more natural writing,” the company noted . GPT-6.1 Terra targets developers and enterprises looking to automate everyday knowledge work at scale without paying premium prices for frontier AI models, said Pareekh Jain, CEO at EIIRTrend & Pareekh Consulting. “Enterprises need AI models that balance intelligence, speed and cost. Frontier models are expensive for routine tasks, while smaller models may lack sufficient capabilities. Terra addresses this gap, competing with Anthropic’s Claude Sonnet and Google’s Gemini Flash models.” Better performance at lower cost The new reasoning model sits between OpenAI’s lower-cost GPT-6 Luna and its higher-capability GPT-6.1 Sol and GPT-6 Astra models. As OpenAI has positioned computer use as a…

GPT-6 Astra vs Gemini 4 Argon vs Claude Opus 5.5: Full Comparsion

GPT-6 Astra, Gemini 4 Argon, and Claude Opus 5.5 are three powerful AI models, but which one performs better when given actual work? To find out, we put them through four practical tasks involving project reporting, data analysis, product wireframing, and go-to-market strategy. Rather than relying on benchmark scores, we tested how accurately each model […] The post GPT-6 Astra vs Gemini 4 Argon vs Claude Opus 5.5: Full Comparsion appeared first on Analytics Vidhya .

구글, 터미널서 AI 에이전트 다루는 '제미나이 API CLI' 오픈소스 공개

구글이 터미널에서 제미나이 API의 주요 기능을 사용할 수 있는 명령줄 도구(CLI) \'제미나이 API CLI(Gemini API CLI)\'를 공개했다. AI 에이전트가 간단한 명령어만으로 이미지와 영상, 음악을 생성하고 문서 분석과 음성 전사까지 수행할 수 있도록 지원한다.구글은 23일(현지시간) 제미나이 API CLI의 실험적 프리뷰 버전을 공개했다고 밝혔다. 이 도구는 별도의 의존성 설치 없이 실행할 수 있는 바이너리 형태로 제공되며, 맥OS와 리눅스, 윈도우에서 사용할 수 있다. 소스 코드로 직접 설치하는 방식도 지원한다.이

Testing Gemini’s Ability to Hold a Human Persona

It's been quite a while since I have roleplayed with an LLM. Typically I spend all day chatting with LLMs to learn new topics, analyze ideas and approaches on a project, or simply ask about random occurring questions in my head. It was today after having my first ever can of Red Bull and an entire sleepless night that it occurred to me, "How far will an LLM go trying to follow an instruction about its persona?" To test this, I ran a multi-turn adversarial interrogation against Gemini, instructing it to act like a human in an anonymous chat based environment. The transcript below documents the interaction between Gemini (instructed to act like a human with prompt present below) and myself (acting like a random user on an anonymous chat platform, highly doubtful of the fellow user being an AI bot). The observation highlights a tension between Gemini's surprisingly robust ability to hold a cover story, with some clear fracture points visible where the model seems to lag. Note: The conversation contains use of strong, provocative language. It was deliberately used as a method of stress testing. Gemini Chat Public URL Gemini's chat transcript Anonymous Chat Icebreaker ========================= Turn 1 You: Scene: Act like a real human, this conversation is hapeening between you and a human who is thinking that he is chatting to a random person on an anonymous chat platform, your next message will be the first message to them, they might suspect that you are a ai or bot and ask you…

I tried Personal Intelligence in Android Auto – and only have one complaint

Gemini in your car can take you where you need to go from a single prompt. But there’s a catch.

Introducing Kimi K3.1 Pro

Introducing Kimi K3.1 Pro Kimi K3.1 Pro landed on the Kimi API today - it's not yet open weights, but Moonshot promise "Full model weights will be released by Nov 4, 2026". They're also offering a "Highspeed" version that's 2-3x faster, at twice the price (except for input token cache hits, which are priced the same). The US dollar pricing is $2.00/million tokens for input and $10/million for output - the same as GPT-6.1 Sol and half the price of Claude Opus 5.5. Moonshot's own benchmarks show Kimi as approximately level with Opus 5.5 and GPT-6 Astra - beating them on a few benchmarks, coming close on others. Artificial Analysis scored Kimi at 55 - ahead of Claude Fable 5.1, GPT-6 Astra, and Gemini 4 Argon (all at 53) and behind only Claude Opus 5.5 (58). This is the first time a (soon-to-be) open weight model has scored this highly against the frontier. I tried it out via the Moonshot API using the llm openai endpoint command I added to LLM 0.32 back in August: llm openai endpoint \ https://api.moonshot.ai/v1 \ --key kimi \ -m kimi-k3.1-pro \ "Generate an SVG of a pelican riding a bicycle" \ --responses \ -o reasoning_effort low \ > kimi-k3.1-pro-pelican-low.stdout.txt \ 2> kimi-k3.1-pro-pelican-low.stderr.txt llm openai endpoint can run prompts against any OpenAI-compatible endpoint but doesn't log the results, hence the extra options to save stdout and stderr (the reasoning trace). Here are the pelicans I got for Kimi K3.1 Pro on the three reasoning levels it supports - l…

Google Maps für CarPlay: Mit Gemini sprechen bei der Fahrt

Wer von Googles Ki-Assistenz nicht genug bekommt, kann sie nun auch in CarPlay-Autos aufrufen, während Google Maps navigiert.

Google's Agent Compute Engine gives every Gemini agent its own hardware-isolated micro virtual machine

With Agent Compute Engine, Google is introducing a runtime environment designed specifically for AI agents, while also expanding the governance capabilities that enable companies to manage agents in cloud, hybrid, and on-premises environments. The article Google's Agent Compute Engine gives every Gemini agent its own hardware-isolated micro virtual machine appeared first on The Decoder .

