“In the race to the future, it’s the long game that matters!” – Futurist Jim Carroll
It feels like 1993.
It’s a whirlwind with AI; new developments every day, staggering advances, relentless hype, somewhat massive hysteria, and yet real glimpses of something BIG happening.
Each and every day, I’ve been busy scouring my sources – newsletters, research services, mailing lists, and social networks – working hard to keep up with the developments in AI. We are probably only a matter of months away before you will be able to download your own personal ChatGPT or equivalent for use on your Mac or Windows machine. You can already do the same type of thing with the Stable Diffusion text-to-image system if you are on a Mac. You are about to be flooded by new ideas that once seemed unimaginable.
And yet, it seems to be moving too fast, like new technology always does. That’s why the post Early Days of AI (and AI Hype Cycle) by Elad Gil caught my attention because I’m always ranting about the fact that despite the speed of technology, it often takes a long time for people and organizations to catch up.
Right now, we are just in the early stages of Wave 2 — and have a long way to go to see what it all really means.
Even so, the pace of development is staggering. Some of the things I’ve seen just today include Meta announcing an AI platform that someone will inevitably use to release a real-time voice translation tool.
Another company announced a platform that would let companies build their own private ChatGPT-like service:
And just after I saw that, an announcement came out that the organization behind ChatGPT, OpenAI, would do the same thing.
Then I saw an AI tool that fixes AI errors made by other AIs….
…and then an AI tool that is geared towards doing nothing but write and provide guidance on writing computer code…
…followed by a tool that would just make deepfake videos…
It really all is moving way too fast, and it’s difficult to keep up. That’s interesting, because I discovered, using one new service I came across, that I’m actually dead. That’s kind of sad! Things are moving fast, and many things are broken.
Anyway, I digress.
It’s 1993 all over again, and it’s important to keep in mind that while we saw a similar explosion of announcements, it wasn’t until ’95, ’96, and beyond that, we started to see real applications of substance. This is where the predictions of Elad Gil bear relevance. From his post:
Wave 3 (coming soon): Next wave of startups currently being founded. It will be exciting to see what is in this mix and may include new formats like voice and video in addition to using natural language in more verticals and more ways, as well as new types of infrastructure. Companies like Eleven Labs/LMNT/LFG Labs, Braintrust, and many more will provide incremental experiences. There is a big wave of new startups coming. The current YC batch alone appears to have a 100 or more AI startups….
Wave 4 (coming 2024/2025?): First big enterprise adopters. Since enterprise planning and build cycles are so long, anticipate the first really products (versus demos or prototypes) from larger companies other than MSFT, Adobe, Google, Meta to start to show up in a year or two. This is when revenue to AI infra companies will start to ramp significantly relative to today, when hype will peak, and we will see further accelerated investment in AI.
This ties in with the approach I’m taking in my talks – something big is going on, but it’s going to take some time to unfold.
That’s why, when it comes to the future, it’s always about the long game!