AI/ML news, top picks, and generated innovation digests.
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Enterprise investment in AI is booming. Gartner is calling 2026 an “inflection year” for organizations to align their AI projects with strategic business objectives. As the pressure to prove ROI mounts, executives and technology leaders are looking to agentic AI to drive the measurable financial outcomes their businesses seek. A prime opportunity for AI agents…
tl;dr: As recursive self-improvement accelerates, we need a top-level agenda to research how to effectively keep humans in the loop. We need to study how humans can best interpret and guide research performed by autonomous agents when those agents lack taste, tacit knowledge or competence, or may try to reward hack, sandbag or sabotage such research. This is one attempt to define the problem and the shape of potential solutions. A Story About the Future of Research Imagine yourself a year or two in the future. Recursive self-improvement (RSI) is accelerating. Agents work in swarms independently for days or weeks at a time doing research. You work in a frontier lab doing AI safety research. You sit in front of your computer and click into the input box, ready to kick off a new project. What do you type? “Solve AI alignment”? Beware giving a magic genie vague wishes. Think about that again: what exactly do you type? How do you know what you type is the best way to prompt this agent swarm into doing your bidding? When the lead agent comes back a week later, what exactly does that output look like? How do you use that output to launch the next phase of the project? How will you validate that output to ensure the agent hasn’t reward hacked, sabotaged or incompetently explored the research space? How will you know what key decisions the agent made? Which research paths they explored? Which research paths they intentionally or unintentionally left unexplored? How will you know how…
Women who were vaccinated against covid-19 in the luteal phase of their menstrual cycle reported having a breakthrough infection sooner than those vaccinated during their follicular phase
As Europe accelerates its green transition, the debate over air conditioning has become emblematic of a broader challenge. Climate policy is no longer judged solely by its environmental ambitions, but also by whether it can reduce emissions without deepening social inequalities.
Die Deutschland-App soll Anträge stark vereinfachen – per Chat, Formular oder KI-Avatar. Zum technischen Konzept und KI-Risiken haben wir nachgehakt.
For the zero-truncated Negative Binomial specification often used in count regression-- e.g., Ch.8 in this book --I seem unable to find published results to verify the derivatives of the log-likelihood with respect to the so-called dispersion parameter, or its reciprocal (which I find more tractable). Below I provide some context and my best stab at the derivatives I am trying to verify. Grateful for any feedback re: What I might have done wrong; Published results (besides the work I cite) that could be used for verification. Disclaimer - posting here after failing to get input in this other forum Context Consider a random count-variable with probability mass function ( p.m.f) : \begin{aligned} Y_i \sim \textrm{Z.T. Neg. Bin}(\lambda_i,\alpha) & \equiv \Pr(Y_i = y_i | Y_i > 0) \\ & = \left. \frac{\Gamma(y_i+\alpha)}{\Gamma(y_i+1)\Gamma(\alpha)}\left(\alpha^{-1}\lambda_i\right)^{y_i}\left(1+\alpha^{-1}\lambda_i\right)^{-(\alpha+y_i)} \middle/ 1-(1+\alpha^{-1}\lambda_i)^{-\alpha} \right. \end{aligned} where: $y_i > 0 \quad (i=1,2,\dots,n)$ denotes the observed realisations (observations enter a zero-truncated sample only after the first count occurs); $\lambda_i = e^{\mathbf{x}_i^T\boldsymbol{\beta}}$ is the link function, with $\mathbf{x}^T_i$ being the $i$ -th row of the regression data matrix; and $\boldsymbol{\beta}$ the unknown vector of regression coefficients (to be estimated); $\alpha$ is another unknown parameter to be estimated, namely the reciprocal of the so-called…
Firefighter pay widely varies across the 50 states. Bureau of Labor Statistics data shows just how big these differences are.
This post was created in partnership with Paramount Advertising Connected TV is evolving into more than a viewing platform—it is becoming a dynamic bridge between storytelling, commerce, and consumer action. […]
![When visualizing data before applying transformations, when would you use a box and whisker plot as opposed to a histogram? [closed]](https://stats.stackexchange.com/Content/Sites/stats/Img/apple-touch-icon@2.png?v=344f57aa10cc)
I would like to know when one would be preferred over the other, I am visualizing my data before applying any transformations to make them normalized. Are there specific cases or rules that one is used over the other?
This post was created in partnership with Empathy Lab The campaign had a good run. One big idea launched everywhere, studied, repeated. Now? Not so much. During an ADWEEK House […]
Samuel Moyn’s new book argues that the elderly wield disproportionate power, leaving young people with diminished opportunities.
Carlo Buontempo, Copernicus Climate Change service director, says heatwaves have become "more intense, lasting longer and starting earlier in the season" in Europe as the continent "is warming faster than the global average".
