That aside, we're obviously in a bubble, that's the easiest claim in the world to make. We're also in a real estate bubble, etc. The only claim that matters is predicting when it will pop, otherwise it's just hot air.
For example I am currently doing self-directed study in maths. It turns out chatgpt is very good at explaining lots of things if you prompt correctly. You need to check things yourself and be on the lookout for plausible but wrong explanations, but it's like having a patient pure maths friend to work on things with - your friend won't get everything right either after all.
Something with real commercial potential is what microsoft released (I think today) [1] which is a sort of wizard thing that accellerates various azure gpt-powered standard deployments that do things like set up private ephemeral instances that connect to your enterprise data sources behind your firewall. This has enormous potential given how difficult it is in most large enterprises to actually join data sources together, find basic information etc. Think of an automated helpdesk that can draw on all of the stuff in all of the various disjointed systems in most big companies. That has the potential to be quite transformative to the workplace for a lot of people.
In general I think this bar of "transforming humanity" is just arbitrary and way too high for any technology. You could look at the map on your phone and say "that's all very well but will it transform humanity?" well no. It won't make toast either, but it's quite useful sometimes. Just as overinflated expectations and hype are unhelpful I think it's easy to be cynical and miss important tech developments just because we impose arbitrary standards on them that other technologies didn't have to meet on their way to adoption.
It's interesting that in the final matrix example it somehow messed up the Latex by forgetting to put \begin{bmatrix} at the front which is why the formatting goes bonkers. It's also kind of cheesy that it chose a diagonal matrix rather than having to find the roots of the characteristic polynomial but any case you get the idea hopefully and can see how this would be helpful when you're trying to learn this stuff yourself? I'm certainly finding it great as I work through textbooks etc to chat through concepts in this way to check my understanding and drill into things.
If you compare with smartphones then we are pretty much in the late 1980s brick phone era where the technology is just starting to be adopted by society.
The key technology, AGI, has not even been invented yet. It’s possible we may see a mini bubble if AGI takes a while to be developed, but I think it’s more likely that we won’t because even the current generation of AI has a lot further to run.
To clarify, I assume you are talking about Gen AI when you say "AI"?
In fact, it wouldn’t surprise me that Wall Street is already using it to trade some non-insignificant fraction of the US economy. Similar to how Linux is probably holding modern civilization together behind the scenes but most people are completely oblivious.
Every smartphone runs multiple AI systems in it. Some are used multiple times a day, most just working and keeping out of your way.
Unless you exclude from AI the stuff we used to call AI until it started working really well.
I understand generative AI as a million monkeys on a million typewriters, but we figured out how to rig the typewriters to generate convincing and sometimes correct output.
Neither monkeys individually or collectively understand anything about how they responded. They just get a treat for doing well.
AGI is something very different IMO. Language and speech will be emergent in AGI without requiring massive inputs, like how a child learns.
LLMs seem like sort of a (very impressive) parlor trick. Neat, useful and terrifying, but not a pathway to AGI.
ChatGPT was the largest growing site in the history of the Internet, reaching 100 millions users in two months. This seems more than 1980 brick phones
It’s disingenuous comparing the way Facebook scaled to ChatGPT which scales primarily along social media vectors with massive distribution.