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Policy with public evidence across Policy & governance, AI business, Safety & security.
Dialog, the private network cofounded by Peter Thiel, grades its event attendees on a hidden scale, ranking them by wealth and fame, tracking their relationships, and using algorithms to help decide who they should meet and sit with, WIRED has learned.
These models being used, and the massive token spend they have, are not really what the average person has access to. Claude found major weaknesses in post quantum cryptography and aes-128 utilizing 1 billion tokens with mythos. www.anthropic.com/research/dis...
I would never trust it for complex systems with millions of lines of code. I think it's fine for quick python scripts or even small personal apps where the cost of using the model is still less than hiring a full engineer. This is a great way to view it. youtu.be/a6sYYrLTOjQ?...
Google is justifying a move to default AI search by saying it "removes friction." The problem is that friction is a necessary part of life and this incessant need to rid ourselves of it is going to lead to so many problems we can't anticipate.
The Trump administration has rolled out AI powered surveillance cameras with motion tracking, facial recognition, spotlights, and horn speakers. This story really encapsulates everything wrong about this administration. Now they're turning the reflecting pool into a surveillance state nightmare.
I get the hate for AI but I was able to use Claude to build tools to get access to hundreds of court records via courtlistener API, hundreds of 990s via Propublicas charity navigator, and thousands of political campaign spending records via FEC and Google to measure anti-trans political spending.
The US government just issued an export restriction on Claude Fable/Mythos preventing any foreign national from accessing the model even in the US and Anthropic employees. As a result, all access is cutoff for the foreseeable future.
This is a pretty cool use of AI. They had it scan reddit comments to analyze adverse effects of GLP1s that weren't analyzed during trials. They noticed menstrual issues were prominent. Then they dug through the FDA adverse event reporting database and were able to verify and publish a paper on it.
People need to grapple with the fact that LLMs are now solving for mathematical conjectures that are decades/centuries old. The common sentiment on here is that they're absolutely useless and are always wrong but that is becoming increasingly separated from reality. This is just the last 2 months.
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