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Aug 1

Aug 1Sat
  1. Andrej KarpathyAI score66

    Karpathy tests Opus 5 by rendering Lord of the Rings opening in 3D

    AIAndrej Karpathy gave Claude Opus 5 the first paragraph of Lord of the Rings with a 1M token budget and asked for a Three.js render. Opus spent about two hours writing 5500 lines of code that procedurally renders the story, which Karpathy calls janky but fun. He notes the model struggled to audit its work because it cannot efficiently perceive video or play the resulting game, relying on slow screenshots that led to several errors.

    Video from @karpathy's post

Jul 30

Jul 30Thu
  1. Jeff DeanAI score38

    Jeff Dean thanks Diana Hu after Startup School conversation at Chase Center

    AIJeff Dean, Google's Chief Scientist, thanked YC partner Diana Hu for an engaging conversation at Chase Center last weekend, his first in a basketball arena. The post is a brief acknowledgment, with the surrounding context describing a Startup School 2026 discussion on AI inference hardware, the origins of TPUs, and advice for founders.

  2. Microsoft AI BlogAI score14

    Leaders share how AI transformation depends on mindset, team adoption, and culture

    AILeaders interviewed for Alysa Taylor's "What's the Tea?" series, including executives at Adobe, Lumen, and Sitecore, say the shift from AI apprehension to expected adoption is the precondition for transformation. Behavioral scientist Jon Levy argues the goal is raising a team's collective intelligence, not just cutting costs, with leadership and continuous training driving scale.

Jul 29

Jul 29Wed
  1. Ahmad Al-DahleAI score52

    Ahmad Al-Dahle argues AI capex is both short on compute and overbuilt

    AIAhmad Al-Dahle argues that AI infrastructure faces both a compute shortage and overbuilding, with the four largest hyperscalers planning roughly $725 billion of capex in 2026, up 77 percent from last year. He describes a "mutually assured construction" dynamic in which every well-capitalized player buys the same insurance against falling behind, so the industry overbuilds by construction.

Jul 28

Jul 28Tue
  1. Tri DaoAI score42

    Putting LLM brains on robots yields 4x SOTA gains without extra training

    AITri Dao reports that connecting an LLM as the "brain" to robot control policies quadruples state-of-the-art performance with no extra training. He says he was surprised by how well it works and expects agents running on robots to arrive soon. Background from a quoted post reports real-robot success rising from 16.7% to 97.3% and simulated LIBERO-PRO success from 12.8% to 53.3%.

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  1. Jeremy HowardAI score16

    Jeremy Howard criticizes employees who ignore their employer's interests

    AIJeremy Howard argues that many people with otherwise sound judgment seem unable to think clearly about actions that affect the company paying them. The post is a general observation and cites no specific company, product, or event. Its quoted context about Nvidia's CUDA and GPU driver open source release is not the post's main subject.

Jul 25

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  1. Alex AlbertAI score34

    Opus 5 now produces consultant-grade spreadsheets and slide decks, Alex Albert says

    AIAlex Albert, of Anthropic, says Opus 5 now produces near-superhuman spreadsheets and slide decks that match what a consultant would make, just over six months after its predecessor. He also notes that finance professionals are reporting strong reactions to Claude for Excel, and he expects agentic progress seen in coding to extend to other fields in 2026.

    Video from @alexalbert__'s post

Jul 23

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  1. Kevin Weil 🇺🇸AI score20

    Kevin Weil says US science leadership is essential to long-term global leadership

    AIOpenAI's Kevin Weil argued that leading over the long term requires leading in science, sharing a post that highlights a report. Mike Kratsios released "Science: A New Golden Age," described as a blueprint for renewing American scientific leadership in the 21st century, in response to a presidential call to revive the nation's scientific enterprise.

Jul 20

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Jul 13

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  1. AI Snake OilAI score57

    Narayanan argues AI job change will unfold over decades, not with one model release

    AIArvind Narayanan's ICML keynote argues that AI's labor impact will depend on slow organizational adaptation rather than a single lab milestone. He cites reliability measurements showing agent accuracy rose much faster than reliability over the last 24 months, and points to software engineering and past technologies like electricity and ATMs. He concludes that evaluation work and human judgment will become more central as building tasks are increasingly automated.

  2. Liquid AI NewsletterAI score6

    Liquid AI invites developers to introduce themselves and share their AI projects

    AILiquid AI is asking developers and researchers who build efficient, general-purpose AI for on-device hardware such as phones, laptops, cars, robots, and enterprise systems to introduce themselves in the comments. It invites readers to describe what they are building or studying, whether shipping products, publishing research, or working on side projects.

Jul 12

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Jul 10

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  1. AI Futures ProjectAI score38

    AI Futures Project Proposes Further Research Into Plan A and Alternative Scenarios

    AIAI Futures Project released AI 2040: Plan A and outlined further research areas, including building competing prescriptive scenarios such as Plan S, a domestic-first Plan A, GPU arms control, and CERN for AI. The group also flagged covert-project modeling and US domestic governance as areas of substantial uncertainty needing further work.

  2. Soumith ChintalaAI score29

    Thinking Machines outlines personalization, human participation, and decentralization goals

    AISoumith Chintala, a Thinking Machines figure, says the lab focuses on personalization and sovereignty, human participation, and decentralization to democratize AI. He argues these reduce society's dependence on centralized AGI companies, including his own. He points to Tinker, interaction models, and openly published research as previews, with more coming soon.

Jul 9

Jul 9Thu
  1. Thinking Machines LabAI score44

    Thinking Machines Argues the Future Worth Building Keeps Humans Central to AI Decisions

    AIThinking Machines Lab says AI should extend human will and judgment, with people shaping its goals through continuous feedback rather than relying on models trained once and frozen. The company outlines three technical directions: training strong models, building tools for customization including training model weights, and developing interfaces that let personal judgment influence AI work. It also says it will publish research for the scientific community.

  2. AI Snake OilAI score62

    AI labs may escape the commodity trap by moving up the stack

    AIThe essay argues that AI labs selling model inference face commodity pricing pressure, but may achieve durable profits by moving into products, enterprise deployments, and switching-cost moats. It cites historical infrastructure industries and the Bertrand paradox to support the view that value capture depends on climbing the stack. The authors also warn that successful lock-in could raise enterprise costs and concentrate power, making early interoperability and portability standards important.

  3. AI Futures ProjectAI score42

    AI Futures Project Releases AI 2040: Plan A Scenario on Delayed Superintelligence

    AIThe AI Futures Project has published AI 2040: Plan A, a detailed scenario recommending policy action that delays superintelligence until 2040 rather than 2030. The authors present it as a recommendation rather than a prediction, and it is available at ai-2040.com in text, audio, and mobile formats, with a fuller experience on a desktop computer.

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