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Nous Research: Crypto x AI Masterclass, 30 Million Model Downloads, Bittensor Subnets and Launching a Matrix Style World Simulator

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Innhold levert av The Delphi Podcast. Alt podcastinnhold, inkludert episoder, grafikk og podcastbeskrivelser, lastes opp og leveres direkte av The Delphi Podcast eller deres podcastplattformpartner. Hvis du tror at noen bruker det opphavsrettsbeskyttede verket ditt uten din tillatelse, kan du følge prosessen skissert her https://no.player.fm/legal.

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

Disclosures: This podcast is strictly informational and educational and is not investment advice or a solicitation to buy or sell any tokens or securities or to make any financial decisions. Do not trade or invest in any project, tokens, or securities based upon this podcast episode. The host and members at Delphi Ventures may personally own tokens or art that are mentioned on the podcast. Our current show features paid sponsorships which may be featured at the start, middle, and/or the end of the episode. These sponsorships are for informational purposes only and are not a solicitation to use any product, service or token. Delphi’s transparency page can be viewed ⁠⁠⁠⁠⁠here⁠⁠⁠⁠⁠.

  continue reading

418 episoder

Artwork
iconDel
 
Manage episode 409667304 series 2478788
Innhold levert av The Delphi Podcast. Alt podcastinnhold, inkludert episoder, grafikk og podcastbeskrivelser, lastes opp og leveres direkte av The Delphi Podcast eller deres podcastplattformpartner. Hvis du tror at noen bruker det opphavsrettsbeskyttede verket ditt uten din tillatelse, kan du følge prosessen skissert her https://no.player.fm/legal.

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

Disclosures: This podcast is strictly informational and educational and is not investment advice or a solicitation to buy or sell any tokens or securities or to make any financial decisions. Do not trade or invest in any project, tokens, or securities based upon this podcast episode. The host and members at Delphi Ventures may personally own tokens or art that are mentioned on the podcast. Our current show features paid sponsorships which may be featured at the start, middle, and/or the end of the episode. These sponsorships are for informational purposes only and are not a solicitation to use any product, service or token. Delphi’s transparency page can be viewed ⁠⁠⁠⁠⁠here⁠⁠⁠⁠⁠.

  continue reading

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