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63 件
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スライド 6 枚25:50EN
MBMatthew 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.Open-weight modelsBenchmarksAI cost & performance+1
スライド 2 枚32:20EN
MBMatthew 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.Local inferenceOpen-weight modelsAI cost & performance+1
2:00:51EN
Cognitive Revolution "How AI Changes Everything"· 2026年10月10日ポッドキャストResample Every Token and You Can Watch the Model Decideホスト Nathan LabenzGoodfire's Eric Bigelow on forking paths, in-context learning, and why chain-of-thought monitoring is getting harder to trust.エージェントPrompting & in-context learningReasoning & test-time compute+3
スライド 5 枚21:29EN
MBMatthew Berman· 2026年10月7日Mistral Large 4 Preview: European Open Weights, Cyber Benchmarks and Setup FrictionMatthew Berman · Forward FutureMatthew Berman reviews the model’s reported specifications and benchmarks, then tests it in an agent coding workflow.Open-weight modelsBenchmarksAI security+1
56:31EN
Unsupervised Learning: With Jacob Effron· 2026年10月6日ポッドキャストPost-Training Wins Inference: Why Owning the Weights Beats Betting on One Labホスト Jacob EffronApplied Compute CEO Yash Patil argues that control, private evals, and post-training on the biggest workloads matter more than fearing that frontier labs will turn malicious.モデルと学習Post-trainingReinforcement Learning+3
スライド 5 枚20:46EN
MBMatthew Berman· 2026年8月26日Open-Weight AI Models: Token Share, Spending and Strategic TradeoffsMatthew Berman · Forward FutureMatthew Berman examines a Vercel AI Gateway snapshot and argues that model usage and spending can tell very different stories.Open-weight modelsAI cost & performanceAI Strategy+2
2:06:11EN
Cognitive Revolution "How AI Changes Everything"· 2026年8月14日ポッドキャストLindy Runs on DeepSeek. Its CEO Still Wants Chinese Models Bannedホスト Nathan LabenzFlo Crivello tells Nathan Labenz how Lindy Teammate lives in Slack, reaches two billion tokens of memory in two model calls, and why he would still outlaw the cheap Chinese models that currently power the product.エージェントAgent memoryコンテキストエンジニアリング+3
2:16:29EN
Cognitive Revolution "How AI Changes Everything"· 2026年8月2日ポッドキャストFrom Two Papers a Month to Sixty: What Two Weeks in China Revealed About AI Safetyホスト Nathan LabenzNathan Labenz argues that the familiar 'China will never slow down' line does not survive contact with the actual Chinese AI safety ecosystem.セキュリティと安全性安全性とガバナンスAI security+3
スライド 5 枚52:29EN
MBMatthew Berman· 2026年7月24日Claude Opus 5: Benchmarks, Cost per Task, and Early ImpressionsMatthew Berman · Forward FutureMatthew Berman reacts to the model launch, examines reported benchmark and pricing data, and explains why the cost of completing a task matters more than token price alone.AnthropicBenchmarksAI cost & performance+2
スライド 4 枚27:13EN
MBMatthew Berman· 2026年7月21日Kimi K3 and the Debate Over Open-Weight AIMatthew Berman · Forward FutureMatthew Berman examines model economics, competition and security arguments after Moonshot AI’s Kimi K3 announcement.Open-weight modelsAI cost & performanceAI Regulation+2
1:47:38EN
Cognitive Revolution "How AI Changes Everything"· 2026年7月4日ポッドキャスト19 Neurons Can Drive a Car. Liquid AI Wants Foundation Models on Every Chipホスト Nathan LabenzRamin Hasani traces liquid neural networks from a worm's 300-cell brain to a 600-megabyte model that will talk from inside a Mercedes, and explains why architecture search now beats architecture avengers.モデルと学習Local inferenceScaling Laws+3
1:06:36EN
Unsupervised Learning: With Jacob Effron· 2026年6月12日ポッドキャストBills Doubled Overnight. Next, the APIs Might Vanish.ホスト Jacob EffronSix months after their last roundup, Ari Morcos and Rob Toews tell Jacob Efron why coding agents finally work, why near-frontier open weights may have peaked, and why a compute famine could pull the plug on public APIs.企業と戦略AI StrategyOpen-source ecosystems+3
スライド 5 枚1:42:54EN
