AI Startup Trends: Insights from Y Combinator’s Latest Batch
updated 7mo ago
AI Startup Trends: Insights from Y Combinator’s Latest Batch
- The moats are in the customers, not the data. We predicted that the best generative AI companies could generate a sustainable competitive advantage through a data flywheel: more usage → more data → better model → more usage. While this is still somewhat true, especially in domains with very specialized and hard-to-get data, the “data moats” are on
... See morefrom Generative AI’s Act Two by Sonya Huang
Darren LI added
- Many of the largest scale uses of AI to date have been at consumer-centric companies that have large data sets to train on (Google, Facebook, Uber, etc). Perhaps incumbents won due to a data advantage that is now going away as companies use the broader internet as an initial training set + are switching to models that work more robustly against sma... See more
from AI: Startup Vs Incumbent Value by Elad Gil
sari added
Darren LI and added
- The existence of AI models means that openness is a bigger liability for user-generated content companies. The existence of a successful company in some category indicates demand for the content, so these are the easiest business models to drop into AI. "Quora, but there's no cold-start problem because our LLM can offer an instant answer" is one of... See more
from AI Turns UGC into a PVP Zone by Byrne Hobart
sari added
- While many of the prior innovations in AI were striking and exciting (AlexNet, CNNs, RNNs, GANs etc) this time does feel different for a few reasons. There is reason to believe while incumbents should capture a good amount of the value in this wave, startups will take a bigger share of AI generated value this time around.
from AI: Startup Vs Incumbent Value by Elad Gil
sari added
- There is no AI Strategy without a Data Strategy
Training AI models requires data. Whether you’re training existing models, developing models from scratch, or simply testing theories, high-quality data is crucial.
Incumbents have the data because they have the customers. They can immediately leverage customers’ data to train models and tune algorithm... See morefrom AI startups require new strategies: This time it's actually different by Jason Cohen
Nicolay Gerold added
I would differentiate between data for existing behaviors vs new behaviors. The world and our tools are constantly changing. I think AI is one of those drivers. I think the startups who can either facilitate new behaviors the best (e.g. Cursor for AI-assisted coding) or who can create entirely new behaviors have a great way to generate unique training data.
Taking existing data and making it workable with AI is a lot of work and takes skilled labor (AI + domain expertise). I wouldn’t say incumbents have the complete edge. They have the edge in certain applications and behaviors under the assumptions these behaviors are not changing to render their applications useless. - Sobriety source #2: AI as the next platform shift. Every wave of new companies that transforms their respective industries is fueled by a major platform or technology shift. The advent of the web did this. The smartphone and mobile applications did this. And there is no doubt that AI is our next wave. But does every new wave always necessarily favo... See more
from The Great Sobriety for Venture Investing, Where To Start with AI, & Undeniable Data
Abie Cohen added
AI notes What we look for in AI companies (and why they are different)
10 highlights
sari added