Deep learning uses powerful algorithms to sift through massive amounts of data that are fed into Deep Neural Networks (DNNs) which mimic how the human brain works. These are powered by Gaming Processing Units (GPUs), which provide the oomph needed for the DNN to handle a mass of information. They also teach the program or machine to learn at a much faster rate.
We’re on the verge of a fourth industrial revolution. Comprised of automation, the Internet of Things, big data and cloud computing technologies, Artificial Intelligence (AI) is leading the charge. But not in the way you think.
"Deep learning is fueling the momentum we’re seeing around AI," says Dr. Damian Borth, Director of the Deep Learning Competence Center at the German Research Center for Artificial Intelligence.
From internet search engines tailoring ads to suit our preferences, to email systems filtering spam, deep learning algorithms are already commonplace in digital scenarios. When applied to the industrial equipment industry, it will allow manufacturers to become faster and more flexible in the face of increasingly demanding and highly connected customers who want more customized products.
“Flexibility is now more important than efficiency in a production line,” says Philippe Bartissol, Vice President, Industrial Equipment, Dassault Systèmes.
Customers want what Bartissol calls "production of one" where products of multiple shapes and sizes can be produced on the same production line. This is something machines grounded in deep learning can provide.
“You need machines you can put together in different configurations, that can talk to and be aware of each other. The data collected from the exchange between these machines can be used for optimization. Then you can be much more ‘just in time’,” says Dr. Borth.
Virtual design and collaborative innovation software like Dassault Systèmes’ 3DEXPERIENCE platform allows manufacturers to test the capabilities of new machinery in a virtual environment before they hit the factory floor. If machines are software-driven from the outset when they require modification in the field, all you need to do is update the software online.
The same concept is also being used to predict machine failure. If you feed Predikto’s deep learning platform enough data, it can predict and solve complex maintenance and operation issues. It figured out that air compressors in the trains of a major European rail company were failing after the trains were painted. Fumes from the paint guns were being sucked in, which reduced the life of the rubber seals inside.
Mario Montag Founder and CEO, Predikto, says, "Deep learning will completely change our world like the cellphone. Everything in your life will have so much intelligence built into it without you noticing. Your alarm clock is going to be setting itself ten minutes earlier because it’s sensing there is an accident on a road between your house and your first appointment in your calendar."
Hollywood has done us no favors with its portrayal of robots as human-hunting Terminators. If not that, some have predicted their wholesale introduction into the workforce will result in the end of jobs for humans. The reality is quite different.
You can now design your own pair of Adidas sneakers instore and have them delivered to you within a few hours.
“Through one of the R&D programmes of the federal [German] government Adidas have developed a fully automated facility that uses robot technology to make the shoes,” says Asha-Maria Sharma, Director of Service Industries, Germany Trade and Invest.
Sharma consults to foreign investors in Industrie 4.0, a $200 million initiative set up by the German Government to make manufacturing smarter, which had a hand in the Adidas project. One of its aims is to help the Mittelstand—a group of successful family-owned small and medium-sized enterprises (SMEs) and the backbone of German manufacturing—become more software-driven and open to technological change.
This means facilitating exchanges between R&D companies and users, going into the regions to be close to SMEs, mapping examples of what is happening around them, creating educational programmes and skills academies to retrain employees, and even introducing them to start-up founders.
“Digitization will help companies stay competitive,” says Sharma. “That is especially important for the SMEs. Many of them [Mittelstand] are state-of-the-art, hidden champions in their disciplines for quite some years. I’m confident they are able to adopt these new changes in technology.”
Deep learning is moving us towards a future where machines will be able to think, learn and adapt with the same—if not more—dexterity as human beings. The industrial equipment industry is becoming more responsive, customer-focused and software driven, as is every industry. We’re so highly connected it will touch every aspect of our lives.
Still, there are philosophical questions to ponder: how much do we let machines influence our decision-making, what contribution—other than financial—should they make to humankind and how do we ensure they don’t completely remove humans from the workforce?
“The future of deep learning in industrial equipment may not be one where machines take our jobs, but adapt to the person operating them,” says Bartissol.
“Let’s suppose you have an operator that has certain level of restriction or is somehow disabled. Maybe artificial intelligence will make machines more mindful about the human being they are working with,” he says.
After two false starts, and with $5 billion invested in start-ups worldwide, the money and intent is there to make it third time lucky for AI. Just as long as we don’t get too ahead of ourselves, says Dr. Borth.
“We have to be very careful of expectation management because we AI researchers are very good at predicting the future very badly.”
Dassault Systèmes, the 3DEXPERIENCE Company, provides business and people with virtual universes to imagine sustainable innovations. Its world-leading solutions transform the way products are designed, produced, and supported. Dassault Systèmes’ collaborative solutions foster social innovation, expanding possibilities for the virtual world to improve the real world. The group brings value to over 210,000 customers of all sizes, in all industries, in more than 140 countries.
