After the insanity of the crypto and metaverse hype, there was of course a suspicion from the start that the excitement about AI could also end in a bubble. But the voices of the doubters could hardly be heard. The screenshots of ChatGPT responses on social media were too dramatic. The self-attempts to chat on your own PC or cell phone are just too fascinating. Too determined Google, Meta and Microsoft as well as many other established companies who jumped on the topic and invested billions upon billions. On the one hand, the media attention to the topic is of course waning somewhat. On the other hand, it must now be clarified what or whether the gigantic investments will bear any fruit at all. The Washington Post has put together a brief overview of why skepticism is warranted. This should be mandatory reading, at least for those in a hurry, before any further discussion (more in-depth, for example, is the substack AI Snakoil by Arvind Narayanan and Sayash Kapoor – whom I interviewed here).
First of all: The now legendary number of 100 million users that ChatGPT was able to win within three months after the start is not really correct – it is a slanted interpretation in the spirit of Open AI. The number is considered proof that we are experiencing an extraordinary moment in the history of technology.
What is missing are tangible numbers: How much have Microsoft and Google actually earned with their generative AI offensive? Isn’t AI perhaps a billion dollar grave? The corporations are just as opaque on this issue as they are on the details of the exact functionality and training data of their language models.
Post reporter Gerrit de Vynck reminds that the tech industry is littered with flops: dot-com, social media sites that no one wanted, crypto, metaverse, and the perennial favorite: self-driving cars
But it’s still unclear how and when this technology will actually become profitable — or if it ever will…“generative AI” is incredibly expensive to build and run — from specialized chips to data server computing power to expensive engineers.
The crucial question is probably: Can generative AI really be a quantum leap or just a gradual improvement of existing technology – because then it would simply be too expensive:
“At the end of the day, AI is just software, it’s expensive software,” Andrew Harrison, CEO of venture capital firm Section 32, said. “It’s low-margin software unless it does something that’s 10 times better.”