- cross-posted to:
- technews@radiation.party
- technology@lemmy.world
- cross-posted to:
- technews@radiation.party
- technology@lemmy.world
Silicon Valley has bet big on generative AI but it’s not totally clear whether that bet will pay off. A new report from the Wall Street Journal claims that, despite the endless hype around large language models and the automated platforms they power, tech companies are struggling to turn a profit when it comes to AI.
Microsoft, which has bet big on the generative AI boom with billions invested in its partner OpenAI, has been losing money on one of its major AI platforms. Github Copilot, which launched in 2021, was designed to automate some parts of a coder’s workflow and, while immensely popular with its user base, has been a huge “money loser,” the Journal reports. The problem is that users pay $10 a month subscription fee for Copilot but, according to a source interviewed by the Journal, Microsoft lost an average of $20 per user during the first few months of this year. Some users cost the company an average loss of over $80 per month, the source told the paper.
OpenAI’s ChatGPT, for instance, has seen an ever declining user base while its operating costs remain incredibly high. A report from the Washington Post in June claimed that chatbots like ChatGPT lose money pretty much every time a customer uses them.
AI platforms are notoriously expensive to operate. Platforms like ChatGPT and DALL-E burn through an enormous amount of computing power and companies are struggling to figure out how to reduce that footprint. At the same time, the infrastructure to run AI systems—like powerful, high-priced AI computer chips—can be quite expensive. The cloud capacity necessary to train algorithms and run AI systems, meanwhile, is also expanding at a frightening rate. All of this energy consumption also means that AI is about as environmentally unfriendly as you can get.
Good. Maybe the hype will finally die down soon and “AI” won’t be shoved into every nook, cranny, and Notepad app anymore.
I’ll say AI is a bit more promising, but all of this just really reminds me of the blockchain craze in 2017. Every single business wanted to add blockchain because the suits upstairs just saw it as free money. Technical people down below were like “yeah cool, but there’s no place for it”. At least I could solve some problems, but business people again just think that it’s going to make them limitless money
Nah, blockchain has extremely limited applications.
Generative AI legitimately does have quite a number of areas that it can be made use of. That doesn’t mean that it can’t be oversold for a given application or technical challenges be disregarded, but it’s not super-niche.
If you wanted to compare it to something that had a lot of buzz at one point, I’d use XML instead. XML does get used in a lot of areas, and it’s definitely not niche, but I remember when it was being heavily used in marketing as a sort of magic bullet for application data interchange some years back, and it’s not that.