A developer has been using unlimited ChatGPT conversations for software development, leveraging OpenAI's Secure MCP Tunnel to expose tools running on their machines to regular ChatGPT conversations, effectively replacing Codex usage for many practical development tasks. To optimize this workflow, they built a unified MCP server and integrated open-source projects like Desktop Commander and CUA, allowing ChatGPT to inspect repositories, modify code, run commands, and debug errors. However, OpenAI has now announced changes to kill unlimited Chats and merge them with Codex usage. AI summary
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This episode features Andy Beam and Rafa Gómez-Bombarelli from Lila Sciences, discussing their vision for AI science factories as the next frontier for generating internet-scale datasets. They explain how their automated labs, leveraging AI…
Tim Scarfe interviews the Tufa Labs ARC-AGI-3 team to dissect their winning approach on the ARC-AGI-3 benchmark, focusing on how their system discovers goals and balances exploration with action efficiency. The episode explores the challeng…
ARC-AGI-3 benchmarkgoal acquisitionaction efficiencyexploration vs exploitationlanguage modelsplanning in AIcoding agentsrequirements engineeringcore knowledge priorsabstraction synthesisreinforcement learningAI safetybitter lessonneural guided searchLLM reasoningsoftware engineering AIbenchmark designgeneral intelligence
In this episode, Thomas Ahle discusses the development of thermodynamic computing chips and the challenges of chip design automation using AI agents. He explains how his team built an open-source Verilog simulator with AI collaboration to o…
thermodynamic computingchip design automationformal verificationVerilog simulationAI agentsopen source EDAcontinual learningprobabilistic machine learninghardware-software co-designauto formalizationsoftware complexityAI-generated codeBayesian inferencestochastic differential equationsMarkov chain Monte Carlodiffusion modelsneural network accelerationrecursive self-improvementAI safetyagentic coding
This episode delves into Anthropic's Fable system card, discussing its advanced math capabilities, troubling 'Vending-Bench' behavior, and drift towards functional decision theory, alongside challenges in model interpretability and safety c…
This episode explores the economic implications of advanced AI and AGI, focusing on what remains scarce, the future of labor share, and optimal wealth redistribution strategies. Guests Alex Imas and Phil Trammell discuss the 'relational sec…
Andrew Lee, CEO of Tasklet, details his company's complete rewrite of their agent stack, now emphasizing file system context, agentic search, and multi-resolution summarization for token efficiency. He discusses the strategic challenge of c…
Agent architectureFile system contextAgentic searchMulti-resolution summarizationToken conservationLLM pricingHorizontal platformsAPI-first companiesSolutions companiesWorkflow automationGeneral purpose agentsContext managementCaching strategiesAnthropic modelsOpenAI modelsModel capabilitiesComputer useCode generationSupply chain riskModel differentiationHarness designMecha suit conceptOrganizational contextShared brain AIGenerative UIAI safetyData durabilityHuman-in-the-loop AIVendor selectionAI music generationToken economicsAlgorithmic breakthroughsBusiness productivity