The image that people have of Artificial Intelligence is quite distorted. “On the one hand, the expectations placed on the capabilities of AI are huge; on the other hand, there is also the fear that super-smart Artificial Intelligence will take over and rule the world,” says Andrea Martin, Chief Technology Officer of IBM for the DACH region. Hollywood has especially shaped this image of a future ruled by machines, with blockbusters such as the “Terminator” series of films. However, statements by renowned scientists, such as Stephen Hawking, have also perturbed people: “When I hear that AI is going to kill us at some point, I just shake my head in dismay,” declares René Büst, Director of Technology Research at Arago. “Assertions such as that only serve to frighten people. And that makes it extremely difficult for us, as providers, to make clear just what AI is capable of and what not.” In this regard, the round-table participants also view the media as being obligated to not only report on horror scenarios in conjunction with Artificial Intelligence but also its opportunities and possibilities. “Unfortunately, though, my impression is that the press would rather focus on sensational doomsday theories because they simply attract more reader attention,” states Reinhard Karger, Spokesman for the German Research Centre for Artificial Intelligence (DFKI).

Yet, on the other hand, the providers of systems are also to blame for the distorted public image of AI: “With high marketing effort and expense, systems are being launched onto the market that are actually rather trivial,” says Thomas Staudinger, Vice President of Marketing at EBV. This creates expectations which many systems ultimately cannot fulfil.

“We should look at the opportunities and possibilities that Artificial Intelligence offers to us.”
Andrea Martin, Chief Technology Officer IBM DACH

More applications than assumed

A typical example is chatbots: many users expect one could conduct a conversation with the digital assistants as with a human. “We will probably not even be able to do this in the long term,” says René Büst. “We should instead try to start with smaller tasks, such as the automation of processes.” Andrea Martin also agrees: “Personalised interaction is only one aspect of Artificial Intelligence. In addition, we should see how AI can help us to gain new insights from enormous amounts of data and thereby assist us in making better decisions.”

The experts can list a whole range of applications where AI is already being used today, delivering real benefits to users: whether it’s predictive maintenance, the organisation of work, in medical research, or in many other areas where AI systems support people. In fact, many more AI solutions have already been deployed than most people realise. Oliver Gürtler, Senior Director Business Group Cloud & Enterprise, Microsoft Germany, makes this very clear: “As of today, 760,000 developers at our partners are already developing solutions that take advantage of AI. And this is only on our platform – there are, of course, other vendors.” This fits in with the figures which Andrea Martin cites: “In 2018, some 70 per cent of all developers will, in one way or another, be integrating Artificial Intelligence capabilities into their products.”

“The decisions made with AI must be transparent and reproducible.”
Oliver Gürtler, Senior Director Business Group Cloud + Enterprise, Microsoft Germany

Various technologies work together

This rapid progress is made possible through the interaction of various technologies, as René Büst explains: “With cloud computing, big data, analytics services and GPUs, the foundation was laid for today’s AI solutions over the past ten years.” Above all else, DFKI Spokesman Karger sees the possibility of massive parallel processing of graphics data, in order to compute neural networks, as having enabled a major breakthrough for AI: “Today, we finally have a supercomputer which we can, for example, integrate into a car in order to process sensor data in real time.” In addition to the possibility of providing computing power to an application via the processors, Thomas Staudinger sees a further building block: “Thanks to the developments in the field of semiconductor technology, the sensors have become so inexpensive that they can be integrated in applications on a wide scale.” Consequently, the data volumes required for AI solutions can be generated. “Data is the crude oil for Artificial Intelligence,” emphasises Oliver Gürtler. “In order to process it, for one thing, databases that can be accessed in milliseconds are required. For another, processing is done much more directly at the front end – on the devices. I also need connectivity to exchange data between devices and data centres.” The development will continue, as the round-table participants emphasised. Among other things, they cited mesh computing, in which end-user devices communicate directly with each other without an Internet connection, or quantum computers – with which initial testing has already been carried out.

“I see AI as a companion technology that helps us to more easily determine our lives.”
René Büst, Director of Technology Research, Arago

Secure AI systems

“Technology development has accelerated exponentially. A major challenge in this range of topics is transparency,” says Oliver Gürtler. If you don’t know why an AI application has made a certain decision, then the results could be easily manipulated without the user’s knowledge. This also means that the results must be reproducible. And, of course, that the data is protected to prevent tampering. “If there is no transparency, i.e. it is not apparent just how AI works at all, then the user has to accept the results without questioning.” The security of AI systems is based on many pillars, as Andrea Martin explains: “Security must be ensured in the hardware, in the software and in the connectivity.
And, then there is a further pillar – human beings. If we ignore people, then we have neglected the most important factor.” Reinhard Karger also views humans, or more specifically the lack of security awareness on the part of users, as being a major risk factor. “In all of the discussions regarding data protection and security, the focus is always on putting better locks on the doors – while the windows are wide open.”