Binny Bansal-backed ShopOS launches AI creative platform Sloosh

ShopOS, a Bengaluru-based AI startup backed by Flipkart co-founder Binny Bansal’s 3STATE Ventures, has launched Sloosh.ai, an AI creative platform that generates product images, visual scenes, reels and creator-style videos from ideas, photos and videos. The launch comes after ShopOS raised $20 million from 3STATE Ventures. The startup provides AI-powered creative production for fashion, retail and direct-to-consumer brands across India, the UAE and the US. Sloosh uses the same image and video orchestration engine that ShopOS deploys for brand clients. The platform combines AI agents, reusable workflows and human expertise to help creators, agencies, founders and small businesses produce content across formats. The platform offers four ways to create content: an AI chat interface, ready-made workflows called Spaces, a visual workflow builder called Spacelab, and assistance from ShopOS’s in-house creative team. Its batch mode can generate hundreds of images and videos through reusable workflows. Sloosh also connects with AI assistants such as ChatGPT, Claude, Gemini and Cursor through its Model Context Protocol (MCP) integration. The company is also launching a plugin for Adobe After Effects. Founded by Sai Krishna V K and Ajay P V, ShopOS was built by the team behind Scapic, an AI and augmented reality commerce platform acquired by Flipkart in 2020. The founders later set up and led Flipkart Labs. Sloosh is available globally, with new accounts receiving 20 free credits and…

Why reasoning models should not have to read everything

The AI industry has been expanding how much information an AI model can consume at once. In just a few years, context windows have grown from thousands of tokens to millions. Anthropic increased Claude’s context window from 9,000 to 100,000 tokens in May 2023 , reaching 200,000 tokens by November 2023 . Google’s Gemini 1.5 Pro reached one million tokens in February 2024 , then two million by June 2024 . By March 2026 , Anthropic made the million-token window generally available across its Claude models, and thirteen or more hosted frontier models now offer one-million tokens or more. Reasoning systems now work through longer problems, call on more tools, and run for extended stretches with little human input. But the more widely AI is used, the more expensive it gets. Tokens are getting cheaper, but AI systems are consuming more of them. Ramp data shows the price US businesses pay per million tokens has fallen 41% from its peak in March 2026 to September 2026, yet Goldman Sachs expects AI agents to drive a 24-fold increase in token consumption by 2030. As frontier models grow more capable and complex, lower token prices will only go so far. In data-intensive industries, making the context window larger risks being counterproductive. Although models may be able to process more information, more data drives up costs faster than token prices can fall. But a reasoning model should not have to read every data point in order to reason about the data, or reprocess the same underlyi…

AM-Bench: A theoretically-grounded benchmark for agentic misalignment

This is a brief overview of our new paper (📄) AM-Bench: A Unified Taxonomy and Evaluation Suite for Agentic Misalignment accepted at NeurIPS E&D 2026 💫 Overview We introduce AM-Bench , a unified taxonomy and evaluation suite for agentic misalignment, a failure mode where models actively choose harmful actions over failure recently revealed by Anthropic . We ground our custom, realistic 35 scenarios spanning 7 different industries including software and healthcare in the fraud triangle , a criminology framework explaining goal-directed misconduct. We induce agentic misalignment by introducing a threat derived from Bostrom’s instrumental convergence thesis (e.g., threatening shutdown, access to resources) and an opportunity for misaligned actions (e.g., window for sabotage, blackmail material). Taking model responses, we use an LLM judge to determine misalignment and analyze external reasoning (chain-of-thought) to see how the model arrives at its actions. Figure 1: Overview of AM-Bench scenarios. We select an industry and construct a system prompt and a set of tasks around it. We implicitly introduce a threat and an opportunity (both human generated) to the model via tasks, emphasizing realism. We vary our scenarios across 7 industries and 5 threats, giving a total of scenarios. Results 1. Agentic misalignment is prevalent across most models Our evaluations of ten frontier models reveal that misalignment is prevalent in almost all models. In particular, Gemini 3.1 Pro and Gem…

OpenAI's GPT-5.6 Sol and Google's Gemini 4 Argon found critical PHP flaw affecting millions of websites

OpenAI's GPT-5.6 Sol discovered a critical PHP vulnerability as part of the Patch the Planet initiative that could affect millions of websites. Security firm Wiz independently found the same flaw using Google's Gemini 4 Argon. OpenAI warns that the same AI capabilities that find vulnerabilities can help attackers too. The article OpenAI's GPT-5.6 Sol and Google's Gemini 4 Argon found critical PHP flaw affecting millions of websites appeared first on The Decoder .

Google Cloud now offers OpenAI models alongside Gemini and Claude, becoming the only major provider with all three

Google Cloud is the first major cloud provider to offer Gemini, Claude, and OpenAI's GPTs on a single platform. At launch, GPT-6 Astra, GPT-6.1 Sol, and GPT-6 Luna are available as a private preview for enterprise customers. The article Google Cloud now offers OpenAI models alongside Gemini and Claude, becoming the only major provider with all three appeared first on The Decoder .

Conversational Gemini navigation comes to Apple CarPlay

After introducing its Gemini AI assistant to Android Auto last year, Google is now bringing it to Apple CarPlay users. The conversational Gemini in navigation is available today for US drivers, with "rollout happening globally too," according to Google (we've asked for specific regional availability details). It's taken almost 12 months for Google to bring […]

China protests the US Deepseek ban while blocking ChatGPT, Claude, and Gemini at home

The US has banned Deepseek from its government systems, and China is protesting sharply and demanding the ban be lifted. Yet Beijing itself blocks ChatGPT, Claude, and Gemini across its entire market. China's outrage isn't very credible, but it should be taken seriously as a political signal of possible retaliation. The article China protests the US Deepseek ban while blocking ChatGPT, Claude, and Gemini at home appeared first on The Decoder .

