1. There is much more supply than demand in terms of Machine Learning and Data Science. There aren't actually that many jobs outside of research, it's just that the hype makes it look that way. Now that all these PhDs seem to be starting in ML, I wonder what they will do in 4-5 years when they finish the degree. I don't think a market for them will exist.
2. Many companies don't know what they are doing. They are hiring ML people because they want to put AI into their marketing materials. In reality, they don't need ML, they just need someone collecting data, building a database, and running a query. They just don't realize that's the case. The same happened with "Data Science" and "Big Data" - What most companies needed were software engineers building infrastructure and data collection, not people running sklearn.
> they want to put AI into their marketing materials.
Somebody should start a thread that captures the silly examples of this. My personal favorite was a workout template “powered by AI”. Mind you, the only information the customer provided was the basics like age, sex, weight, and goal. This signaled peak AI hype for me.
1. There is much more supply than demand in terms of Machine Learning and Data Science. There aren't actually that many jobs outside of research, it's just that the hype makes it look that way. Now that all these PhDs seem to be starting in ML, I wonder what they will do in 4-5 years when they finish the degree. I don't think a market for them will exist.
2. Many companies don't know what they are doing. They are hiring ML people because they want to put AI into their marketing materials. In reality, they don't need ML, they just need someone collecting data, building a database, and running a query. They just don't realize that's the case. The same happened with "Data Science" and "Big Data" - What most companies needed were software engineers building infrastructure and data collection, not people running sklearn.