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899 件
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スライド0:59EN
Matthew Berman· 2025年2月13日What Is Vibe Coding? Matthew Berman Explains His WorkflowMatthew Berman · Forward FutureBerman describes using voice input and an AI coding editor to build software, test it, and feed errors back without reading the code.Vibe Codingコーディングエージェント開発ワークフローとテスト
スライド 3 枚6:50EN
Matthew Berman· 2025年2月12日DeepScaleR: A Small Reasoning Model Tested on Competition MathMatthew Berman · Forward FutureMatthew Berman reviews a 1.5B model’s reported benchmark results and runs a quantized version locally on one AIME problem.Reinforcement LearningBenchmarksLocal inference+2
スライド 3 枚21:10EN
Matthew Berman· 2025年2月11日Sam Altman’s 2025 AI Coding Forecast and Three ObservationsMatthew Berman, Sam Altman · Forward FutureMatthew Berman examines predictions about reasoning models, software agents and AI economics, distinguishing competitive-programming results from broader work.コーディングエージェントScaling LawsReinforcement Learning+2
スライド 5 枚10:01EN
Matthew Berman· 2025年2月5日DeepSeek R1 Code Optimization and a $3 Visual Counting ExperimentMatthew Berman · Forward FutureMatthew Berman examines a human-guided coding improvement and a small reinforcement-learning experiment, then considers their implications for AI research.Reinforcement LearningGPU programming & kernelsAI research+2
スライド13:04EN
Matthew Berman· 2025年2月4日Deep Research, AI Takeoff and the Limits of Early ReactionsMatthew Berman, Sam Altman · Forward FutureMatthew Berman surveys February 2025 reactions to OpenAI’s research agent and argues that reasoning and tools could accelerate AI progress.AI agentsAGI TimelinesBenchmarks+2
スライド 5 枚12:07EN
Matthew Berman· 2025年2月2日TinyZero: A $30 Reinforcement-Learning Experiment on a Small Arithmetic TaskMatthew Berman · Forward FutureMatthew Berman explains how a pretrained Qwen model learned to search and check answers in Countdown, and why the experiment does not recreate DeepSeek-R1.Reinforcement LearningReasoning & test-time computeAI research+2
スライド 7 枚9:58EN
Matthew Berman· 2025年2月1日Matthew Berman Tests o3-mini on Games, Puzzles and Web SearchMatthew Berman · Forward FutureA 2025 hands-on test finds working game prototypes and several successful answers alongside a delayed Tetris row, an ambiguous puzzle and a search configuration mistake.評価(Evals)コーディングエージェントReasoning & test-time compute+2
スライド 3 枚6:44EN
Matthew Berman· 2025年2月1日Testing DeepSeek Janus-Pro for Image Understanding and GenerationMatthew Berman · Forward FutureMatthew Berman tries the 7B multimodal model on diagrams, memes and image prompts using a sponsored cloud GPU demonstration.画像と動画Generative mediaMultimodal AI+2
スライド 6 枚24:22EN
Matthew Berman· 2025年1月31日Dario Amodei on DeepSeek, AI Costs and Chip Export ControlsMatthew Berman, Jonathan Ross, David Sacks · Forward FutureMatthew Berman examines the Anthropic CEO’s 2025 essay, the limited evidence behind distillation allegations and the economics of model training.モデルと学習AI cost & performanceGeopolitics+2
スライド 4 枚9:58EN
Matthew Berman· 2025年1月31日OpenAI o3-mini Launch: Reasoning Effort, Benchmarks and a Snake TestMatthew Berman · Forward FutureIn January 2025, Matthew Berman reviews OpenAI’s reported results and tries two coding examples with different reasoning settings.OpenAIReasoning & test-time computeBenchmarks+1
スライド 5 枚7:41EN
Matthew Berman· 2025年1月30日CES 2025 and Running DeepSeek R1 Distills on an RTX 5090Matthew Berman · Forward FutureMatthew Berman tours AI demonstrations at CES and runs two quantized DeepSeek R1 distilled models locally on an NVIDIA GPU.Local inferenceOpen-weight modelsSemiconductors+2
1:50EN
