Meta AI readies Avocado, Manus Agent, and OpenClaw integration (5 minute read) Meta AI is reportedly preparing to release new models named Avocado. It is also adding MCP support and a Memory section to its settings menu. Meta AI has revamped its website to include a lot of additional functionality. The company appears to be working on an AI agent and a browser agent, and a new feature called Tasks that will allow users to schedule recurring executions of Meta AI. | Nvidia becomes first $5T company; AI chips fuel market value (4 minute read) Nvidia achieved a historic milestone by briefly surpassing a $5 trillion market valuation, driven by overwhelming demand for its AI chips and dominance in data-center accelerators. Its advanced Blackwell and Rubin GPU platforms power the bulk of large-model training and inference workloads, underpinning investor confidence in continued AI infrastructure growth. This valuation reflects Nvidia's central role in the AI economy and illustrates how hardware leadership translates to extraordinary market value. | | Open Models Will Never Catch Up (42 minute read) Open models will probably never catch up with closed ones. However, they don't need to - open models are an engine for exploration in a way that companies can't really nurture. Open models are the main place where experimentation still happens. They will be the engine for the next ten years of AI research. | World Models and the Data Problem in Robotics (17 minute read) World models are trained to predict how the world evolves. They enable generalization that pure action prediction cannot achieve. Combining world models with robotics could create robots that can do everything humans can do. However, this will require a lot of data captured by real people. | | Learning from context is harder than we thought (9 minute read) The role of humans in AI systems will shift if context learning improves significantly. Humans would focus on context engineering rather than primarily providing training data. Once this is achieved, we then need to focus on making context persistent. | Monty (GitHub Repo) Monty is a minimal, secure Python interpreter written in Rust for use by AI. It lets users safely run Python code written by agents. Monty completely blocks access to the host environment, and it can only call functions it has access to. It makes it possible to safely run LLM-generated code without the complexity of a sandbox or the risk of running code directly on the host. | | G's Last Exam (16 minute read) The profession of software engineering has forever changed, but it is still unknown what role humans will exactly play. This post presents a list of the most ambitious and creative software accomplishments by humans. A world in which agents autonomously solve these challenges would be equal parts humbling, exciting, and unsettling. | Do Markets Believe in Transformative AI? (1 minute read) Transformative technologies influence interest rates by changing growth expectations, increasing uncertainty about growth, or raising concerns about existential risk. There were economically large and statistically significant movements concentrated at longer maturities for US bond yields around major AI model releases in 2023 and 2024. These movements correspond to downward revisions in expected consumption growth and/or a reduction in the perceived probability of extreme outcomes. It appears the markets do not believe in transformative AI. | The Anthropic Hive Mind (16 minute read) While every company quickly becomes professional and 'grown up', Anthropic still hasn't bothered. It isn't run like any other company of its size. The company's employees describe the company as a hive mind run entirely on vibes. This article takes a look inside one of the leading AI labs, examining the company's culture, history, work style, and more. | | | Love TLDR? Tell your friends and get rewards! | | Share your referral link below with friends to get free TLDR swag! | | | | Track your referrals here. | | | |
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