Comment by jph00 | Hacker News Reader

Comment by jph00 | Hacker News Reader

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> Smart Reply, WaveNet, Translate, Speech Recognition, RankBrain, Photo/Image Search, Retinal diagnosis, Waymo (soon), and numerous other components that are used in Android and the Assistant.

These aren't examples of just productionizing a PhD thesis - they're thoughtfully designed products that solve a real problem.

Unfortunately we've watched as many ML PhD graduates launch startups which are little more than an API wrapped around the key algorithm from their thesis. These startups nearly always fail, because they don't actually address a market need.

> The only way to know if someone will be successful is to try it and let it succeed or fail in the marketplace.

There are many ways to estimate potential market size, product-market fit, etc ahead of time. They're not perfect, but they're a lot better than nothing.

> These aren't examples of just productionizing a PhD thesis

His point is that sometimes research bears fruit, and sometimes it doesn't. All universities (in my country) now have metrics for how much research must successfully bear commercial-fruit or else they lose funding from the government and the EU. As such, they have commercialisation pipelines that funnel viable commercial research into products. However, even these funding bodies don't expect that anything more than a fraction of research will be commercialisable. That isn't the point of research.

> we've watched as many ML PhD graduates launch startups which are little more than an API wrapped around the key algorithm from their thesis. These startups nearly always fail, because they don't actually address a market need.

Why do you care what someone does with their PhD research anyway?

Without PhDs work, you have no clue where to look. Pushing the idea to market not only requires a market fit, but also requires BS everywhere to educate customers. Building a product are efforts, but it is as equal as the efforts of creating the idea.

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