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327 件
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スライド 8 枚1:59:37EN
Matthew Berman· 2026年9月22日Opus 5.5 and GPT-6 Sol and Luna: A Launch-Day LivestreamMatthew Berman, Thariq Shihipar, Alex, Brian · Forward FutureMatthew Berman interviews Anthropic’s Thariq Shihipar, shows early demos and then reviews two OpenAI models announced during the stream.コーディングエージェントAI cost & performance評価(Evals)+2
スライド 10 枚30:29EN
Theo - t3․gg· 2026年9月21日Jev: A Fast Classifier for Structured DecisionsTheo Browne · T3Theo Browne explores Typesafe AI’s Jev through classification, game and developer-workflow demos, and explains where he thinks a reasoning model is still needed.Structured outputsModel routing & gatewaysコーディングエージェント+2
1:19:54EN
20VC with Harry Stebbings· 2026年9月19日ポッドキャスト · 2 人Thomas Sohmers on AI Inference, Memory and Data-Center Growthゲスト Thomas Sohmers · ホスト Harry StebbingsPositron’s co-founder discusses the engineering economics of inference, his views on AI infrastructure and regulation, and the risks he sees in financing and concentration.InferenceSemiconductorsAI cost & performance+2
スライド 4 枚27:09EN
Theo - t3․gg· 2026年9月18日Why Theo Values Reliable Coding Agents Over Peak PerformanceTheo Browne · T3Theo Browne argues that a model’s weakest moments matter when a coding task stretches from investigation through testing and review.コーディングエージェントDeveloper productivityAI cost & performance+2
38:14EN
No Priors: AI, Machine Learning, Tech, & Startups· 2026年9月18日ポッドキャスト · 2 人Diffusion Will Win Inference: Stefano Ermon Bets Parallel Tokens Beat Custom Siliconホスト Sarah Guo, Elad GilThe Stanford diffusion pioneer tells No Priors why a 50-person lab is training language models that generate many tokens at once — and why that maps to GPUs the way transformers once mapped to training.モデルと学習InferenceAI cost & performance+3
スライド 5 枚12:31EN
Matthew Berman· 2026年9月18日Jev's Fast Decisions: Demos, Tradeoffs and Reliability ClaimsMatthew Berman · Forward FutureMatthew Berman explores a decision-oriented AI model through routing, simulated worlds, chess and game-control examples.AI agentsAI cost & performance評価とオブザーバビリティ+1
スライド1:12EN
Matthew Berman· 2026年9月17日A Sponsored Look at Higgsfield's Image and Video APIMatthew Berman · Forward FutureMatthew Berman uses a real-versus-AI video comparison to introduce Higgsfield's model catalog and generation-based API billing.Generative media画像と動画AI cost & performance
1:06:47EN
Cognitive Revolution "How AI Changes Everything"· 2026年9月17日ポッドキャストEighty percent of what agents do should still be ordinary codeホスト Nathan LabenzZapier CEO Wade Foster tells Nathan Labenz that models top out at 40% on real automation tasks, users will not leave their daily driver, and the winning move is headless tools delivered through MCP.MCP とツールMCPWorkflow automation+3
スライド0:38EN
Matthew Berman· 2026年9月13日A Quick DeepSeek Speed Test and V4.1 Flash API PricingMatthew Berman · Forward FutureMatthew Berman demonstrates a short essay response and reviews the peak and off-peak API rates displayed in September 2026.AI cost & performanceモデルと学習
0:22EN
Theo - t3․gg· 2026年9月12日Theo’s Take on GPT-6 Astra: A Next-Generation Model With Rough EdgesTheoTheo praises the model across coding and other tasks while warning that it can still over-engineer and get stuck in loops.モデルと学習AI cost & performanceコーディングエージェント
スライド 7 枚16:39EN
Matthew Berman· 2026年9月11日DeepSeek V4.1 Flash: Low-Cost Inference Meets Mixed Results in Practical TestsMatthew Berman · Forward FutureMatthew Berman examines DeepSeek’s efficient new open-weight model, its reported benchmarks and API pricing, then tests its speed, coding and visual work. His small set of demos reveals both impressive speed and problems with simulation accuracy.モデルと学習Open-weight modelsAI cost & performance+2
スライド 9 枚1:16:51EN