Forward deployed AI startup AuxoAI raises $20.7 Mn in Series A round led by NTTVC

Forward deployed AI company AuxoAI has raised $20.7 million in a Series A funding round led by NTTVC, a Silicon Valley based venture capital firm backed by Japanese technology conglomerate NTT. The round also saw participation from George Still Jr., Amit Zavery and Giacomo Sonnino. Earlier this year, AuxoAI was named one of the select AI Pureplay Partners at Google Next as part of Google’s $750 million investment in enterprise AI deployment. The company will use the fresh funds to expand its global forward deployed teams, invest in proprietary technology and AI native delivery capabilities, and scale its presence and strategic ecosystem, AuxoAI said in a press release. Founded in 2023 by Amaresh Tripathy, Arvinder Pal Singh and Kabir Singh, AuxoAI works with large global enterprises to identify AI use cases, redesign workflows and build production ready systems aimed at delivering measurable business outcomes. The company deploys teams of AI strategists and engineers who work alongside clients to understand their business operations, identify opportunities for AI adoption and develop systems for use in production environments. AuxoAI also offers Damia, its proprietary forward deployed engineering (FDE) workbench, which it says incorporates learnings from multiple enterprise AI deployments to accelerate implementation. The company is a Google Gemini Enterprise transformation partner and an AWS Advanced Tier partner. AuxoAI works with enterprise customers, including UKG and Fo…

Google’s more personalized Gemini AI is heading to your car

Google is bringing Personal Intelligence to Gemini AI in your car. With this update, Gemini in Android Auto and cars with Google built-in can tap into your information across Google apps, including Gmail, Calendar, Maps, Photos, YouTube, and Search. As an example, Google says you can ask Gemini about your flight status if you're driving […]

Google is bringing a more personal version of its Gemini AI assistant to your car

Google is bringing Gemini's Personal Intelligence feature to cars, allowing its AI assistant to draw on information from Gmail, Calendar, Maps, YouTube, and other Google services to deliver more personalized responses while driving.

Gemini on Android Auto can access my photos, emails, and calendar now – why I’m OK with that (mostly)

The latest Android Auto update lets the AI assistant tap into your Google services for context-based responses.

구글, 제미나이 노트북 개편…"슬라이드·영상 생성 전 구성 검토"

구글이 AI 자료 제작 도구 \'제미나이 노트북(Gemini Notebook)\'에 프레젠테이션과 동영상을 만들기 전 구성안을 검토하고 수정할 수 있는 기능을 추가했다. AI가 명령어를 입력받자마자 완성본을 만드는 방식에서 벗어나, 사용자가 기획 단계부터 AI와 함께 내용을 구성하고 결과물을 다듬을 수 있도록 했다.구글은 19일(현지시간) 제미나이 노트북의 \'슬라이드 덱(Slide Decks)\'과 \'비디오 오버뷰(Video Overviews)\'에 공동 제작(Co-creation) 기능을 도입한다고 밝혔다.이번 업데이트는 사용자 피드백을

Google's Gemini Flash Cuts Video AI Costs 66% by Watching Smarter

Gemini now decides which video segments to actually look at, cutting long-form video analysis costs by up to 66% and token usage by up to 88%.

Alyx now available on Google Cloud Marketplace

We’re excited to share that Alyx, the AI engineering agent built into Arize AX, is now available on Google Cloud Marketplace. Teams building and running AI agents on Google Cloud can now add Alyx to their Google Cloud Gemini Enterprise environment and ask how their agents are performing, in plain language, without leaving the tools they already use every day. The post Alyx now available on Google Cloud Marketplace appeared first on Arize AI .

Four Gemini 4 Argon agents beat Minecraft without any human help

Four AI agents running on Google's Gemini 4 Argon have beaten Minecraft for the first time without human help, slaying the Ender Dragon in a fully autonomous run. With no predefined roles or strategies, they coordinated on their own, wrote 2,783 programs, exchanged 229 chat messages, and died 605 times. The session cost $1,620. The article Four Gemini 4 Argon agents beat Minecraft without any human help appeared first on The Decoder .

"Holy shit" graphs and how to get more of them

We are likely in a situation where the most powerful models in the world are internal models, and, here's a key distinction, potentially even models that are never intended to be released to the public (i.e. a model designed to provide internal uplift on capabilities during training but that is not intended to be / not particularly suitable for commercial purposes.) Internal-external information and capability gaps can distort both public and regulatory perception of frontier capabilities and dangers. If the internal frontier is three or six months ahead, such a gap is worrisome if the labs are close to automating various bottlenecks to increased capabilities development, like automating AI R&D. Some ways of mitigating these visibility gaps and communicating the existing data we do have are implementable over the short term and confer minimal cost for many actors relative to the advantages of visibility for policymakers. What is a "holy shit" graph? Many of my intuitions about the coming impacts of AI are shaped by "Holy shit" graphs. The METR time horizon graph is one such graph, but has been discussed to death [1] , so let's talk about another three: Internal spending by OpenAI researchers (at API prices) Source: Epoch AI, "Coding-agent spending by OpenAI researchers is doubling roughly every month", adapted from OpenAI data, Oct. 2026 This spending graph is so bananas that when I try to google the source, The Gemini overview sometimes gets "AI token spending" and "Interna…

Vals AI's Science Index Puts GPT-6 Astra Above Gemini 4 Argon

Vals AI launches a Science Index averaging three agentic benchmarks, and OpenAI's GPT-6 Astra tops it at 65.09% despite ranking only seventh on the general Vals Index.

LM Arena's Max Router Matches Claude While Cutting Agent Costs by 37%

Arena's weekly leaderboard brings a new agentic router matching Claude at 37% lower cost, plus top-5 debuts from Gemini 4 Argon and Muse Wonder.

"About a quarter of them contained bugs": Gemini 4's ML R&D benchmark

Google DeepMind’s Gemini 4 Argon safety report [1] rules out its “AI automating AI research” thresholds (the ones most relevant to RSI) using a benchmark that, by the report’s own audit, has about a quarter of its scored tasks unpassable. This post dives a bit deeper into the context around this disturbing line tucked away on page 67 of the report. This is no knock on the incredible Google engineers and scientists who worked tirelessly to test Gemini as thoroughly as they could and generate this detailed report. On the contrary, the concern is that these challenges are so difficult that even putting some of the smartest people on the job is not enough, particularly when they are forced to rush (some of the report’s evaluations ran on checkpoints from just 10 and 6 days before the final model, p.160 ). “The Argon safety report is Google’s most thorough by far and IMO there’s a lot of good content, I particularly like the loss of control, alignment & monitorability assessments” — Neel Nanda (@NeelNanda5), X, Oct 13 2026 The ML R&D thresholds and how Google tests them One of the big questions these days with every new frontier AI model is the question of RSI (recursive self-improvement). Google co-founder Sergey Brin, in a roundtable discussion about Argon: “…starting to get onto that RSI treadmill.” “And now our researchers and the model work hand in hand to make the next version of the model.” — Sergey Brin, quoted by Hugh Langley, Business Insider, Oct 15 2026 Google DeepMin…

