EXCLUSIVE: How Decentralized AI Stands Out Over AGI With OKX Ventures Head

Artificial intelligence rose to the pedestal last year as developers raced toward delivering the most impressive AI models, and along with the rise of the likes of GPT4, Grok, and DeepSeek, decentralized AI gradually turned heads.

Artificial general intelligence (AGI), which works around developing human-like intelligence and self-teaching in AI, has been at the center of recent rivalries, but growing interest in decentralized AI is challenging AGI’s dominance in the discussions.

In an exclusive with International Business Times, Jeff Ren, the head of OKX Ventures, leading cryptocurrency exchange OKX’s venture capital arm, delved into the differences between decentralized AI and AGI, and why the former could be bigger than the latter in the future due to its unique advantages in helping drive economic development.

Decentralization’s Unique Facets in an Evolving AI Realm

Decentralized AI and AGI are two different technologies that could both do good if developed with the right motives. On the other hand, decentralized AI has strikingly unique facets that could challenge the focus on AGI.

For Ren, a comparison between the two may not necessarily determine which technology is better, since the two are trekking different paths.

He noted how AI has three pillars: data, algorithm, and computing power. With the current landscape in Web3 and AI, Ren believes decentralization has exceptional factors that make decentralized AI stand out over AGI.

“I believe decentralized AI frameworks offer a unique advantage in democratizing both value creation and distribution. While centralized AI platforms like OpenAI have shown impressive technological capabilities, they’ve created concentrated value pools that don’t effectively reward the broader ecosystem of contributors,” he said.

He went on to note that OKX Ventures, through its investments, has seen how decentralized frameworks enable a more sustainable economic model wherein data providers, developers and computational resource providers can all participate in the value creation process.

He noted how democratization is paving the way for talented small teams to compete effectively with the tech giants ruling the AI sector. “This shift from centralized to distributed innovation is creating new economic opportunities while driving more rapid technological advancement,” he added.

The domination of a select number of big tech giants in AI is also raising concerns around centralized systems.

An MIT Media Lab report found that at a time when AI is evolving beyond screen assistants, “decentralization emerges as the critical factor for unlocking its full potential.”

It argued that centralized models dominated by just a few AI giants, such as OpenAI, have started reaching their limits, potentially hampering or delaying AI’s growth. “To unlock the true power of AI, we need a new paradigm: decentralized AI,” the research stated.

The Issue on Ethical Application and Decentralized AI’s Answer

When AI started making waves in the broader tech space, ethical application became a key talking point, especially amid concerns about biased datasets and other unforeseen consequences. This is where decentralized AI has an answer.

Ren explained that “ethical alignment isn’t a one-size-fits-all proposition,” but decentralized AI frameworks do provide a unique solution “by enabling transparent, community-driven governance models.”

Through collaborations with AI projects, OKX Ventures has seen projects that demonstrate how multi-agent systems with built-in verification mechanisms can create more accountable AI development.

“The key advantage lies in the combination of blockchain transparency and decentralized governance. Unlike centralized AGI systems where decisions are made behind closed doors, decentralized frameworks enable real-time auditability of the entire AI pipeline – from data collection to model training. This transparency, coupled with economic incentives through token mechanisms, creates a natural alignment between ethical behavior and economic success,” he said.

How Decentralized AI Solves Some of AGI’s Challenges

Decentralization is already showing much promise in potentially solving some of the critical issues faced by AI developers, but Ren identified two crucial aspects where the technology is providing an answer to challenges around AGI development.

• Transparency and Verifiability – Questions were raised after news outlets sued OpenAI over its AI training, but with decentralization, the entire AI pipeline has no choice but to be more transparent and verifiable. Projects that offer AI infrastructure hubs for verifiable inference demonstrate how blockchain infrastructure can track and verify every step of the process, “addressing the fundamental need to understand how AI models are trained and what their original intentions are,” he said.
• Resource Democratization – Decentralization has always been about democratization, and with decentralized AI’s promise of democratizing resources, innovative frameworks are on the rise. Ren specifically mentioned an open-source Rust framework for creating LLM-powered applications, which enables efficient resource sharing and coordination through blockchain tech. “This is particularly important because it allows specialized teams to focus on solving specific business needs without requiring massive infrastructure investments. The diversity of data and compute resources in a decentralized ecosystem also leads to more robust and adaptable AI systems,” he said.

2025: The Year of Decentralized AI

2024 was the year of AI, but 2025 just could be the year of decentralized AI, especially as the technology continues to evolve significantly, making pipelines more practical and efficient.

OKX Ventures is actively involved in the market, with over 300 portfolio projects across five continents. Ren expects significant growth in decentralized AI investments throughout the year.

“What’s particularly encouraging is how the market is evolving beyond simple token speculation to focus on real utility. Projects are demonstrating how AI can enhance existing blockchain applications while creating entirely new use cases,” he said.

Aside from an apparent shift from speculation to real utility, there’s also the pivot in regulation across the broader blockchain spectrum.

Ren projected that when improved infrastructure and clearer regulatory frameworks are combined, partnered with stronger technical foundations (solid innovation and sustainable models), there will be increased investment flows into decentralized projects, demonstrating the said triple threat combo.