Deep learning uses powerful algorithms to sift through massive amounts of data that are fed into Deep Neural Networks (DNNs) which mimic how the human brain works. These are powered by Gaming Processing Units (GPUs), which provide the oomph needed for the DNN to handle a mass of information. They also teach the program or machine to learn at a much faster rate.
We’re on the verge of a fourth industrial revolution. Comprised of automation, the Internet of Things, big data and cloud computing technologies, Artificial Intelligence (AI) is leading the charge. But not in the way you think.
"Deep learning is fueling the momentum we’re seeing around AI," says Dr. Damian Borth, Director of the Deep Learning Competence Center at the German Research Center for Artificial Intelligence.
From internet search engines tailoring ads to suit our preferences, to email systems filtering spam, deep learning algorithms are already commonplace in digital scenarios. When applied to the industrial equipment industry, it will allow manufacturers to become faster and more flexible in the face of increasingly demanding and highly connected customers who want more customized products.
“Flexibility is now more important than efficiency in a production line,” says Philippe Bartissol, Vice President, Industrial Equipment, Dassault Systèmes.
Customers want what Bartissol calls "production of one" where products of multiple shapes and sizes can be produced on the same production line. This is something machines grounded in deep learning can provide.
“You need machines you can put together in different configurations, that can talk to and be aware of each other. The data collected from the exchange between these machines can be used for optimization. Then you can be much more ‘just in time’,” says Dr. Borth.
Virtual design and collaborative innovation software like Dassault Systèmes’ 3DEXPERIENCE platform allows manufacturers to test the capabilities of new machinery in a virtual environment before they hit the factory floor. If machines are software-driven from the outset when they require modification in the field, all you need to do is update the software online.
The same concept is also being used to predict machine failure. If you feed Predikto’s deep learning platform enough data, it can predict and solve complex maintenance and operation issues. It figured out that air compressors in the trains of a major European rail company were failing after the trains were painted. Fumes from the paint guns were being sucked in, which reduced the life of the rubber seals inside.
Mario Montag Founder and CEO, Predikto, says, "Deep learning will completely change our world like the cellphone. Everything in your life will have so much intelligence built into it without you noticing. Your alarm clock is going to be setting itself ten minutes earlier because it’s sensing there is an accident on a road between your house and your first appointment in your calendar."
Hollywood has done us no favors with its portrayal of robots as human-hunting Terminators. If not that, some have predicted their wholesale introduction into the workforce will result in the end of jobs for humans. The reality is quite different.
You can now design your own pair of Adidas sneakers instore and have them delivered to you within a few hours.
“Through one of the R&D programmes of the federal [German] government Adidas have developed a fully automated facility that uses robot technology to make the shoes,” says Asha-Maria Sharma, Director of Service Industries, Germany Trade and Invest.
Sharma consults to foreign investors in Industrie 4.0, a $200 million initiative set up by the German Government to make manufacturing smarter, which had a hand in the Adidas project. One of its aims is to help the Mittelstand—a group of successful family-owned small and medium-sized enterprises (SMEs) and the backbone of German manufacturing—become more software-driven and open to technological change.
This means facilitating exchanges between R&D companies and users, going into the regions to be close to SMEs, mapping examples of what is happening around them, creating educational programmes and skills academies to retrain employees, and even introducing them to start-up founders.
“Digitization will help companies stay competitive,” says Sharma. “That is especially important for the SMEs. Many of them [Mittelstand] are state-of-the-art, hidden champions in their disciplines for quite some years. I’m confident they are able to adopt these new changes in technology.”
Deep learning is moving us towards a future where machines will be able to think, learn and adapt with the same—if not more—dexterity as human beings. The industrial equipment industry is becoming more responsive, customer-focused and software driven, as is every industry. We’re so highly connected it will touch every aspect of our lives.
Still, there are philosophical questions to ponder: how much do we let machines influence our decision-making, what contribution—other than financial—should they make to humankind and how do we ensure they don’t completely remove humans from the workforce?
“The future of deep learning in industrial equipment may not be one where machines take our jobs, but adapt to the person operating them,” says Bartissol.
“Let’s suppose you have an operator that has certain level of restriction or is somehow disabled. Maybe artificial intelligence will make machines more mindful about the human being they are working with,” he says.
After two false starts, and with $5 billion invested in start-ups worldwide, the money and intent is there to make it third time lucky for AI. Just as long as we don’t get too ahead of ourselves, says Dr. Borth.
“We have to be very careful of expectation management because we AI researchers are very good at predicting the future very badly.”
Dassault Systèmes, the 3DEXPERIENCE Company, provides business and people with virtual universes to imagine sustainable innovations. Its world-leading solutions transform the way products are designed, produced, and supported. Dassault Systèmes’ collaborative solutions foster social innovation, expanding possibilities for the virtual world to improve the real world. The group brings value to over 210,000 customers of all sizes, in all industries, in more than 140 countries.
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