絞り込み結果
156 件並び順
23:22EN
AI Engineer· 2026年10月27日Noyan Tokgozoglu: How Optiver Builds an AI Platform for Fast, Measurable DecisionsNoyan Tokgozoglu · OptiverThe trading firm’s AI engineering lead explains same-day model adoption, on-premises infrastructure, cost controls and the limits of replaying agent evaluations.
36:07EN
Theo - t3․gg· 2026年10月27日Theo on Token Costs, Coding Agents, and the Price of AI CapabilityTheo Browne · Ping LabsA viral estimate of Lauren's AI spending prompts a closer look at cache pricing, benchmarks, and the changing work of coding agents.
16:38ENAI Engineer· 2026年10月27日Aiden Sochowski: Securing 300 Agents in a 60-Person CompanyAiden Sochowski · RunlayerRunlayer’s founding engineer explains what session monitoring revealed about agent permissions, prompt injection, tool errors and runaway cost.
20:55ENAI Engineer· 2026年10月26日Jesse Hall: Build Voice Agents for Conversations, Not LeaderboardsJesse Hall · LiveKitLiveKit’s Jesse Hall explains how to evaluate voice agents as real-time systems: understand callers, handle interruptions, keep talking while tools run, and measure the delay people actually hear.
18:27ENAI Engineer· 2026年10月26日Daksh Gupta on Building a Better AI Code Review AgentDaksh Gupta · GreptileGreptile co-founder Daksh Gupta explains why a webhook plus a coding agent is not enough for reliable pull-request review—and how targeted prompts, incident data, model inversion, codebase context, browser testing, and task-specific model routing can help.
25:50EN
Matthew Berman· 2026年10月24日Kimi K3.1 Pro Tested: Strong 3D Demos, Uneven Results and Competitive PricingMatthew Berman · Forward FutureMatthew Berman tests the open-weight model on coding, 3D rendering and visual explanations, then compares benchmark results and prices.
32:20ENMatthew Berman· 2026年10月23日Who Is Local AI For? The Costs, Trade-offs and a Hybrid FutureMatthew Berman · Forward FutureMatthew Berman weighs data control and independence against hardware cost, setup complexity and inference speed.
17:42ENAI Engineer· 2026年10月21日Is a Faster Model Actually Faster? Measure the Finished Job, Not the TokensMorgan Suo · MiniMaxMiniMax's Morgan Suo takes the engineering changes inside M3.1 Flash one by one and asks the question that matters to users: does the job an analyst needs actually get done sooner, cheaper and correctly?
17:42ENAI Engineer· 2026年10月20日Oliver Kennon: Why GPU Operating Capability Changes the Cost of AIOliver Kennon · SemiAnalysisA comparison of inference configurations leads to a broader discussion of useful output, security, costs and compute futures.
38:30ENTheo - t3․gg· 2026年10月14日Theo Tests Gemini 4 Argon: Design Strengths and Code-Review ConcernsTheo Browne · Ping LabsA strong result on a narrow skateboarding benchmark contrasts with poor findings in Theo’s own codebase audits.
10:36ENMatthew Berman· 2026年10月13日Meta Muse Wonder Tested: Strong Benchmarks, Mixed Demos and Quota FrictionMatthew Berman · Forward FutureMatthew Berman tests Meta’s models on browser demos and reviews their published benchmark scores, availability and cost.
38:02ENTheo - t3․gg· 2026年10月13日Meta’s Muse Wonder Full: A Coding Agent Tested Against Opus and SolTheo Browne · Ping LabsTheo Browne tests Meta’s new model on code review, debugging, delegation and benchmarks, finding promising strengths alongside important limits.
18:18ENTheo - t3․gg· 2026年10月12日Why AI Bills Can Rise as Intelligence Gets CheaperTheo Browne · Ping LabsTheo Browne explains the difference between token prices, task costs and capability, and why more useful agents can still drive larger bills.
0:23ENTheo - t3․gg· 2026年10月12日Why Theo Would Wait Before Upgrading for UltrafastTheo Browne · Ping LabsA short cost comparison leads Theo Browne to caution against upgrading to the $500 tier solely for Astra Ultrafast.
41:10ENTheo - t3․gg· 2026年10月9日Haiku 5.5: Where a Cheaper Small Model Helps Coding AgentsTheo Browne · Ping LabsTheo Browne examines Haiku 5.5 pricing, benchmark results and practical tests, including a failed pull-request audit.
1:26:46EN
Cognitive Revolution "How AI Changes Everything"· 2026年10月8日ポッドキャストThere Likely Is a Level of Intelligence We Shouldn't Go Pastホスト Nathan LabenzNathan Labenz brings notes from The Curve, a chip startup whose token bill beat payroll, and a software industry that now performance-reviews people for Claude slop.
33:33ENTheo - t3․gg· 2026年10月7日Is the $200 Codex Plan Still Worth It?Theo Browne · Ping LabsTheo Browne compares subscription usage, API-equivalent estimates, model efficiency and the cost of Ultrafast.
1:10:12ENCognitive Revolution "How AI Changes Everything"· 2026年10月7日ポッドキャストOutSystems Went From 4 Major Features a Quarter to 26. Token Spend Fell Anywayホスト Nathan LabenzCEO Woodson Martin on software that never breaks, why most enterprise work does not need a frontier model, and how AI is finally shrinking the IT backlog.
0:29ENTheo - t3․gg· 2026年10月7日Theo’s Ultrafast Test: $600 of Usage for Two PR ReviewsTheo Browne · Ping LabsA short example illustrates how quickly token costs can rise when using Ultrafast for everyday review work.
28:17ENTheo - t3․gg· 2026年10月6日Ultrafast Coding: A Live Design Loop With a Steep CostTheo Browne · Ping LabsTheo Browne explores how fast inference changes his workflow, and why he still advises against upgrading solely for Ultrafast.
1:06:36ENTheo - t3․gg· 2026年10月2日Theo’s Guide to Running Coding Agents in ParallelTheo Browne · T3Theo explains his approach to subscription usage, agent delegation, review and remote machines, while acknowledging that parts of his setup may violate provider rules.
1:28:08ENCognitive Revolution "How AI Changes Everything"· 2026年10月1日ポッドキャストThe same H100 costs 3x at AWS, and a four-month-old lab is catching genes the top sequencers missedホスト Nathan LabenzA Cognitive Revolution weekly briefing on a possible U.S.–China AI hotline, why hyperscalers charge two to three times as much for identical chips, co-writing a novel with frontier models, and an AI loop that re-diagnosed a child a premier prenatal lab had cleared.
10:00ENMatthew Berman· 2026年9月30日OpenAI DevDay: Dots, Faster Inference, Codex and ChatGPT SpaceMatthew Berman · Forward FutureMatthew Berman reviews the event’s personal assistant, model, developer tooling and collaboration announcements.
30:58ENTheo - t3․gg· 2026年9月29日GPT-6.1 Sol: Cheap, Thorough at Code Review, but Uneven at Long BuildsTheo Browne · T3Theo compares early tests of GPT-6.1 Sol with competing models, from benchmark cost to real code reviews and a 3D game demo.もっと見る156 件中 24 件を表示