The integration of AI within the Web3 ecosystem is taking a significant leap forward, according to Nick Havryliak, CEO and co-founder of data provenance protocol Assisterr.
Havryliak told Benzinga in an exclusive interview on Tuesday about the importance of creating a decentralized AI infrastructure to democratize the benefits of AI advancements.
“Major tech corporations have accumulated vast amounts of global data for free, using it to develop proprietary models in closed environments,” Havryliak said. “This results in a situation where only a privileged few reap significant benefits, perpetuating an imbalance in the AI ecosystem.”
Significant AI Adoption In Web3 Ecosystem
AI has found substantial adoption in finance and trading, with the emergence of Generative AI (GenAI) driving broader integration.
Assisterr, which recently announced a $1.7 million raise in a pre-seed round, is streamlining developer interactions within leading Web3 protocols by training models on meticulously curated datasets to achieve high-level accuracy for developing decentralized applications (dApps).
“Introducing AI assistants capable of deploying dApps on users’ behalf will democratize access to the Web3 space, fostering diverse and creative use-cases,” Havryliak said.
The impact of decentralized AI will be discussed at Benzinga’s Future of Digital Assets event on Nov. 19 in a panel discussion titled Blockchain for Good: From Fixing Poverty to Boosting Productivity.
Decentralized AI And DePIN Projects
The adoption of AI in the Web3 space is seen as crucial.
Havryliak highlighted the significance of Decentralized Physical Infrastructure Network (DePIN) projects, which leverage decentralized providers to mitigate challenges associated with centralized GPU/CPUs.
“The greatest value lies in decentralized coordination capabilities inherent to blockchains, which can effectively manage peer-to-peer interactions between devices and users,” he explained.
Havryliak also underscored the importance of generating sustainable demand for cloud services, GPUs and CPUs through Assisterr’s community equipped with thousands of Small Language Models (SLMs).
Community-Owned Small Language Models
Community-owned Small Language Models (SLMs) are pivotal for AI development, differing from traditional Large Language Models (LLMs).
“SLMs are neural networks trained on targeted text datasets, making them ideal for applications prioritizing data privacy and operational efficiency,” Havryliak said.
Assisterr has developed The Data Provenance Protocol to ensure fair compensation for data contributors within its ecosystem.
This protocol tracks data modifications on the blockchain, allowing transparent allocation of rewards based on contributions.
Challenges In Data Sharing For AI Applications
Addressing data ownership and incentivizing participation are foundational to the AI data market.
“Individuals must have the ability to assert ownership over their data, allowing them the right to sell and monetize what is rightfully theirs,” he said.
Also Read: Michelle Obama For Democratic Nominee? Crypto Bettors Think Her Odds Have Just Tripled
AI Agents For Developer Efficiency
Assisterr has developed AI agents for platforms like Solana SOL/USD and NEAR NEAR/USD to automate developer support and assist the community, particularly during hackathons.
These agents have significantly improved operational efficiency by automating up to 95% of support requests.
Incentive-Driven Inference Verification
Assisterr’s incentive-driven inference verification ensures the relevance and effectiveness of community-owned SLMs over time.
Havryliak explained that this approach operates effectively within game theory principles, with contributors and validators receiving rewards for accurate contributions.
Future Of AI In Web3
Assisterr plans to maintain the quality and accuracy of its SLMs through community crowdsourcing and clear financial incentives going forward and envisions tens of thousands of SLMs tailored for business applications and everyday tasks, providing a more efficient approach to these processes.
Competing With Big Tech
Community-owned SLMs are well-positioned to compete with Big Tech’s LLMs. Havryliak highlighted that Assisterr’s models have outperformed ChatGPT in providing accurate and detailed responses.
“Our Small Language Models (SLMs) will excel in providing users with current and beneficial information,” he said.
Role Of Crypto In AI Ecosystem
Cryptocurrency plays a crucial role in the AI ecosystem, serving as an ideal payment rail for AI.
“Crypto facilitates small transactions and rewards distribution, making it integral to the intersection of AI and Web3,” Havryliak said.
Benzinga’s Future of Digital Assets event on Nov. 19 promises to be a crucial platform for exploring the intersection of AI and blockchain technology, highlighting the transformative potential of these innovations.
Read Next:
Image: Shutterstock
© 2024 Benzinga.com. Benzinga does not provide investment advice. All rights reserved.
Comments
Trade confidently with insights and alerts from analyst ratings, free reports and breaking news that affects the stocks you care about.
