{"id":"KD1BMaNLuts","title":"Decentralized Compute Enabling Adaptive, Intelligent Agents in Real Time","description":"How do we take AI agents from basic automation to fully autonomous, intelligent decision-makers? In this talk from ETH Denver, Matthew from Open Gradient explores the evolution of AI agents, the key challenges they face, and how real-time intelligence, verifiable workflows, and decentralized AI models will push them forward.\n\nMatthew Wang - OpenGradient\nhttps://x.com/0xDeltaHedged\n\nKey Takeaways:\nAI agents must evolve beyond basic automation to handle complex decision-making.\nData pipelines & computational workflows are critical for AI to analyze and act intelligently.\nAgent interoperability allows AI to collaborate and execute multi-step, high-level strategies.\nVerifiable, decentralized AI models can power trustless decision-making in finance and beyond.\nOpen Gradient provides a full-stack AI infrastructure for building real-time adaptive agents.\n\nTimestamps\n00:00 – Introduction | Matthew’s background & Open Gradient\n00:45 – The Three Stages of AI Agent Evolution\n02:30 – Challenges in Advancing AI Agents | Data, computation, and collaboration\n04:40 – The Role of Verifiable AI Models in Web3\n06:00 – How Open Gradient Works | Full-stack AI for blockchain\n08:15 – Live AI Agent Use Cases | DeFi trading, risk analysis, & prediction markets\n09:45 – Demo of Open Gradient’s AI Model Hub\n10:30 – Future of AI Agents | Smarter, composable, and autonomous\n\nNEAR is the Blockchain for AI\nWebsite: https://near.org/\nNEAR AI: https://near.ai/\nIntents: https://near.org/intents\nChain Abstraction: https://www.proximity.dev/\nSharding: https://nearone.org/\n\nFor the devs\nGitHub: https://github.com/near \nDev Docs: https://docs.near.org/\nDevhub: https://devhub.near.page/ @NEARDevHub\n\nConnect with socials\nTwitter:   / nearprotocol  \nBlog: https://near.org/blog/\nMedium:   / nearprotocol  \n#NEAR #nearprotocol #NEARAI","channel_name":"NEAR Protocol","published_at":"2025-02-28T00:00:00.000Z","thumbnail_url":"https://img.youtube.com/vi/KD1BMaNLuts/hqdefault.jpg","transcript_text":"hey everyone my name is Matthew excited to be here uh yeah I'm uh one of the co-founders of open gradients and today I'm here to talk about how to make uh intelligent adaptive agents in real time a little bit about myself before I get started uh I spent most of my professional career as a research engineer at a Quant fund called two Sigma in New York um when I was in school i' had also done stints of HCI as well as ml research notably in applying unsupervised learning methods um in Market Reg detection and using that for portfolio optimization and uh I will give everyone a quick rundown of open gradient shortly but excited to first talk about what the road to a trillion Advanced agent kind of looks like in my view so I kind of think about agent development in a couple different stages stage one you have agents that can you know synthesize and reason about with data which you can already see with all these Twitter agents popping up tweeting interestingly provocative things secondly you have stage two which is agents are able to complete tasks on the behalf of their human overlords such as placing simple transactions such as you know buying a simple token and you kind of already see a lot of AI agents notably on uh the near chain kind of able to do this and serve as assistance um and here I've also attached a little screenshot of um one of the tweets that Ilia had put out about how a lot of these agents are kind of helping humans with mundane tasks like routing trades and routing orders and and lastly the kind of final stage for AI agent development in my opinion is when AI agents are able to surpass clearly human abilities in handling complex tasks and this might look like you know AI agents that are able to run fully autonomous companies AI agents that are able to run and participate in Dow Dows uh as well as AI agents that can manage portfolios and be able to you know trade effectively and generate profit consistently but if you look at the state of uh you know Frontier Model LMS and AI agents today a lot of them are extremely intelligent and uh you know especially given the previous panel can access things such as tool calls and rag in order to make it smarter but when you ask it hey what is the price forecast for sui what you know asset should I buy to minimize my risk adjusted return so to maximize my risk adjusted returns things like that the llms or AI agents aren't able to give you a very textured or detailed response and in our