Machine Learning: The Great Stagnation
There is about to be a &#x27;great pivot&#x27; in ML.<p>There has been a rabid frenzy of throwing money at anything that has ML in it. Soon investors and CEOs will realize that ML is effective in narrow ways and that not everything needs ML.<p>They will also realize that 1 ML team + ML as a service (Azure ML, Sagemaker, Google AI platform) is cheaper and works more reliably. The services will keep improving and an underpaid mediocre ML-Engineering team can work to keep the production system up and running.<p>Basically, ML teams might lose jobs just as DB&#x2F;Cluster admins did with the advent of serverless compute as service.<p>I expect it to (already happening) create a day trading company like hierarchy. The Fair&#x2F;Brain&#x2F;OpenAIs will pay 7 figures to the top grads to be first to market. BigN ML product teams will expand and stay as well paid as they are. Then there will be a huge drop as we move to offshore ML product teams that are viewed as cost centers by the remainder of 99% companies. These will be most of the jobs available.<p>In such a system, a pure ML scientist (usually a PhD) will only exist at the top companies. So if you are not in the top 1-3% percentile, you will not have a pure ML job. However, there will still be hybrid DS-SDE jobs (ML engineering, ML product maintenance, ML-as-a-service user) or hybrid DS-PM jobs (Analysts, Consultants, data driven business decision makers). So, anyone who is not in that top 1-3% will have to pivot to one of these 3 roles.<p>______________<p>I won&#x27;t call this an AI winter. But, it will definitely become boring majority of those employed in the field..