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The Decoder 2026-06-28 12:14 UTC Score 39.0 AI-168-20260628-regional-ai--b2598f50 Full article

Coinbase joins the rush to Chinese AI models as Western labs face a pricing stress test

Coinbase CEO Brian Armstrong is switching his company to Chinese AI models like GLM 5.2 and Kimi 2.7. An automated routing system picks the best model for each request based on task and price, and better caching pushed the hit rate from 5 to 60 percent. Coinbase has cut its AI spending in half even as token usage keeps climbing. The article Coinbase joins the rush to Chinese AI models as Western labs face a pricing stress test appeared first on The Decoder .

국내 AI 업계, 마누스 외면… "중국산 거부감보다 대체재 풍부"
Korea AI Times 2026-06-28 12:08 UTC Score 40.0 USR-0048-20260628-global-ai-ne-01ec3c6e Full article

국내 AI 업계, 마누스 외면… "중국산 거부감보다 대체재 풍부"

AI 에이전트 서비스 마누스(Manus)가 최근 국내 진출을 검토 중인 것으로 알려졌다. 마누스는 지난해 출시 직후 뛰어난 성능으로 주목받았으며, 최근에는 메타의 인수 추진 과정에서 중국 정부가 이례적으로 \'거래 철회 명령\'을 내리며 미국과의 기술 갈등의 중심에 선 바 있다. 이 때문에 시장에서는 이를 ‘중국계 AI’로 인식하는 분위기가 짙다. 마누스도 국내 진출에 가장 큰 걸림돌로 이런 점을 꼽은 것으로 알려졌다.이에 따라 국내 AI 기업 10여 곳을 대상으로 마누스와 중국산 AI 이미지에 대한 시각과 실제 도입 여부를 조사했다.

Nest’s quest to fix your thermostat
The Verge AI 2026-06-28 12:02 UTC Score 50.0 AI-016-20260628-global-ai-ne-ab04daa1 Full article

Nest’s quest to fix your thermostat

The founding story of Nest is pretty much a perfect tech myth. A legendary product maker (in this case, Tony Fadell) helps create one of the most successful products ever (the iPhone) and then rides off into the sunset to enjoy the rest of his life, only to have an experience that drags him back […]

Ad-free streaming is a luxury now
The Verge AI 2026-06-28 12:00 UTC Score 47.0 AI-016-20260628-global-ai-ne-3c7a3546 Full article

Ad-free streaming is a luxury now

This is The Stepback, a weekly newsletter breaking down one essential story from the tech world. For more news about the streaming industry, follow Emma Roth. The Stepback arrives in our subscribers' inboxes at 8AM ET. Opt in for The Stepback here. How it started Streaming was once a reprieve from cable. Not only could […]

LessWrong AI 2026-06-28 11:09 UTC Score 58.0 USR-0152-20260628-community-fo-165a11bf

Power Laws in NNs: A Possible Mechanism for Inductive Bias towards Sparse Representations

This post was produced as part of the Iliad Fellowship under the mentorship of Dmitry Vaintrob. Tl;dr: Power-law ("heavy-tailed") distributions have universality theorems similar to those which make Gaussians common. We observe many things in ML are power-law distributed, most robustly and interestingly, the spectra of weight matrices. I explain how we can think of power-laws as being a natural generalization of the idea of 'sparsity', interpolating between true sparsity and Gaussianity according to the 'tail-index' of the distribution. I share some hypotheses about how this might relate to the 'sparse'/'discrete'/'factored' representations that neural networks seem to learn. I promise this is not a Santa-Fe-Institute encomium for power laws or "black swans"; different genre. Contents 1. The generalized central limit theorem proves power-law distributions are universality classes 2. Power laws observed in NNs might help us understand representation learning 2.A. HTSR: phase changes in weight-matrix spectra and data-free prediction of generalization 2.B. BBP transition as a quantum of learning 2.C. HTSR as an extended BBP transition 2.D. Training evidence for heavy tails is mixed, and I'm not sure if they're important 3. The tail exponent α is a smooth proxy for sparsity and compressibility 3.A. α captures compressibility across heavy tails 3.B. α-stable noise can make discrete codebooks optimal 3.C. Heavy-tailed noise can convert analog inputs into discrete codebooks 4. Summ…

LessWrong AI 2026-06-28 11:07 UTC Score 71.0 USR-0152-20260628-community-fo-3c7a44c6

