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39 件
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スライド 5 枚7:26EN
Matthew Berman· 2026年9月23日GPT-6 Sol and Luna: Price and Benchmark Trade-offsMatthew Berman · Forward FutureMatthew Berman examines OpenAI’s September 2026 launch, comparing API prices and reported agent benchmarks with larger models.OpenAIAI cost & performanceBenchmarks+2
スライド 15 枚1:05:23EN
Matthew Berman· 2026年9月3日Matthew Berman Tests GPT-6 Astra: Benchmarks, Browser Agents and GamesMatthew Berman · Forward FutureAn early-access tour compares model benchmarks and pricing with practical browser workflows, presentations and a wide range of generated games.OpenAIFoundation ModelsBenchmarks+2
スライド 5 枚15:37EN
Matthew Berman· 2026年8月4日Matthew Berman on Qwen3.8-Max, AI Costs and Open-Weight CompetitionMatthew Berman · Forward FutureA 2026 review of reported benchmark results and research demonstrations leads to questions about deployment economics and geopolitical dependence.Open-weight modelsBenchmarksAI cost & performance+2
スライド 5 枚52:29EN
Matthew 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 10 枚1:42:41EN
Matthew Berman· 2026年5月1日Testing AI Reasoning, App Store Lookalikes and the Debate Over AnthropicMatthew Berman · Forward FutureIn a May 2026 livestream, Matthew Berman tests a car-wash prompt, discusses AI subscription limits and considers reported employee monitoring for model training.AI agentsBenchmarksPrompting & in-context learning+2
スライド 6 枚18:07EN
Matthew Berman· 2026年4月16日Claude Opus 4.7: Benchmarks, Cyber Safeguards and Open QuestionsMatthew Berman · Forward FutureMatthew Berman compares Anthropic’s April 2026 Opus release with the limited Mythos Preview and examines its system card.AnthropicBenchmarksAI Safety+2
スライド 5 枚9:47EN
Matthew Berman· 2026年4月3日Gemma 4: Smaller Open-Weight Models for Local AIMatthew Berman · Forward FutureMatthew Berman reviews Google’s model sizes, multimodal features and reported benchmarks, with an eye toward local agents.Open-weight modelsLocal inferenceFoundation Models+2
スライド0:37EN
Matthew Berman· 2026年2月20日Gemini 3.1 Pro: A Look at the Reported Benchmark ScoresMatthew Berman · Forward FutureMatthew Berman reacts to a Gemini 3.1 Pro comparison and highlights results on Humanity’s Last Exam.GeminiBenchmarksFoundation Models
スライド 9 枚11:49EN
Matthew Berman· 2026年2月17日Matthew Berman Reviews Claude Sonnet 4.6: Benchmarks, Computer Use and SafetyMatthew Berman · Forward FutureA launch-day overview examines Anthropic’s reported knowledge-work and agent results, along with prompt-injection and capability evaluations.AnthropicFoundation ModelsBenchmarks+2
スライド 2 枚1:11EN
Matthew Berman· 2025年11月18日Gemini 3's Launch: Benchmarks, Antigravity, and AgentsMatthew Berman · Forward FutureMatthew Berman summarizes Google's November 2025 model launch and its developer and assistant demos.GeminiBenchmarksコーディングエージェント+1
スライド 6 枚13:53EN
Matthew Berman· 2025年10月10日Tiny Recursive Models and the Limits of Puzzle Benchmark ComparisonsMatthew Berman · Forward FutureMatthew Berman examines a small recursive network that reports strong ARC and Sudoku results, and what its experimental setup means.AI researchBenchmarksReasoning & test-time compute+1
スライド 4 枚8:47EN
Matthew Berman· 2025年9月16日Why Identical LLM Prompts Can Produce Different Answers at Temperature ZeroMatthew Berman · Forward FutureMatthew Berman explains Thinking Machines Lab’s work on batch-invariant inference and what its reproducibility experiment actually showed.InferenceAI researchオブザーバビリティと信頼性+1
スライド 7 枚15:13EN
