Generative AI: What's Next? | Talia Goldberg | Bessemer Venture Partners

TL;DR

The rapid development of AI, particularly large general-purpose transformer models, is unlocking new possibilities, making AI the new frontier. This has become more accessible to startups and developers, leading to exciting opportunities.

Transcript

In 2021, everything had to have a blockchain angle, and then you got a little valuation boost. And in 2022, if you have an AI angle, that's the case. So if you thought you could escape hearing about transformers or LLMs or AI, you were wrong. AI is the new web3 this year, and even though there's a lot of hype, we do think a lot of this hype is a lo... Read More

Key Insights

• 🌥️ AI, driven by large transformer models, is experiencing rapid progress, unlocking possibilities in various fields.
• 🤗 Startups and developers now have more accessibility to AI technology, thanks to developer APIs and open-source contributions.
• 🥹 Categories such as AI-native applications, personalized search, and model-agnostic enablers hold potential for significant value creation.
• 🈸 Full-stack companies with data moats, first movers in specialized applications like Jasper, and bilingual founders (technical and commercial) are particularly attractive to investors.
• 🤩 Usage patterns and retention curves over time are key indicators of sticky and successful AI products.
• 💁 AI has the potential to revolutionize information discovery, human-computer interaction, and data analysis, with examples like Replica, LLMs, and image generation using AI.
• 🏂 The AI market offers opportunities for collaboration and collaboration through AI advisory boards and partnerships.

Questions & Answers

Q: What is the main driver behind the hype and progress in AI?

The development of large general-purpose transformer models and their ability to generate high-quality output, driving interest and investments in AI.

Q: How is the accessibility of AI technology changing?

Previously, access to compute power and data was limited to centralized organizations. However, developer APIs and open-source contributions have made AI more accessible to startups and developers, enabling them to build models at parity with centralized organizations.

Q: What are the key areas of focus for investors in AI?

Investors are primarily interested in AI-native categories, including AI-powered applications like Jasper, personalized search experiences, and model-agnostic enablers that differentiate through network effects and community participation.

Q: What are the challenges and risks associated with the rapid pace of AI development?

The fast-moving nature of AI development creates uncertainty and makes it challenging for investors to identify long-lasting opportunities. Models that are considered state-of-the-art today can quickly be superseded, leading to potential disruptions in the market.

Summary & Key Takeaways

• AI, particularly large transformer models, has progressed at an astounding rate, enabling the generation of text, audio, and speech that is on par with human quality.

• The advancement in GPUs and model efficiency allows for faster progress and increased training on larger datasets, surpassing Moore's Law.

• The accessibility of AI to startups and developers is increasing due to developer APIs and open-source contributions, thus lowering costs and democratizing access to AI technology.