Artificial Intelligence Sub-Sectors
Related research

The Battle of the AI Agent Frameworks
By
Anil Lulla•
The AI application bubble has only just begun. RL, distillation, inference time compute: the cat is out of the bag. Even if models were not scaling along four vectors (which they are) and the capabilities stall out (which they won't), we have enough fire power to transform entire industries as developers and organizations figure out how to harness these new capabilities. Based on adoption to date, $ai16z, $Virtual, and $ARC are likely the best positioned to capture these tailwinds. ai16z due to its developer ecosystem. Virtuals do to its launchpad and GTM execution, and ARC due to its differentiated approach to high-performance agents.

The Year Ahead for AI + DePIN 2025
By
Anil Lulla•
2025 is poised to be a big year for both DeAI and DePIN, two crypto sectors we expect to continue outperforming as Bitcoin charts it’s course into the unknown. We expect 2025 to be the year where mainstream users and AI experts alike begin to recognize the benefits of this unlikely marriage: synthetic intelligence and a permissionless global ledger. From distributed training runs, to verified identity and inference, to data collection and attribution, to exchange and speculation, it will become obvious that DeAI is not a “massive grift” but the intersection of what will be our generations two defining technologies.

DeAI IV: The Agentic Economy
By
Anil Lulla•
The agentic economy may prove to be the most lucrative investment theme of our generation. With the value of your labor going to zero, the train only leaves the station once. The industrial revolution provoked changes in societal organization - from farms to factories - which demanded institutional reform - from feudalism to markets - which, in turn, required new legal and governance arrangements to cope with, and capitalize on, these fundamental shifts. Looking at our current trajectory, AI's impact on the economy will be more meaningful: transforming society not in two centuries, but in as little as two decades.

DeAI III: Composable Compute
By
Anil Lulla•
Software is eating the world. AI is eating software. AI is largely the combination of data, compute and talent. The entity or network which most effectively organizes these resources is set to own the 21st century. Whether you or I have any role to play in this future may very well be decided by how efficiently the long-tail can coordinate. Distributed training, efficient routing, verifiability, privacy, and effective developer incentives may will decide the difference. DeAI will live or die based on this test. The test of composable compute.

DeAI II: Seizing the Means of Production
By
Anil Lulla•
Dive into the Infrastructure Layer of the Decentralized AI (DeAI) crypto stack in part 2 of our DeAI series. Learn about Compute projects like Render, Gensyn, io.net and more, plus whether the "Airbnb for GPUs" narrative has legs. Then focus on Data: Scaling Data, Synthetic Data, AI Search and how Agentic Protocols like DataDAOs and DePIN fit in. Finally, the enablers of these data ecosystems like marketplaces, Lakehouses Storage and Retrieval. Will DeAI helps us achieve Digital Liberalism?

The Delegated Authorization Network: Trust Minimization in the Age of AI
By
Anil Lulla•
The report discusses the longstanding user experience (UX) problems in on-chain applications within the cryptocurrency space, emphasizing the need for improved interfaces to make interactions more accessible for new users. It highlights how current methods, especially in EVM ecosystems, still rely heavily on browser extensions like MetaMask, creating a steep learning curve for users transitioning from centralized exchanges (CEXs) to decentralized finance (DeFi).
The introduction of AI agents is proposed as a potential solution to streamline on-chain interactions. These AI agents can automate complex processes by translating natural language instructions into executable blockchain transactions. However, they come with risks, such as the tendency for AI to produce incorrect outputs ("hallucinations").
The report also details the Delegation Authorization Network (DAN) developed by Biconomy and Silence Labs, which enhances security by managing transaction authorizations without exposing user keys. This network aims to facilitate permission management, allowing users to set specific parameters for AI agents to operate within.
Overall, while AI agents hold promise for enhancing the crypto UX, the report suggests that we are still a significant time away from widespread, secure adoption of this technology, with ongoing developments needed to ensure reliability and safety.
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