Anthropic Confirms Data Breach Exposed After FTC Investigation Initiated


Recently, Anthropic released Fable5.1, and OpenAI launched Astra, further intensifying the global competition in large models. Although Astra has sparked discussions about its performance and cost-effectiveness, the massive financial and hardware consumption behind it highlights the gap in computing infrastructure between China and the United States. Reports indicate that OpenAI has not disclosed specific parameters, but it has used the StarGate program to train models utilizing over 100,000 NVIDIA GPUs.
Anthropic reached a settlement in a copyright class-action lawsuit. The court ruled that using copyrighted materials to train AI models constitutes fair use and is legal; however, obtaining uncopyrighted materials through piracy is not. Therefore, Anthropic will compensate the original authors of nearly 500,000 pirated works used in training, at $3,000 per work, totaling $1.5 billion.
On September 3rd, the global AI industry experienced a rare collective failure. Mainstream large models such as OpenAI's ChatGPT, Grok, and Claude suffered large-scale outages almost simultaneously, affecting many users' daily usage and workflows. The incident impacted leading large model platforms, drawing significant attention from the industry and users. Technical teams have urgently investigated and repaired the issue.
Patrick Chi, president of Broadcom, predicts that as large model vendors intensify their competition for computing power, Anthropic and OpenAI will surpass Google to become the top two core customers for Broadcom's AI ASIC business. Anthropic is expected to become the largest XPU custom chip customer by 2027 to 2028, followed closely by OpenAI in second place.
Anthropic released its new flagship large model Fable 5.1 ahead of its listing, and simultaneously launched Mythos5.1 for Mythos access users. As the core of its product lineup, this model surpasses the previous Fable5 and competitors in multiple benchmark tests, while significantly reducing usage costs. It maintains strong performance, highlighting that the competition in large models is moving toward extreme cost-effectiveness.