How Can Tech Startups Compete In Deep Learning?

How can startups compete in Deep Learning when the tech giants (Google, Amazon, Baidu, Microsoft, Apple) have so much more data? originally appeared on Quora: the place to gain and share knowledge, empowering people to learn from others and better understand the world.

Answer by Eric Vishria, General Partner at Benchmark, on Quora:

There is this narrative out there that it is “all about the data,” “whoever has the most data wins…” I may have subscribed to that theory in the past but I now think it is largely wrong, and may have been perpetuated by the big companies to tout their advantage. Deep Learning tools and frameworks are so nascent, and the skill set so rare, that meaningfully better algorithms are possible, and make a huge difference.

For example, I believe Blue Hexagon has those. When there are literally 100’s of thousands of new malware variants PER DAY, it just makes sense that IF you could get neural networks to analyze the traffic, at line speed, it would be order of magnitude better than the current signature and sandbox based approaches. But getting the algorithms right are hard and matter a lot. Another example Benchmark has invested in (not Deep Learning specifically but related) is DeepL, a machine translation company. Google Translate is widespread and obviously has way more data and compute than just about anyone you could imagine, and yet a small company, DeepL, produces meaningfully better translations almost every time – try it for yourself.

The large incumbents do have real advantages when it comes to talent, and paying really high salaries for talent, and access to nearly unlimited compute. But even those advantages can be overcome with novel technical approaches, and I believe engineers who have that rare technical capability AND desire to have a huge impact on the world will continue to choose the startup path rather than be a cog in a huge machine.

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