It is reported that Anthropic has formed a self-developed chip team to create an exclusive hardware ecosystem for Claude. With the rapid increase in the computing power requirements of the underlying AI model, the artificial intelligence start-up Anthropic is officially preparing to establish a self-developed chip team to develop exclusive artificial intelligence chips for its Claude model.

It is reported that Anthropic has formed a self-developed chip team to create an exclusive hardware ecosystem for Claude. With the rapid increase in computing power requirements of the underlying AI model, the artificial intelligence start-up Anthropic is officially preparing to establish a self-developed chip team to develop exclusive artificial intelligence chips for its Claude model. A spokesperson for ZXQKEEP3 ZXQ has confirmed this strategic plan to the media. This is the first time the company has publicly confirmed that it will independently develop chips. A spokesperson for Anthropic said that the company is forming an internal silicon chip team to enable Claude to run faster and more efficiently through the collaborative design of hardware and models when responding to ultra-large-scale customer needs. At the same time, the spokesperson emphasized that Anthropic will still adhere to the "multi-chip parallel" strategy in the future, and hardware from manufacturers such as Amazon Cloud Technology (AWS), Google, NVIDIA, and AMD will still be the core support for its computing power expansion. It has been previously reported that Anthropic has contacted Samsung Electronics to discuss potential OEM manufacturing cooperation. According to the latest recruitment information released by Anthropic, it is recruiting chip design and verification engineers in multiple fields for its "custom silicon chip team", with a salary range of US$320,000 to US$485,000. The position requires candidates to have direct experience in chip tape-out and shipment, and to be able to independently undertake major technical decisions without the support of a large organization. As the cost of computing power for large models remains high, self-designed AI chips, despite huge R&D investment and extremely high technical threshold, can effectively reduce dependence on industry giant NVIDIA and customize the most matching computing architecture for specific models. At present, major AI leading companies are deploying hardware self-research. For example, OpenAI has teamed up with Broadcom to develop exclusive chips, and Meta also plans to put a new generation of AI chips into mass production. The competition for hardware autonomy in the field of artificial intelligence is becoming increasingly fierce. via cnBeta.COM - Chinese industry information station (author: source: cnBeta.COM)