Robinhood’s OpenAI stunt just backfired

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🪙 Robinhood’s OpenAI Tokens Ignite Controversy Across Crypto and Equity Lines

European investors were surprised this week as Robinhood launched “tokenized stocks” tied to OpenAI, without the company’s consent. Framed as a way to democratize access to private equity, the move drew a sharp rebuke from OpenAI, which made clear these tokens are neither equity nor approved. 

The Decode:

1. Robinhood launches tokenized OpenAI shares in Europe - Robinhood offered €5 worth of tokenized shares in OpenAI and SpaceX to European users as part of a crypto promo. The tokens track the value of private shares via blockchain but don’t confer ownership. 

2. OpenAI responds with sharp denial and legal warning - OpenAI issued an urgent statement denying any partnership, approval, or endorsement of the token sale. The company emphasized that “OpenAI tokens are not OpenAI equity” and that any transfer of stock requires its direct approval. 

3. How the tokens actually work - Robinhood clarified that the tokens reflect ownership in a Special Purpose Vehicle (SPV) that holds shares, not the shares themselves. These SPVs can diverge in value from real equity and are not authorized by the companies in question. 

Robinhood is blurring the line between real equity and speculative assets by offering tokens tied to private companies without their approval. Robinhood CEO Vlad Tenev calls it “a seed for something bigger,” but these tokens don’t grant actual ownership.

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🤖 Sakana AI Proves Smarter Isn’t Solo: A New Era of Collaborative AI

Sakana AI’s new AB-MCTS algorithm flips the AI game, instead of relying on one frontier model, it lets multiple AIs like ChatGPT, Gemini, and DeepSeek collaborate in real time to solve complex problems. 

The Decode:

1. AI Teamwork Outperforms Solo Models - AB-MCTS uses adaptive search to let different AI models handle specific roles, boosting ARC-AGI-2 performance from 23% to 30%. One model might handle logic, another code, and each plays to its strengths. 

2. Error Correction Through Collaboration - Researchers found models could fix each other’s mistakes mid-process, turning flawed outputs into correct answers. This feedback loop mimics human peer review and accelerates problem-solving.

3. Open-Source Framework Unlocks DIY Collective AI - Sakana released “TreeQuest,” the tool powering this collaboration, for anyone to build with. It’s designed to make orchestrating multi-AI systems simple and modular. 

Instead of betting on one giant model, Sakana is proving that many minds, even artificial ones, work better together. Collective intelligence could be the key to solving AI’s hardest unsolved puzzles. And now, anyone can experiment with that future.

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⚡OpenAI is expanding its Stargate partnership with Oracle, securing approximately 4.5 gigawatts of U.S. data center power.

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