view we kind of want to build AI agents that are able to address those tasks and give you textured responses and execute on them effectively and from my view there are essentially three different kind of bottlenecks and Technical hurdles that we need to overcome in order to advance Agents from stage two to stage three firstly data pipelines you need to give AI agents the ability to reason about with more complex and a wider variety of different data sources as an example if you have a portfolio manager agent that agent might want to be able to pull Twitter data in order to analyze the sentiment around certain crypto assets on crypto Twitter secondly computational workflows allowing AI agents to um you know venture outside the world of using a large language model and run a computational workflow that might involve as an example um a mean variance portfolio optimization workflow that gives the aih and the ability to optimize its portfolio Holdings or run a simple risk analysis on uh you know various assets things like that allowing it to you know uh actually perform detailed analysis uh and um you know become smarter with domain specific intelligence and lastly is Agent interoperability uh so I'm extremely personally bullish on the ability to allow agents to compose with one another in order to comp in order to complete extremely complex um and Abstract goals as an example uh portfolio manager agent U might leverage an execution agent in order to find the best venue to trade to minimize Market impact or to minimize uh you know the cost and fees that they would have to pay in order to cross the spread and might use a marketing agent to you know pump uh tokens that it might hold in its portfolio things of the sort and I think these are all extremely exciting kind of um you know Primitives that we are building at open gradient as well which I'll get to shortly um and this is just a quick screenshot of a little piece of writing that we had put out about how the three kind of key pieces that I just spoke about will allow agents to become more intelligent with access to you know computational workflows data pipelines and uh you know access to other agents and you know allowing us to compose different agents together to create powerful computational applications but what's next so briefly on what open gradient is we're building uh a full stack infrastructure platform that allows developers to very freely be able to build AI or ml applications on chain in a way that is both verifiable and extremely seamless uh we want to allow developers to integrate quite simply any model into any application on any chain uh we have an infrastructure layer uh that has you know various nodes they handle compute heavy tasks including inference including running secure data pipelines we have uh our blockchain Network which allows developers to build um using these data pipelines using different models uh directly in their solidity smart contracts uh and we also have cross-chain messaging that allows these computational workflows to service apps or agents or protocols on any other chain we have a model Hub that is live at hub. openg gradient. that you can check out with a couple hundred models many of them are web 3 specific we host sentience uh you know large language models so this is Dobby we host flocks uh small language models we have many many uh you know defi quantitative ml models that do spot forecasting volatility forecasting risk analysis and more and this is all live you can go check out and play around with those models and we have many active Builders building with these models and lastly we have uh pythonic SDK that allows developers to leverage our Tech and interact with all of these models and workflows without having to deal with the complexity of block blockchains for smart contracts and we also partner very closely with clients in order to get their agents protocols and applications off the ground by partnering with them and a lot of the time building models um and agentic workflows alongside these clients and I'll get to a couple interesting use cases later um you know quick overview on how we make this magic happen essentially it's through node specialization so uh unlike a typical blockchain we have many different types of nodes that do very specific things including inference nodes that run verifiable inference and generate proofs and AD stations uh data nodes that are able to you know run secure data pipelines to make these workflows data rich in nature and a decentralized file Store where all the models are stored and we have today one of