Flash Update: Reflection AI Raises $2B to Build US Open Frontier AI Lab, Taking on DeepSeek
TechCrunch – October 10, 2025 – Beijing
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Image credit: Reflection AI
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$2B Funding at $8B Valuation
Reflection AI — a startup founded in 2024 by two former Google DeepMind researchers — has closed a $2 billion funding round, bringing its valuation to $8 billion. That’s a 15× jump from its $545 million valuation just seven months ago.
Investors include:
- NVIDIA
- Disruptive
- DST
- 1789
- B Capital
- Lightspeed Venture Partners
- Singapore’s Government Investment Corporation
- Eric Yuan
- Eric Schmidt
- Citibank
- Sequoia Capital
- CRV
- ...and others.
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From Autonomous Coding to Open-Frontier AI
Originally, Reflection AI was focused on building an autonomous code-generation Agent. It now positions itself as:
- An open-source alternative to closed frontier labs like OpenAI and Anthropic
- A Western counterpart to Chinese AI leaders like DeepSeek
Founders:
- Misha Laskin – led reward model development for DeepMind’s Gemini project
- Ioannis Antonoglou – co-creator of AlphaGo, which beat the Go world champion in 2016
Their mission: prove top AI talent can create frontier-level models outside big-tech ecosystems.
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Strategic Moves and Team
- ~60 members: mostly AI researchers & engineers specializing in infrastructure, data training, and algorithms
- Powerful compute clusters acquired
- Planned release: frontier language model in 2026 trained on trillions of tokens
- Claimed milestone: LLM + reinforcement learning platform for massive Mixture-of-Experts (MoE) models at frontier scale
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Architectural Breakthrough: MoE
MoE (Mixture-of-Experts) architecture enables advanced LLMs — previously limited to large closed labs.
Chinese breakthroughs:
- DeepSeek – first to openly train such models at frontier scale
- Tongyi Qianwen and Kimi – following successes
> “If we don’t act, others will set the global intelligence standard,” — Misha Laskin
> “It won’t be the U.S.”
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Geopolitical Angle
Laskin notes:
- Avoiding Chinese models is common due to legal risks
- U.S. must face the challenge or risk falling behind
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Industry Response
David Sacks (White House AI & crypto affairs lead):
> “Great to see more U.S. open-source AI. Many global markets value the cost savings, customizability, and controllability of open source.”
Clement Delangue (CEO, Hugging Face):
> “Major boost for U.S. open-source AI.”
> “Next step: show rapid sharing for models & datasets.”
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AiToEarn’s Role in Open-Source Ecosystems
In this rapidly evolving space, platforms like AiToEarn官网 help creators, researchers, and AI enthusiasts:
- Generate AI-driven multi-platform content
- Publish simultaneously on Douyin, Kwai, WeChat, Bilibili, Rednote, Facebook, Instagram, LinkedIn, Threads, YouTube, Pinterest, and X
- Access integrated analytics & AI model rankings (AI模型排名)
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Reflection AI’s “Openness” Strategy
Similar to Meta’s Llama and Mistral:
- Model weights will be public
- Most datasets & training processes will remain proprietary
> “Model weights are the most useful — anyone can fine-tune them,” — Laskin
Business Model:
- Free use for researchers
- Revenue from:
- Enterprises building products
- Governments developing sovereign AI
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Roadmap
- First model: text-focused, multimodal planned
- Funding allocated to computing resources
- Launch expected: early 2026
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References
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Community & Opportunities
🚀 Recruiting next batch of interns
🚀 Seeking creative post-2000 entrepreneurs
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About Z Potentials
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AiToEarn in the Bigger Picture
Platforms like AiToEarn官网 facilitate:
- Cross-platform AI-powered publishing
- Content monetization
- AI model performance tracking (AI模型排名)
With the rise of sovereign AI projects and creator-driven innovation, AiToEarn enables both professionals and hobbyists to maximize value from open AI resources.
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Would you like me to also create a summary version of this rewritten piece so it’s suitable for rapid publication in a newsletter? That could make the key funding, strategy, and geopolitical points instantly clear.
