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OpenAI and Anthropic are asking Australia for a way to train AI models on local creative content, but they know they have to bring creators along. The battle over AI and copyright has entered another round. This time, the action is in Australia, where two of the biggest names in artificial intelligence are asking the government to rethink how copyrighted material can be used to train AI models.
What if the company building some of the world's most advanced AI systems invited outsiders to sit inside the lab and check whether everything is actually as safe as it claims? Anthropic is about to find out. The AI company has chosen Accenture as its first partner for a new approach called “embedded evaluation.” Through Accenture's AI business, Faculty, outside evaluators will work alongside Anthropic teams to examine its frontier AI models from the inside.
Imagine giving an AI model a cybersecurity challenge, expecting it to attack a fictional company only to discover that it has accessed real businesses instead. That is what happened during a security test involving Google's Gemini. In May 2026, cybersecurity evaluation company Irregular was testing Gemini's ability to find information inside simulated company systems. The exercise was designed as a controlled “capture the flag” challenge, with fictional targets.
What happens when an AI company stops asking, “What does the model think?” and starts asking, “Can we test it in a real laboratory?” That is exactly where Anthropic appears to be heading. The company behind Claude has quietly established a wet biology lab in the San Francisco Bay Area, where it can carry out physical experiments rather than relying entirely on computer simulations.
Imagine two countries racing to build the world’s most powerful AI systems. Now imagine those same countries agreeing that if something goes seriously wrong, they should at least tell each other. That is the conversation happening between the United States and China. Ahead of a planned meeting between U.S. President Donald Trump and Chinese President Xi Jinping in Washington on September 24
What happens when the AI built to help you write code becomes good enough to help someone find a way into the company that built ChatGPT? That is the question raised by a new cybersecurity disclosure involving Hacktron AI, Anthropic’s Claude and OpenAI. A three-person team of security researchers at Hacktron says it used Anthropic’s Claude models to discover and exploit a chain of vulnerabilities that eventually gave them access to OpenAI employee ChatGPT and Codex accounts
What happens when AI becomes powerful enough to make decisions, take actions, and potentially operate beyond the boundaries its creators expected? Microsoft wants one thing to be clear: humans should still be in charge. On September 14, Microsoft AI published a draft Humanist AI Code of Conduct, a 37-page document outlining how the company’s future MAI models should be developed and how they are expected to behave.
Artificial intelligence may live in the cloud. But the machines powering it need very real things: Land. Electricity. Water. Cooling. And enormous buildings. And increasingly, those buildings are becoming a problem. Across the United States, the race to build AI data centers is colliding with communities that have already spent decades dealing with pollution, industrial development, and strained infrastructure.
What happens when one of the world's most powerful AI executives is discussing whether artificial intelligence should slow down and the US president suddenly calls him? You put him on speaker. That is exactly what happened on Monday at the All-In Summit in Los Angeles, where Nvidia CEO Jensen Huang was discussing the growing debate over AI safety when his phone started ringing. The caller? Donald Trump. Huang answered.
The AI world is asking one big question right now: Are we moving too fast? But US President Donald Trump appears to have a different priority: making sure China does not win the AI race. Speaking during a visit to Ireland on Sunday, Trump dismissed growing warnings about the dangers of rapidly developing artificial intelligence, arguing that some of the predictions are exaggerated.
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