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Open Models and Maturation: Assessing the Generative AI Market

May 17, 2024

Exploring the maturation of the generative AI market, from the emergence of open source LLMs to AI-generated music. Discussion on the sawtooth pattern of growth in AI applications, the importance of fine-tuning models, and the evolution of founders and products in the AI industry. Delving into advancements in model creation and the shift towards open-source models, with a focus on benchmarking and evaluating performance in the LLM market. Exploring the wide-ranging impact of AI breakthroughs in music and education.

40:21

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Quick takeaways

Generative AI market growth follows a sawtooth pattern, with new spikes after flat periods.

Convergence of open source and close source AI models driven by extensive training data sets.

Deep dives

Future of Multi-Modal Models

The future of AI models seems to be oriented towards integrating multiple input and output modalities into one model, such as combining images and text. There is a widespread belief that model architectures are converging, with examples like the prominent role of Transformers in image generation evolving rapidly over time. As architectures continue to converge, these models are expected to become more popular and mature.

Value of Making Commitments

01:23

Market Dynamics and Future Trends for Language Models

01:38

Advancement of Open Source Models

01:00

Introduction

2min

Emergence of Competitive Open Models and Convergence with Closed Models

2min

Advancements in AI Model Creation and Scaling Ratios

2min

The Evolution of AI Models and Market Dynamics

22min

Comparing LLM Market to Database Market: Issues with Benchmarking and Evaluation

2min

Evolution of Founders and Products in the AI Industry

9min

Exploring AI Breakthroughs in Music and Education

2min

a16z partners Guido Appenzeller and Matt Bornstein join Derrick Harris to discuss the state of the generative AI market, about 18 months after it really kicked into high gear with the release of ChatGPT — everything from the emergence of powerful open source LLMs to the excitement around AI-generated music.

If there's one major lesson to learn, it's that although we've made some very impressive technological strides and companies are generating meaningful revenue, this is still a a very fluid space. As Matt puts it during the discussion:

"For nearly all AI applications and most model providers, growth is kind of a sawtooth pattern, meaning when there's a big new amazing thing announced, you see very fast growth. And when it's been a while since the last release, growth kind of can flatten off. And you can imagine retention can be all over the place, too . . .

"I think every time we're in a flat period, people start to think, 'Oh, it's mature now, the, the gold rush is over. What happens next?' But then a new spike almost always comes, or at least has over the last 18 months or so. So a lot of this depends on your time horizon, and I think we're still in this period of, like, if you think growth has slowed, wait a month and see it change."

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Guido Appenzeller

Matt Bornstein

Derrick Harris

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