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by Steeeve
3187 days ago
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It's an interesting time. Anyone paying attention knew that AI was the up and coming topic of interest for the last 5 years or more - which is why we're at a point now where several major providers offer cloud services and APIs dedicated to machine learning. The problems to solve are many, and relatively few people are actually looking at the enterprise market because the challenges associated with big consumer data are obvious, profitable, and data is widely available for research. The high dollar hires right now are primarily people with masters and phds that are highly relevant, but that will change in short order IMO like the whole market did in the mid-90s as markets grew out of nowhere. I think in three years - after we have a bit of a slump and nobody is investing in mobile apps or IOT anymore - we'll see a real rise in AI workflows that apply to mid-size enterprises. To get ahead of the game, start paying attention. Take the suite of AI courses from coursera, fast.ai, etc. Participate in Kaggle. Then find a job that is loosely related and allows you to keep pace. Three to five years down the road you'll be leading the way in a gigantic shift in the enterprise market. It's worth paying attention to distributed computing as well to understand how the whole data pipeline comes together. Not everybody will be structured the same way, but constantly changing large datasets are valuable and there are only so many ways to handle them. |
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I'm sure a lot of ML specialists are good coders, but they don't have a lifetime of experience in building production level software. Left to their own devices, they are going to be forced to re-invent the wheel over and over again, wasting time on over-engineered and under-utilized tools. There's value in being the guy who understands ML, and understands development but isn't an expert in linear algebra. There isn't a giant market for people like that at this point, but there is a market.