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The New PayPal Mafia: How 10 HRT Interns Built Over $100 Billion in Valuation

In 2015, ten people joined Hudson River Trading's inaugural internship program. A decade later, the companies they founded or lead are collectively valued at over $100 billion, and Alexandr Wang has dubbed them the new generation of the "PayPal Mafia." Among them, Meta acquired a 49% stake in Scale AI for $14.3 billion; Hyperliquid, with a team of just 11 people, achieved annual profits exceeding $900 million and a market value of $76 billion; and Cognition's Devin is approaching $1 billion in annualized revenue with a valuation of $48 billion. The same cohort of interns also founded Decagon ($4.5 billion), Perplexity (approximately $30 billion), and Pika ($470 million).

Hugging Face shared training compute rises from $40 million to about $1 billion

Thomas Wolf, citing his own post, said that the value of training compute shared on the Hugging Face Hub by Meta, NVIDIA, Alibaba, DeepSeek, Moonshot, Mistral and about 30 other labs has approached $1 billion, compared with less than $40 million at the end of 2023. He called this a conservative lower bound: about half comes from official compute figures, the rest is estimated, and it does not yet include the roughly 900,000 community fine-tunes.

The training compute shared on Hugging Face is worth nearly $1 billion

Thomas Wolf estimates that the value of training compute shared on the Hugging Face Hub by about 30-plus labs, including Meta, NVIDIA, Alibaba, DeepSeek, Moonshot, and Mistral, is approaching $1 billion, and it can be downloaded for free; at the end of 2023, that figure was still less than $40 million. He calls this number a lower bound: about half comes from official compute data, the rest is reasonable inference, and it does not yet include the roughly 900,000 community fine-tuned models.

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Reflection Releases Its First Model Beam, Scoring 30 on the Artificial Analysis Intelligence Index

Reflection has released its first model, Beam, an open-weight model with 501B total parameters and 23B activated parameters. It scores 30 on the Artificial Analysis Intelligence Index, ranking second among US open-weight models, behind only Meta's Muse Spark Open (39) and ahead of NVIDIA's Nemotron 3.5 Super VL (26). Beam consumes about 26k output tokens per Intelligence Index task, of which about 19k are used for reasoning and 7k for answering; it scores 48.5% on AutomationBench-AA, but only 3.0% on Terminal-Bench 4.0. On AA-Omniscience, it answers 33% of questions correctly, with a hallucination rate of 47% and a net index score of 1.5.

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Anthropic Report: AI Agents' Work Hours Reach 6 Times That of Humans, Share of Junior Tech Job Openings Falls to 9%

Anthropic released a report stating that by August 2026, the working hours of interactive AI agents deployed by employees had reached 6 times that of human employees, and in March, the company-wide total agent work hours exceeded human work hours for the first time. The report shows that the share of junior employees in the technology department fell from 21% in early 2025 to 14%, the share of junior tech job openings fell from 27% to 9%, and engineers using coding agents averaged 5 times as many code commits as they did 6 months earlier. The report also says its revenue per employee is 2 to 4 times that of Meta and Google during their high-growth periods, but Epoch AI cautions that the related estimates carry uncertainty.

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Aditya Agarwal previews Sriram Krishnan as guest for SPC fireside chat

Aditya Agarwal said that next week he will welcome his friend Sriram Krishnan as a guest at @spc for a fireside chat and Q&A. He noted that Krishnan helped build Azure, led the scaling of Meta's mobile ads, and drove a16z's international expansion, after which he went to the White House to help draft the U.S. AI Action Plan.