| >I've noticed lately lots of discussions about AI and ML being just hype. Examples given in those discussions of where ML fails is in driverless cars and the fact that it cost too much to train. This is mainly in traditional media and specialized blogs. Their job is to get content out there. Of all that is written, what is useful to me is in homeopathic concentration. The most popular blogs are targeted for people getting into machine learning. We actually spend time with candidates breaking the news to them à out what the job is. They tend to think training the model is the most valuable/hard part. >Despite all of this is there a big enough problem space where Machine Learning is still the solution? We've been delivering such solutions for enterprise for the past seven years. The catch is that to deliver this value, you need to get many things right. To get these things right, you need to have gotten the chance to do it before. To get the chance to do it, you need to get in front of the right people. Most content and solutions concentrate on training models, which in our experience delivering projects in the real world, is the most trivial thing compared to other parts of the whole. Training is like building a concept car: compared to getting the actual car to market to actual drivers, this is a walk in the park. The majority of the work isn't news worthy. I mean, who would write about taking clients by their hand, communication, problem definition, empathy, building infrastructure, managing expectation, defining jobs to be done, measuring real world metrics [not talking about F1 scores], having long conversations about ethics, dealing with data dumps, moral support for your people, making your counterparts successful... These are topics that are common and not newsworthy. >Do we need Machine Learning experts or we're fine with software engineers who use Machine Learning techniques in their toolkit? Not mutually exclusive. These are different roles who do different tasks and have different outputs. One of the problems is precisely in interfaces between these roles. I write a bit about these things: - https://twitter.com/jugurthahadjar/status/130810318863405056... - https://news.ycombinator.com/item?id=24326473 - https://news.ycombinator.com/item?id=24463187 - https://news.ycombinator.com/item?id=24325090 |