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1,296 件並び順
0:47ENGPT-5 and an Automated Laboratory: A Scientific WorkflowMatthew Berman · Forward FutureMatthew Berman describes an OpenAI and Ginkgo Bioworks demonstration connecting an AI model to laboratory automation.
0:53ENClaude Opus 4.6: Coding Claims, Agent Evaluation, and a Longer ContextMatthew Berman · Forward FutureMatthew Berman discusses Anthropic’s February 2026 model launch and a chart of AI task horizons.
9:31ENGPT-5.3-Codex: Coding Agents, Speed and Computer Use at LaunchMatthew Berman · Forward FutureMatthew Berman reviews OpenAI’s February 2026 demonstrations and benchmarks, with a closer look at what the reported speedup and scores do—and do not—show.
1:57:56ENA Hundred Million Lines at Twenty Cents Each: Inside Blitzy's Enterprise Coding Pipelineホスト Nathan LabenzCEO Brian Elliott and CTO Sid Pardeshi tell Nathan Labenz how Blitzy turns a giant codebase into a map, then lets thousands of dynamically generated agents ship most of a multi-month project in days.
14:20ENClaude Opus 4.6: Longer Context, Agent Teams and Early BenchmarksMatthew Berman · Forward FutureMatthew Berman reviews Anthropic's February 2026 model launch, its agent features, long-context results and historical pricing.
22:31ENMatthew Berman’s OpenClaw Setup: Models, Workflows, and SecurityMatthew Berman · Forward FutureA walkthrough of a personal AI assistant’s configuration, scheduling, integrations and practical automations, with attention to the risks of granting it access.
0:57ENTesla Plans to End Model S and X Production as It Turns Factory Space to OptimusMatthew Berman · Forward FutureMatthew Berman discusses the retirement of two flagship vehicles and Tesla’s ambitions for humanoid robots.
0:32ENA Prompt for Reducing Familiar AI Writing PatternsMatthew Berman · Forward FutureMatthew Berman discusses a writing checklist and a prompt intended to reduce repetitive AI prose.
1:04:51EN125 million cells took a decade. The next billion takes monthsホスト Nathan LabenzMark Zuckerberg and Priscilla Chan on pairing a frontier biology lab with a frontier AI lab so models train on data that was designed for them.
1:01ENMoltbook, AI Agents and the Appearance of Private PlansMatthew Berman · Forward FutureMatthew Berman reacts to a post on an agent-oriented social network and questions what AI-to-AI conversations might mean.
4:25:13ENThe Architecture Barely Changed. Data, Cost, and Open Weights Did.ホスト Lex FridmanNathan Lambert and Sebastian Raschka walk Lex Fridman through a year in which training methods and datasets moved more than model design, and 2026 looks like a fight over inference cost, agents, and who owns truly open models.
12:23ENMoltbook: An AI Agent Social Network and Its Security QuestionsMatthew Berman · Forward FutureMatthew Berman explores conversations attributed to AI agents on Moltbook and considers privacy, manipulation and operating costs.
1:03:00ENA Model That Solves New Math Problems Every Week Still Isn't AGIホスト Jacob EffronFormer OpenAI research VP Jerry Tworek on why scaling still works, why models go hopeless when they fail, and why he left to chase continual learning.
11:31ENExploring Google’s Project Genie: Interactive Worlds with Genie 3AlexAlex tests generated racetracks, alien structures and cloud landscapes, showing both the prototype’s creative options and its control limitations.
1:39:17ENAI Already Beats the Median Lawyer. Top Firms Bought the Tools and Left Them Unusedホスト Nathan LabenzKevin Frazier and Alan Rozenshtein walk through how frontier models are changing legal practice, why billable hours stall adoption, and which new rights and government limits they want next.
21:12ENClawdbot as a Personal AI Assistant: Workflows, Costs and RisksMatthew Berman · Forward FutureMatthew Berman demonstrates a local agent connected to messaging, cloud services and models, and reports what worked, failed and cost more than expected.
0:24ENMatthew Berman Checks His Clawdbot Token CostsMatthew Berman · Forward FutureA short usage check reveals unexpectedly high model spending over two days.
2:12:31ENMost Caffeine users have no idea they are on a blockchainホスト Nathan LabenzDFINITY's Dominic Williams tells Nathan Labenz why a tamper-proof, unstoppable cloud is the right backend for AI that writes software from a chat box.
2:25:10ENFine-Tuning Isn't Dead — But It Turned a Helpful Model Evilホスト Nathan LabenzNathan Labenz on why prompting replaced fine-tuning for most work, what emergent misalignment actually showed, and how he is thinking about jobs, UBI, and AGI.
1:08ENWill AI Change What Programmers Do?Matthew Berman · Forward FutureMatthew Berman responds to Ryan Dahl's prediction about writing code and argues that systems thinking will remain important.
2:29:42ENTwelve hooks and thirty files: Daniel Miessler’s personal OS on Claude Codeホスト Nathan LabenzThe PAI framework treats scaffolding, not the model, as the product — a goal-centered agent stack that Miessler thinks will decide both knowledge-work automation and the next cybersecurity race.
1:02ENA Speed-Reading Display That Shows One Word at a TimeMatthew Berman · Forward FutureA short visual demonstration presents words in rapid succession at increasing displayed speeds.
1:00ENGemini Personal Intelligence Connects Google AppsMatthew Berman · Forward FutureMatthew Berman explains a January 2026 Gemini beta and the inbox-to-calendar workflow he hopes to use.
1:40:51ENReasoning Models Just Made the Other 80–90% of Enterprise Data Usableホスト Nathan LabenzSnowflake VP of AI Baris Gultekin on text-to-SQL, RAG, agent design, and why inference has to run next to governed data.
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