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The Guardian interprets a report released this week by Anthropic's offensive research team: the team says it has built a malicious AI program that can spread autonomously among internet-connected smart TVs, splitting itself across 15 TVs and borrowing a little computing power from each to keep running. The researchers believe a successful AI worm would need stronger capabilities on lower-powered devices, but that current trends make this potentially feasible by the end of the year; the worm in an earlier University of Toronto paper instead infected a full-sized computer and could spread faster. Security experts disagree: some stress that IoT devices such as smart TVs are slow to receive patch updates and their risks are hard to fix, while others argue the experiment moves slowly and its actions are predictable and interceptable, making it stunt hacking.
The Guardian interprets a report released this week by Anthropic's offensive research team: the team says it has built a malicious AI program that can spread autonomously among internet-connected smart TVs, splitting itself across 15 TVs and borrowing a little computing power from each to keep running. The researchers believe a successful AI worm would need stronger capabilities on lower-powered devices, but that current trends make this potentially feasible by the end of the year; the worm in a
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Anthropic co-founder Jack Clark said the company's internal models predict that, under certain conditions, AI could boost US economic output by nearly 50% by 2030, with potential US GDP reaching $44 trillion. He also warned that growing evidence points to a "technological singularity," that AI development will outpace human control, and that the window to build safety safeguards is only "a few short years."
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Anthropic published a study: an employee gave Claude's internal research model the question of the source of the NIST elliptic curve seeds, which had puzzled the cryptography community for more than twenty years, and Claude traced within less than half an hour that the seeds for P-192, P-224, P-256, P-384 and P-521 came from the lrand48 pseudorandom number generator in the C language library, with the initial state determined by the Unix timestamp. Anthropic said the finding did not break ECDSA and did not bring new attack methods, but it reduced the possibility that the relevant curves had been deliberately implanted with backdoors. Claude also traced that the base points of six curves including P-192 came from FreeLIP's random number generator, though the source of the B-163 curve seed and how the base points of some curves were generated remain unexplained.
Anthropic published a study: an employee gave Claude's internal research model the question of the source of the NIST elliptic curve seeds, which had puzzled the cryptography community for more than twenty years, and Claude traced within less than half an hour that the seeds for P-192, P-224, P-256, P-384 and P-521 came from the lrand48 pseudorandom number generator in the C language library, with the initial state determined by the Unix timestamp. Anthropic said the finding did not break ECDSA
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Anthropic announced a study in which Mythos 5, given only natural language task descriptions, fully autonomously closed-loop designed 8 basic quantum circuits within 53 hours, all surpassing the best publicly published human designs. In the divsteps task in number theory and cryptography, it autonomously derived a new algebraic identity and completed formalization in Lean, reducing the number of quantum gates by 17 times while increasing qubits by only 12%; in the DQI decoding task, it switched to the Berlekamp-Massey decoding method and precisely calculated storage requirements, reducing gate count by 12 times compared with the original architecture. The research comes from Anthropic's STEM Fellows project, and the text also mentions that FeMoco simulation gate count dropped from the 50 trillion estimated by humans in 2017 to 340 million over 8 years.
Anthropic announced a study in which Mythos 5, given only natural language task descriptions, fully autonomously closed-loop designed 8 basic quantum circuits within 53 hours, all surpassing the best publicly published human designs. In the divsteps task in number theory and cryptography, it autonomously derived a new algebraic identity and completed formalization in Lean, reducing the number of quantum gates by 17 times while increasing qubits by only 12%; in the DQI decoding task, it switched
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