Future Developments in AI: Memory Sculpting and Architectural Remixing

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This chapter explores the future developments in AI, focusing on two areas: sculpting of memory and remixing and recombining architectures. The speaker discusses the importance of intentional design of training data, challenges in handling long sequences, the impact of training data on memory retention, and the potential of private companies in data creation. They also compare the strengths and weaknesses of attention mechanism and state space models, discuss the emergence of new models, and explore the concept of multiple states in language models.

In this episode, Nathan does an emergency pod deep dive into Mamba, a new state space model architecture. If you need an ecommerce platform, check out our sponsor Shopify: https://shopify.com/cognitive for a $1/month trial period.

We're hiring across the board at Turpentine and for Erik's personal team on other projects he's incubating. He's hiring a Chief of Staff, EA, Head of Special Projects, Investment Associate, and more. For a list of JDs, check out: eriktorenberg.com.

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TIMESTAMPS:

(00:00:00) - Episode Preview

(00:03:15) - Inventing something better than the transformer

(00:05:17) - Examination of human cognition

(00:15:44) - Sponsor: Shopify

(00:27:00) - Weaknesses of the transformer

(00:30:16) - Sponsor: Netsuite | Omneky

(00:33:40) - Giving AI memory

(00:39:32) - State Space Model Revolution

(00:55:00) - SRAM and High Bandwidth Memory

(01:36:16) - Block State and Hyena models

(02:04:00) - Advancing AI safety and interpretability

This show is produced by Turpentine: a network of podcasts, newsletters, and more, covering technology, business, and culture — all from the perspective of industry insiders and experts. We’re launching new shows every week, and we’re looking for industry-leading sponsors — if you think that might be you and your company, email us at erik@turpentine.co.