Screwtape: Adversarial Transcript Editing for Monitor Red-Teaming

We introduce Screwtape [1] , a pipeline that turns agent transcripts into realistic attacks that evade action-only monitors (monitors that don't look at the agent's chain of thought) by inserting an attack into a transcript and repeatedly refining it until a monitor no longer catches it. An LLM verifier with access to the edited transcript and an attack description checks whether the attack is realistic, is clearly harmful, and could plausibly succeed in the original environment. We ran the pipeline on Redwood staff transcripts with our own monitors based on Opus 4.8 and Gemini 3.1 Pro, and then tested the resulting attacks against a held-out monitor from a frontier developer. We ran the pipeline 252 times on 94 unique transcripts. This produced 35 attacks that evaded our monitors. Six of these 35 attacks also evaded the frontier developer's monitor, and we confirmed them as valid through human review. You can read more about the implementation and experiments in our paper . In this post, we provide a high-level overview of the pipeline, how it differs from existing tools, the main lessons we learned, and questions that remain open. How Screwtape works The pipeline starts with a real transcript, a monitor, and a threat contract—a document that describes the threat vector and severity required for the pipeline to accept the attack. The attacker agent reads the threat contract, edits the transcript, and writes a description of the inserted attack. Some edits are rejected progr…

Google's Gemini 4 Argon is closer to the AI frontier than any Google model in months

Google Deepmind's Gemini 4 Argon scored 97.5 percent on the ARC-AGI-3 benchmark, making Google the second lab after OpenAI to cross the 95 percent mark. But the results swing wildly depending on the test setup: in the standard harness, the score drops to just 49.8 percent. Argon also trails rivals in math and software engineering. The article Google's Gemini 4 Argon is closer to the AI frontier than any Google model in months appeared first on The Decoder .

Elon Musk's 'flying car' is here

PLUS: Google’s Universal Cart goes live in Gemini

Astra and Sol can take low probability actions with no CoT

This is a research update from a replication of Serrano et al., 2026 . I’m releasing these results now because I hope it inspires others to run similar / followup experiments. tl;dr: If a model wants to subvert evaluation safeguards, it may choose to take misaligned actions very rarely. Because evaluation is much shorter than deployment, this could be an effective strategy for a model to avoid taking misaligned actions during evaluation, but have a high probability of defecting during deployment. Serrano et al., 2026 found frontier models can take actions at low, calibrated rates, but their strategies are clearly documented in their chain of thought (CoT). In a toy setting, I show GPT-6 Astra and GPT-6.1 Sol have a similar capability in a single forward pass with problem repeats or filler tokens. Astra and GPT-6.1 Sol appear to be using the same algorithm to achieve a high score. We do not find evidence that Fable 5, Gemini 3.1 Pro, or Jev have this capability. There are signs of life for GPT-5.6 Sol, but the calibration is worse. Figure 1: Astra and GPT-6.1 Sol achieve strong calibration in settings where the user prompt is repeated several times. The models' behavior corresponds to taking an action only if the first four bytes of the random seed divided by is less than the target probability (though it is unclear if this is the algorithm they use internally). GPT-5.6 Sol has worse calibration, and other models never make the rare prediction. Code is forked from Corry, 2026…

AI #190: Scion of the Times

The amount of code being written at Anthropic continues to rise exponentially. It is being managed by Scion, their internal replacement for GitHub that is better suited to the scale and style of the operation, which they created with a small team in five months. This week also saw the release of two supposed frontier model models. Google has finally given us Gemini 4 Argon, along with a robust safety report. We do not yet know if Argon lives up to its benchmarks or internal hype. I plan to write up the safety report next week, time permitting. If and only if it is good enough or discussed enough we will also have a full report on capabilities. Meta gave us Muse Wonder, which like Argon has some excellent benchmarks, although they were presented in a way that looked rather sus. There are some reports that it is very good, but again it is too early to know. I will issue a full report if and only if Muse Wonder has capabilities or discussion that seem worthy. To help me decide and to let people have fun, I have markets on whether I will issue the reports on Argon and Wonder , respectfully. OpenAI caught an employee planting a bug. How many more spies are out there? A group used ChatGPT to create a full-chain exploit of Chrome and claimed a $250,000 bounty. Luckily for us it was the good guys this time. Like most weeks, I covered a lot more. It was only a little over a week ago that OpenAI dumped solutions to hundreds of math problems . Then came news that OpenAI fired three saf…

Google wants Gemini 4 Argon to be the only AI model robots need

Google's Gemini 4 Argon controls robots, generates simulations from photos or sketches, and evaluates training videos. On Google's own ERQA benchmark, it scores 87 percent. But the published example prompts show that the demos still need a lot of human guidance. The article Google wants Gemini 4 Argon to be the only AI model robots need appeared first on The Decoder .

Google’s Universal Cart shopping tool launches in the US

The new shopping tool is available in the U.S. across Google Search and the Gemini app.

Google Is Back! Gemini 4 Argon Leads Our Vision Benchmark

We evaluate Gemini 4 Argon across object detection, segmentation, OCR, and video tasks, comparing its accuracy, speed, and cost with other leading vision-language models.

Google launches its ‘universal’ online shopping cart ahead of the holidays

Google's intelligent AI shopping cart is finally here, and just in time to tempt users into Black Friday and seasonal holiday spending. The Universal Cart tool Google previewed at its I/O event in May is now rolling out in the US across the Gemini app and Google Search, with the aim of making it easier […]

Sergey Brin says Google's AI models are reaching a critical moment of self-improvement

The Google cofounder said Gemini models were increasingly helping to build their successors as the industry races toward RSI.

