The AI Hype Cycle

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Unless you’ve been living under a rock, you’ve been hit by the AI hype wave. If you’re more than average interested you’ve wondered when the downturn comes. It always does – it’s as predictable as gravity – and the Gartner Hype Cycle. What happens then?

It’s predictable. We’ve been here before – many times. The hype balloon deflates, companies fail, investors bleed, customers get burned, interest fades etc. But not all hype cycles are the same, and one important parameter that distinguish them is whether the technology is fundamental or derivative.

Being able to distinguish between the two is important because it helps us make smarter choices, avoid the bad ones. How do we do that? Learn from history is the obvious rule number one. Listen to the ‘right’ advisors is number two – and comes with a big question: ‘Who’s that?’

It’s hard and there are no absolutes. Again it’s about trust, which is subjective. Most of us have our favorites which change over time (as they should). If you’re a regular reader, you’ve noticed references to Scott Galloway several times recently. He’s currently one of my favorite sources of insight into many areas, including technology – although he’s not a technologist or expert in any particular technology. More like a thinker, philosopher – which in many cases is just what we need: More thinking, less ‘just follow the pack’.

Galloway has ‘philosophized’ about AI and the future many times over the past year, delivering very meaningful and thought-provoking reasoning about us, technology, AI and the world (check out The World is Burning, Can AI Rescue Us? for an example).

Galloway is well known and easily discernible above the market noise level. Most thinkers and writes are not, even very good ones. Hence, discovering a new voice is a big deal, at least to someone on continuous search for them, like myself. And here is a recent acquaintance in this category: Mark Maunder of Defiant, Inc. – the very anonymous company behind the widely known security product WordFence.

In a blog published last April, Maunder philosophizes about the AI hype cycle in a way that had me come back to the pice several times, most recently a week ago. That’s a good sign. Not only bookmarking something (you too do that all the time, don’t you?) but actually using the bookmark (rarely, right?). 

What to do About AI is a longread if ever you saw one, and it’s oriented towards technical people (devops in particular), but worth checking out even if you’re not. It will leave you with more understanding of both how we got here and what to expect.

TL;DR? Need a summary? Sure. And since the subject at hand is AI, why not have GhatGPT create it? Here it is – slightly shortened.

The post discusses the impact of AI on various aspects of life and offers insights into navigating the AI revolution. Maunder provides his perspective on AI’s history, its current state, and the implications for different professions. The author highlights the cyclical nature of tech hype and outlines the characteristics of derivative and fundamental technology innovations. The transformative potential of AI, specifically neural networks, is emphasized, as it enables programming by training rather than writing code by hand.
Maunder observes that AI has experienced periods of interest and disappointment in the past, but recent advancements, such as GPT-4 and MidJourney, are leading to exponential growth in capabilities. He addresses the need for adaptation in the face of AI-driven disruption and suggests that creators, including writers, artists, and entrepreneurs, should become proficient in using AI tools to enhance their work.
For developers, Maunder recommends a shift from being AI users to becoming AI developers. He encourages learning Python and highlights the importance of practical experience, using resources like Jupyter Notebooks and platforms like Kaggle to build AI skills. The post concludes with an emphasis on embracing AI as a transformative force and positioning oneself to thrive in the evolving landscape.

Kind of rigid language and not necessarily emphasizing the same points as I would, but that can possibly be good, right? 

By the way, I’m not agreeing with Maunder on all points, but that too may be good – it compels me to rethink. And re-read. You may have the same experience.

Check it out – you may become wiser. I believe I did.

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