Sahara AI colaboration between an artificial intelligence and blockchain technology.
15/Aug/2024
Sahara AI has successfully secured $43 million in funding to advance its vision of a collaborative economy powered by artificial intelligence and blockchain technology. The funding round was spearheaded by prominent investors including Pantera Capital, Binance Labs, and Polychain Capital, with additional backing from Samsung NEXT, Matrix Partners, dao5, Geekcartel, Nomad Capital, SCB 10X, Canonical Capital, Mirana Ventures, Foresight Ventures, and others.
Since its inception in 2022, Sahara AI has been dedicated to creating a platform that facilitates on-chain attribution throughout the AI development process. This innovative approach aims to reward participants for various contributions, such as operating infrastructure, fine-tuning models, building autonomous agents, sharing knowledge, or developing applications.
Sean Ren, CEO and co-founder of Sahara Labs, expressed concerns about the current state of AI, stating, “Most AI today remains trapped in a Web2 paradigm where users trade their knowledge for access to AI or machine learning tools. There is often no transparency on how users’ proprietary models and agents are used by these centralized AI providers, and no protection or compensation for users’ contributions.”
To address these issues, the company is committed to establishing a secure and transparent “copyright” framework for managing AI assets on the blockchain through its Sahara Blockchain Protocols. Ren explained that these protocols encompass AI-driven solutions for asset tracking, licensing for access control, ownership for safeguarding non-transferable records, and attribution for monitoring contributions and revenue distribution.
“This ensures that all contributors are fairly compensated,
sovereignty of data and models are maintained, and AI
assets can be securely created, shared, and traded, all while
preserving privacy and promoting inclusivity,” Ren added.
Tyler Zhou, co-founder and COO of Sahara AI, is also a key
figure in the startup, he serves as an investment director
at Binance Labs.
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Co-founder of Cohere, emphasizes the importance of having a realistic perspective on the capabilities and limitations of AI
Nick Frosst, co-founder of Cohere, emphasizes the importance of having a realistic perspective on the capabilities and limitations of AI.
Cohere, a company specializing in developing custom AI models for enterprise clients, is part of a rapidly growing sector where AI firms are attracting significant investment and achieving high valuations early in their development. This trend has led some observers to label the AI industry as a bubble.
In a recent appearance on TechCrunch’s Found podcast, Frosst expressed his belief that the AI sector is not in a bubble, despite recognizing some speculative elements. He argues that labeling it as such undermines the efforts of companies like Cohere that are delivering genuinely valuable solutions to their clients.
“I often encounter instances where users of our model have unlocked entirely new features that were previously unattainable or have streamlined processes that were hindering their productivity,” Frosst noted. “This represents real value, making it difficult to claim there is a complete bubble when such utility exists.”
However, Frosst is not overly optimistic about every aspect of the industry.
He is skeptical about the prospect of achieving artificial general intelligence,
which is characterized by human-like cognitive abilities. This stance contrasts
with the views of some of his contemporaries, such as Mark Zuckerberg and
Jensen Huang. He remarked that even if the industry were to reach that level,
it would be a long time coming.
“I don’t foresee the emergence of digital deities in the near future,” Frosst stated. “More individuals are beginning to understand that while this technology is remarkable, powerful, and highly beneficial, it is not a digital deity. This realization necessitates a shift in how we conceptualize the technology.”
At Cohere, Frosst and his team strive to maintain a realistic outlook on the potential and limitations of AI technology, as well as the types of neural networks that can deliver the most significant benefits.
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