the only repositories of web 3 specific models including like I mentioned kind of these small language models large language models and a variety of quantitative defi focused ml models that allow developers to build many of these powerful AI agents that can manage portfolios trade you know analyze risk on different assets and uh we also host yeah many um of our partners' uh models including ponds model which does Cil address detection and repos uh and file coins models which do uh minor allocation and and reputation uh analysis and uh kind of tying this back into how we intend to make AI agents intelligent and adaptive and real Real Time by leveraging these computational workflows powered by these highly specific models we are able to give AI agents domain specific intelligence instead of getting a extremely generic response from Claude now when you work with clients on open gradients like exponet when you ask it hey you know give me a short-term price prediction on an asset or you know uh give me the risk profile on a on suie it can actually query these models and give you you know historical forast as well as the current live forecast that can give you a much more textured and detailed response that actually addresses um you know the user's concerns in this case if I want to buy sui I want to understand the risk profile the current volatility associated with the crypto asset um another interesting one um one of our clients which is uh double up they are a gamble five prediction Market protocol um launch an AI agent that allows users to actually bet against the AI agent on The Price Forecast of different crypto assets um so the human can you know the human user can type in some Price Forecast and the AI agent of course can't forecast these prices so it runs a spot forecasting model on open gradient and that's able to give it um you know a very specific forecast powered by time series analysis and uh you know in 30 minutes where when the the market resolves either the user double up doubles up or doubles their money or they lose uh their stake right um and from a quick preliminary analysis since the launch of this agent last month we can see that hey you know users actually perform worse than the AI agent because the AI agent has obviously access to uh ml models that can inform it of what the price predictions are and this is kind of like a very barebones live in production dealing with real user assets example of how we can give AI agents the ability to you know predict prices to eventually trade and manage portfolios effectively through the use of these modular um Ai and ml you know focused workflows and we're also working with many clients um you know big D5 protocols on building analytical quantitative defi AI agents that can give them uh you know that can give the protocol and users of the protocol access to many of these analytical capabilities and workflows powered by the kind of a ml models on our Hub and on our infrastructure so you can ask you know these quantitative agents hey you know what asset should I buy to maximize my risk adjusted returns if I have a million dollars of Bitcoin where which vaults should I deposit in in order to uh you know improve you know to to maximize the yield I can get on these assets and this AI agent is able to query and leverage these workflows in order to help users um achieve these abstract goals so I have a quick demo here which unfortunately probably is not going to load uh but this is just a quick example of if you go to hub. openg gradient. you can go upload any arbitrary AI ml model and inference it within seconds verifiably and there are tons of different models on there um you know courtesy of us as well as many of our modeling Partners as well as individual contributors for Aon ml specific web 3 models that you can go and play around with today um and yeah uh with these models we're excited to be introducing them as tool calls to the AI agents and we're working with many of the popular Frameworks as well to implement these tool calls um and uh very excited to be uh you know unleashing the new era of intelligent agents that can leverage these computational workflows to do much more complex and Abstract tasks thank you","transcript_synced_at":"2026-11-03T05:04:04.584Z","segments":[{"start_seconds":0,"text":"hey everyone my name is Matthew excited to be here uh yeah I'm uh one of the co-founders of open gradients and today I'm here to talk","url":"https://www.youtube.com/watch?v=KD1BMaNLuts&t=0s"},{"start_seconds":8,"text":"about how to make uh intelligent adaptive agents in real time a little