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The only metric that matters for a business is whatever helps their bottom line. No one really cares about competitive results if they can just fine tune some o
by haltist 3y ago
The only metric that matters for a business is whatever helps their bottom line. No one really cares about competitive results if they can just fine tune some open source model on their own data set and get good business outcomes. So if there is good data and access to compute infrastructure to train and fine tune some open source model then the only obstruction to figuring out if AI works for the business or not is just a matter of setting up the training and deployment pipeline. That requires some expertise but that can be learned on the job as well or from any number of freely available tutorials.
I don't think AI is hard to learn. The fundamentals are extremely simple and a competent software engineer can learn all the required concepts in a few months. It's easier if you already have a background in mathematics but not required. If you can write software then you can learn how to write differentiable tensor programs with any of the AI frameworks.
- Jensson 3y agoYes, and those businesses don't need to hire an AI person. This topic is AI research jobs, not for people who sometimes has to call an ML library once in a while in their normal software job. Edit: You asked what it is about these jobs that requires expertise. I answered: it requires expertise to create competitive models. So companies that need competitive models requires expertise.
- haltist 3y agoDo you build competitive AI models?
- Jensson 3y agoI worked on AI at Google, some would say Google isn't competitive in the space but at least they try to be and their business model depends on it. Edit: Why do you ask? I don't see why it is relevant for the discussion.
- haltist 3y agoHN is often full of abstract argumentation so it helps to know if someone has actual experience doing something instead of just pontificating about it on an internet forum.
- Jensson 3y agoI thought what I said was common knowledge on HN, it was last time I was in one of these discussions a few years ago. But something seems to have changed, I guess the "use ml library" jobs drowned out the others by now and that colored these discussions.
- haltist 3y agoPeople come and go so I don't know how much can be assumed to be common knowledge but what changed is that big enterprises figured out that ML/AI can now be applied in their business contexts with low enough cost to justify the investment to shareholders without anyone getting fired if things don't work out as expected. Every business has data that can be turned into profits and investing in AI is perceived to be a good way to do that now.
- Jensson 3y agoThose jobs has been on the rise for over a decade now, it was the majority of people talking a few years ago as well, but at least there was more awareness of the different kinds of jobs out there.