Artificial intelligence (AI) has been a hot topic in the tech world for years, and it’s no surprise that many investors are eager to invest in AI-related companies. But one Fast Money trader isn’t convinced that AI is all it’s cracked up to be.
Dan Nathan, a long-time Fast Money trader and frequent guest on CNBC’s Halftime Report, recently shared his thoughts on why he doesn’t think investing in AI is wise. According to Nathan, “I don’t believe we’re at the point where artificial intelligence can really make decisions better than humans can… I think this whole idea of artificial intelligence being some sort of panacea or savior for us is sillyville.”
Nathan believes that while there are certainly applications for AI technology today – such as facial recognition software or self-driving cars – these technologies still require human oversight and input. He argues that when it comes to making complex decisions about investments or other financial matters, humans will always have an edge over machines because they possess something machines do not: intuition.
Nathan also points out that while machine learning algorithms may be able to identify patterns more quickly than humans can, they lack the ability to interpret those patterns correctly without human guidance. As he puts it: “The problem with machine learning algorithms is you need someone who understands what the algorithm means… You need somebody who knows how to interpret what the algorithm says.” In other words, even if an algorithm identifies a pattern accurately enough for a computer program to act upon it autonomously, there must still be someone overseeing its actions so as not to make any mistakes due to misinterpretation of data.
In addition, Nathan notes that although computers may be able process large amounts of data faster than humans ever could before now thanks advances in computing power and speed; this does not necessarily mean they will come up with better solutions than people would have otherwise come up with using their own judgment and experience. As he explains: “You might get more information quicker but you’re going through all this stuff just like we used too — only now you’ve got computers doing it instead of people.”
Ultimately then Dan Nathan believes investing in Artificial Intelligence should remain off limits until further advancements are made which allow machines greater autonomy when interpreting data sets accurately without requiring human intervention every step along the way – something which currently remains beyond our reach despite recent breakthroughs within certain areas such as facial recognition software or self driving cars etc.. Until then however he suggests sticking with traditional methods involving human judgement rather than relying solely upon automated systems powered by Artificial Intelligence alone given their current limitations regarding interpretation accuracy without direct supervision from experienced professionals within each respective field .