Matthew Berman· 2025年1月30日Five AI Trends Discussed by Coveo’s Sébastien PaquetMatthew Berman · Forward FutureMatthew Berman summarizes a 2025 interview on production systems, smaller models, agents and trust.エンタープライズ AIエージェントモデルと学習+1
スライド0:52EN
Matthew Berman· 2025年1月29日Genie 2 Generates Interactive Worlds for AI ResearchMatthew Berman · Forward FutureMatthew Berman explains why Google DeepMind’s image-conditioned world model could help researchers create environments for agents, while the early demonstrations have clear limits.World modelsGenerative mediaRobotics
スライド 3 枚5:27EN
Matthew Berman· 2025年1月29日Ways to Try DeepSeek R1: Hosted and Local Distilled ModelsMatthew Berman · Forward FutureMatthew Berman demonstrates DeepSeek chat, Groq’s hosted distill and a local model in LM Studio.Local inferenceOpen-weight modelsQuantization
スライド 4 枚20:34EN
Matthew Berman· 2025年1月28日DeepSeek R1 and the Debate Over AI Costs and ComputeMatthew Berman · Forward FutureMatthew Berman examines 2025 reactions to DeepSeek, from training efficiency and market losses to open weights, privacy and the possibility of a demand rebound.モデルと学習AI cost & performanceOpen-weight models+2
スライド16:45EN
Matthew Berman· 2025年1月27日DeepSeek-R1 and the Debate Over AI Costs and ComputeMatthew Berman · Forward FutureMatthew Berman examines the January 2025 reaction to an open-weight reasoning model, disputed cost claims and competing views of future demand for AI chips.Foundation ModelsReasoning & test-time computeOpen Source+1
スライド 4 枚14:55EN
Matthew Berman· 2025年1月25日How the Industry Reacted to OpenAI Operator in 2025Matthew Berman · Forward FutureMatthew Berman reviews early views on browser agents, their limitations, competing projects and examples of delegated tasks.AI agentsComputer useOpenAI+2
スライド0:55EN
Matthew Berman· 2025年1月23日A Quick RTX 5090 Local AI TestMatthew Berman · Forward FutureMatthew Berman runs an 8B DeepSeek R1 distillation locally and reports the speed of one generation.Local inferenceSemiconductorsOpen-weight models
スライド 5 枚37:58EN
Matthew Berman· 2025年1月23日OpenAI Operator’s 2025 Launch: Browser Tasks, Human Control and LimitsMatthew Berman, Sam Altman · Forward FutureMatthew Berman watches the early Operator demonstration, from restaurant bookings and groceries to safety controls and benchmark results.Computer useエージェントAI Safety+1
スライド 4 枚15:10EN
Matthew Berman· 2025年1月22日DeepSeek R1 Tested on Coding, Reasoning and Sensitive QuestionsMatthew Berman · Forward FutureMatthew Berman runs the full R1 model on cloud GPUs and tries game programming, reasoning puzzles and politically sensitive prompts.Reasoning & test-time compute評価(Evals)Open-weight models+2
スライド 2 枚7:57EN
Matthew Berman· 2025年1月22日Stargate’s 2025 Announcement and the OpenAI–Microsoft PartnershipMatthew Berman · Forward FutureMatthew Berman reviews the planned US AI infrastructure project and a contemporaneous change to compute arrangements.インフラとデプロイOpenAIAGI(汎用人工知能)+1
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 3 枚12:15EN
Matthew Berman· 2025年1月20日DeepSeek-R1: Open-Weight Reasoning, Benchmark Results and a First TestMatthew Berman · Forward FutureMatthew Berman examines DeepSeek’s January 2025 release, compares reported benchmarks and prices, and tries a handful of reasoning prompts.Reasoning & test-time computeOpen-weight modelsReinforcement Learning+2
スライド 3 枚16:25EN
Matthew Berman· 2025年1月18日Why Test-Time Compute Could Reshape AI InferenceMatthew Berman, Lisa Su, Jensen Huang · Forward FutureMatthew Berman explains how extra computation at inference can improve model outputs, and why hardware executives expect a much larger inference market.AI researchモデルと学習AI cost & performance+1
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