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8 件
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スライド 9 枚13:09EN
Matthew Berman· 2026年8月14日AI News: Ultrafast Inference, Claude Watermarks and New ModelsMatthew Berman · Forward FutureMatthew Berman reviews an ultrafast coding preview, text watermarking, Grok Bot, open-weight models and Computer History.InferenceOpen-weight modelsコーディングエージェント+2
スライド 6 枚41:05EN
Matthew Berman· 2026年5月15日Anthropic’s 2028 AI Leadership Scenarios: Chips, Open Models and a Policy DebateMatthew Berman, Jensen Huang · Forward FutureMatthew Berman examines Anthropic’s US–China scenarios, questions its proposed export restrictions and argues that adoption and open-weight models matter as much as frontier capability.GeopoliticsAI RegulationSemiconductors+2
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
44:08EN
Matthew Berman· 2024年7月25日Mark Zuckerberg on Llama 3.1, Open Models and Meta’s AI StrategyMatthew Berman, Mark Zuckerberg · Forward FutureMatthew Berman reacts to Zuckerberg’s 2024 interview on open-weight AI, safety, platform control and a future of personalized agents.Open-weight modelsAI StrategyAI Safety+2
スライド 6 枚18:57EN
Matthew Berman· 2024年7月9日AI News in July 2024: Small Models, Voice Tools and OpenAI SecurityMatthew Berman, Andrej Karpathy · Forward FutureMatthew Berman reviews AI product announcements, model evaluation and security reporting, and shares his predictions about the future of computing.AI researchモデルと学習AI security+2
3:37EN
Matthew Berman· 2024年1月18日Mark Zuckerberg Announces Llama 3 Training and Meta’s AI PlansMatthew Berman, Mark Zuckerberg · Forward FutureIn January 2024, Matthew Berman reacts to Zuckerberg’s remarks on general intelligence, compute and AI devices.Open-weight modelsAI Historyインフラとデプロイ+1
スライド 5 枚59:36EN
Matthew Berman· 2023年6月27日Pascal Pfeiffer on Retrieval, Open Models, Kaggle and Fine-Tuning with H2O LLM StudioMatthew Berman, Pascal Pfeiffer · Forward FutureIn a 2023 interview, H2O.ai’s Pascal Pfeiffer explains document retrieval and parameter-efficient fine-tuning, reflects on Kaggle competitions and demonstrates LLM Studio. He and Matthew Berman also consider coding assistants and unverified rumors about model architecture.ファインチューニング検索拡張生成(RAG)Open-weight models+2
1:13:52EN
Matthew Berman· 2023年4月15日Andriy Mulyar on GPT4All, Data Quality and Open Local ModelsMatthew Berman, Andriy Mulyar · Forward FutureThe Nomic AI co-founder explains how GPT4All emerged, why training data matters, and the tradeoffs between local and centralized AI.Local inferenceOpen-weight modelsData quality & curation+2