Theo - t3․gg· 2026年9月11日Fable 5.1 vs GPT-6 Astra: Theo on Coding, Computer Use and CostTheoTheo compares the models through coding projects, 3D demos and agent workflows, and explains why he uses each for different jobs.コーディングエージェントAI cost & performanceComputer use+2
1:16:00EN
20VC with Harry Stebbings· 2026年9月7日ポッドキャスト · 2 人JD Grèze on Building Town and Competing in AI Assistantsゲスト Jean-Denis Greze · ホスト Harry StebbingsTown’s co-founder discusses privacy, model costs, competition and why he prioritizes customer value over token consumption.AI agentsAI cost & performanceProduct Strategy+2
1:04:35EN
20VC with Harry Stebbings· 2026年9月5日ポッドキャスト · 2 人Cliff Weitzman on Owning GPUs, Voice AI and Building Speechifyゲスト Cliff Weitzman · ホスト Harry StebbingsSpeechify's CEO makes the case for owning part of a compute fleet, reflects on a missed business-software opportunity and discusses AI-assisted teams.インフラとデプロイ音声 AIAI cost & performance+2
スライド 10 枚13:31EN
Matthew Berman· 2026年9月4日Matthew Berman Tests GPT-6 Astra with Games and Browser TasksMatthew Berman · Forward FutureAn early-access tour shows playable prototypes, computer-use demonstrations and a sponsor’s enterprise evaluation, alongside observations about visual style and limitations.コーディングエージェントComputer useAI cost & performance+2
スライド 11 枚44:12EN
Theo - t3․gg· 2026年9月4日GPT-6 Astra: Theo’s Early Tests of Computer Use, 3D and CodingTheoTheo reviews launch-era pricing and benchmarks, shows projects built with the model, and recounts a frustrating PR-review failure.モデルと学習Computer useコーディングエージェント+2
スライド 10 枚55:06EN
Theo - t3․gg· 2026年9月3日Fable 5.1 in Practice: Theo on Costs, Agent Workflows and PR QualityTheoTheo reviews the launch, prompting guidance and his early coding experiments, including an observational comparison of pull requests.コーディングエージェントAI cost & performanceCode review & verification+2
スライド 2 枚0:24EN
Theo - t3․gg· 2026年9月3日Theo’s Low-Cost Experiment Auditing T3 Code Pull RequestsTheoTheo describes using an inexpensive model to review recently updated pull requests and proposes a recurring readiness check.Code review & verificationコーディングエージェントAI cost & performance
37:07EN
No Priors: AI, Machine Learning, Tech, & Startups· 2026年9月3日ポッドキャスト · 2 人Arm’s 98.5% margin business just started shipping chipsホスト Sarah Guo, Elad GilCEO Rene Haas tells No Priors why the IP company built a physical CPU for Meta, and why CPUs still sit at the center of AI systems.インフラとデプロイCompany BuildingAI Strategy+3
スライド 5 枚16:50EN
Matthew Berman· 2026年9月3日Gemini 3.8 Flash: Benchmarks, Cost and Hands-On Coding TestsMatthew Berman · Forward FutureMatthew Berman compares Google's September 2026 model announcement with several practical visual and web-building examples.GeminiBenchmarksAI cost & performance+2
スライド 9 枚19:08EN
Matthew Berman· 2026年9月1日Claude Fable 5.1 and Mythos 5.1: Pricing, Safeguards and Hands-On TestsMatthew Berman · Forward FutureMatthew Berman examines Anthropic’s cost claims and benchmarks, an alternative cost estimate, and his own coding and design tests.Foundation ModelsBenchmarksAI cost & performance+2
1:29:22EN
20VC with Harry Stebbings· 2026年8月29日ポッドキャスト · 2 人Eno Reyes on AI Model Economics, Enterprise Control and Factory's Strategyゲスト Eno Reyes · ホスト Harry StebbingsFactory's CTO discusses cost per outcome, model routing, open models, enterprise hiring and his expectations for the AI market.エージェント工学エンタープライズ AIAI cost & performance+2
スライド 7 枚18:57EN
Matthew Berman· 2026年8月29日GLM-5.3-Flash: Ox Alpha Benchmarks, Costs and Coding TestsMatthew Berman · Forward FutureMatthew Berman reviews Z.ai’s open-weight model, compares benchmark costs and tries coding and presentation tasks against a competing model.Open-weight modelsBenchmarksAI cost & performance+2
スライド 3 枚0:36EN
Theo - t3․gg· 2026年8月28日Theo on Ox Alpha, Revealed as GLM-5.3-FlashTheo Browne · Ping LabsTheo discusses the model’s price, multimodal inputs and Chinese-chip deployment in a short first impression.Foundation ModelsAI cost & performanceMultimodal AI+1
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