Tech Update October

At MM Guide I have worked on several AI projects. One of those projects involved writing our own AI framework based on a feedforward neural network using a backpropagation training algorithm. The platform allowed for expansion in different directions, one of which was adding more training algorithms. We added training methods like simulated annealing and genetic algorithms to the framework to test this expandability of the framework.

While AI is a very powerful tool, its use should be limited to instances where there is added value. One of the pitfalls of learning a certain technology is that you want to use it everywhere. When you learn of the hammer, everything looks like a nail. Using AI can add a level of complexity that could also be solved in a simpler manner. As data scientist Brandon Rohrer suggested:

Looking at AI from a broader perspective, we should also make sure we. If we are ready to give control to AI in cars, trading systems, telecommunications, the electrical grid, and many other vital systems we better make sure the AI behaves the way we intend it to behave. We would not want a system with a beneficial goal but uses a destructive path to get to that goal. Then there is the other obvious way AI can be destructive,  it can be programmed to do something malicious. This illustrates that the concern is not necessarily about malice, but about competence. A future super performing AI will be really good at its task and if those tasks are not aligned with our goals, we will have a problem. You probably don’t mean to kill any ants when walking to the park, but there most likely will be some squashed under your boot. We need to make sure humans will be never in the path of the boots. We need to do research on how to develop AI safely.

This is not to say you should not use AI or ML. According to Microsoft there several ways enterprises are benefitting from AI.

  1. Improving common IoT-enabled applications
  2. Enhancing employee safety, patient care, and customer service
  3. Reducing complexity for developers and users
  4. Accelerating potential return on investment
On top of that, we just started our own research into using AI to empower the QA process in a porcelain factory. Stay tuned for more info on that once we have more to share with you all!
 

And these are just the tip of the iceberg. With AI becoming more and more accessible through different tools, we can expect to see many good (and bad) initiatives in our time ahead.

Share on linkedin
Share on telegram
Share on whatsapp
Share on facebook

More to explore

From manual to automated: how software solutions are revolutionizing SMEs 

In the dynamic landscape of contemporary business, a significant transformation is underway within small and medium-sized enterprises (SMEs). This shift centers on the adoption of software automation, a catalyst for evolving traditional operational paradigms. This article explores the transition from manual processes to automated systems, highlighting how tailor-made software solutions are revolutionizing SMEs, enhancing efficiency, and driving innovation.

Privacy Preferences
When you visit our website, it may store information through your browser from specific services, usually in form of cookies. Here you can change your privacy preferences. Please note that blocking some types of cookies may impact your experience on our website and the services we offer.