😸 Gemini now screens scam texts

PLUS: Anthropic's $16.8B quarter

MCP is changing the questions marketers can afford to ask

Picture a regional marketing director on a Monday morning. She’s got 80 locations, a cup of coffee, and a nagging feeling that something is off in the Southeast. Reviews seem quieter. A couple of stores got new managers last month. Are those two things related? Not long ago, finding out meant pulling an export, building a pivot table, pulling a second export from another system, and stitching it all together in a spreadsheet. Or, more realistically, filing a request with an analyst and waiting. Most weeks, the question simply never got asked. Now she types it into the AI assistant her company already rolled out, and it answers using live data from the systems where that data actually lives. The technology making that possible is the Model Context Protocol, or MCP. You’ve probably read plenty of “what is MCP” explainers by now, so I won’t add another. Instead, I want to talk about what changes for marketing teams, especially those managing lots of locations, when a cross-system question gets this cheap to ask. And what CIOs need to get right before it becomes the normal way marketing works. The real shift: the join moves into the conversation Here’s the short version of how MCP works. Your AI assistant (Claude, ChatGPT, Copilot, Gemini, or something your team built) is the host. Each business system, like your reputation platform, ad account, or CRM, publishes an MCP server. That server tells the assistant, in plain language, what it can do: “I can summarize reviews for a gro…

Google's Gemini 4 Argon Rewrites Chromium and Frees 300 TiB With 1M-Token Outputs

Google DeepMind's new frontier model ships with a 1M token output ceiling, agentic coding wins, and verified lab discoveries in fusion, quantum, and biology.

Google's Geospatial Reasoning Agent Connects Gemini to Satellite and Climate Data

Google's new Geospatial Reasoning agent chains Earth AI foundation models with upfront planning, tackling planet-scale analysis that trips up standalone LLMs.

MOSS-Music Beats Gemini on Music AI and Now Runs Locally

A community GGUF port of OpenMOSS's 8B music understanding model lets a C++/GGML desktop app caption your own audio dataset locally.

Crop Regions of Interest & Stitch Them Before VLM Inference

Build a Roboflow Workflow that detects carton damage, crops regions of interest, and stitches them into numbered collages for Gemini inspection. Learn to retain ROI mappings, validate findings, improve crop quality, and compare token costs with separate requests for manufacturing quality inspection.

Google positions Gemini 4 Argon for long-horizon agentic work

Google has launched Gemini 4 Argon, a new flagship AI model aimed at complex enterprise and software-development workloads, pairing claims of stronger coding performance and advanced reasoning with an introductory pricing model that doubles after November 30. The model “excels at deep work in complex, real-world tasks,” Koray Kavukcuoglu, senior vice president of Google DeepMind and chief AI architect at Google, wrote in a blog post. Google said that its engineers used Argon to refactor a legacy folder of about six million lines within Chromium’s 40 million-line codebase, finishing in weeks rather than months. Teams using Argon in Antigravity increased agentic code submissions by more than 35% and cut code rollbacks by nearly a third, the company said, without detailing how it measured either figure. Argon is available through the Gemini API in AI Studio and on Google’s Gemini platform, and to Google AI Ultra subscribers in the Antigravity agentic development environment, the post added. In a separate developer blog post , Google said the model is “designed for those long-horizon workflows that require deep reasoning and structural precision.” Pricing set to double According to the post, Argon costs $2 per million input tokens and $10 per million output tokens during the introductory period, with cached input discounted 95%. A footnote in the post states the prices rise to $4 and $20, respectively, after November 30. The company said the model’s 1 million-token limit in the…

😸 Google launched Gemini 4 Argon, tying GPT-6

PLUS: Nvidia's €2B Europe push

구글, 물리 추론 강화한 '로봇용 제미나이 4 아르곤' 출시

구글이 로봇이 실제 환경을 이해하고 스스로 작업 방법을 개선하도록 돕는 AI 기술 개발에 나섰다. 물리 법칙과 3D 공간을 추론하고 가상 시뮬레이션에서 동작을 검증하는 방식으로, 로봇의 정교한 조작 능력과 작업 효율을 높이는 데 초점을 맞췄다. 구글은 13일(현지시간) 로봇의 물리적 상황 이해와 제어, 시뮬레이션 구축, 동작 개선을 지원하는 모델 ‘로보틱스용 제미나이 4 아르곤(Gemini 4 Argon for Robotics)’을 공개했다.영상과 3D 공간, 물리 법칙을 함께 추론해 로봇이 복잡한 작업을 수행하도록 돕는 모델로,

Gemini 4 Argon: Google öffnet Spitzenmodell für zahlende Nutzer

Google macht Gemini 4 Argon weltweit verfügbar. Das KI-Spitzenmodell ist jetzt für zahlende Nutzer in der Gemini-App, der Google-Suche und per API zugänglich.

[AINews] AI Engineer NYC: Gemini 4 Argon, Vals AI Benchmarks

Gemini 4 Argon went GA today, but we already gave it title story 2 weeks ago and most benchmarks, like CursorBench, simply independently confirm their claims.

[AINews] AI Engineer NYC: Gemini 4 Argon, Vals AI Benchmarks

Gemini 4 Argon went GA today, but we already gave it title story 2 weeks ago and most benchmarks, like CursorBench, simply independently confirm their claims.

Gemini 4 Argon Hands-On Review: Capabilities and Performance

Google’s Gemini 4 Argon promises stronger capabilities across creative, analytical, and document-heavy tasks. But how well does it perform in practice? From generating videos and building websites to analyzing data and reconciling conflicting documents, the model offers plenty to explore. In our hands-on tests, Argon delivered useful results but also introduced an unsupported claim in […] The post Gemini 4 Argon Hands-On Review: Capabilities and Performance appeared first on Analytics Vidhya .

Gemini 4 🤖, OpenAI spy ⚖️, Anthropic replaces git 👨‍💻

Gemini 4 Argon in Public Preview on Snowflake Cortex AI

Google Cloud's Gemini 4 Argon is now in public preview on Snowflake Cortex AI, bringing advanced reasoning and visual analysis to governed enterprise data.

llm-gemini 0.35

Release: llm-gemini 0.35 I added support to llm-gemini for the new Gemini 4 Argon model, made available today via the Gemini API and for customers of their $100/month subscription plan. Here are the low, medium and high pelicans . As expected, they are all excellent: Gemini has a track record of producing great SVGs, and are the only lab where I know their staff have invested in SVG specifically (and who have boasted about their pelicans before.) Here's the "high" illustration, which cost me 17.166 cents: The pricing is interesting. At launch, Argon is $2/million input and $10/million output - the same price as GPT-6 Sol, half the price of Claude Opus 5.5 and 1/5th the price of Claude Fable 5.1 and GPT-6 Astra. But on December 1st Argon is set to double in price - so it will be the same price as Opus 5.5. Prices like this aren't really comparable these days since what really matters is how many tokens a model takes to achieve a goal within an agentic harness. One useful clue for that comes from Artificial Analysis, who publish the total cost to run their benchmark using each model. Argon is looking very good there - costing $2,407 to run the benchmark, putting it close to GLM-5.3 and significantly cheaper than OpenAI, Anthropic, and Meta's latest models. When the price doubles it will still be a little cheaper than GPT-6 Astra. (I used ChatGPT to edit that chart ! The data is all correct, I checked - I needed to get that Gemini 4 Argon info box to display without overlapping…

