Cardano blockchain’s founder, Charles Hoskinson, wasted no time extending an invitation to Sam Altman, the recently ousted CEO of OpenAI, following Altman’s abrupt departure from the OpenAI leadership. Hoskinson proposed a collaboration on a decentralized Large Language Model (LLM) project in a lighthearted post on the X platform.
Barely 24 hours after OpenAI’s board of directors parted ways with Altman, citing allegations of inconsistencies and opaque communications, Hoskinson reached out with an intriguing offer. Hoskinson playfully noted Altman’s newfound free time in his tweet and suggested a partnership in decentralized LLMs.
“Sam Altman, since you have some free time now, if you are interested in doing a decentralized LLM, then hit me up,” Hoskinson remarked in his tweet.
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Partnership Between Hoskinson and Altman for Decentralized LLM
The Cardano founder expressed his confidence in Altman’s expertise in artificial intelligence, considering it a valuable asset in advancing the development of decentralized LLMs. However, the nature of Hoskinson’s proposal remains somewhat enigmatic due to the teasing tone of the tweet, leaving room for speculation about the seriousness of the proposition.
In his invitation note to Altman, Hoskinson conveyed a conviction that Cardano provides an ideal platform for the development of decentralized LLMs. Cardano, designed to be secure, scalable, and sustainable, could offer a robust foundation for such innovative projects.
Decentralized LLMs Garner Attention
Despite the offer’s ambiguous nature, the decentralised LLMs concept has garnered significant attention. Following the introduction of ChatGPT, large language models have achieved unprecedented capabilities in comprehending and processing human thoughts.
Nevertheless, apprehensions surrounding data privacy, security, and computational resources have prompted experts to scrutinize the widespread adoption of centralized LLMs.
Gareth Hinde, a Solutions Architect at Swipe iX, underscored the risks linked to centralized LLMs, emphasizing their susceptibility to exposure, misuse, and breaches. Typically, centralized models involve transmitting data to a central server for processing, raising valid concerns about privacy and security.
In contrast, decentralized LLMs emerge as a promising solution to these challenges. By distributing control across a network of computers, they eradicate dependence on a singular company or organization.
This approach ensures that sensitive data remains stored on users’ local devices, addressing concerns about privacy and security associated with centralized models.
