The AI Hyperbole: Is Gen-AI the new 3D-TV? 📺

The AI Hyperbole: Is Gen-AI the new 3D-TV? 📺

Written by
Fred Thompson
Date published
November 16, 2023

The trigger point to write this was when I felt washed up in the “another day, another new AI tool” part of the week when Josh Bersin and Sana Labs have created Galileo™️, "The world's first AI powered expert-assistant for HR".

I haven’t seen or tested Galileo, so I can’t directly comment on its effectiveness, but the hyperbolic marketing around this product (Josh describes it a “paradigm-shattering offering”) made me think about the current excitement around the technology and wondered where I’d see this level of hysteria before 🤔

📺 The three-dimensional hype train

There's a lot of noise around generative AI at the moment, and a lot of FOMO too. Whilst I appreciate the endeavour to deliver on this trend, I still can't help but feel a certain "3D TV" 👓📺 moment in the world of AI.

In around 2010 the world was seemingly going mad over the future of television, and it seemingly wasn't possible to purchase a new TV without it having 3D capabilities.

Everyone loved it, we couldn’t wait to watch Despicable Me in 3D as we lovingly reached out of our chairs to grab Dave, Kevin, Stuart, or Bob.

Fast forward ⏩ to 2020 and its near on impossible to purchase a 3D television, as all major manufacturers have stopped making 3D-capable televisions.

🛑 So what went wrong?

The jury is out as to what the nail in the coffin for 3D in your home actually was, but despite the enthusiastic interest of customers (and ultimately, it was largely well liked), the product category failed due in part to the following facts:

  • 🤑 High cost.
  • 😎 Difficult to use (3D glasses!).
  • 🖼️ Technology progression (new picture formats emerging like 4k).
  • 🗑️ Poor content (3D conversions were sub-par)
  • ⏳ The “novel” effect wore off.


🤖 Right, so how does this apply to generative AI?

A lot of the signature failings of the 3D TV time appear parallel to how I see the market and the consumers position with artificial intelligence right now.

There is no doubt that the technology is great - and there is a definite excitement about using it and seeing how it can influence and change our every day life - but in most cases and sectors, akin to 3D, we’re still searching for an effective use case for it.

Furthermore, let’s cross-reference the 3D TV failure highlights against our current AI position:

High Cost

Generative Artificial Intelligence solutions are currently either stand along with a cost, or a additional feature to a product with a separate additional cost. Running AI tools currently (or even just standing on the shoulders of OpenAI) is expensive, and you have to pass that cost on to the customer at some point. Is the current crop of AI tools worth that cost to the end user?

Difficult to use

Generative AI is not difficult to use in the sense of getting started and producing some content, but it is currently difficult for a standard user to end up with a result that is actually immediately helpful without assistance or modification post generation. It’s perfect to get you started but trusting AI to write your resume generally takes a good understanding of how to tailor and craft your requests in the perfect manor to achieve the desired results.

Technology progression

This space is moving super fast 🏎️ right now, and I some-what fear for the first-movers. We’ve seen this before with VR, augmented reality, and even mobile phone manufacturers (<cough>Nokia</cough>) that you can be usurped by a late mover with a far superior product long into the game.

Make no doubt about it, we are in early adopter phase of AI right now.

Poor content

The Large Language Models (LLMs) that train the generative AI at present are an incredible step up from where we were merely a year ago, but there is still a lot of work to be done. The Galileo™️ product at least attempts to train the results to a certain niche use-case (and this may be the way the most success is had), but it doesn’t take too long experimenting with generative AI tools to build up a distrust in their responses that on initial inspection look factually correct but are in fact far from it.

The “novel” effect wore off

This is my current largest fear with the technology in general. Every single platform I am using at the moment is announcing a “breakthrough” AI solution that will revolutionize my world. I love technology (and despite this post, love AI) - and I’ll try pretty much every solution offered to me - but I’m still only making serious use of one or two tools and the rest didn’t provide the value promised.

The noise around this space and the constant bombardment of solutions will lead to an impassive mentality by the consumer, and I feel all but a few will be able to see the cash burn through long enough to come out of the other side.

💗 But, I actually do love generative AI

To compare this technology to the beloved red and green lens glasses is a certainly tongue and cheek, and the technology does genuinely impress me. It is here to stay, it will get better, and it will become embedded in our lives like never before.

We’re talking about its use case across all of our businesses - and where it can sit in our products - but we are ensuring we stay focused on the aim of delivering value first, and looking beyond the marketing buzz to ensure the feature we next release - AI driven or otherwise - have a meaningful impact on our end user.

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