Matthew Berman· 2025年5月10日Absolute Zero: Training a Reasoner on Self-Generated Coding TasksMatthew Berman · Forward FutureMatthew Berman examines a 2025 paper in which a pretrained language model proposes and solves code tasks using verifiable feedback.Reinforcement LearningSynthetic dataReasoning & test-time compute+2
スライド0:34EN
Matthew Berman· 2025年5月1日DeepSeek-Prover-V2 and Its Formal Math ResultsMatthew Berman · Forward FutureMatthew Berman highlights DeepSeek’s reported theorem-proving results on miniF2F, PutnamBench and formalized AIME problems.MathematicsAI researchBenchmarks+1
スライド 7 枚14:04EN
Matthew Berman· 2025年4月29日Qwen3: Open Weights, Adjustable Reasoning and Tool UseMatthew Berman · Forward FutureMatthew Berman reviews the April 2025 Qwen3 family, its benchmark claims, training pipeline and local demonstration.Open-weight modelsモデルと学習Reasoning & test-time compute+2
スライド 7 枚15:15EN
Matthew Berman· 2025年4月19日Early Reactions to OpenAI o3 and o4-mini: Tool Use, Math and MistakesMatthew Berman · Forward FutureMatthew Berman reviews 2025 demos and benchmark reports, from location guessing and coding to simple failures that challenge the hype.OpenAIBenchmarksReasoning & test-time compute+2
スライド 3 枚7:33EN
Matthew Berman· 2025年4月4日Ace Computer-Use Agent: Fast Desktop and Browser DemonstrationsMatthew Berman · Forward FutureMatthew Berman reviews General Agents’ examples and reported click accuracy and latency, while noting he has not yet tested Ace himself.Computer useエージェントBenchmarks
スライド 6 枚11:31EN
Matthew Berman· 2025年3月29日AI News in March 2025: GPT-4o, Gemini, DeepSeek and MCPMatthew Berman · Forward FutureMatthew Berman reviews model updates, the ARC-AGI-2 benchmark, image generators and early adoption of Model Context Protocol.Foundation ModelsBenchmarksMCP+2
スライド 5 枚8:52EN
Matthew Berman· 2025年1月21日Industry Reactions to DeepSeek R1’s 2025 ReleaseMatthew Berman · Forward FutureMatthew Berman reviews early reactions to DeepSeek R1, from open-weight reasoning models and local hardware to benchmark results and API pricing.Open-weight modelsReasoning & test-time computeBenchmarks+2
スライド 6 枚21:02EN
Matthew Berman· 2024年12月24日Reactions to OpenAI’s 2024 o3 Preview: Benchmarks, Cost and LimitsMatthew Berman · Forward FutureMatthew Berman surveys the responses to the o3 preview, from mathematical benchmarks to debates about AGI, compute and reliability.BenchmarksReasoning & test-time computeAGI(汎用人工知能)+2
スライド 3 枚9:00EN
Matthew Berman· 2024年12月20日Best-of-N Jailbreaking: What Repeated Prompt Variations Revealed in 2024Matthew Berman · Forward FutureMatthew Berman reviews research on how repeated input variations can expose safety failures in text, vision and audio models.Agent red teamingAI SafetyMultimodal AI+2
スライド 6 枚26:43EN
Matthew Berman· 2024年10月10日Testing OpenAI o1 on Planning, Rules and Spatial ReasoningMatthew Berman · Forward FutureMatthew Berman reviews a 2024 pilot study comparing o1-preview, o1-mini and GPT-4 on six planning domains.評価(Evals)Reasoning & test-time computeAI research+2
スライド 6 枚18:09EN
Matthew Berman· 2024年9月17日AI News in September 2024: Copilot, NotebookLM, o1 and World ModelsMatthew Berman · Forward FutureMatthew Berman reviews a week of AI announcements, from workplace assistants and audio overviews to benchmark results, generative video and spatial AI.AI researchAI agentsGenerative media+2
スライド 8 枚21:21EN
Matthew Berman· 2024年9月12日OpenAI o1’s 2024 Launch: Reasoning Benchmarks and Early TestsMatthew Berman · Forward FutureMatthew Berman reviews o1-preview and o1-mini, OpenAI’s reported evaluations, and his own early coding experiments.OpenAIReasoning & test-time computeBenchmarks+2
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