LLMs are actually spectacular for indexing large amounts of text data and pulling out the answer to a query. Combine that with natural language processing and it is literally what we all thought Ask Jeeves was back in the day. If you ever spent time sifting through stack overflow pages or parsing discussion threads, that is what it is good at. And many models actually provide ways to get a readout of the “thought process” and links to pages that support the answer which drastically reduces the impact of hallucinations.
And many of those don’t necessarily require significant power usage… relative to what is already running in data centers.
The problem is that people use it and decide it is “like magic” and then insist on using it for EVERYTHING. And you go from “Write me a simple function to interface with this specific API” to “Write me an application to do my taxes and then file them for me”
Of course, there is also the issue of where training data comes from. Which is why so much of the “generative AI” stuff is so disgusting because it is just stealing copyrighted data left and right. Rather than the search engine style LLMs that mostly just ignore the proverbial README_FBI.txt file.
And the “this is magic” is on both sides. The evangelists are demonstrably morons. But the rabid anti-AI/“AI” crowd are just as bad with “it gave you a wrong answer, it is worthless”. Think of it less like a magic box and more like asking a question on a message board. You are gonna get a LOT of FUD and it is on you to do additional searches to corroborate when it actually matters.
Like a lot of things AI/“AI”, they are REALLY good at replacing intern/junior level employees (and all the consequences of that…) and are a way to speed through grunt work. And, much like farming a task out to that junior level employee, you need to actually supervise it and check the results. Whether that is making sure it actually does what you want it to do or making sure they didn’t steal copyrighted work.
LLMs are actually spectacular for indexing large amounts of text data and pulling out the answer to a query. Combine that with natural language processing and it is literally what we all thought Ask Jeeves was back in the day. If you ever spent time sifting through stack overflow pages or parsing discussion threads, that is what it is good at. And many models actually provide ways to get a readout of the “thought process” and links to pages that support the answer which drastically reduces the impact of hallucinations.
And many of those don’t necessarily require significant power usage… relative to what is already running in data centers.
The problem is that people use it and decide it is “like magic” and then insist on using it for EVERYTHING. And you go from “Write me a simple function to interface with this specific API” to “Write me an application to do my taxes and then file them for me”
Of course, there is also the issue of where training data comes from. Which is why so much of the “generative AI” stuff is so disgusting because it is just stealing copyrighted data left and right. Rather than the search engine style LLMs that mostly just ignore the proverbial
README_FBI.txtfile.And the “this is magic” is on both sides. The evangelists are demonstrably morons. But the rabid anti-AI/“AI” crowd are just as bad with “it gave you a wrong answer, it is worthless”. Think of it less like a magic box and more like asking a question on a message board. You are gonna get a LOT of FUD and it is on you to do additional searches to corroborate when it actually matters.
Like a lot of things AI/“AI”, they are REALLY good at replacing intern/junior level employees (and all the consequences of that…) and are a way to speed through grunt work. And, much like farming a task out to that junior level employee, you need to actually supervise it and check the results. Whether that is making sure it actually does what you want it to do or making sure they didn’t steal copyrighted work.