Amazon Just Did A Big Favor to FTX Creditors, Details
The latest development shows that e-commerce giant Amazon (NASDAQ: AMZN) is looking for a massive $4 billion investment in Anthropic, the rival to ChatGPT parent firm OpenAI.
Interestingly, Anthropic is the same company in which crypto exchange FTX invested ahead of its bankruptcy announcement in November 2022. Earlier this year around June 2023, FTX decided to pause the sale of its Anthropic stake after conducting its due bidding process in the first half of the year.
Popular crypto journalist Colin Wu explains that this could be FTX’s moment to sell their $500 million stake in Anthropic and repay the creditors. Wu writes:
Amazon plans to invest up to $4 billion in OpenAI rival Anthropic, with an initial investment of $1.25 billion. In 2022, FTX invested $500m in Anthropic before the ChatGPT hot. In theory, FTX should sell the shares for more than $500 million, which is also good news for creditors.
Amid its latest revamp, crypto exchange FTX has been working on its restructuring plan to repay the creditors. By revamping the exchange, they are also planning to relaunch it as FTX 2.0.
Amazon’s Interest in Anthropic
Anthropic, recently valued at nearly $5 billion in a recent funding round, has forged a new partnership with Amazon Web Services (AWS), indicating a shift from its prior alignment with Google, which invested $300 million in the company last year.
This change comes seven months after Anthropic announced plans to utilize Google’s chips and cloud for training its models. Anthropic’s Claude chatbot, a competitor to ChatGPT, is already part of AWS’s Bedrock service, which enables customers to build generative AI applications in the cloud.
AWS’s Adam Selipsky describes this new collaboration is described as a “significant expansion of the partnership”. Also, with this, Anthropic will gain access to Trainium chips to train future versions of its foundational models. Furthermore, Amazon will become Anthropic’s “primary” cloud provider for “mission critical workloads.”
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