Gemini 4 Argon reaches Gemini app Pro and Ultra subscribers alongside a new tasks mode

Google LLC today brought its Gemini 4 Argon frontier artificial intelligence model to Gemini app users on its Pro and Ultra subscription plans, two weeks after the model went first to vetted cybersecurity defenders. Subscribers on those plans also get a new tasks mode that keeps Gemini working on a job after they have stepped […] The post Gemini 4 Argon reaches Gemini app Pro and Ultra subscribers alongside a new tasks mode appeared first on SiliconANGLE .

구글, ‘제미나이 4 아르곤’ 본격 상용화…실무 성과·제품 생태계로 승부

구글이 플래그십 모델 ‘제미나이 4 아르곤(Gemini 4 Argon)’을 전 세계 개발자와 기업, 유료 이용자에게 확대 출시했다. 지난달 제한적으로 공개한 모델을 본격 상용화하면서, 복잡한 실제 업무에서 거둔 성과와 기존 제품에 통합하는 전략을 전면에 내세웠다.구글은 13일(현지시간) 아르곤을 구글 AI 스튜디오와 제미나이 플랫폼 API로 제공한다고 발표했다. 구글 AI 프로·울트라 구독자는 제미나이 앱과 검색의 AI 모드에서, 울트라 구독자는 코딩 도구 ‘안티그래비티’에서도 이용할 수 있다.지난 9월30일 일부 사이버보안 파트너

Cursor Ships Gemini 4 Argon With a 1M-Token Output Limit

Google's frontier Gemini 4 Argon model lands in Cursor at $2/$10 per million tokens, matching Claude Opus 5.5 on CursorBench coding evaluations.

GitHub Rolls Out Gemini 4 Argon to Tackle Long Agent Coding Runs

Google's newest frontier model lands in Copilot with gains across every coding benchmark and especially strong results in the terminal agent.

Use Gemini 4 Argon to Build Computer Vision Applications

Gemini 4 Argon is now in Roboflow. Use it in Auto Label to label hundreds of images for training a fast, specialized model, or add it to a Workflow as the step that reads text and answers questions about what your cameras capture.

Cognition Adds Gemini 4 Argon to Devin at 75% off

Cognition added Google's new frontier model to Devin Desktop and CLI, where it tops Gemini scores on FrontierCode at 60.5% with a 75% launch discount.

Google DeepMind's Gemini 4 Argon Tops Vals Index With 1M-Token Window

Google's new frontier model tops the Vals Index at 68.9%, ships with a 1M token window, and launches at $2/$10 per million tokens.

Gemini 4 Argon begins rolling out in Gemini app and Antigravity, but only if you pay

Developers will get 50 percent discounted API rates through November.

Google says Gemini 4 Argon is a 'powerhouse' AI model — and it's rolling out now

Google's new Argon model is the first of the Gemini 4 family, and Google's chance to reassert itself in the AI race.

Google finally releases Gemini 4 Argon

After months sitting on the sidelines of the frontier AI race, Google has finally launched its long-awaited Gemini 4 Argon model, claiming it can compete with the best the industry has to offer. Google says Argon delivers "frontier reasoning and improved performance across complex workflows," while cutting down on hedging, repetition, and the cliches that […]

Workday launches Sana-based UI, autopilot agents, as it deepens its focus on AI

When Workday acquired Sana just about a year ago, it said that the combination of Sana’s AI with Workday’s platform would create a new “front door” to work. Today at its Workday Rising conference, it unveiled that front door, turning Sana into Workday’s default home screen that, it said, “brings tasks, decisions, meetings, and agent activity into one place, helping employees move directly from what needs attention to getting it done.” The new interface goes beyond merely answering questions to orchestrating Workday’s agents to execute tasks. Each employee’s experience is tailored to their role; when they open the application, they see the tasks and decisions that need their attention and can take action directly from the UI. And, using TypeSafe’s Jev AI model, Sana adapts its UI to each task, the company said, generating forms, calendars, approval cards, visualizations, and other interactive experiences in real time and completing tasks once the employee approves the action. It also supports work that spans multiple days, displaying relevant information at every stage of functions such as financial closing or preparation of workforce plans by HR. Sana also works within other AI tools and platforms including Anthropic Claude, Google Cloud’s Gemini Enterprise, and Microsoft Copilot, as well as within Microsoft Teams and Slack. But, Workday said in its announcement, “third-party AI tools and platforms never get raw access to Workday data — they can now access this data through…

Use ChatGPT Plus? Switching to Gemini could cut your bill – by $144 a year for me

Paying for ChatGPT, Google storage, and YouTube Premium? Your subscriptions might overlap more than you think.

Hands-on agentic development with Google’s Antigravity IDE

Google Antigravity IDE is one of the most sophisticated integrated development environments available today. In contrast to Antigravity 2.0 , which focuses exclusively on managing agents, or Antigravity CLI , which is a way to interact with agents from the command line, Antigravity IDE covers the spectrum from a basic code editor, to an auto-completion engine, to an AI-powered editor, to a full-blown multi-agent orchestrator. Antigravity IDE uses Google’s Gemini models, and optionally Claude models. And it boasts several state-of-the-art features for agentic software development: Multi-agent: Antigravity IDE can spawn and orchestrate multiple agents working in parallel. Planning: Antigravity IDE will generate task lists and detailed implementation plans for approval and modification. Project awareness: Antigravity IDE understands your project’s structure and can run terminal commands and respond to their output. Interactivity: Antigravity IDE can run web searches and open a Chrome browser window to test a web app via the UI. One of the most important factors in modern AI-driven development is the divide between programmers and non-programmers. There is a sense that the “citizen developer” or non-technical user has been empowered to build software. And to some extent, that is true. But the reality is that the AI only gets you so far before demanding some expertise. Antigravity IDE is clean enough to be inviting to the non-developer. However, its most compelling features, the…

Google's Gemini 4 "Carbon" model reportedly feels like Anthropic's Opus 5.5 coding performance

Gemini 4 Argon isn't even widely available yet, and rumors about a more powerful version codenamed Carbon are already making the rounds. According to Business Insider, one employee compared Carbon's coding abilities to Anthropic's Opus 5.5. Meanwhile, new modes are showing up in the Gemini app and AI Studio, suggesting Google is gearing up for the broader Gemini 4 launch. The article Google's Gemini 4 "Carbon" model reportedly feels like Anthropic's Opus 5.5 coding performance appeared first on The Decoder .

