The tech world has a new obsession with AI

The latest advances in AI (GPT, LLM, transformers, etc.) are like a Nokia phone in the 90s – everyone could see the appeal, but no one could predict what it would lead to. The tech world has a new obsession with large language models (LLM), GPT and AI in general.

Editor’s Note:
Guest author Jonathan Goldberg is the founder of D2D Advisory, a multi-functional consulting firm. Jonathan has developed growth strategies and alliances for companies in the mobile, networking, gaming and software industries.

Almost all of our news feeds are filled with AI content. We know a lot of software startups who are told they have to have GPT in their product or they won’t get paid. And so, of course, the mainstream media is consumed with stories of AI alarmism and various billionaires with their GPT thoughts. For our part, we have read a very large number of newspapers, blog posts and even Stanford’s 300+ State of AI report.

Despite all this, we are not convinced.

There is no doubt that LLMs and transformers are important technically. The latest development marks a major breakthrough in software capabilities. That said, we’re not sure anyone really knows what to do with these features.

A few weeks ago we talked AI Edge Summit, where the organization’s president, Jeff Bier, said something that catalyzed our view of AI and GPT. To paraphrase, he said ChatGPT is like seeing the first Nokia phone in the 1990s. We’d all heard of mobile phones before then, and these Nokia devices were for many the first phone that looked like something we’d actually want to buy. But at the same time, no one looking at the device could have predicted all the things that would eventually flow from it – 3G, mobile data, smartphones, iPhones, apps, and a complete reorganization of how we structure our time and daily activities.

That seems like a good analogy for ChatGPT. It is useful. The first “AI” application that is useful to ordinary people, but not something that will change their lives too meaningfully. For those who have watched technology for a long time it is clear that LLMs and transformers have huge potential, we may well only scratch the surface of what they can provide.

This has some implications for what happens next:

1. We are very much in the midst of a massive hype cycle. Without some incredible product surprise, this cycle will eventually fizzle out and turn into a trough of doubt and despair. It’s no coincidence that the media’s eye on Sauron has focused so intently on AI just as the rest of the bubble is deflating. As always oracle at The onion said it best.
2. No one really knows what all this means. Maybe somewhere a rogue genius is sitting in her closet or in her mother’s basement with a vision of 1,000 suns pointing ahead. For everyone else, the future is much less certain. There are plenty of people arguing (very quietly right now) that AI is a dead end, with ChatGPT just the latest version of chatbots (remember when it was hot? It was only a few years ago.) There’s also AI -maximalists are currently building their Skynet-proof bunkers in preparation for the impending AI apocalypse because LLMs are just that awesome. Of course, the reality is somewhere in between.
3. We have to remember that AI is just software. These latest new tools are very powerful, but for the foreseeable future we should mostly just expect some aspects of our interaction with software to improve. Developers definitely seem to enjoy huge benefits from tools like Microsoft’s Copilot. Everyone else can probably just expect better written spam email content for now.

We don’t mean to be pessimistic, we aim for realistic. From what we can tell, LLM and GPT offer huge potential for handling really large data sets. Critically, transformers will probably allow us to examine problems that were previously too large to approach, or even data problems that we hadn’t even realized existed before. Furthermore, there is the tantalizing possibility that these gains will be self-reinforcing, a Moore’s Law of data analytics. This is important, albeit unexplored.

Finally, we believe that everyone needs to take a more sober approach to the ethical and societal implications of these tools. We don’t usually cover this topic and would skip it here except for the fact that almost everyone involved in this advancement seems to happily (perhaps deliberately) avoid the topic.

We are likely months away from being able to create highly realistic videos of anything. Something. It’s going to mess with a lot of people’s heads and maybe we should take a more constructive approach to preparing the world at large for what it means. Meanwhile, the alarmists calling for a complete end to AI must face the reality that the ship has sailed.

Overall, we are deeply pleased with this latest development. After years of incremental SaaS improvements hailed as “technological progress,” it’s exciting to have a truly compelling new capability in front of us. We just wish everyone took a breath.