The Cost and Performance of Large Language Models

Ron Bodkin is a self-described “serial entrepreneur focused on beneficial uses of AI”. Ron founded ChainML in April 2022 to make it easier to integrate AI models into applications. The AI we know today is immature in so many ways and many of them relate to how crude the tooling is for traditional developers building AI-first features. 

The ChainML protocol is a cost-efficient, decentralized network built for compute-intensive applications running on blockchain technology. Prior to founding ChainML Ron had a distinguished entrepreneurial career having founded Think Big Analytics before it was eventually acquired by Teradata after which he spent three years in applied AI at Google. Ron is also an active investor and advisor and has degrees in Computer Science from McGill and MIT.

Listen and learn...

1. What led Ron to focus on how AI can have a positive impact on the world
2. Why Hinton's right when he says "we've invented a superior form of learning"
3. Where the current toolstack for building LLM apps is incredibly immature
4. How to control the cost and performance of LLM apps
5. Why human brains are inefficient
6. Why the "effective cost of computing" is being reduced by 50% every year
7. How we may get to AGI within 20 years
8. Why proprietary datasets and commercial issues will slow down AI innovation
9. The right way to regulate AI

References in this episode...

• Meredith Broussard, professor and author, on AI and the Future of Work
• Attorney relies on court cases made up by ChatGPT
• The Microsoft Sparks of AGI paper