MBMatthew Berman· 2026年5月12日AI and Cybersecurity: Matthew Berman’s Warnings, Predictions and Open QuestionsMatthew Berman · Forward FutureA livestream reviews reported AI-assisted threats and debates whether stronger defensive models can keep pace with attackers.AI securityセキュリティと安全性AI Safety+2
54:26EN
Cognitive Revolution "How AI Changes Everything"· 2026年2月22日ポッドキャストTen Billion Active Parameters, and the Unsexy Work of Making Them Agent-Readyホスト Nathan LabenzMiniMax researcher Olive Song explains how M2 was trained with expert developers as reward models, interleaved thinking, and a perturbation pipeline that treats every scaffold change as the real generalization test.コーディングエージェントReinforcement Learningエージェント工学+3
4:25:13EN
Lex Fridman· 2026年1月31日ポッドキャストThe 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.モデルと学習Scaling LawsOpen-weight models+3
1:54:30EN
Cognitive Revolution "How AI Changes Everything"· 2026年1月9日ポッドキャストFrom One in Ten Cancer Cells to One in a Millionホスト Nathan LabenzNathan Labenz's solo AMA updates his son's lymphoma treatment, calls Claude Opus 4.5 software AGI, and ranks the live players of early 2026.企業と戦略AI Strategyコーディングエージェント+3
1:18:40EN
Cognitive Revolution "How AI Changes Everything"· 2026年1月1日ポッドキャストWhen AI Becomes the Oil Well: Luke Drago on the Intelligence Curseホスト Nathan LabenzThe Workshop Labs co-founder tells the FLI Podcast why a world of non-human production could recreate the resource curse — and how private data, open weights, and moonshot careers might still break it.企業と戦略AI Strategy安全性とガバナンス+3
1:32:38EN
Cognitive Revolution "How AI Changes Everything"· 2025年12月6日ポッドキャストPolish Is 1% of Frontier Training Data, So Poland Built Its Own Modelホスト Nathan LabenzMarek Kozlowski of Poland's National Information Processing Institute explains how PLLuM uses language adaptation, organic instructions, and on-prem small models to keep a mid-size country in control of its AI.企業と戦略Open-weight modelsData quality & curation+3
1:09:48EN
Unsupervised Learning: With Jacob Effron· 2025年12月5日ポッドキャストChina's AI Labs Went From 15 to Six. The Compute Gap Is 15-to-1.ホスト Jacob EffronJordan Schneider tells Unsupervised Learning that Chinese models were a private-capital story, that Beijing still thinks in hardware, and that the West's real edge is chips it can serve — not a state master plan.企業と戦略GeopoliticsAI Strategy+3
1:25:54EN
Cognitive Revolution "How AI Changes Everything"· 2025年12月3日ポッドキャストHours after training ends, Z.ai puts the weights on the internetホスト Nathan LabenzZixuan Li of Z.ai tells ChinaTalk how a Chinese lab ships GLM, treats open weights as a ticket into Western ecosystems, and still sees itself as an upstart.企業と戦略Open-source ecosystemsOpen-weight models+3
スライド 4 枚17:51EN
MBMatthew Berman· 2025年8月28日AI News in August 2025: Claude for Chrome, New Models and AI InfrastructureMatthew Berman · Forward FutureMatthew Berman reviews a browser-agent preview, model releases, reported Apple discussions and research on inference and weather.AI agentsOpen-weight modelsGenerative media+2
スライド1:01EN
MBMatthew Berman· 2025年8月5日OpenAI’s gpt-oss Release and a Coding BenchmarkMatthew Berman · Forward FutureMatthew Berman introduces two open-weight models and reviews a Codeforces comparison from the launch.Open-weight modelsOpenAIBenchmarks+1
2:14:55EN
Cognitive Revolution "How AI Changes Everything"· 2025年7月26日ポッドキャストFrom Character AI to a 1% Warning Shot: Gabriel Weil's Case for Liability as AI Governanceホスト Nathan LabenzA Touro law professor tells Nathan Labenz how negligence, strict liability, and punitive damages could make frontier labs treat public risk as a hit to their own balance sheet.セキュリティと安全性安全性とガバナンスAI Regulation+3
スライド 16 枚23:39ZH
跟李沐学AI· 2025年7月23日李沐:给文本大模型加入一千万小时语音,开源 Higgs Audio李沐 · Boson AI李沐介绍团队如何在文本大语言模型的训练里加入大量语音数据,做成能听能说的 AudioLLM,并把 Higgs Audio 开源。他讲了架构取舍、token 压缩、数据从哪来,以及怎么在 3090 上跑起来。音声 AIMultimodal AIモデルと学習+2
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