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.
This article isn’t saying that AI is a fad or otherwise not taking off, it absolutely is, but it’s also absolutely taking too much money to run
And if these AI companies aren’t capable of turning a profit on this technology and consumers aren’t able to run these technologies themselves, then these technologies may very well just fall out of the public stage and back into computer science research papers, despite how versatile the tech may be
What good is a ginie if you can’t get the lamp?
Well, maybe they should raise their prices then?
If they raise the prices too far though, I’ll just switch to running Facebook’s open source llama model on my workstation. I’ve tested and it works with acceptable quality and performance, only thing that’s missing is tight integration with other tools I use. That could (and I expect will soon) be fixed.