The latest advances in AI (GPT, LLM, Transformers, etc.) are like a Nokia phone in the ’90s – everyone could see the attraction, but no one could predict what it would lead to. The tech world has a new obsession with Large Language Models (LLMs), GPTs, and AI in general.
Editor’s note:
Guest author Jonathan Goldberg is the founder of D2D Advisory, a multifunctional 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 many software startups that are told they have to have GPT-something in their product or they won’t get funded. And then, of course, the general media is consumed with stories about AI alarmism and various billionaires with their GPT musings. For our part, we’ve read a very large number of articles, blog posts, and even Stanford’s 300+ State of AI report.
Despite all this, we are not convinced.
There is no question that LLMs and transformers are technically important. The latest developments mark a major breakthrough in software capabilities. That being said, we’re not sure anyone really knows what to do with these abilities.
A few weeks ago we were speaking at the AI Edge Summit, where the organization’s chairman, Jeff Bier, said something that catalyzed our view of AI and GPT. In short, he said ChatGPT is like seeing the first Nokia phone back in the 1990s. We’d all heard of cell phones before, and for many, these Nokia devices were the first phone that looked like we might actually want to buy one. But at the same time, no one looking at the device would be able to predict what will ultimately result – 3G, mobile data, smartphones, the iPhone, apps and a total reorganization of our time and daily activities.
That seems like a good analogy for ChatGPT. It is useful. The first “AI” application that is useful for ordinary people, but will not change their life too significantly. For those who have been watching technology for a long time, it is clear that LLMs and transformers have immense potential, we may only be scratching the surface of what they can offer.
This has some implications for what happens next:
We are in the middle of a massive hype cycle. Without an incredible product surprise, this cycle will eventually fade into a valley of doubt and despair. It’s no coincidence that Sauron’s eyes of the media have turned so intensely to the AI while the rest of the bubble is collapsing. As always, the oracles at The Onion said it best. Nobody really knows what it all means. Perhaps there is a renegade genius sitting somewhere in her cabin or in his mother’s basement with a vision of 1,000 suns pointing the way forward. For everyone else, the future is much more uncertain. There are many people arguing (very quietly at the moment) that AI is a dead end, with ChatGPT being just the latest version of chat bots (remember when those were the hot thing? It was only a few years ago .) There are also AI maximalists currently building their Skynet secure bunkers in preparation for the upcoming AI apocalypse because LLMs are just so awesome. Of course, the reality lies somewhere in between. We must remember that AI is just software. These latest new tools are very powerful, but for the foreseeable future we should mainly just expect some aspects of how we interact with software to improve. Developers definitely seem to be reaping great benefits from tools like Microsoft’s Copilot. Everyone else can probably only expect better-written spam email content for now.
We don’t want to be pessimistic, we shoot realistically. As far as we can tell, LLMs and GPT offer tremendous potential to handle really big data sets. Crucially, Transformers will likely allow us to query problems that were previously too big to tackle, or even data problems we didn’t even know existed before. Furthermore, there is an enticing possibility that these gains are self-reinforcing, a law of Moore’s for data analysis. This is important, albeit unexplored.
Finally, we believe everyone should take a more sober approach to the ethics and societal impact of these tools. We don’t normally cover this topic and would skip it here, apart from the fact that almost everyone concerned with these advances seems to be happily (perhaps intentionally) avoiding the topic.
We’re probably months away from being able to create highly realistic video of anything. anything. This will turn a lot of people’s heads, and perhaps we should take a more constructive approach to preparing the world at large for what this means. At the same time, the alarmists calling for a complete end to AI must face the reality that the ship has sailed.
All in all, we are very excited about these latest developments. After years of incremental SaaS improvements being hailed as “technology advances,” it’s exciting to have a truly compelling new capability ahead of us. We just wish everyone would take a breath.
Have you used ChatGPT to complete work-related tasks?