Court says Redmond can file briefs, take part in hearings amid challenge to the current path Big Tech's data spice uses to legally flow
Vegvisir, an Estonian defence technology company building the command-and-control software layer for the multi-domain battlefield, today announced a venture investment from Iron Wolf Capital (IWC). V...
Assistive technology policy activity has accelerated since 2016, with at least 38 countries adopting national strategies aligned with the World Health Organisation and United Nations frameworks.
TL;DR PyTorch now has a Cross-Repository CI Relay (CRCR) that automatically triggers and tracks CI in downstream repositories whenever a PR is opened or a commit is pushed against pytorch/pytorch....
Value of some chip manufacturers have tripled, or more, driving Asia Pacific stock markets sharply higher Shares in chipmakers have surged in the first half of this year as investors piled into companies that make the hardware underpinning the AI boom, according to analysis. Investors have driven up the value of semiconductor and memory chip manufacturers, whose profits have soared during 2026, at the expense of some large software companies, which have fallen out of favour this year. Continue reading...
Claude Code creator Boris Cherny wrote about "what roles might look like in the future," from the "builder" to the "sweeper" to the "grower."
I went to my first World Cup game, the US opener against Paraguay in Los Angeles' SoFi Stadium. It was worth it, especially from my suite seats.
Diana Ürge-Vorsatz, Vice-Chair of the Intergovernmental Panel on Climate Change, said governments should provide "temporary measures" such as cooling centres during heatwaves. High air conditioning use is "already jeopardising" the EU's energy capacity, she said.
Italian VC P101 has integrated PranaVentures, an operational venture capital company specialising in Seed investments. The combination brings together more than €600 million in assets raised, creating...
As a chef and former line cook, I've got easy tips for making perfect, juicy, flavorful burgers from ground beef that easily cook evenly on a grill.
Social media users and music lovers are starting to panic about their record collections during the ongoing heatwave. Euronews Culture dispels a few myths and puts you on the right track...
I rode the Amtrak Coast Starlight for 32 hours up the West Coast. I loved my personal roomette, but I don't think it's affordable for routine travel.
Learn what to reach for when retrieval-augmented generation fails in production.
The startup, Proception, is taking a unique approach to collecting training data to tackle one of the hardest problems in robotics: hands.
Get an exclusive look at the breakthroughs, tools, and workflows shaping the path to quantum advantage.
It’s time for our annual Fourth of July grill episode here at Decoder. This is when we invite the CEOs of outdoor cooking companies onto the show to explain just how their businesses kind of look like every other business. And this is a very special edition. Today I’m talking to Roger Dahle, the CEO […]
Comcast spent 25 years arguing that media and broadband belonged together. Now it's breaking them apart.
Fashion was a highlight of the 2026 BET Awards. Stars like Janet Jackson and Teyana Taylor arrived in statement outfits, while others missed the mark.
Despite an initially expected downturn, Deputy Tourism Minister Kostas Koumis said tourism in Cyprus had returned to a "stable course", adding that improving performance in recent months showed government measures had "a positive impact".
A few days ago I shared a project I’ve been working on called “LatentGate” — a local-first pipeline that reduces LLM API token usage by processing inputs before sending them to the model. After some great feedback, I’ve now turned it into: A pip-installable Python package A VS Code extension (runs as a local proxy) MCP server support for tools like Claude Code, Cursor, Cline, Continue PyPI → pip install latent-gate VS Code → LatentGate — Local-First AI Compression What it does Images (~1000–1300 tokens) → compressed to ~150 tokens using local vision models (Ollama + LLaVA) Long prompts / conversations → compressed locally before hitting cloud APIs Works with OpenAI / Claude / Gemini APIs Fully local preprocessing (no data leaves your machine before compression) The idea is inspired by VL-JEPA — predicting in embedding space, then decoding selectively. Why I built this While experimenting with GPT-4o / vision APIs, I noticed most costs come from raw input size (especially images and long prompts). So instead of optimizing prompts endlessly, I tried: → “What if we reduce what we send in the first place?” What I’m looking for I’d love feedback from this community, especially: Edge cases where compression breaks context Cases where output quality drops noticeably Prompt / API compatibility issues (OpenAI especially) Performance bottlenecks Better approaches to selective decoding or compression If you try it and something fails — that’s honestly the most valuable thing for me rig…
Rocket Lab, the space company best known for its small satellite launcher Electron, has announced plans to acquire Iridium Communications for $8 billion. The deal will combine Rocket Lab's launch services and spacecraft manufacturing with Iridium's satellite-based communications network, putting it in a better position to challenge SpaceX. Iridium offers communications services to over 2.5 […]
Hours after Absa Bank Kenya announced the departure of chief executive Abdi Mohamed after a 32-year career at the lender, rival I&M Group named him as the next CEO of its Kenyan banking business.
