AI & Machine Learning
Suddenly in the limelight: artificial intelligence (AI) spent many years on the back burner in industry. However, according to analysts from Hamburg-based IoT-Analytics, AI is now among the top five topics for decision-makers. What is responsible for this change in fortunes? A good front-end with a great language model in the back-end: ChatGPT. Find out how industry can use generative AI, and why it does not always help, at HANNOVER MESSE.
The topic of artificial intelligence (AI) now ranks among the top five challenges facing CIOs in industry. This is the conclusion reached by the Hamburg-based company IoT-Analytics. We are living the iPhone moment of AI: since the beginning of the year, industry has been asking itself, "What can ChatGPT mean for us?"
Generative AI and how industry uses it
Almost every week, companies and initiatives publish new Large Language Models (LLM), and former Metaverse experts transform into LLM specialists. At HANNOVER MESSE, Siemens presented a first application with ChatGPT in the TIA Portal to simplify programming. What the technology group has done is to extend the prompt (the task given to the model) and to optimize it in the direction of automation knowledge.
Beckhoff is also moving in this direction. HPE presented an ABB robot including LLM from the German startup Aleph Alpha. Companies are testing out what ChatGPT and the others can do. Technology consultancies like Zühlke Engineering sum up the most important use cases of large language models for the engineering industry: patent research, analyzing job ads, and providing statistical answers to customized natural language questions about IoT data to reduce analysis time – and these are just three examples.
Maybe that does not sound terribly exciting!? One participant at the Festo "IO Conference" explained how he used the power of generative AI to simplify his code. Others had robotics programs written or optimized in ROS. The first pioneers are tinkering, using interfaces, building proofs of concept, and thinking of LLMs with their own data.
Artificial intelligence transforms development
Generative AI, such as GPT or the DALL-E tool, will also change the face of industrial product development – the designer receives support from an artificial intelligence. Festo has been working in the area of reinforcement learning for manufacturing processes for several years now. The next step is to use generative algorithms for product development. OpenAI recently published 3D models for DALL-E.
Beside the challenge of 3D, industry also has to overcome the following obstacle: the products must be able to move. And Dr. Jan Seyler from Festo Research poses the provocative question: Can machines build machines? He is sure: "Many aspects of engineering can be supported by AI methodology. The challenges are primarily semantic, functional understanding and accurate simulation."
And Festo's CTO Ansgar Kriwet defined the future of a Festo product in simplified terms at a conference: A multipurpose hardware as a software defined product packed with AI. He gave this reminder: industrial AI / Industrie 4.0 are also educational topics.
As revolutionary as LLMs and generative AI are, sensor data/tabular data dominates everyday life in industry. Many optimization tasks can be solved using other machine learning approaches. It is therefore not surprising that the topics of computer vision and quality control continue to be the most sought-after applications in the field.
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