In this conversation, Jeff from Nous Research discusses their work on open source models and the BitTensor subnet. They address the challenges of ranking models on platforms like Hugging Face and the need for a more reliable and commercially viable model ranking system. Nous Research has developed Nous Hermes, an open source model that can be fine-tuned to follow specific instructions. They also created the BitTensor subnet, which allows developers to submit their models and rank them against synthetic data generated by GPT-4 and Claude. The goal is to approximate the state-of-the-art models and incentivize the creation of high-quality models. The conversation explores the potential of synthetic data generation, the future of model selection, the world simulator and amorphous applications, the intersection of AI and crypto, concerns and risks in the crypto AI space, the inevitability of AGI, the role of crypto in AI, regulation and over-regulation in crypto AI, the potential interaction between AGI and centralized systems, proof of personhood and verifying authenticity, and Nous Research's mission and focus.
Chapters
00:00 Introduction to Noose Research and Open Source Models
07:12 Overview of Nous Hermes and Fine-Tuning Models
26:30 Challenges with Open Source Models and the Need for BitTensor
32:10 Ranking and Reputation in BitTensor Subnet
34:27 Approaching GPT-4 with BitTensor
37:42 The Potential of Synthetic Data Generation
39:07 The Future of Model Selection
41:29 The World Simulator and Amorphous Applications
44:48 The Intersection of AI and Crypto
48:32 Concerns and Risks in the Crypto AI Space
51:17 The Inevitability of AGI
53:35 The Role of Crypto in AI
56:01 Regulation and Over-Regulation in Crypto AI
58:52 The Potential Interaction Between AGI and Centralized Systems
01:05:24 Proof of Personhood and Verifying Authenticity
01:10:04 Nous Research's Mission and Focus
01:12:26 Attracting AI Developers to Nous Research
Disclosures
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