Boston-based artificial intelligence software company Neurala recently announced the launch of its European subsidiary, Neurala Europe, based in Italy. Establishing a presence in Europe will allow Neurala to enhance its industrial efforts and enhance expertise on the ground and support its European partners, VARs, and manufacturing clients where AI and automation are prioritized as part of Industry 4.0 initiatives. In an interview with EEWeb, Neurala CEO and co-founder Max Versace said this new phase will provide an opportunity to engage more closely with the industry by bringing AI to the entire product line. Versace showed his delight at the opportunity, seeing a return to his roots and an opportunity to create a bridge between Italy and the United States. The onset of Industry 4.0 has prompted manufacturers to become more open to change by implementing new solutions. Versace highlighted how manufacturers are recognizing the need to revolutionize processes such as quality checks and resource management to stay competitive. Max Versace AI and Skills from Neurala One of the biggest challenges when it comes to implementing AI in industrial settings is the skills gap as well as costs. In 2020, the European Commission published the first quantitative overview of European companies’ uptake of AI technology. Versace highlighted that the study found that a major barrier to organizations adopting AI is hiring employees with the right skills (57%), while just over half of respondents mentioned the cost of adoption (52%). “The perception is that it will be difficult and expensive — it will require a significant investment in new equipment at high upfront costs, and it will take a lot of time and effort to get the AI up and running,” Versace said. “Long story short: It’s not justified in terms of ROI. But that’s where Neurala steps in. Our products offer a huge advantage for manufacturers: Our VIA software can run on a variety of devices, and doesn’t require an expensive GPU, as It’s so easy to use that it can be set up and trained quickly.” Another challenge to consider is the need for massive amounts of well-balanced data. Artificial intelligence provides the device with computational and data analysis capabilities that enable it to perform complex “thinking” similar to what a human would do. However, this intelligence is not limited to machines only; It also applies to software systems. From this concept comes the distinction between robotics and machine learning or artificial intelligence where the main components are machine, software and communication (cloud and big data). Versace added, “Another challenge is the need for massive amounts of balanced data. Both AI and deep learning require both good and bad data to work successfully. Take quality checks as an example – bad data is required so that the algorithm can figure out what is considered ‘incorrect’.” or “bad.” This, of course, is an obstacle for manufacturers who often produce high-quality products.” Inspecting bottle caps Industry 4.0 AI manufacturing is a very traditional industry, but Versace noted that 2020 changed all that: “During every phase of the pandemic, we’ve seen multiple challenges arise – from significant disruption in the supply chain and fluctuating demands to the necessity of continuing operations in the face of COVID-19 infection Among these challenges, social distancing and lockdowns have specifically limited the number of people on the factory floor, as employees, system integrators and customers struggle to get to factories.In 2020, the industry has been hit by the harsh realization that the traditional method of production will not Accommodating new, stricter requirements for pandemic social distancing. “Secondly is the issue of budget and cost. Manufacturers – like any business – need to make money. But keeping the plant up and running is no small feat. To meet their strict budgets, manufacturers are looking to invest in products that work,” he added. This is a relatively tedious and time-consuming task that can be automated with the help of the right AI solution. If leveraged properly, Vision AI software can be used to improve quality checks and ultimately reduce industry overheads. Versace noted that AI is an opportunity for everyone, not only for industrial operators but also for the entire automation sector. “In cases where inspections were previously conducted on a discrete or percentage random basis, manufacturers can now achieve 100% inspection rates. For example, solutions like VIA can be used to automatically identify defects in products or packaging on a production line. By enabling production facilities to detect defects early, they are able to reduce waste and downtime. VIA also addresses the problem of the skills gap, as it enables manufacturers who have not worked with AI before to train and use visual AI. And with the ability to run directly on in-plant hardware, VIA AI enables access to AI for industrial automation users who prefer not to rely on internet access or cloud connectivity. “When Artificial Intelligence meets the Internet of Things, also known as AIoT, there is a huge potential for AI to augment human workers. Today’s manufacturing floors and industrial machines are equipped with dozens of cheap sensors and cameras that collect data on products, as well as basic diagnostics from industrial equipment. “There is an opportunity for manufacturers to leverage human-level AI to extract actionable insights from that data at the computing edge, right inside industrial machines,” Versace said. “In this case, AI works alongside human operators by learning what it’s like “Normal production operation” of a particular machine. This allows operators to manage multiple machines and identify problems in production that, prior to AI, would have required heavy human supervision or would have brought production to a halt.” Using AI offers a myriad of benefits – undeniable. For businesses, offering AI technologies are the gift of automation, which improves productivity and efficiency, leading to increased profits and jobs.Similarly, it helps humans to focus more on important issues by automating repetitive processes.This and others are the reasons why companies use AI systems more growing to strengthen its operations.This article was originally published on the sister site EE Times Europe.
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