Refusal Is Complicated As Hell: An Update

TL;DR It would make sense to briefly skim through our previous post that introduces our experiments on refusal in LLMs . There we explain how it started, here we’ll tell how it’s going. The primary goal of this text is to try and structure the list of whack-a-mole research questions. The secondary goal is to get some outside perspective, so if you run a similar research or have seen a similar research, please lend us a hand. Feel free to jump straight to the section that looks most appealing. We recommend skimming through “The Main Question” as this section provides a broader perspective. Then we listed all other questions that arose during research. You’ll find them under headers “Another Question: …” and “Wording Also Matters”. The first one discusses how refusal is represented in different layers and what it might mean. The second one is dedicated to two parts of refusal – its wording and actual detection of a potentially harmful request. “The Main Question” is split into two parts: in “Our suggestion” we outline our main hypothesis and proofs we found during our experiments; in “An Alternative Suggestion” we highlight the opposing point of view and proofs behind it. The Main Question (MQ) We experiment on open-weight small (~9B) instruct models trying to understand what exactly happens when they refuse to provide an answer given different contexts. One of the core observations is, refusal looks different for different categories of potential harm (for example, a request…

Faster AI, lower costs: DSpark eases inference bottlenecks and chip strain, says DeepSeek
South China Morning Post AI 2026-06-28 11:00 UTC Score 55.0 AI-156-20260628-regional-ai--1e1aa69e Full article

Faster AI, lower costs: DSpark eases inference bottlenecks and chip strain, says DeepSeek

Chinese artificial intelligence start-up DeepSeek has rolled out a major upgrade to its flagship V4 model aimed at sharply accelerating AI response generation, as competition among Chinese developers increasingly shifts to reducing serving costs and enhancing user experience. DeepSeek, by adopting what it called a speculative decoding framework, DSpark, said it increased per-user response speeds by up to 85 per cent, an efficiency gain that could reduce AI systems’ reliance on larger, more...

Slate's new affordable EV truck has our newsroom divided
Business Insider AI 2026-06-28 10:37 UTC Score 40.0 USR-0098-20260628-global-ai-ne-1dd66d8c Full article

Slate's new affordable EV truck has our newsroom divided

In this Sunday edition of Business Insider Today, we're talking about the ungainly quality of Slate's new EV truck and why some people would buy it anyway.

저커버그, '예측 시장' 앱 개발 이어 선두주자와 협력 지시
Korea AI Times 2026-06-28 10:36 UTC Score 35.0 USR-0048-20260628-global-ai-ne-7c8391b5 Full article

저커버그, '예측 시장' 앱 개발 이어 선두주자와 협력 지시

메타가 최근 폭발적으로 성장 중인 ‘예측 시장’에 도전하기 위해 자체 앱 개발에 나섰다는 소식에 이어, 이 분야 선두주자들과의 협력에 나선 것으로 알려졌다.26일(현지시간) 뉴욕타임스에 따르면, 마크 저커버그 CEO는 최근 참모진에게 폴리마켓(Polymarket)과 칼시(Kalshi) 등 대표 플랫폼과의 제휴 방안을 모색하라고 지시했다.이에 앞서 저커버그 CEO가 사내 소규모 팀을 통해 예측 시장 플랫폼을 모델로 한 독립형 모바일 앱 ‘아레나(Arena)’를 비밀리에 개발해 왔다는 소식이 전해졌다. 구체적인 협력 형태는 알려지지 않

The British restaurants are coming
Business Insider AI 2026-06-28 10:21 UTC Score 43.0 USR-0098-20260628-global-ai-ne-91cabf16 Full article

The British restaurants are coming

From fish and chips to fine dining, New York City is in the middle of a British restaurant boom.

The Decoder 2026-06-28 10:16 UTC Score 60.0 AI-168-20260628-regional-ai--8d3f58db Full article

Only three AI models finished above starting capital in a 500-day startup survival test

Researchers at Princeton University built CEO-Bench, a test where AI agents have to run a fictional software company for 500 simulated days. Most current models go broke, and a simple rule-based heuristic with no AI beats nearly all of them. The article Only three AI models finished above starting capital in a 500-day startup survival test appeared first on The Decoder .

Latest news bulletin | June 28th, 2026 – Midday
Euronews AI 2026-06-28 10:00 UTC Score 40.0 AI-164-20260628-regional-ai--3e0d2de2 Full article

Latest news bulletin | June 28th, 2026 – Midday

Catch up with the most important stories from around Europe and beyond this June 28th, 2026 - latest news, breaking news, World, Business, Entertainment, Politics, Culture, Travel.

Chinese cybersecurity firm builds AI tools to rival Mythos and frames the race as cyber-nuclear deterrence
The Decoder 2026-06-28 09:30 UTC Score 47.0 AI-168-20260628-regional-ai--25626d95 Full article

Chinese cybersecurity firm builds AI tools to rival Mythos and frames the race as cyber-nuclear deterrence

360 founder Zhou Hongyi presents two AI security tools designed to compete with Anthropic's Mythos. One has already flagged 3,432 vulnerabilities. Zhou admits Chinese models trail Western ones by 20 to 30 percent, but compares Mythos to "cyber nuclear weapons" and calls for China to build its own strategic deterrent. The article Chinese cybersecurity firm builds AI tools to rival Mythos and frames the race as cyber-nuclear deterrence appeared first on The Decoder .