楊衣終於開了推特啦~~ 第一篇文就給小玉了! ついにTwitterを使い始めました 最初の記事はに捧げられています玉藻の前 Finally started using Twitter The first article is dedicated to Tamamo no Mae #玉藻前# #玉藻の前# #小玉# #FGO# #迦勒底的夏日#

# Learning Palantir Foundry 🚀 Put business logic right on the ontology. Functions cure the "numbers don't match across departments" problem by centralizing logic in one place. 📌 Title and Feature URL Title: ファンクション URL: 📝 Overview Functions let you write server-side logic that executes in isolated environments, powering operational apps like dashboards and decision-support tools. They are designed to work with Foundry ontologies, so they can read object properties, traverse links, and perform flexible ontology edits. 🔧 How It Works - Supported languages: TypeScript (full feature support) and Python (beta, with growing support especially for serverless and deployed execution). - Serverless execution: spins up on demand when invoked and bills only during execution, with a 60-second total wall-clock timeout (30s CPU plus a 30s network buffer). Multiple versions can run simultaneously, making upgrades safer. - Deployed execution: reserves dedicated resources for cases serverless cannot meet, runs a single version at a time, and bills continuously while deployed. - Capability differences: ontology read/write, Workshop integration, and external API calls work in both languages. Pipeline Builder is Python, while model embedding and semantic search are TypeScript. 🛠 Practical Usage - Derived properties: display function-computed values as table columns. - Function-backed Actions: implement complex edits spanning multiple objects. - Workshop integration: run functions to compute or display variables. - API gateway: invoke query functions programmatically to reuse the same logic everywhere. 🎯 Use Cases - Implement derived-KPI logic once and return identical results to Workshop, OSDK, and the API. - Query external systems to enrich ontology objects. - Build complex validation or bulk updates as function-backed Actions. ⚠️ Caveats - The 60-second timeout applies uniformly across execution modes, so optimize for efficiency. - Available capabilities depend on the invocation context (for example, model embedding and semantic search are TypeScript only), so decide on language early. #PalantirFoundry# #DataEngineering#

Sakana AI CEOの David Ha（@hardmaru）が、Tim Romero 氏のポッドキャスト Disrupting Japan Podcast に出演しました。 日本におけるAIの未来は、米国や中国とは少し違った形を取り得るのか。Sakana AIの内側から何が見えているのか。そうしたテーマで、長めの対談を行っています。 Davidは、Sakana AI の事業展開戦略、メガバンクとの取り組みがPoCから本番運用へと進みつつある現状、巨大なフロンティアモデル一つに依存するよりも複数のモデルを束ねるオーケストレーションのほうが長期的には合理的であるという見方、そして実務における「AI主権」とはスタック全体を自前で所有することではなく、グローバルなサプライチェーンの中で、AIを国内で開発・適応・運用していく能力を確保することだと、Davidは語りました。 対話のなかでは、当社の研究成果やプロダクトにも多く触れました。Sakana Fuguは、強化学習で訓練したオーケストレーションモデルで、複数ステップのタスクを多様なLLMに振り分けます。Namazuは、日本の知識や価値観を反映するようにポストトレーニングを施した、オープンウェイトモデルのシリーズです。東京のRSI Labは、The AI Scientistから続く取り組みとして、再帰的自己改善とAIによる科学的発見を専門に扱う研究組織です。共同創業者のLlion Jonesは、Transformerそのものを超えるアーキテクチャの探求という、より長期的な目標を追い続けています。 最後に「日本について一つだけ変えられるとしたら」と問われたDavidの答えは、「希望（hope）」でした。 「皆が集団として希望を感じていることが必要だと思います。その希望こそが、物事を動かしていく。日本に希望をもたらすのは何でしょうか。お金でしょうか。減税でしょうか。社会保障の充実でしょうか。おそらく、そのどれでもないはずです。もし魔法の杖を一本持てるとしたら、日本の人々が未来をもっと楽観的に捉えられるようにしたい。希望によって変化が起こり、その変化がさらなる希望をもたらすのではないでしょうか。」 ⸻⸻⸻⸻⸻⸻ Our CEO David Ha joined Tim Romero on Disrupting Japan Podcast for a long conversation on how the future of AI may take a different shape in Japan than in the U.S. or China, and on what that looks like from inside Sakana AI. David walks through Sakana AI’s go-to-market strategy, how Japanese megabanks have moved real AI workflows from proof-of-concept into production, why orchestration across many models is likely to win out over a single massive frontier model, and what sovereign AI actually means in practice: not owning the entire stack, but having the capability to develop, adapt, and run AI domestically as part of a global supply chain. The conversation also covers the research directions behind the company. Sakana Fugu is our orchestration model, trained with reinforcement learning to route multi-step tasks across a variety of underlying LLMs. Namazu is our line of post-trained open-weight models tuned to reflect Japanese knowledge and values. The RSI Lab in Tokyo is dedicated to recursive self-improvement and AI-driven scientific discovery, continuing the work that began with The AI Scientist. And our co-founder Llion Jones keeps pushing on a longer-horizon goal of moving beyond the Transformer architecture itself. Asked at the end what one thing he would change about Japan, David’s answer was “hope.” “To really move the needle in terms of innovation, like the era in Japan when you have companies like Sony or Panasonic come out, there are a few factors. One is that the nation needs to have a collective sense of hope. A nation needs to feel hopeful. It could be poor. Everyone can be dirt poor, but they have hope. And that hope leads to things being done. So, what creates hope in Japan? Is it more money? Is it less taxes? Or is it more benefits? Probably not. I think it’s stories and narratives. If I have a magic wand, if the population in Japan is more optimistic about the future of this country, suddenly they’re persuaded, to be more optimistic. People should be optimistic. With optimism comes change. And change leads to more optimism.” Listen to the full episode: 🎏