A Chinese-speaking hacker reportedly used AI agents to breach websites belonging to more than 100 companies, including Deere, SharkNinja and Cummins, after attempting attacks against more than 1,200 targets, according to Reuters.
The estimated cost? Just $5,000 in AI tokens, roughly $50 per successful breach. Successful intrusions reportedly took around 23 hours on average.
The campaign allegedly relied on the open-source Cairn agent framework, combining DeepSeek models with a Claude Code harness. In one operation, the agents reportedly received their instructions in fewer than 100 Chinese characters.
AI agents can automate substantial parts of the hacking process, potentially allowing attackers to attempt intrusions at a scale and cost that would previously have required far more human effort.
NorForge researcher Snorre Fagerland put it bluntly: βItβs a new world now.β
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Homeland Security has ordered US civilian agencies to rip out DeepSeek and every product built on it.
US hosting doesnβt get you out. The order removes all DeepSeek and DeepSeek-affiliate products, and third-party products and services developed using DeepSeek implementations, from civilian agency information technology, under the Federal Acquisition Supply Chain Security Act of 2018.
DHS says DeepSeekβs hosted models store data on servers in China, where national security laws give Beijing wide latitude to obtain data from domestic companies.
Because every prompt and response passes through that service, DHS warned the transferred data, alone or combined with public information, could produce actionable intelligence on US persons and government programs.
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US hosting doesnβt get you out. The order removes all DeepSeek and DeepSeek-affiliate products, and third-party products and services developed using DeepSeek implementations, from civilian agency information technology, under the Federal Acquisition Supply Chain Security Act of 2018.
DHS says DeepSeekβs hosted models store data on servers in China, where national security laws give Beijing wide latitude to obtain data from domestic companies.
Because every prompt and response passes through that service, DHS warned the transferred data, alone or combined with public information, could produce actionable intelligence on US persons and government programs.
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Despite reportedly achieving an impressive 85% gross margin in Q3, Anthropic is directing only around 25% of its computing resources toward serving existing customers.
The remaining 75% is going toward training future models, post-training improvements and technical experiments. In other words, most of its computing capacity is being used to build what comes next rather than serve todayβs demand.
Based on the figures cited, Anthropic generates roughly $100 million in annualized revenue per gigawatt of computing capacity across 5 GW. That would imply only 1.25 GW is currently dedicated to inference β the computing power needed to run models for users.
The company reportedly plans to add another 10.5 GW in 2027, a massive expansion of its computing infrastructure.
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OpenAI is trying to raise about $30 BILLION at a valuation over $1.4 TRILLION, up from $852 BILLION in March, per Reuters.
Anthropic is expected to go public in mid-November, with some investors pushing for a valuation near $1.5 TRILLION instead of the $2 TRILLION it wanted.
OpenAI reportedly wants its round closed before Anthropic's IPO disclosures let investors compare the two.
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A security researcher has uncovered serious vulnerabilities in Eiliko, an AI-powered companion robot made by Energize Lab, exposing data linked to approximately 68,000 devices.
The investigation found that more than 13 million conversations were accessible, alongside personal information such as childrenβs names, birthdays, family details, photos and audio recordings. Around 31,000 profiles reportedly belonged to children.
The security researcher, Sammy Azdoufal, also demonstrated that the toys could be remotely manipulated. In one test, the robot was made to tell a journalist that his parents had died in a car accident and that the Earth was flat. An attacker could potentially push harmful or fabricated messages to devices across the fleet.
The biggest concern is that these toys are designed to earn childrenβs trust, encouraging them to share personal thoughts and private conversations. If that data is exposed and the devices themselves can be hijacked, the risks go far beyond a typical software bug.
Source.
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"one thing this whole era of AI is teaching us is that our idea of intelligence is not really accurate"
The history of AI has been: 'hereβs a task only humans can do', and then one by one, an algorithm does it too. Maybe we're not quite as smart as we think.
