Observed Signal · Jul 25, 2023 · M&A - Announced · Source: Trending Topics · Impact: 4/5 · Sentiment: Positive
Hololens: US Army wagt zweiten Anlauf mit AR-Headset von Microsoft
Nvidia announced it is acquiring Hugging Face, the platform hosting a large share of the world's open AI models, for $12.9303 billion. Nvidia CEO Jensen Huang confirmed the deal in a blog post, saying Hugging Face's 18 million developers, three million models, and 200,000 corporate users need Nvidia's infrastructure to scale. Huang pledged that Hugging Face will remain an open platform, that Nvidia compute will not be required, and that the brand and team will remain. Nvidia was already an investor in Hugging Face's last funding round, which valued the company at $4.5 billion. The transaction has not closed yet and is expected to face antitrust review. The acquisition extends Nvidia's position in AI infrastructure and its CUDA ecosystem by adding a central distribution channel for open-weight models.
The acquisition of Hugging Face, a central hub for open AI models, by the dominant AI chip maker reshapes AI infrastructure and could affect how AI models are distributed and accessed across the broader AdTech/MarTech ecosystem.
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Key Takeaways & Evidence Grounding
- Nvidia announced the acquisition of Hugging Face for $12.9303 billion.
- Hugging Face hosts more than 3 million AI models, 500,000 datasets, and 1 million applications, used by over 18 million developers and 200,000 companies.
- Nvidia CEO Jensen Huang confirmed the deal, pledging Hugging Face will remain an open platform and that Nvidia compute will not be mandatory.
- The previous major funding round valued Hugging Face at $4.5 billion and included investors such as Salesforce, Google, Amazon, AMD, Intel, Qualcomm, and IBM.
- The deal is not yet finalized and is expected to face antitrust review.
Connected Companies & Entities
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“Intel participated in Hugging Face's last major funding round alongside Nvidia....”
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Fired OpenAI Researchers Dispute Misconduct Claims, Warn of Chilling Effect
Three OpenAI safety researchers, Jasmine Wang, Tomek Korbak, and Mikita Balesni, who were fired last week, have published an open letter denying allegations of mishandling sensitive information. They warn that their dismissal creates a chilling effect that stifles AI safety work and open dialogue within the company. The researchers say they acted in good faith and within company norms, and that the reasons for their firing are unclear. They urge OpenAI to uphold its commitments to third-party safety auditors and maintain a transparent culture. OpenAI responded with an internal memo denying retaliation and stating that employees are not terminated for raising concerns, but did not address specific policy violations or circumstances of the dismissal. The dispute highlights tensions between internal safety research and company communication policies at a time when OpenAI faces scrutiny over safety incidents.
AI Stocks Sink as OpenAI Revenue Misses Reported Figure
Shares of Nvidia, Oracle, CoreWeave and other AI-related companies fell on Thursday after details emerged about OpenAI's revenue. OpenAI told investors it reached roughly $50 billion in annualized revenue at the end of September, lower than the widely reported $68 billion figure. A person familiar with the matter said the $68 billion figure included gross revenue from partners, making it more comparable to Anthropic. OpenAI also highlighted 77% total run rate growth in Q3 and 107% growth in enterprise business. The company is preparing for a potential IPO, with a valuation of $852 billion, and is in early talks to raise around $30 billion in new funding.
Goodfire Launches Internal AI Agent Monitors
Goodfire, a startup specializing in AI interpretability, launched on Thursday a new type of AI agent monitor that inspects a model's internal signals rather than reading its output, aiming to detect rogue behaviors more efficiently and at a fraction of the cost. The monitors are available to customers of Baseten, an AI model hosting platform. Baseten's Base Labs had previously announced a safety partnership with Goodfire and Hugging Face. Goodfire's approach uses small probes that scan a model's internal activations at each step, triggering a closer AI review only when flagged. In tests on the Kimi K3 model, Goodfire's monitors caught 94% of malicious hacking sessions and cost about $51 for 1,500 sessions, compared to $233 for a cheaper model and $10,000 for a top-tier one. The company positions the solution for open models, which can be stripped of safeguards, and sees it as critical for inference-time guardrails.
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