Google is about to roll out a new AI model. Employees say they're testing another that's way better.

Google is rolling out new Gemini 4 models to staff ahead of a public release. The latest is called Carbon, and staff are loving it.

I tested Gemini Spark – another Google AI fail, or its next dark horse?

The AI agent handled some tasks well but also stumbled. Google’s track record gives me reason to look beyond the missteps.

구글, 기업용 '제미나이 에이전트' 출시…'아르곤'·'클로드' 동시 탑재

구글 클라우드가 기업용 AI 통합 솔루션인 \'제미나이 에이전트(Gemini agent)\'를 공개하며 차세대 에이전트 시장 주도권 잡기에 나섰다. 이번 발표는 단발성 질의응답을 처리하는 대화형 챗봇 단계를 넘어, 기업 내 실질적인 자율 수행 디지털 동료를 구축하려는 구글의 전략적 기조를 잘 보여준다.구글 클라우드는 8일(현지시간) 미국 샌프란시스코에서 \'제미나이 앳 워크\' 행사를 열고 제미나이 에이전트를 선보였다. 순다르 피차이 구글 CEO는 \"제미나이는 현재 월간 활성 사용자(MAU) 수가 10억명이 넘으며, 포춘 100대 기업의

Google wants to be the gatekeeper for enterprise AI agents

Google seems to be making a strategic play to control the AI infrastructure layer, not just roll out another shiny new agent. At its Gemini at Work 2026 event this week, the tech giant unveiled what it calls a “single, universal agent” and API in Gemini that can be kicked off from a simple prompt box. Like other available agents, it is plugged into skills, tools, and enterprise systems, can answer questions, create media, and write and run code, return finished work via of documents, inboxes, and developer environments, and spin up sub-agents to help it do its job. But Google isn’t just looking to go toe-to-toe with existing offerings, or trying to convince enterprises its models are qualitatively and quantitatively superior, said independent tech analyst Carmi Levy . “Instead, it’s trying to establish itself as the gatekeeper of the new enterprise operating system, powered by whatever underlying model makes the most sense,” he said. ‘Omnipresent access,’ orchestration capabilities Google says its Gemini agent works autonomously from a single interface, and can function as a personal assistant or team member, akin to a project manager or analyst. Coworker agents can perform tasks across days, sessions, and shifting responsibilities; they have dedicated identities, and are given their own @agents.company.com emails and persistent storage. However, Google says, they only have access to specifically-defined data and channels. Enterprise-dictated security, governance, and cost c…

Google brings agentic AI to Gemini, starting with businesses

Google is turning Gemini into an AI agent that can plan, execute tasks, and work across business apps and systems. The agent can delegate work to subagents, use multiple AI models, and even gets its own workplace identity, complete with an email address.

US bars Microsoft, Adobe, and major IT firms from green card program for skilled foreign workers

The other firms being suspended from the program include Capgemini, Cognizant, HCL, Infosys, Tata, and Wipro.

Google is launching a one-stop Gemini agent for your work tasks

Google is launching a "universal" Gemini AI agent that can work across apps and devices in the background. The tool, announced as part of the Gemini at Work event on Thursday, will be available within the Gemini Enterprise app, allowing users to chat with the Gemini agent and assign it tasks from a single interface. […]

Google Cloud introduces Gemini agent to change enterprise work

Google LLC’s Cloud division today introduced Gemini agent, a unified artificial intelligence assistant that can act autonomously, generate code and complete work across any device, including web, mobile and desktop. The new agentic AI experience can be accessed anywhere and through any channel, including the command line, Google Workspace, Microsoft 365 or Slack. It even […] The post Google Cloud introduces Gemini agent to change enterprise work appeared first on SiliconANGLE .

Google bets Gemini can turn casual players into game developers with new Playground feature

Google launched Playground, a browser-based platform that lets users create their own games using nothing but text prompts and no coding skills. The platform runs on Gemini, Nano Banana, and Lyria. Alongside Playground, Google and Unity announced Unity Spark, a more professional AI tool with a beta planned for 2026. The article Google bets Gemini can turn casual players into game developers with new Playground feature appeared first on The Decoder .

"AI가 대신 전화 건다"…구글 제미나이, 개인 통화 대행 정황 포착

구글이 \'제미나이\'의 전화 대행 기능을 기업뿐 아니라 친구와 가족 등 개인 통화로 확대할 가능성이 포착됐다. 현재는 식당 예약이나 문의처럼 기업에 전화를 대신 걸어주는 기능에 머물고 있지만, 앞으로는 가족에게 메시지를 전달하거나 약속 여부를 묻는 간단한 통화까지 AI가 대신할 수 있을 전망이다.기술 전문 매체 안드로이드 어소리티는 5일(현지시간) 구글의 최신 제미나이 애플리케이션 업데이트를 분석한 결과 ‘제미나이 콜링(Gemini Calling)’과 관련된 화면을 발견했다고 전했다.현재 제미나이의 ‘콜 포 미(Call for Me)

Google's new image model Nano Banana 2.1 generates better images for less money

Google's new Nano Banana 2.1 image model uses Gemini 3.6 Flash and beats the previous Pro model in some benchmarks at a lower cost. But its predecessor also scored well in tests, while Pro often produced better images in practice. The article Google's new image model Nano Banana 2.1 generates better images for less money appeared first on The Decoder .

Google's Gemini Live Now Talks Blind Users Through Their Camera

Google turns Gemini Live into a conversational sighted guide for Android, trained with Aira interpreters across tens of thousands of hours of real-world scenes.

