When I was a kid, I remember watching Star Trek IV: The Voyage Home. In this film, the crew of the Enterprise traveled back in time from 2286 to 1986. Scotty tried to use a MacIntosh computer by speaking to it, “Hello Computer”. Of course, it didn’t respond. Bones handed him the mouse, and Scotty spoke into it as if it were a microphone. Of course, that didn’t work either.
If you need a refresher, check out the scene here:
Back in 1986, and up until recently, the way the Star Trek crew interacted with their computers seemed like science fiction. Now, finally, 37 years later, I have a line-of-sight into how this can become our reality.
Another article about AI
You’ve probably noticed that I’ve been on an AI kick as of late. I’ve written about it here, here, and here, just in the past few months. Just two years ago, I was highly skeptical of what we could or should achieve with AI, but a lot has changed lately.
So much has changed, that I’ve been able to continue writing about this subject without repeating myself at all.
Star Trek
There’s a lot to like about the way the crew of the Enterprise interacts with their onboard computer. Of course, there are plenty of touch panels running the LCARS interface, hand-held tricorders, and other gadgets, but the big one is the voice interface. The ship’s computer seemingly contains all historical knowledge, every piece of ship telemetry, knows every language, and does contextual analysis on the fly. While we don’t have all of that just yet, the building blocks are emerging quickly.
AWS re:Invent
I just spent this week attending AWS re:Invent for the first time. I thought I was going to a cloud computing conference, but as it turns out, it was a Generative AI conference. I don’t have time to go to every big tech conference, but I imagine all of the big events from the big tech companies have the same feel this year.
That’s both good and important. It’s good because I’d hate for any one company to get a monopoly on Generative AI, that’s downright dystopian. It’s important because there’s a lot of experimentation to be done, and it’s too early to pick a winner. I like having a lot of options.
A major shift
It’s tempting to be cynical here. Yes, Generative AI is hyped up. Yes, other technology trends, like blockchain, have been overhyped and didn’t change the world. So, I get it, but I also have good reasons to believe this is critically important beyond the hype.
I believe Generative AI is a major shift in the technology landscape. As far as I am concerned, it’s on par with other major shifts like the PC, the internet, and the cloud. Each of those cases had early adopters, skeptics, and hold-outs. So will there be with Generative AI. Yet undeniably each of these shifts changed the way we compute forever.
The work ahead
Digital transformation and cloud computing gave us this opportunity. Even more, I’ll credit the enterprise business intelligence efforts for bringing our enterprise data together with quality and governance. What started as a better way to run reports will be the foundation of a new generation of computing.
Through digital transformation, enterprises have learned the value of breaking data free from source system applications to make it available to the enterprise. Now, we are learning to put AI models, tools, and applications on top of that data to unleash its potential value.
Each company is now furiously building its own capability to put the power of AI into the hands of its business and customers.
Hello Computer
Today, we have the building blocks to design corporate systems and interfaces that contain all historical knowledge, contain every piece of company telemetry, understand our languages, and perform contextual analysis on the fly.
The world we are moving from is designed with the layers of databases, applications, and interfaces. The world we are moving to is designed with the layers of an enterprise data lake, fine-tuned AI models, and an interface.
What to do next
This is going to take all of us. This isn’t the domain of the few AI nerds in the corner. We all need to get a whole lot more comfortable with this technology. It may be fun to read an article like this, and get a little inspiration, but what should you do about it?
It’s imperative to look at every problem we are trying to solve, and ask, is there a way I could leverage Generative AI to make this better? The answer isn’t yes every time, but it’s probably yes more than you think it is.
We need to stretch ourselves. We need to educate ourselves. I took it upon myself to learn about AI models, fine-tuning, temperature, embeddings, and vectors. You should too.
“But, Zach, I’m too busy.” Sure. Some technologists were too busy when the internet came out too. Mark my words. We are in those days, right now. The next 12 months are going to blow your mind. Get in now.
If you continue to build solutions the old-fashioned way, Scotty will visit you from the future and remark, “How quaint.”
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