The Paloma Chain flies high as it enters the blockchain AI space! In this week’s AMA episode, the host, Taariq Lewis @LewisTaariq, CEO of VolumeFi (
volume.finance
) is joined by GNUS (
GNUS.AI
) CEO Ken Hurley, and CTO/Co-founder Brent Arias to introduce their company and their role in AI and blockchain.
As the demand for GPU access grows at phenomenal levels, GNUS harnesses GPU resources from the collective power of millions of mobile phones by allowing its apps to participate in a network of decentralized physical infrastructure. Device owners and game developers monetize video games and earn tokens in return by utilizing the mobile phones’ GPU functionality to perform advanced AI/ML jobs such as video inference and smaller model training. Developers access the platform by integrating the GNUS SDK into their app and paying end-users with GNUS tokens
The potential for a partnership with GNUS and other GPU providers was also discussed where Paloma can integrate a frictionless, seamless cross-chain execution and a smooth UI/UX while eliminating the worry about token price, slippage, and price volatility.
Palomabots have zero fees for the remainder of May enabling users to do TWAP, limit orders, and leverage trade with no fees.
The host welcomes everyone to Volume’s Twitter Spaces. He explains that there is a shift in today’s topic from creating Palomabots using OpenAI, to learning more about GNUS and their vision of blockchain and AI. He extends a warm welcome to today’s special guests from
GNUS.AI
.
Taariq shares a brief about Volume.
As the DeFi market slows down, Volume is opening up to opportunities in the blockchain AI space for more community and growth.
Palomabots have zero service fees for the whole month of May. Users can do TWAP, limit orders, and leverage trade with no fees.
Paloma has successfully recovered the 12ETH that was stuck on the old Messenger Chain. The team is now working on helping Paloma developers use AI to build Paloma bots.
Taariq asks the guests to introduce
GNUS.AI
and their role in AI.
Brent offers a brief background on GNUS.
From the seed of that idea, and with Ken’s expert knowledge of GPU capabilities, the premise was the processing would be done by GPU. In the era of blockchain and recognizing the value of decentralization, this concept was put into a Web3 context.
He explains that beyond video games, any application that integrates the SDK benefits from this capability. The trifecta of a vendor that has integrated this SDK can be earning crypto with their app, with processing time shaved off to contribute to the user of a device that has opened that application.
While there is a substantial surge in demand for ML, there is a shortage of supply for processors for this kind of work. With a billion devices potentially available with apps running on them, GNUS SDK alleviates that problem using a horizontal scaling approach.
Taariq notes that this is where DePins touches AI and blockchains. He cites the game Temple Run played on a user’s mobile phone as an example of how GNUS works.
He adds that with billions of mobile phones, a massive network of decentralized physical infrastructure can run GPU jobs. The mobile phone user in return gets tokens from the utility of both a free game, and a free published app that yields tokens.
Volume has been looking for companies that can customize or retrain a massive model by finding a small subsection of parameters to help fine-tune and customize models for users. He asks GNUS what model sizes can be taken up by their network with the view that Volume is keen on training and fine-tuning smaller models.
Brent replies that this is determined by the level of parallelization that the algorithms will permit. Some algorithms permit 20% of the endeavor to be parallelized while others 80%. He notes that although memory can be a challenge, GNUS intends for solutions to be based on streaming technology to minimize the amount of memory needed at any given point.
Ken chimes in to say that GNUS does not retrain very large models because they may not fit in mobile memory easily.
Taariq asks what kinds of jobs GNUS focuses on. What is their sweet spot?
Ken explains that they are mainly working with high-speed video inference in partnership with a couple of companies, although this has not been announced.
In general, GNUS assures that they can do about 90% of model training on smaller language models that do not require a lot of memory.
The Docs at
GNUS.Ai
is a starting point for developers to learn more about their process. GNUS SDK is nearly finished and up for testnet. Their entire source code is open source on GitHub.
Taariq asks how the GNUS token relates to the protocol itself.
Ken explains that the protocol token is basically a DePIN crypto. It is generally like a compute infrastructure with a crypto token payment system.
He adds that users who need to fine-tune or execute inference on an image can send the job over to GNUS.
Ken explains that GNUS is the DePIN part of the infrastructure. Their customers include game developers and partners who want to integrate with GNUS and use AI for machine learning and analytics. Others use the network for personal projects in research and similar endeavors. They are currently working on a deal that will be providing hundreds of thousands of nodes, and utilizing small portions of it for video analysis. He underscores the growing demand, especially for users working with smaller language models.
Taariq shares some frustrations they have encountered in starting to use a GPU resource. While there are ongoing conversations with Akash, he describes a user experience to access Akash.
He emphasizes that transactions should be frictionless and recognizes the many opportunities for Paloma to smooth out the UI/UX experience emphasizing their strength in automated bots. He gives an example of a potential opportunity for Paloma to partner with GNUS.
Paloma can ensure seamless cross-chain execution where developers can build on GNUS and do not have to worry about token price, slippage, and price volatility. He shares his excitement at the prospect of creating bots on GNUS and other GPU providers like Akash where Paloma can integrate frictionless transactions and ease of use for customers.
Taariq thanks his guests and all the listeners who tuned in to today’s AMA.
Next week’s episode will be about breaking down Palomabots’ code using OpenAI to help folks understand how they work.
Stay tuned for the next AMA!
To find out more about Volume, check out Volume Finance (
), join the Discord (
), and follow us on Twitter
Check out Paloma Chain on
(
), follow them on Twitter (@palomachain), and join the flock on Discord (
). Coo! Coo!
Learn more about
GNUS.AI
, the GNUS team, and what’s next for these AI & blockchain pioneers at
& follow them on Twitter at