Anthropic CEO Dario Amodei wants the AI industry to slow down, but his own company may be preparing to step on the accelerator again. According to Reuters, Anthropic is considering releasing a new AI model to counter growing momentum from OpenAI, just days after Amodei called for the industry to deliberately moderate the pace of AI development.
All this makes for a rather awkward situation. Amodei recently argued that AI capabilities are advancing so quickly that safety measures need more time to catch up. In his September 12 essay, he wrote, “We must slow the pace at which we improve the capabilities of AI models.” He proposed measures including permanent access for independent third-party evaluators, coordinated safety standards, and international cooperation.
The reason Anthropic may still be considering another model is fairly straightforward: OpenAI’s GPT-6 Astra is gaining traction with businesses, putting pressure on Anthropic’s position in the enterprise AI market. Reuters reports that three sources familiar with the matter say Anthropic is weighing a new release, although the company has not publicly confirmed that it is preparing one.
That competitive pressure matters even more with Anthropic preparing for a potential IPO. Investors are reportedly reassessing the company’s position as OpenAI gains enterprise momentum, creating an uncomfortable choice: slow down development for safety, or keep pace with rivals that aren’t necessarily hitting the brakes.
Amodei’s concerns have received support from other major AI figures. OpenAI CEO Sam Altman and SpaceX CEO Elon Musk backed calls for a more deliberate pace, while Google DeepMind’s Demis Hassabis has also acknowledged the need for greater coordination around AI safety.
Dario is right https://t.co/EwKgqQGaUo
But the competitive reality remains stubborn. If one company slows down while another keeps releasing increasingly capable models, the incentive to keep pushing becomes difficult to ignore. Anthropic’s reported dilemma therefore captures the bigger problem facing the entire industry: everyone may agree that the AI race needs a speed limit, but nobody seems particularly keen on being the first to take their foot off the accelerator.
AI companies spend enormous amounts of time convincing us their technology is safe and secure. But what happens when those same companies become targets of increasingly sophisticated AI-powered attacks? Anthropic, the company behind Claude, is now facing that question. According to a Washington Post report, cybersecurity startup Cathedral discovered vulnerabilities that let its researchers access sensitive information in Anthropic's internal systems.
The researchers used AI agents to identify potential entry points in less than 12 hours. Interestingly, they didn't need to crack Claude itself. Instead, they exploited weaknesses in third-party business applications that Anthropic uses for everyday operations. Anthropic's security testing program disclosed the findings, which allows outside researchers to identify and report vulnerabilities.
Military working dogs charge into places the rest of us would flee. So, I understand why anyone would want to breed tougher, healthier dogs for the job.
Warhound, a new startup from Colossal Biosciences co-founder Ben Lamm and Anduril co-founder Palmer Luckey, has stepped out of stealth with $200 million to clone and gene-edit working dogs for American troops, police departments, and emergency services (via TechCrunch).
AI can describe a picture, identify objects, and answer questions about what a camera sees. But when a blind user needs a quick answer, getting an entire spoken essay about the scene isn't exactly helpful. Researchers at the University of Maryland (UMD) have found that AI-powered visual assistance can leave blind users doing too much work to get the information they actually need.
The study, titled Say It My Way: Exploring Control in Conversational Visual Question Answering with Blind Users, examined how people interact with Be My AI, an AI-powered feature of the Be My Eyes app. The researchers found that users often received lengthy descriptions that didn't adequately address their immediate goals, forcing them to ask follow-up questions or find ways to steer the AI towards a more useful answer.