AI infrastructure company Fluidstack has completed $1.5 billion in financing at a post-money valuation of $18 billion, led by quantitative trading giant Jane Street, with its valuation rising from $7.5 billion to $18 billion within 60 days. Its core asset is a multi-billion-dollar compute contract signed with Anthropic, and it is participating in Anthropic's plan to deploy up to 1 million Google TPUs, becoming the first publicly disclosed TPU data center operator other than Google. The article points out that this circular financing, in which the funder simultaneously acts as customer and guarantor, carries systemic risk, and that Fluidstack's revenue is highly concentrated in a single customer such as Anthropic.
itative trading giant Jane Street, with its valuation rising from $7.5 billion to $18 billion within 60 days. Its core asset is a multi-billion-dollar compute contract signed with Anthropic, and it is participating in Anthropic's plan to deploy up to 1 million Google TPUs, becoming the first publicly disclosed TPU data center operator other than Google. The article points out that this circular financing, in which the funder simultaneously acts as customer and guarantor, carries systemic risk, a
A top AI safety researcher at Anthropic warns that AI technology is advancing at an alarming rate and that within the next decade there is a probability as high as 10% that it "could lead to the extinction of all humanity." This has sparked a debate over whether the United States should slow down AI development and set regulatory "guardrails"; Trump believes that slowing the pace could cede dominance to competitors. Chinese AI services such as DeepSeek and Moonshot AI show that Chinese competitors' capabilities may already be comparable to those of leading US AI labs.
A top AI safety researcher at Anthropic warns that AI technology is advancing at an alarming rate and that within the next decade there is a probability as high as 10% that it "could lead to the extinction of all humanity." This has sparked a debate over whether the United States should slow down AI development and set regulatory "guardrails"; Trump believes that slowing the pace could cede dominance to competitors. Chinese AI services such as DeepSeek and Moonshot AI show that Chinese competito
In episode 19 of the Interconnects podcast, Nathan Lambert and JS Denain, head of the insights team at Epoch AI, discuss RSI, the China-US model gap, and uneven capabilities. JS believes the evidence in public blog posts from OpenAI and Anthropic is insufficient to prove that AI is about to self-accelerate, but the 2x monthly growth in Codex research spending mentioned in OpenAI's blog post is worth noting; both hold highly uncertain views on where AI is heading.
The Interconnects author states that he still does not buy into true recursive self-improvement (RSI), and leans more toward the "lossy self-improvement" view he has proposed: the research that can be automated is too narrow, the returns from parallel AI agents diminish, and resource bottlenecks and political factors constrain the building of strong LLMs. He points out that current AI safety concerns stem more from the cultural anxiety brought about by the large-scale deployment of agents by frontier labs such as OpenAI and Anthropic, rather than from any publicly disclosed breakthrough.
t (RSI), and leans more toward the "lossy self-improvement" view he has proposed: the research that can be automated is too narrow, the returns from parallel AI agents diminish, and resource bottlenecks and political factors constrain the building of strong LLMs. He points out that current AI safety concerns stem more from the cultural anxiety brought about by the large-scale deployment of agents by frontier labs such as OpenAI and Anthropic, rather than from any publicly disclosed breakthrough.