bit about myself before I get started uh I spent most of my professional career","url":"https://www.youtube.com/watch?v=KD1BMaNLuts&t=8s"},{"start_seconds":16,"text":"as a research engineer at a Quant fund called two Sigma in New York um when I was in school i' had also done stints of","url":"https://www.youtube.com/watch?v=KD1BMaNLuts&t=16s"},{"start_seconds":24,"text":"HCI as well as ml research notably in applying unsupervised learning methods um in Market Reg detection and using","url":"https://www.youtube.com/watch?v=KD1BMaNLuts&t=24s"},{"start_seconds":30,"text":"that for portfolio optimization and uh I will give everyone a quick rundown of open gradient shortly but excited to","url":"https://www.youtube.com/watch?v=KD1BMaNLuts&t=30s"},{"start_seconds":38,"text":"first talk about what the road to a trillion Advanced agent kind of looks like in my view so I kind of think about agent development in a couple different","url":"https://www.youtube.com/watch?v=KD1BMaNLuts&t=38s"},{"start_seconds":46,"text":"stages stage one you have agents that can you know synthesize and reason about with data which you can already see with all these Twitter agents popping up","url":"https://www.youtube.com/watch?v=KD1BMaNLuts&t=46s"},{"start_seconds":54,"text":"tweeting interestingly provocative things secondly you have stage two which is agents are able to complete tasks on","url":"https://www.youtube.com/watch?v=KD1BMaNLuts&t=54s"},{"start_seconds":62,"text":"the behalf of their human overlords such as placing simple transactions such as you know buying a simple token and you","url":"https://www.youtube.com/watch?v=KD1BMaNLuts&t=62s"},{"start_seconds":69,"text":"kind of already see a lot of AI agents notably on uh the near chain kind of able to do this and serve as assistance","url":"https://www.youtube.com/watch?v=KD1BMaNLuts&t=69s"},{"start_seconds":77,"text":"um and here I've also attached a little screenshot of um one of the tweets that Ilia had put out about how a lot of these agents are kind of helping humans","url":"https://www.youtube.com/watch?v=KD1BMaNLuts&t=77s"},{"start_seconds":85,"text":"with mundane tasks like routing trades and routing orders and and lastly the kind of final stage for AI agent","url":"https://www.youtube.com/watch?v=KD1BMaNLuts&t=85s"},{"start_seconds":92,"text":"development in my opinion is when AI agents are able to surpass clearly human abilities in handling complex tasks and","url":"https://www.youtube.com/watch?v=KD1BMaNLuts&t=92s"},{"start_seconds":100,"text":"this might look like you know AI agents that are able to run fully autonomous companies AI agents that are able to run and participate in Dow Dows uh as well","url":"https://www.youtube.com/watch?v=KD1BMaNLuts&t=100s"},{"start_seconds":109,"text":"as AI agents that can manage portfolios and be able to you know trade effectively and generate profit consistently but if you look at the","url":"https://www.youtube.com/watch?v=KD1BMaNLuts&t=109s"},{"start_seconds":117,"text":"state of uh you know Frontier Model LMS and AI agents today a lot of them are extremely intelligent and uh you know especially given the previous panel can","url":"https://www.youtube.com/watch?v=KD1BMaNLuts&t=117s"},{"start_seconds":126,"text":"access things such as tool calls and rag in order to make it smarter but when you ask it hey what is the price forecast","url":"https://www.youtube.com/watch?v=KD1BMaNLuts&t=126s"},{"start_seconds":133,"text":"for sui what you know asset should I buy to minimize my risk adjusted return so to maximize my risk adjusted returns things like that the llms or AI agents","url":"https://www.youtube.com/watch?v=KD1BMaNLuts&t=133s"},{"start_seconds":142,"text":"aren't able to give you a very textured or detailed response and in our view we kind of want","url":"https://www.youtube.com/watch?v=KD1BMaNLuts&t=142s"},{"start_seconds":150,"text":"to build AI agents that are able to address those tasks and give you textured responses and execute on them effectively and from my view there are","url":"https://www.youtube.com/watch?v=KD1BMaNLuts&t=150s"},{"start_seconds":158,"text":"essentially three different kind of bottlenecks and Technical hurdles that we need to overcome in order to advance Agents from stage two to stage three","url":"https://www.youtube.com/watch?v=KD1BMaNLuts&t=158s"},{"start_seconds":167,"text":"firstly data pipelines you need to give AI agents the ability to reason about with more complex and a wider variety of different data sources as an example if","url":"https://www.youtube.com/watch?v=KD1BMaNLuts&t=167s"},{"start_seconds":175,"text":"you