Answer by Tikhon Jelvis, researched programming languages, on Quora: I’ve seen machine learning overrated in a few ways, both by people with little experience and, more perniciously, people deeply invested in the field. Businesses are increasingly reducing, offloading, and offshoring their data science capabilities. ... few people really understand the techniques that are in the center of play. The most common belief is that machine learning is more general and more powerful than it really is. Why can't programming languages agree on some basic syntax? Thanks! Unlike so many hyped technologies and overrated buzzwords, machine learning is not going away — probably ever. A lot of consumer products now feature machine learning at their core—think of Quora and Facebook’s feed. In a manner of speaking, machine learning is simply statistics at speed and scale. It’s like this example: you never see any ads that say, “eat more meat.” (You see ads for types of meat because they’re competing with each other.) Learning from success is already baked into our brains. What really matters is that Quora has a feed and lets you follow people and topics. Unlik e so many hyped technologies and overrated buzzwords, machine learning is not going away — probably ever. Machine learning is good at things machine learning is good at and, of course, it’s bad at everything else. I’m not surprised by this state of events. Take the problem of forecasting demand for items at a store. EY & Citi On The Importance Of Resilience And Innovation, Impact 50: Investors Seeking Profit — And Pushing For Change, Michigan Economic Development Corporation with Forbes Insights. Just because it didn't use ML doesn't mean it's not a form of artificial intelligence. Machine learning models work off of the same inductive principles. You’ll need to spend a lot of time configuring the algorithm for your problem, even if your problem is almost identical to the original you’re working from. In what ways is machine learning overrated? originally appeared on Quora: the place to gain and share knowledge, empowering people to learn from others and better understand the world. You might think you can just apply some machine learning algorithm you’ve heard about to your problem, but chances are it won’t work nearly as well as the blog post or paper you got it from. A related problem is that people overstate the impact of machine learning in a product. It is almost certainly a buzzword, vigorously lapped by journalists, analysts and even CEOs. Not a day passes without us hearing or reading something about machine learning or artificial intelligence. by . But that might just be wishful thinking and it is a long way out! But too many people don’t design problems like this because they see machine learning as a panacea and see building a black box that operates solely on data as a goal. Neural nets are “just ‘another tool in your machine learning toolbox’” and, more importantly, machine learning is just another tool in your programming toolbox! Got a burning unpopular opinion you want to share? Though they look at 60-70% accuracy, eventually they want to increase accuracy to add more business value. What is the relationship between psychology & computer science? The pandemic has increased the demand — and the hype. Data Science is Overrated, But Do It Anyway. Press J to jump to the feed. I am a bot, and this action was performed automatically. You’ll need to tune hyperparameters, find the right architecture, pre-process your data in weird ways, maybe even restate parts of your problem… You can’t just throw your problem at an existing algorithm; you’ll either need extensive experience or a lot of trial and error. I mostly chalk this down to inexperience and misplaced enthusiasm, but it’s also a result of aggressive hype by people who should know better. Some strategies were developed or discovered with machine learning techniques (also known as “statistics”) but others are created more thanks to deep domain expertise. If you listen to some people though, you’d believe you could throw a neural net at any problem and get a solid solution.