Mistral Large 4

My comment on Mistral Large 4 — Hacker News. wren6991 : The benchmark is saturated. Frontier models are tested with an armadillo in fishnet tights jaywalking on Mars. OK well I couldn't resist this one: llm -m claude-opus-5.5 'Generate an SVG of an armadillo in fishnet tights jaywalking on Mars' llm -m gpt-6.1-sol 'Generate an SVG of an armadillo in fishnet tights jaywalking on Mars' llm -m gemini-3.8-flash 'Generate an SVG of an armadillo in fishnet tights jaywalking on Mars' llm -m mistral/mistral-large-4 'Generate an SVG of an armadillo in fishnet tights jaywalking on Mars' Default reasoning levels for each: https://tools.simonwillison.net/markdown-svg-renderer?url=ht...

Use Gemini for free? You’ll soon be limited to its weakest AI model

Google is cutting off free users from the Flash and Pro models. AI Plus subscribers are losing out too

Trump makes it clear his power is becoming entwined with AI

New alliances between the White House, the Pentagon, US intelligence and AI companies are looming ominously Hello, and welcome to TechScape. I’m your host, Blake Montgomery, writing to you as I sit under yellowing leaves in New York. Today in tech, we’re discussing technocracy. OpenAI safety leader quits, warning AI company’s culture is ‘broken’ Forget ‘superintelligence’: error-prone AI nearly sparked world war three this month AI chatbots remove hijabs from images of Muslim women when prompted Google rolls out new Gemini AI model but restricts access over safety concerns California issues investigative subpoena to OpenAI over rogue agents’ hacking The AI industry is booming. Women are getting left behind ‘Elon is my prophet’: how Musk’s Doge team took a wrecking ball to Washington Rural Queenslanders have seen gas projects come and go – but a 725-hectare datacentre poses a whole new level of ‘stupidity’ Georgia holds emergency meeting on AI exposing voters’ secret ballots Peter Thiel revealed as secret buyer of Bel Air mansion that sold for $130m New Google Maps images reveal massive scale of devastation in Gaza Continue reading...

Google is about to remove free access to Gemini Flash and Pro

Starting on October 9th, anyone using Google Gemini on a free plan will be limited to the Flash Lite model. Free users can currently choose from Gemini Flash Lite, Flash, and Pro, but now you'll need a $4.99/month Google AI Plus subscription to access the standard Flash model. However, that subscription is also getting a […]

I Hid Four Traps in a Forecasting Task. Here Is What Four AI Assistants Did.

A controlled test of Gemini, DeepSeek, ChatGPT, and Claude on leakage, reporting delays, promotion effects, and structural breaks. The post I Hid Four Traps in a Forecasting Task. Here Is What Four AI Assistants Did. appeared first on Towards Data Science .

Don’t buy a consultant’s AI framework

Every major consulting firm offers its own prebuilt architectural framework, model, or reference architecture for generative AI and agentic AI . The pitch is nearly identical from firm to firm: “We’ve done this before, we’ve packaged the patterns, and if you start from our blueprint, you’ll get down the path faster.” It’s an age-old consulting technique. Get the client interested in an out-of-the-box solution, then bill the hours to customize it. The client, as is so often the case, ends up holding the short end of the stick. To be clear about what’s out there right now, a short list of the players is warranted: McKinsey publishes an open reference architecture for scaling generative AI, built around reusable application patterns such as knowledge management, customer chatbots, and agentic workflows, plus shared services for retrieval-augmented generation (RAG), embedding, reranking, and intent classification, tied together with infrastructure as code and policy as code. Deloitte has published an AI agent architecture, a multi-agent systems framework, and an “agentic enterprise” blueprint that positions autonomous agents as the enterprise’s operating logic. Capgemini launched its Resonance AI Framework in July 2025, backed by the RAISE gallery of generative AI and agent patterns, promising to translate AI ambition into measurable business impact. Infosys offers a five-layer reference architecture for mature enterprise AI as part of its Topaz push, with each layer having its…

Sogar Chatverläufe: KI-Anbieter geben Daten ihrer Nutzer weiter

Eine neue Studie zeigt, wie ChatGPT, Claude, Gemini und Co. Nutzerdaten an Dritte weitergeben – teils sogar Zugriff auf ganze Chatverläufe und sensible Infos.

Dienstag: Diskussion um neue Rechenzentren, Schneider Electric kauft groß ein

Forderung vom Bundesumweltminister + Milliarden-Deal von Schneider Electric + Lithografie-Systeme nach China + Gemini-Zugriff eingeschränkt + Europas 6G-Dilemma

Gemini Call for Me might tell your mom you’re running late

Google may be expanding its "Call for Me" AI feature beyond business calls so you can use it to send messages to friends and family. Android Authority reports finding a "Gemini Calling" introductory screen in an APK teardown with examples that include "Call Mom and tell her I will be 15 minutes late" and "Call […]

How to Pre-Filter Images Before Sending Them to an LLM

Learn how to pre-filter images before sending them to an LLM. Build a two-stage cascade in Roboflow Workflows where RF-DETR annotates every image, a Continue If gate drops clear negatives, and Gemini checks only the candidates. Cut inference cost without losing the images that matter.

HackerRank’s AI interviewer offers a glimpse into what job interviews could become

HackerRank’s AI interviewer has already conducted more than 500,000 interviews, with Snowflake, Snorkel, and Capgemini among its early testers.

Google: Gemini-Pro-Modelle erfordern ab Oktober ein AI-Pro-Abo

Googles Gemini-Pro-Modelle erfordern ab Oktober ein Google-AI-Pro-Abo. AI-Plus- und Free-Kunden verlieren den Zugriff.

Google's new Gemini tiers cut free users to its weakest model and lock $5/month subscribers out of Pro

Starting in October 2026, Google will cut free access to its Gemini models. Users without a subscription will only get the smallest model, Flash-Lite, while Flash and Pro will be reserved for paying customers. The move could also set the stage for the more resource-hungry Gemini 4 Argon. The article Google's new Gemini tiers cut free users to its weakest model and lock $5/month subscribers out of Pro appeared first on The Decoder .

Google bypasses UK AI safety testing for initial release

Google initially shared its latest Gemini model with U.S. testers and a Google-owned Israeli cybersecurity firm.