have a portfolio manager agent that agent might want to be able to pull Twitter data in order to analyze the sentiment around certain crypto assets","url":"https://www.youtube.com/watch?v=KD1BMaNLuts&t=175s"},{"start_seconds":183,"text":"on crypto Twitter secondly computational workflows allowing AI agents to um you know venture outside the world of using","url":"https://www.youtube.com/watch?v=KD1BMaNLuts&t=183s"},{"start_seconds":191,"text":"a large language model and run a computational workflow that might involve as an example um a mean variance portfolio optimization workflow that","url":"https://www.youtube.com/watch?v=KD1BMaNLuts&t=191s"},{"start_seconds":199,"text":"gives the aih and the ability to optimize its portfolio Holdings or run a simple risk analysis on uh you know","url":"https://www.youtube.com/watch?v=KD1BMaNLuts&t=199s"},{"start_seconds":206,"text":"various assets things like that allowing it to you know uh actually perform detailed analysis uh and um you know","url":"https://www.youtube.com/watch?v=KD1BMaNLuts&t=206s"},{"start_seconds":215,"text":"become smarter with domain specific intelligence and lastly is Agent interoperability uh so I'm extremely","url":"https://www.youtube.com/watch?v=KD1BMaNLuts&t=215s"},{"start_seconds":222,"text":"personally bullish on the ability to allow agents to compose with one another in order to comp in order to complete extremely complex um and Abstract goals","url":"https://www.youtube.com/watch?v=KD1BMaNLuts&t=222s"},{"start_seconds":231,"text":"as an example uh portfolio manager agent U might leverage an execution agent in order to find the best venue to trade to minimize Market impact","url":"https://www.youtube.com/watch?v=KD1BMaNLuts&t=231s"},{"start_seconds":240,"text":"or to minimize uh you know the cost and fees that they would have to pay in order to cross the spread and might use a marketing agent to you know pump uh","url":"https://www.youtube.com/watch?v=KD1BMaNLuts&t=240s"},{"start_seconds":248,"text":"tokens that it might hold in its portfolio things of the sort and I think these are all extremely exciting kind of um you know Primitives that we are","url":"https://www.youtube.com/watch?v=KD1BMaNLuts&t=248s"},{"start_seconds":257,"text":"building at open gradient as well which I'll get to shortly um and this is just a quick screenshot of a little piece of writing that we had put out about how","url":"https://www.youtube.com/watch?v=KD1BMaNLuts&t=257s"},{"start_seconds":265,"text":"the three kind of key pieces that I just spoke about will allow agents to become more intelligent with access to you know computational workflows data pipelines","url":"https://www.youtube.com/watch?v=KD1BMaNLuts&t=265s"},{"start_seconds":274,"text":"and uh you know access to other agents and you know allowing us to compose different agents together to create powerful computational","url":"https://www.youtube.com/watch?v=KD1BMaNLuts&t=274s"},{"start_seconds":281,"text":"applications but what's next so briefly on what open gradient is we're building uh a full stack infrastructure platform that allows developers to very freely be","url":"https://www.youtube.com/watch?v=KD1BMaNLuts&t=281s"},{"start_seconds":290,"text":"able to build AI or ml applications on chain in a way that is both verifiable and extremely seamless uh we want to","url":"https://www.youtube.com/watch?v=KD1BMaNLuts&t=290s"},{"start_seconds":297,"text":"allow developers to integrate quite simply any model into any application on any chain uh we have an infrastructure layer uh that has you know various nodes","url":"https://www.youtube.com/watch?v=KD1BMaNLuts&t=297s"},{"start_seconds":306,"text":"they handle compute heavy tasks including inference including running secure data pipelines we have uh our blockchain Network which allows","url":"https://www.youtube.com/watch?v=KD1BMaNLuts&t=306s"},{"start_seconds":313,"text":"developers to build um using these data pipelines using different models uh directly in their solidity smart contracts uh and we also have","url":"https://www.youtube.com/watch?v=KD1BMaNLuts&t=313s"},{"start_seconds":321,"text":"cross-chain messaging that allows these computational workflows to service apps or agents or protocols on any other chain we have a model Hub that is live","url":"https://www.youtube.com/watch?v=KD1BMaNLuts&t=321s"},{"start_seconds":330,"text":"at hub. openg gradient. that you can check out with a couple hundred models many of them are web 3 specific we host sentience uh you know large language","url":"https://www.youtube.com/watch?v=KD1BMaNLuts&t=330s"},{"start_seconds":339,"text":"models