Is Data Still a Moat?

RelatedHighlights

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 more

Jason Cohen • AI startups require new strategies: This time it's actually different

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.

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

Sonya Huang • Generative AI’s Act Two

Darren LI added

The Empty Promise of Data Moats | Andreessen Horowitz

Peter Lauten a16z.com

Jack Mcclelland and added

LLMs are a moat, but for how long?

An LLM vendor like OpenAI isn’t an aggregator, As far as I can tell.

• An aggregator leverages a monopoly on demand to commodify supply .

• Whereas a traditional industrial monopoly leverages a monopoly on supply to extract $ from demand .

LLM vendors seem more like a traditional industrial monopoly. Like an industr

Gordon Brander from Subconscious • LLMs and Information Post-Scarcity

Daniel Santos added

Data is the new oil. We believe it also has the potential to cause the next "data oil spill".

Bessemer Venture Partners • Roadmap: Data Privacy Engineering

sari added

Big Data Is Dead

Jordan Tigani motherduck.com

and added

With AI/ML technologies making the leap in recent years, the seductive illusion of data has only grown. More Founders are falling prey to the idea we had at Tickle: the phantom value and defensibility of data. Collecting data is easy now, but turning that exhaust into value is not trivial. Further, a world of abundant data, it’s getting harder to d... See more

NFX • What Makes Data Valuable: The Truth About Data Network Effects

Sixian added

To the extent that large language models (and I should note that while I’m focusing on image generation, there are a whole host of companies working on text output as well) are dependent not on carefully curated data, but rather on the Internet itself, is the extent to which AI will be democratized, for better or worse.

Ben Thompson • The AI Unbundling

sari added