Labour's likely next PM set out a 10-year economic plan in his Manchester speech, promising greater regional powers and a shift away from trickle-down economics.
The Strawberry Moon rises over Europe this evening, bringing with it centuries of tradition and absolutely no strawberry colouring whatsoever.
Swiss engineering startup Subatron has obtained €162,000 (CHF 150,000) from Venture Kick to develop a new generation of underwater communication technology. The solution aims to enable faster, more r...
You don't need Mythos or GPT-5.5-Cyber to find a vuln to exploit when the world's password habits are so sloppy
Excellent breakdown of SRPO and its impact on AI reasoning. The emergence of self-verification and structured thinking is particularly impressive. These advancements could significantly improve the effectiveness of a href="mathssolverai.com">many problem-solving tools and intelligent applications. Thanks for sharing this insightful research.
I've come across a situation that I haven't had to deal with before and I've reached an impasse. Problem Patients in a health system are routinely monitored for a lab value important for diabetes management (A1c). When A1c reaches a particular level (higher than normal) a nurse reaches out to the patient to discuss medication and other proper treatment strategies. There is no natural control group, but we have A1c values for all patients over a number of months prior to the contact and after the contact. We would like to test the hypothesis that the intervention positively affects A1c (brings it down toward normal). My thoughts Initially, I thought that an interrupted time series would work since this intervention started at a particular calendar date, and we have information about the entire cohort. However, individuals were contacted over a 2-year period, so this will not work. Then, I thought that longitudinal modeling, with some kind of linear spline function. However, I'm concerned about the fact that enrollment / inclusion in the study (intervention) is based on the outcome. There is also substantial autocorrelation in each patient's series. While there is no natural control group, one could use individuals for whom contact was attempted, but did not engage. I'd imagine that some kind of propensity score would be needed in that case. Any citations or suggestions are appreciated.
ive also been experiencing the same issue with both 5.5,5.4 and 5.4 mini
Scientists in Norway have found that exclusively breastfed babies are less likely to develop ADHD symptoms, with girls showing the strongest benefits.
Healthcare startup MyKare.ai has raised $3.2 million, including an additional $1 million in Series A funding round. The round saw participation from Andrew and Alfredo, founders of Papa.com, and a leading family office from the Middle East. The fresh funds will be used to enhance AI capabilities, accelerate product development, and support global expansion, MyKare said in a press release. Co-founded in 2021 by Senu Sam, Rahmathulla T M, and Joash Philipose, MyKare.ai develops an AI native healthcare operating system for clinics and hospitals. Its platform helps automate patient acquisition, appointment booking, follow ups, communication, feedback collection, and other administrative workflows through AI agents and voice AI. The startup aims to improve operational efficiency and patient experience by integrating these functions into a single platform. Its AI agents can also manage patient queries, identify intent, answer calls, update CRM records, and support patient retention. According to the company, it serves healthcare organizations across India, the Middle East, the United Kingdom, and the United States. It directly competes with the other notable players in this space such as Yellow.ai, Haptik, Senseforth.ai, Hyro, and Cognigy.
Feature request Please add a reading / focus mode in the ChatGPT mobile app that lets users temporarily hide persistent on-screen UI while reading long responses. Problem When reading a long ChatGPT response on mobile, the persistent app UI takes up a significant amount of vertical screen space. On my device, the header, input area, and related controls occupy more than 20% of the visible screen . That is workable while composing a message, but it becomes a problem once the user’s intent shifts from writing to reading . For long-form answers, research summaries, code explanations, writing drafts, planning output, or step-by-step instructions, the current mobile UI makes the response feel cramped and forces substantially more scrolling than necessary. The issue is not that these UI elements persist in most cases – the issue is that there is currently no way to temporarily dismiss them when the user is reading, or otherwise has a reason to. Expected behavior ChatGPT could support a mobile reading pattern where non-essential UI can be hidden while the user is consuming long-form content. There are many apps that already employ straight-forward approaches to this that users would already expect and be familiar with, requiring no acclimation or adjustment. Any of these interaction models would fit common user mental models: Auto-hide on scroll: Hide the header and/or input area when the user scrolls down through a response, then restore them when the user scrolls up. Menu option:…
Holocene is not trying to build the next billion-dollar climate company in Africa but is trying to build several worth $30 to $50 million each and sell them within three to five years.
Anti-immigration protestors are demanding the removal of undocumented migrants and tighter border enforcement, setting their own deadline of June 30.
The 33+ unauthenticated API endpoints in the entity responsible for RBI's bank.in domain registry exposed 5000 bank employees' sensitive data, like password hashes, login IPs, for 13 months. The post Explained: How vulnerabilities in RBI’s bank.in registry exposed sensitive data for 13 months appeared first on MEDIANAMA .