so this is Dobby we host flocks uh small language models we have many many uh you know defi quantitative ml models that do spot forecasting","url":"https://www.youtube.com/watch?v=KD1BMaNLuts&t=339s"},{"start_seconds":348,"text":"volatility forecasting risk analysis and more and this is all live you can go check out and play around with those models and we have many active Builders building with these models and lastly we","url":"https://www.youtube.com/watch?v=KD1BMaNLuts&t=348s"},{"start_seconds":356,"text":"have uh pythonic SDK that allows developers to leverage our Tech and interact with all of these models and workflows without having to deal with","url":"https://www.youtube.com/watch?v=KD1BMaNLuts&t=356s"},{"start_seconds":363,"text":"the complexity of block blockchains for smart contracts and we also partner very closely with clients in order to get their agents protocols and applications","url":"https://www.youtube.com/watch?v=KD1BMaNLuts&t=363s"},{"start_seconds":371,"text":"off the ground by partnering with them and a lot of the time building models um and agentic workflows alongside these clients and I'll get to a couple","url":"https://www.youtube.com/watch?v=KD1BMaNLuts&t=371s"},{"start_seconds":379,"text":"interesting use cases later um you know quick overview on how we make this magic happen essentially it's through node","url":"https://www.youtube.com/watch?v=KD1BMaNLuts&t=379s"},{"start_seconds":386,"text":"specialization so uh unlike a typical blockchain we have many different types of nodes that do very specific things including inference nodes that run","url":"https://www.youtube.com/watch?v=KD1BMaNLuts&t=386s"},{"start_seconds":394,"text":"verifiable inference and generate proofs and AD stations uh data nodes that are able to you know run secure data pipelines to make these workflows data","url":"https://www.youtube.com/watch?v=KD1BMaNLuts&t=394s"},{"start_seconds":402,"text":"rich in nature and a decentralized file Store where all the models are stored and we have today one of the only","url":"https://www.youtube.com/watch?v=KD1BMaNLuts&t=402s"},{"start_seconds":410,"text":"repositories of web 3 specific models including like I mentioned kind of these small language models large language models and a variety of quantitative","url":"https://www.youtube.com/watch?v=KD1BMaNLuts&t=410s"},{"start_seconds":417,"text":"defi focused ml models that allow developers to build many of these powerful AI agents that can manage","url":"https://www.youtube.com/watch?v=KD1BMaNLuts&t=417s"},{"start_seconds":424,"text":"portfolios trade you know analyze risk on different assets and uh we also host yeah many um of our partners' uh models","url":"https://www.youtube.com/watch?v=KD1BMaNLuts&t=424s"},{"start_seconds":432,"text":"including ponds model which does Cil address detection and repos uh and file coins models which do uh minor","url":"https://www.youtube.com/watch?v=KD1BMaNLuts&t=432s"},{"start_seconds":439,"text":"allocation and and reputation uh analysis and uh kind of tying this back into how we intend to make AI agents","url":"https://www.youtube.com/watch?v=KD1BMaNLuts&t=439s"},{"start_seconds":447,"text":"intelligent and adaptive and real Real Time by leveraging these computational workflows powered by these highly specific models we are able to give AI","url":"https://www.youtube.com/watch?v=KD1BMaNLuts&t=447s"},{"start_seconds":455,"text":"agents domain specific intelligence instead of getting a extremely generic response from Claude now when you work with clients on open gradients like exponet when you ask it hey you know","url":"https://www.youtube.com/watch?v=KD1BMaNLuts&t=455s"},{"start_seconds":464,"text":"give me a short-term price prediction on an asset or you know uh give me the risk profile on a on suie it can actually query these models and give you you know","url":"https://www.youtube.com/watch?v=KD1BMaNLuts&t=464s"},{"start_seconds":472,"text":"historical forast as well as the current live forecast that can give you a much more textured and detailed response that actually addresses um you know the","url":"https://www.youtube.com/watch?v=KD1BMaNLuts&t=472s"},{"start_seconds":480,"text":"user's concerns in this case if I want to buy sui I want to understand the risk profile the current volatility associated with the crypto asset um","url":"https://www.youtube.com/watch?v=KD1BMaNLuts&t=480s"},{"start_seconds":488,"text":"another interesting one um one of our clients which is uh double up they are a gamble five prediction Market protocol","url":"https://www.youtube.com/watch?v=KD1BMaNLuts&t=488s"},{"start_seconds":494,"text":"um