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Generative AI in industry

Must-Have or Show-Stopper?

Hardly any other technology has been accompanied by as much hype and promises of salvation over the past year as generative AI (artificial intelligence). And it has also polarized opinion enormously. While some dismiss the technical innovations as gimmicks, others are jumping on the bandwagon and want to solve “everything” with AI from now on.

Both extremes are, of course, dangerous.

Generative AI refers to a class of AI algorithms that are able to create new data similar to that on which they have been trained. Imagine giving a computer examples of images or text and it learns to create something similar. This technology is often used for creative purposes such as generating art, music or even human-like text. Generative AI can also be used in image processing, medicine and other fields to generate data that is useful for analysis and decision making. Ultimately, it aims to enable computers to be creative and generate new content in a human-like way.

OVERVIEW

Don't miss out on progress!

Firstly, we should not underestimate a new technology. Yes, there are still some problems and “teething troubles”, but the conclusion “My business doesn’t need to change!” with the justification “I tried ChatGPT and it can’t do XY, people are still needed for that!” is unfortunately too short-sighted.

Technology will continue to develop rapidly, and the fact that an AI is not yet able to do something is no guarantee that it never will be. It has always been dangerous for business to miss out on progress; there are numerous examples of this.

Do not utilize AI according to the "one size fits all" principle!

On the other hand, it is also fatal to want to use a new technology unseen for “just anything”. There are sensible areas of application, and there are less sensible areas of application. And there are also security risks, as our colleagues at sequire technology showed us very clearly last year in their research on the topic of “Indirect Prompt Injection”. Not only can sensitive data be leaked, but entire chat systems can also be taken over by malicious attackers without the user noticing. This is not a “show stopper”, but it is certainly something to keep in mind.

So how do we deal with this? Our recommendation:

  • Identify a specific area within the company where Generative AI could be meaningful.
  • Evaluate how its implementation could look through a prototype.
  • Determine in what form AI could be used and how the new technology "feels."
  • Finally, after a few test runs – considering data security and security measures – integrate it into company systems.
As part of this year’s DIGITAL COMMERCE SUMMIT automotive & industry Managing Director Kevin Dewi referred to an example from the field of product configuration product configuration:
When configuring a valve block, for example, there are many redundant or predictable steps that could be taken care of by an intelligent assistant. We are currently demonstrating in a showcase how a machine-readable JSON document is generated from a natural language request for the design of a valve block. In its current state, this already feels very pleasant and convenient for the user. But we can also go one step further. What if, for example, a configuration proposal could be generated automatically and directly from the customer’s specifications? After that, only minor adjustments by a human expert would be necessary. This would save an enormous amount of time and increase efficiency.
christoph-endres

CHRISTOPH ENDRES
Managing Director
sequire technology

LinkedIn

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