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研究人員啟動 40 億美元計畫研發自我改進 AI

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📰閱讀原文： New York Times Technology
#agi#automated-research#funding#recursive-airecursive-superintelligencegooglemetaopenairecursive superintelligence

💡前科技巨頭研究人員投入 40 億美元賭 AI 能自我進化。了解他們如何實現研發週期的自動化。

⚡ 30-Second TL;DR

有什麼變化

Recursive Superintelligence 由前 Google、Meta 和 OpenAI 的研究人員創立。

為什麼重要

此舉標誌著 AI 領域向「遞迴自我改進」邁出重要一步，可能加速通往 AGI 的進程。這凸顯了業界致力於減少模型訓練生命週期中對人類依賴的趨勢。

下一步行動

密切關注 Recursive Superintelligence 發布的白皮書，以了解他們在自動化模型架構搜尋方面的技術路徑。

誰應關注：Researchers & Academics

關鍵要點

  • •Recursive Superintelligence 由前 Google、Meta 和 OpenAI 的研究人員創立。
  • •獲得 40 億美元資金，專注於開發自我改進的 AI 系統。
  • •核心目標是實現人工智慧創建與擴展過程的自動化。

🧠 深度解析

Web-grounded analysis with 13 cited sources.

🔑 增強重點摘要

  • •Recursive Superintelligence (RSI) was co-founded by Richard Socher, former chief scientist at Salesforce, and Tim Rocktäschel, an AI professor at University College London and former Google DeepMind scientist.
  • •The company, incorporated in London approximately four months prior to April 2026, has secured between $500 million and $650 million in seed funding, not $4 billion, which is its reported valuation.
  • •The funding round was led by Google Ventures (GV) and Greycroft, with additional investment from chipmakers Nvidia and AMD Ventures.
  • •RSI's core mission is to develop AI systems that can autonomously improve their own architecture, training methods, evaluation processes, and research direction without continuous human oversight.
  • •The company, currently operating with a team of less than 30 researchers and engineers across offices in London and San Francisco, remains in the research phase and has not yet launched commercial products or generated revenue.

🛠️ 技術深入

  • RSI's approach centers on recursive self-improvement through open-ended algorithms to drive continuous innovation.
  • The foundational architecture is based on the transformer model, optimized for context-aware language processing, multi-modal data integration, and recursive learning.
  • The company aims to automate the entire AI development pipeline, including improving its own architecture, training methods, evaluation processes, and research direction.
  • Key areas of expertise within the team include open-ended algorithms, quality diversity algorithms, AI-generating algorithms, self-improving coding agents, automated red teaming, capability discovery, prompt engineering automation, foundational world models, deep learning in NLP, vision transformers, and retrieval-augmented generation.
  • RSI plans to run its first "Level 1" autonomous training system, indicating a phased approach to achieving full self-improvement.

🔮 前景展望AI analysis grounded in cited sources

Recursive Superintelligence will significantly accelerate the pace of AI development beyond current human-driven methods.
By automating the entire AI development pipeline, including research and architecture design, RSI aims to create a positive feedback loop that compounds improvements faster than human-led efforts.
The success of Recursive Superintelligence could lead to an 'intelligence explosion' as theorized by early AI pioneers.
The concept of recursive self-improvement inherently suggests a rapid, exponential increase in AI capabilities, potentially leading to superintelligence that far surpasses human understanding and control.
The development of self-improving AI systems like those pursued by Recursive Superintelligence will necessitate new paradigms for AI safety and governance.
The potential for unforeseen evolution and surpassing human control in self-improving systems raises significant ethical and safety concerns, requiring robust safeguards and regulatory frameworks.

⏳ 時間線

2025-12
Recursive Superintelligence Inc. incorporated in London.
2026-04-18
Reports begin to surface about Recursive Superintelligence raising at least $500 million at a $4 billion valuation.
2026-05-13
Recursive Superintelligence officially emerges from stealth, announcing it has raised over $650 million at a $4.65 billion valuation.
📰閱讀原文： New York Times Technology
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