- 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.
AI has been paying of for decades, it is used in all industries for appropriate tasks.
Now it is even better we are doing stuff no one thought it could be possible and advancing our work.
Perfect use case is for things that are simple to do but take too much time to be economical for humans (ex. counting products, plants, trees, cars, disease detection…) and using additional data to make better decisions.
Generative AI (for writing text, coding,… ) is of course no where close to being useful, but it can interesting to try. It is just a toy, expensive one, but still a toy.
I disagree. It’s absolutely useful… in certain industries, for appropriate tasks.
That doesn’t stop it from also being used as a toy.
100% agree with this. Good, sharp knives are incredibly useful for creating wonderful dishes in the kitchen. But people can also use them for harm.
I’ve seen some incredibly useful ways in which gen-AI can be used. A few months or so back, there was someone here on the Fediverse that was able to spin up a working prototype of a self-hosted Spotify replacement after only 8 or so hours of gen-AI code development. Stuff that would’ve taken 5x as long to research and code with just a human.
Gen-AI is ultimately a useful technology… when used the right way.