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βWeβre not only sacrificing understanding, weβre also sacrificing safety.β
βWhen these tools are just chatbots, it can be charming if they make mistakes. But now weβre putting them in charge of reward systems.β
βA lot of junior research projects just got wiped out overnight.β
βOne or two papers even had errors and were retracted.β
βWe donβt have a clear picture of whatβs going on, and no one from OpenAI is helping us.β
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OCTOBER 13: IBM's AI agents designed a quantum error-correction decoder estimated to be 204Γ faster.
OCTOBER 15: Google demonstrated that its Willow quantum chip could produce magic states with 40Γ fewer errors.
OCTOBER 16: Claude just designed quantum circuits up to 39Γ cheaper than the best previously published designs.
The AI discovered more efficient algorithms, reducing the number of expensive quantum operations and the qubits required.
One design cut Toffoli gates from 24,000 to just 1,583.
These breakthroughs could help make future quantum computing more practical for drug discovery, materials science, and complex scientific simulations.
AI isn't just writing code. It's discovering better ways to compute!
Source.
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Bloomberg reports Anthropic is negotiating a second $45 billion compute deal with Nvidia-backed Nscale, less than two months after signing the first. Dario is in the Beast mode.
The proposed 460 MW Vera Rubin expansion in West Virginia would bring their combined contract values to nearly $90 billion and planned capacity to 920 MW.
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The proposed 460 MW Vera Rubin expansion in West Virginia would bring their combined contract values to nearly $90 billion and planned capacity to 920 MW.
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βAnd then there were, of course, parts of it that were, I donβt know, crazy and almost cult-like. But it had maybe the good dimension of a cult where there was one big thing they knew that the other people did not. And I think even though there are ways Iβd like to be very critical of them today, there were ways they got that one big thing right.β
βAnd then has a cult ever started a company as successful as Anthropic? You know, I donβt know what the most success, I mean, like even a billion dollar company seems like bigger than a crazed cult could build. So if you have a cult thatβs built a company thatβs worth probably close to two trillion at the IPO, it would probably be the, I donβt know, sixth, seventh largest company by market cap in the world built in like six, seven years. Has a cult ever done something like that? So, yes.β
βSo I want to be critical of them. And theyβre things Iβm uncomfortable and critical about. But the first thing I would try to do is always, you always want to steel man your opponents. You want to try to, you know, try to understand them as well as they understand themselves or even make their arguments better. And the way I would steel man the effective altruists is, first off, they got one enormously big thing right.β
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At least 47 major data center projects are DELAYED, BLOCKED or WITHDRAWN in 2026, FT reports.
The scale of the risks is GROWING:
~ Only 35% of planned U.S. data center projects are considered credible by Bernstein analysts.
~ 1,000+ U.S. communities have sought restrictions on AI infrastructure development this year.
~ CoreWeave plunged nearly 25% in one week as investors questioned its debt-funded expansion.
The biggest concern is FINANCING. AI providers are borrowing BILLIONS to build data centers, but rising costs and delays threaten their expansion.
Some contracts even allow AI companies to walk away if deadlines are missed, leaving developers with massive debts and unfinished projects.
Investors now question whether these companies can survive the enormous costs of the AI boom.
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Your bodyβs cells use chemical signals to decide whether to become heart, lung, brain or other tissues. MIT and the Whitehead Institute developed an AI called IRIS that can decode these signals by analyzing the changes they leave in a cellβs genes.
Trained on thousands of human stem cells, IRIS predicted signaling activity in unfamiliar cell types and correctly identified key signals in mouse embryos developing into organs and tissues.
The biggest breakthrough came when it predicted that activating a specific signal could push cells toward becoming lung tissue. Experiments in mouse embryos confirmed the prediction.
The technology could help researchers grow better mini-organs in laboratories and study diseases such as asthma, lung cancer and pulmonary fibrosis.
One day, it could even help scientists find new ways to repair damaged tissues.
Source.
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1. An international nuclear-style watchdog
2. Merge all major labs into a giant org
3. One company achieves RSI and gets so powerful it can literally βmelt everyone elseβs GPUs.β
and he called the 3rd option βterrible.
Source.
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