launch an AI agent that allows users to actually bet against the AI agent on The Price Forecast of different crypto","url":"https://www.youtube.com/watch?v=KD1BMaNLuts&t=494s"},{"start_seconds":502,"text":"assets um so the human can you know the human user can type in some Price Forecast and the AI agent of course can't forecast these prices so it runs a","url":"https://www.youtube.com/watch?v=KD1BMaNLuts&t=502s"},{"start_seconds":509,"text":"spot forecasting model on open gradient and that's able to give it um you know a very specific forecast powered by time series analysis and uh you know in 30","url":"https://www.youtube.com/watch?v=KD1BMaNLuts&t=509s"},{"start_seconds":518,"text":"minutes where when the the market resolves either the user double up doubles up or doubles their money or they lose uh their stake right um and","url":"https://www.youtube.com/watch?v=KD1BMaNLuts&t=518s"},{"start_seconds":526,"text":"from a quick preliminary analysis since the launch of this agent last month we can see that hey you know users actually perform worse than the AI agent because","url":"https://www.youtube.com/watch?v=KD1BMaNLuts&t=526s"},{"start_seconds":535,"text":"the AI agent has obviously access to uh ml models that can inform it of what the price predictions are and this is kind of like a very barebones live in","url":"https://www.youtube.com/watch?v=KD1BMaNLuts&t=535s"},{"start_seconds":543,"text":"production dealing with real user assets example of how we can give AI agents the ability to you know predict prices to","url":"https://www.youtube.com/watch?v=KD1BMaNLuts&t=543s"},{"start_seconds":550,"text":"eventually trade and manage portfolios effectively through the use of these modular um Ai and ml you know focused","url":"https://www.youtube.com/watch?v=KD1BMaNLuts&t=550s"},{"start_seconds":557,"text":"workflows and we're also working with many clients um you know big D5 protocols on building analytical quantitative defi AI agents that can","url":"https://www.youtube.com/watch?v=KD1BMaNLuts&t=557s"},{"start_seconds":566,"text":"give them uh you know that can give the protocol and users of the protocol access to many of these analytical capabilities and workflows powered by","url":"https://www.youtube.com/watch?v=KD1BMaNLuts&t=566s"},{"start_seconds":574,"text":"the kind of a ml models on our Hub and on our infrastructure so you can ask you know these quantitative agents hey you","url":"https://www.youtube.com/watch?v=KD1BMaNLuts&t=574s"},{"start_seconds":581,"text":"know what asset should I buy to maximize my risk adjusted returns if I have a million dollars of Bitcoin where which vaults should I deposit in in order to","url":"https://www.youtube.com/watch?v=KD1BMaNLuts&t=581s"},{"start_seconds":589,"text":"uh you know improve you know to to maximize the yield I can get on these assets and this AI agent is able to query and leverage these workflows in","url":"https://www.youtube.com/watch?v=KD1BMaNLuts&t=589s"},{"start_seconds":597,"text":"order to help users um achieve these abstract goals so I have a quick demo here which unfortunately probably is not going to","url":"https://www.youtube.com/watch?v=KD1BMaNLuts&t=597s"},{"start_seconds":606,"text":"load uh but this is just a quick example of if you go to hub. openg gradient. you can go upload any arbitrary AI ml model","url":"https://www.youtube.com/watch?v=KD1BMaNLuts&t=606s"},{"start_seconds":615,"text":"and inference it within seconds verifiably and there are tons of different models on there um you know courtesy of us as well as many of our","url":"https://www.youtube.com/watch?v=KD1BMaNLuts&t=615s"},{"start_seconds":622,"text":"modeling Partners as well as individual contributors for Aon ml specific web 3 models that you can go and play around with today um and yeah uh with these","url":"https://www.youtube.com/watch?v=KD1BMaNLuts&t=622s"},{"start_seconds":631,"text":"models we're excited to be introducing them as tool calls to the AI agents and we're working with many of the popular Frameworks as well to implement these","url":"https://www.youtube.com/watch?v=KD1BMaNLuts&t=631s"},{"start_seconds":638,"text":"tool calls um and uh very excited to be uh you know unleashing the new era of intelligent agents that can leverage these computational workflows to do much","url":"https://www.youtube.com/watch?v=KD1BMaNLuts&t=638s"},{"start_seconds":647,"text":"more complex and Abstract tasks thank you","url":"https://www.youtube.com/watch?v=KD1BMaNLuts&t=647s"}],"youtube_url":"https://youtube.com/watch?v=KD1BMaNLuts","url":"https://near-pedia.xyz/videos/KD1BMaNLuts"}