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Sanjay Gangal
Sanjay Gangal
Sanjay Gangal is the President of IBSystems, the parent company of AECCafe.com, MCADCafe, EDACafe.Com, GISCafe.Com, and ShareCG.Com.

MCADCafe Industry Predictions for 2024 – CloudNC

 
January 1st, 2024 by Sanjay Gangal

By  Theo Saville, CEO, CloudNC

Theo Saville

 The main manufacturing tech trend for 2024: what happens when you start applying generative AI to physical problems.

For example… what if you could create anything you wanted – at the touch of a button?

It’s a dream of humanity, rendered (and parodied) ad nauseum in science-fiction, from Star Trek to Iron Man to Red Dwarf – that with a single click, a smart computer could create whatever you need: from hot drinks and food, to a super-powerful exoskeleton – and everything in between.

We are, of course, still some distance from any such vision becoming a reality. But recent advances in generative AI mean we aren’t quite as far away as we think.

Artificial intelligence tools like Chat-GPT and DALL-E can create new words, images and video, based on only a few inputs. The results can range from the curious (such as new AI-generated episodes of the Simpsons) to the scary (like Bing’s AI telling a NYT reporter in a chat that it wants to be alive), to the pretty funny (and genuinely impressive).

We now know that AIs can create convincing facsimiles of real-life very quickly. While this power will create problems – from students using Chat-GPT to fulfil essay assignments, or shadowy conspiracists using it to generate fake news– the potential benefits are also exponential. Effortless computer-led creativity is at our fingertips – allowing us to short-cut the creation of words, pictures, designs, video or code.

So, we need to ask ourselves: what happens when you apply this technology to an industry like manufacturing?

At my company, CloudNC, we’ve started to answer that question. Our CAM Assist solution greatly accelerates how quickly a programmer can tell a CNC machine – the mini-factory where metal components are made – how to create a part, saving hours upon hours of production time.

The AI doesn’t work in exactly the same way as Chat-GPT and DALL-E, but there are strong similarities. All are based and trained on robust data sets, using guidance from real-life examples to shape responses to new questions.

In CloudNC’s case, when using our solutions, a user can upload a 3D model of any part that they want to create. Our software autonomously determines the tools needed, how they will be used, and drafts the code to tell a CNC machine how to make it – bringing the simplicity of using a 3D printer to the complex world of precision machining.

This assistance automates the generation of the programming of the part production from the prompt the software has received – in a similar way to how Chat-GPT creates copy based on text, or DALL-E produces an image. Effectively, it’s accelerating the design process, short-circuiting it so that the path from ideation to creation is orders of magnitude shorter than previously possible.

To be clear, we definitely aren’t yet operating in a world where we can press a button and command an AI to generate an item of our choice – that’s still in the realms of science-fiction, and will be for some time. (Single-click manufacturing of anything is some way off.)

However, we can clearly dramatically accelerate certain parts of the generation process of anything with technology – whether that’s with Chat-GPT, DALL-E, or CloudNC. And in terms of where we are today – manufacturers in the US and across the world are already using this technology to save hundreds of programming hours a year, while US corporates like Autodesk and Lockheed Martin are backing our application of the technology.

And that means that we’re getting much better at removing the bottlenecks that stymie production, allowing innovation to thrive. And in 2024, we’ll start seeing the benefits of the application of this technology to heavy industry – making it easier for us to make what we need, when we need it.

Category: Predictions

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