With the upcoming release of Nav3-small and the focus on democratizing AI model creation, how do you plan to handle scalability and resource management on decentralized GPU platforms like io.net 3 and Render Network to ensure consistent performance for all users, especially as the demand for complex tasks increases?
How does NavyAI plan to balance the need for decentralization and democratization with the potential need for oversight and regulation in AI development, particularly in areas like bias and ethics?
What are your advantages and disadvantages to other AI project in the space such as NodeAI($GPU) and IO.net? What is your main edge your compititors?
NavyAI’s approach to democratizing AI model creation through a decentralized GPU network on Solana is impressive. However, I have a question regarding the implementation and future plans
What are the strategic goals and partnerships planned for 2024-2025 to ensure NavyAI’s growth and sustainability?
Nice read ! is there a place to get more information about the creators of NavyAI ?
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In Token utility I don’t really understand what is governance… Please explain it more
good project!! we want good news from you. Do you gonna have more team ups with other AI projects?
Do you have a discord account or have any KOL your working with?
“Looks intriguing! Not to nitpick, just genuinely curious about the ‘proof in the pudding’ aspect. I couldn’t spot detailed LinkedIn profiles or team identities—would love to see those to better understand the impressive claims in your employee structure. It adds a touch of reality for me.”
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Very interesting project indeed. I have one question to the team that summarize many aspects of NavyAI project:
Given the current rise of projects on Decentralized AI, Depin GPU and AI Model Training, how will NavyAI ensure in the long term that their ecosystem will continue to be the go-to standard for AI Developers?
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What are your advantages and disadvantages to other AI project in the space such as NodeAI($GPU) and IO.net? What is your main edge your compititors?
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What specific benefits does NavyAI’s decentralized approach offer for AI model training and deployment, and how does it address current challenges in the field, such as data privacy, model bias, and access to computing resources, to enable more efficient, transparent, and inclusive AI development and deployment?
I’ll like to ask still.
With the surge of many AI models, what’s the selling point, or what’s the unique features that distinguishes NAVY AI from the rest?
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Can you tell us how in the future the Navyai project will run as it should, sir, then will we get more profit from purchasing nodes that run from tier 1 - the specified tier?
So will Navyai continue to look for more partners to create bigger projects in the future?
Please let us know if there is any extraordinary announcement from you sir , thankyou !
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What specific benefits does NavyAI’s decentralized approach offer for AI model training and deployment, and how does it address current challenges in the field, such as data privacy, model bias, and access to computing resources, to enable more efficient, transparent, and inclusive AI development and deployment?
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Unless the uncertainty on what benefit this project will bring, investors will be a little hesitant to shell out capital.
Delete
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I think the proposal is a good one and I’m anticipating what NavyAI has to offer.
NavyAI’s proposal on jupresear.ch is intriguing. Could you provide more details on how you plan to integrate AI-driven insights into the research process? Specifically, how will this enhance the efficiency and accuracy of data analysis compared to traditional methods?
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TGE is just around the corner. Lets see how this project goes.
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Looks pretty much abandoned tbh apart from the 3 variations each of the same 3 different comments coming in from first timer accounts without any further activity on Jupresearch.
Last time they interacted with that topic has been end of June, and they maybe did not like the identity related questions 
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