NEAR AI Office Hours w EQTY Lab and Theoriq

A discussion on the latest AI research topics and unpacking some NEAR.AI focus areas

NEAR AI: https://near.ai/
Illia Polosukhin https://x.com/ilblackdragon
Alex Skidanov https://x.com/AlexSkidanov

guests
EQTY Lab
  / eqtylab  
Theoriq
https://x.com/TheoriqAI
Ron Bodkin
https://x.com/ronbodkin

In this NEAR AI Office Hours AI experts discuss the transformative potential of community-owned AI agents, the challenges of proprietary models, and the importance of open-source solutions. They explore the balance between commercial and open models, the role of data provenance, and how to ensure AI integrity and fair compensation for creators.

Takeaways
• Community-Owned AI Agents: Emphasizing the importance of community-created AI agents to avoid monopolistic control and foster collaborative problem-solving.
• Proprietary vs. Open Models: Discussion on the lead proprietary models have over open-source models and the implications for future AI development.
• Data Provenance and Integrity: The need for robust tools to ensure AI model integrity and data provenance, crucial for building trust in AI systems.
• Challenges in AI Attribution: Exploring the complexities of attributing data contributions to AI models and the computational challenges involved.
• Future of AI Governance: Highlighting the importance of developing governance models that ensure fair compensation and accountability in AI development.

Timestamps:
00:01:03 - Introduction to AI Agents: Definition and potential of autonomous AI agents.
00:02:48 - The Metaverse and AI Agents: Comparing the evolving understanding of the Metaverse to current perceptions of AI agents.
00:04:00 - Capabilities of AI Agents: Discussing the various tasks AI agents can perform and the advancements in AI models.
00:05:47 - Proprietary Models vs. Open Models: Analyzing the lead proprietary models have and their impact on the AI landscape.
00:09:45 - Integrity and Observability in AI: Importance of data provenance and governance in AI systems.
00:13:30 - Challenges in AI Attribution: Discussing the difficulties in proving what data trained a particular AI model.
00:18:14 - New Models for Rewarding Creators: Need for new compensation models in the age of AI.
00:22:10 - Gutenberg Press Analogy: Drawing parallels between the transformative impact of the Gutenberg Press and AI.
00:24:44 - Public AI Initiatives: Potential for public AI initiatives and the importance of keeping AI models open.
00:29:25 - Long-Term Stewardship of AI Models: Ensuring proper incentives and governance for the long-term stewardship of AI models.
00:33:36 - Proof of Alignment and Collaboration: Exploring methods to verify AI model computations and collaboration.
00:36:01 - Future of Verifiable Computing: Discussing advancements in verifiable computing and the role of cryptographic proofs.

Join NEAR's ecosystem:
Website: https://near.org/
Twitter:   / nearprotocol  
Blog: https://near.org/blog/