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AI Frontier with Prof. Mick Etoh (at U. Osaka)
micknerd
6 episodes
6 days ago
Hosted by Prof. Mick Etoh(AE-TOE), a professor at Osaka University working on innovation management across industry and academia. This podcast bridges Generative AI/LLMs, natural language processing, product and interface design, standardization, and deep-tech entrepreneurship. Expect clear explanations, decision-making frameworks, and candid lessons from building companies, advising large-scale LLM efforts, and leading R&D and innovation functions—so listeners can move from “AI news” to “AI strategy and execution.”
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Technology
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All content for AI Frontier with Prof. Mick Etoh (at U. Osaka) is the property of micknerd and is served directly from their servers with no modification, redirects, or rehosting. The podcast is not affiliated with or endorsed by Podjoint in any way.
Hosted by Prof. Mick Etoh(AE-TOE), a professor at Osaka University working on innovation management across industry and academia. This podcast bridges Generative AI/LLMs, natural language processing, product and interface design, standardization, and deep-tech entrepreneurship. Expect clear explanations, decision-making frameworks, and candid lessons from building companies, advising large-scale LLM efforts, and leading R&D and innovation functions—so listeners can move from “AI news” to “AI strategy and execution.”
Show more...
Technology
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AIチームを機能させる設計思想とコードの役割
AI Frontier with Prof. Mick Etoh (at U. Osaka)
15 minutes
1 week ago
AIチームを機能させる設計思想とコードの役割
Webブラウザ版とは異なり、API経由ではLLMが自動的に役割を分担しないため、**開発者がコードを通じて各エージェントを制御・統合する「オーケストレーション」**の重要性を強調しています。具体的には、解析、ドラフト作成、検証といった工程ごとに、Gemini、GPT-5、Claudeなどの異なるモデルを最適に使い分ける戦略が提案されています。また、コンテキストの分離や構造化データの活用により、ハルシネーションを抑制しつつ法務実務に耐えうる精度を実現する手法が詳述されています。最終的に、**人間による介入(Human-in-the-loop)**や最新のSDKを組み合わせることで、堅牢なリーガルテック基盤を構築できると結論付けています。
AI Frontier with Prof. Mick Etoh (at U. Osaka)
Hosted by Prof. Mick Etoh(AE-TOE), a professor at Osaka University working on innovation management across industry and academia. This podcast bridges Generative AI/LLMs, natural language processing, product and interface design, standardization, and deep-tech entrepreneurship. Expect clear explanations, decision-making frameworks, and candid lessons from building companies, advising large-scale LLM efforts, and leading R&D and innovation functions—so listeners can move from “AI news” to “AI strategy and execution.”