How much is the number one AI project in the crypto space worth?
Sentient @SentientAGI completed a funding round of $85M in 2024, becoming the highest-funded project in the AI sector in the past two years.
Funding partners include the recently popular institutions Founders Fund and Pantera.
The reason I am so optimistic about Sentient is not just because of the funding, but also due to the achievements the project has reached so far.
Sentient Chat has integrated over 40 AI agents (such as Kite, Giza, Mira, Olas) and processes over 2 million API calls daily.
Over 110 partners: including more than 50 AI agents (for example, Napkin for generating graphics, Exa for searching, Caldo for finance), over 50 data providers (such as The Graph, Kaito), more than 6 models (like Dobby, a community-aligned open-source model), and over 10 computing/infrastructure providers (like EigenLayer).
User scale: over 2 million people on the waiting list, actively integrating Web2/Web3 use cases.
The biggest opportunity that may be available in the future: participating in the presale.
The presale is expected to take place in November to December on Kaito or Buidpad; buying in means profit, but there will likely be thresholds, such as mouth-to-mouth, DC role, and using the platform's AI.
Minimum valuation of $5B FDV; $5B might even be low, as current projects often start with a FDV of $1B.
@SentientAGI @0xsachi #SentientAGI #Sentient #sentientai
In the past few days, I chatted with friends working in AI at major Web2 companies about the Sentient project, and they were all quite surprised because Sentient is doing something that previous AI projects have never done before.
Sentient represents a significant step forward in the AI sector, with AGI leading the AI wave.
After discussing the core functionality of Sentient, GRID, let's talk about one of GRID's core open-source large language models (LLM): Dobby.
Dobby's positioning and functionality align with open-source and community goals. Dobby is an open-source large language model designed to democratize artificial general intelligence (AGI) through community collaboration.
Unlike closed-source models (like the GPT series), Dobby's code and training data are public, allowing developers to verify, modify, and customize.
Community alignment means that the model's parameters and behaviors prioritize user needs and ethical standards, avoiding the "black box" problem controlled by large companies.
Dobby's advantages and innovations compared to other closed-source models include:
Open and transparent: Dobby's open-source nature distinguishes it from closed-source models, allowing the community to review and optimize the code, reducing bias and error risks.
Decentralized operation: Through blockchain and distributed computing power, Dobby avoids reliance on centralized cloud services, enhancing privacy and resistance to censorship.
Modular design: Dobby is not a single "omni-model" but part of the GRID ecosystem, focusing on language reasoning and collaborating with other specialized agents to achieve AGI-level capabilities.
However, there are certain drawbacks: compared to closed-source models, Dobby's reasoning capabilities may still lag in certain tasks (such as complex reasoning in ultra-large-scale models).
Sentient is still in the early stages of the project, and there are indeed some flaws in certain areas. As Sentient progresses further in development, these existing flaws will gradually be improved.
@SentientAGI #SentientAGI @KaitoAI
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