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AI • 6 min read • Feb 24, 2021

What Is AI?

Tom Stockton
Tom Stockton
CEO, Fuzzy Labs

(*skip to the end of this blog to read the AI generated summary of it.)

This is not another “What is AI?” blog, not really.

There are already too many of those out there that will tell you the history and basic principles of artificial intelligence. In fact, we’ve written a massive blog about this already.

However, in spite of all the blogs out there, there’s not much said on why we should be using AI now. What’s made it so special over the last few years?

That’s what I want to cover in this article. I’ll be looking at the growing need for businesses to start applying AI today, and what that means for the future of your business, especially in innovative industries like MedTech.

AI is not going away

There has never been more buzz and hype around AI than there is today. Since its conception in the 1950s, there have been at least two “AI winters” where, although there was some hype around AI, it never really took off.

Recently, however, the AI train has got going again, and this time it doesn’t look like there will be another winter in sight.

So, what’s driven this evergreen AI boom?

For starters, there’s the availability of hardware, computing power speed, and all the cloud providers out there these days. This all means that AI has become so widely accessible that, very soon, it will become commonplace everywhere you look.

It’s already starting…

Nowadays, AI has become more of a commodity solution than ever before. Previously, trying to deploy AI was like attempting to build a car and everything inside it from scratch. All of the code and all the frameworks had to be built from the ground up, which meant it wasn’t just time-consuming, it was also very expensive.

That’s no longer the case. Today you can literally buy pre-built systems and just plug them together yourself. Instead of building the car, you can buy the wheels, engine, door and body, and you’ve got the total solution.

AI is becoming commonplace in business

This has huge implications for businesses that are looking to implement it. For example, let’s say you wanted a system to detect human handwriting. A few years ago, a LOT of work would have to go into gathering all of the data and writing the algorithm to understand how to interpret someone’s handwriting and translate it into the actual letters and words.

Whereas now, you almost don’t need any programming experience at all! There are so many “pre-trained” models that have all this knowledge already built.



What’s more, they are easy to find. Not only are these modules available in the open-source world, so you can take someone else’s code and run with it, but big cloud providers are also providing them as a paid service.

Amazon, Google, Microsoft, etc. have got all this stuff available at the click of a button (if you pay them of course).

These pre-trained modules have all sorts of functions and a lot of them apply to human cognitive functions like speech and vision.

This same story has been repeated in the world of technology for years. If you wanted something as mundane as a database in the 1980s, that was a big undertaking. You were going to need very specialist skills, and you were going to need to spend a lot of money to do it.

Now a database is just a resource that you can use in the cloud — you don’t really need to own one.

How Fuzzy Labs uses AI

That’s the same thing that’s happening with AI capabilities now. Today, if you want something that will recognise different types of products in a photo for instance, you can build that reasonably easily and cheaply, without hiring a team of PhDs.

But why would businesses need these new capabilities?

It’s worth mentioning here that Fuzzy Labs is a team of AI practitioners, but we’re not trying to build a machine version of human intelligence. Unlike Ridley Scott’s Tyrell Corporation in Blade Runner, “More human than human” is not our motto.



For us, it’s about finding the things that come easily to humans that we can replicate on a computer. For example, can our AI read the words from a scanned document? Can it recognise different products/logos in a photo? Can it transcribe some audio to text?

We also want to find out where AI can help us with planning, problem-solving and simplified decision-making.

However, humans can do all this just fine, so what’s the big deal?

The scalability of AI

Well, these capabilities alone aren’t what make AI so important. It’s how AI can scale these capabilities that makes the real difference. AI gives you the opportunity to scale substantially the abilities a human already has, to well beyond what a human could do — and AI can do it in a fraction of the time!

This scalability has massive implications for businesses, and Fuzzy Labs is taking this to the MedTech industry. Take medical imaging as an example. One project we did recently was on wound analysis.

Medical professionals are trained to recognise different wounds, but you can teach AI to do the same thing. The aim is not to replace the human but to give them some insight and help speed up that identification process. In situations like that, a human will always verify the final decision. There’s too much at stake.

However, that same image recognition software could have many other implications too. Sometimes, in a less critical user case, you might be able to rely solely on AI for decision-making. Product cataloguing is a good example of that.

Applying off-the-shelf AI

That’s the beauty of AI today. To get some quick value, you can apply completely off-the-shelf stuff that does a wide range of things, rather than creating costly, bespoke AI solutions. You can leverage existing technologies but add your own layer on top of that technology to make it more specific.

In the case of our wound analysis project, we didn’t have to write the whole thing from scratch. We could take an existing image classifying service and add all the specific bits we needed. That allowed us to train a unique model for the MedTech client and give them business value.

Building off existing technology isn’t a new idea, but it’s only in the last few years that it’s become a lot more widely implemented. That’s because with all the resources available to us now, it’s become both easy and relatively cheap to do.

AI for small businesses

The many uses of AI have been known for years, but only now are they becoming readily available for smaller businesses that might not have a large budget, and that is very exciting!

With AI, processes can be automated, anomalies found, and everything just moves faster and more efficiently. It doesn’t have a bad night’s sleep after one too many beers!

As I mentioned earlier in this article, it’s highly unlikely we are going to see AI slow down anytime soon. That means a lot of businesses out there that haven’t yet looked into AI will want to start soon, or risk getting left behind.

These days, the technology is so available and it doesn’t take the time and money it used to. Therefore, it’s crucial to understand what your competition is doing with AI and what benefits they’re getting from it, because if you don’t, you may be holding yourself back.

It may still be early on the bell curve, but it’s increasing fast — and you need to be there.

Remember, you don’t need a team of 20 data scientists any more in order to get started. You can start small, with an easy proof of concept, and scale from there.

And if you need any help, you know where to find us!

More to come next week…

P.S. For more great content around AI and how it’s impacting the world today, please feel free to email any questions to me at tom@fuzzylabs.ai, or follow us on LinkedIn for updates on all our latest projects.



AI generated summary below courtesy of hugging face. Look how good it is! Although it seems to have missed the nuance of the blade runner quote!

There has never been more buzz and hype around AI than there is today. You can literally buy pre-built systems and plug them together yourself. Amazon, Google, Microsoft, etc. have got all this stuff available at the click of a button. Fuzzy Labs is a team of AI practitioners, but we’re not trying to build a machine. Unlike Ridley Scott’s Tyrell Corporation, our motto is ‘More human than human’

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