“There is a plurality of assistant systems, but no singularity of AI.”
Reinhard Karger, Company Spokesman of the German Research Centre for Artificial Intelligence

The challenge of bias

Whereas data protection and data security are already familiar issues from many other areas, AI solutions pose an additional aspect: personal bias. “If facial recognition is developed by a team which, for example, consists of a group of white men, it could happen that the system returns incorrect results for people who do not have white skin colour,” explains Oliver Gürtler as an example. “This can be avoided if diversity is taken into account in the development teams. The industry is only finding out about this right now.” He stresses that guidelines are necessary for AI developers for this. “Microsoft, IBM, Google, Facebook, Amazon and a few other companies have founded the non-profit organisation ‘Partnership on AI’ to address this,” Andrea Martin mentions.
“There they jointly devise principles for best practices in the development of AI solutions. This is so that the things that we do can benefit society as well as business to the greatest extent possible, and not be in conflict with them.” Reinhard Karger points out just how difficult this can be: “Massive amounts of data are required to train neural networks. But how can we verify whether this data actually corresponds to the demands of today’s society? Should thousands of people be trained to individually check the data? What are the criteria? And, must this examination be repeated on a regular basis? It is very difficult to eliminate the bias of a system.”

“Especially with an aim towards productivity and efficiency gains, Artificial Intelligence can trigger very positive developments.”
Thomas Staudinger, Vice President Marketing, EBV

Rules for AI development

A similar challenge is the question of the ethics of decisions made by AI systems. What should an autonomously driven car do, for example, if it is in an emergency situation and must choose between the life of the driver, a child on the street, or an old man on the sidewalk? “In my view this is much more important than the discussion as to whether machines enslave us at some point,” says René Büst. However, Reinhard Karger is a bit annoyed by this issue: “The probability of such a scenario occurring is infinitesimally small. When humans get into such disastrous situations, they react reflexively and do not decide according to ethical principles, which do not even exist for such a difficult dilemma.” But here, he comes up against contradiction: “There is a lot of uncertainty in this context because there are so many unanswered questions,”
surmises Oliver Gürtler, for example. “These need to be answered before decisions made by an AI solution can be accepted – not only with regard to autonomous driving but also regarding applications such as those in the field of medicine.” Andrea Martin, too, considers the issue of ethics in conjunction with AI to be pertinent: “The question is, of course, raised by that segment of society which is not so intensely preoccupied with Artificial Intelligence. We still have a very long way to go, however; there are still many technical basics to be mastered before a car has to make such decisions. I therefore believe that we still have time to answer the question.” Nevertheless, just as with René Büst, she sees the need to form ethics commissions which are dedicated to resolving moral issues arising from AI use. “Not to frighten people, but instead to make AI socially acceptable,” Büst emphasizes.

Approaches to integration in companies

Consumers are one thing, says Thomas Staudinger: “But how can I, as a medium-sized company, integrate AI into my business processes? AI is not an end in itself.” Ultimately, it is a question of the strategy which acompany’s management must set forth, declares Oliver Gürtler, among others, and emphasises: “AI offers a great opportunity for an enterprise to differentiate themselves from the competition.” As a company, though, what can you really do with AI? How can you set up a new business model based on it? What processes can be improved with it? According to Staudinger, these are all questions which confront many decision-makers in companies today: “There is still great need for clarification. Best practice examples could help to make the benefits of AI solutions more understandable and the topic more tangible.”

Andrea Martin advises to switch the perspective: “The field of AI is so broad that it could crush companies. Instead of seeing it as a giant beast which needs to be slain, one should clearly understand that AI is a modular concept. You can pick out individual elements and create dedicated solutions.” René Büst recommends to first start by automating processes in a company’s IT area with the help of AI. “With the information you collect while doing this, you can then extend AI solutions to other business processes and, to the same extent, create an awareness in the company.” Thomas Staudinger, who has his focus on the end-customers of his customers, sees the responsibility at the decision-maker level: “It’s all about providing the end customer with better service based on AI. I can’t achieve this with IT; instead, this is a business decision.” To the contrary, Oliver Gürtler recommends just getting on with it: “In our experience, it is extremely productive if both young professionals and experienced staff creatively work together, then simply implement the solution. To begin with, these are all mini-projects which do not require five years of software development, but can instead be implemented as a very “lean” solution to supplement the existing IT. Once companies start to see the benefits of AI, then they will also learn to understand AI for themselves.” This would lead to the emergence of truly transformative projects, according to Gürtler. Reinhard Karger also thinks that much of the potential that lies in staff: “For small businesses in particular, it makes sense for them to ask their own employees – through the company-internal suggestion programme, for example. Because, above all else, imagination is needed to introduce AI aas opposed to technological expertise.”

Realising opportunities

All participants agree that one should look at the opportunities offered by Artificial Intelligence – in production, research, and logistics, but also in the back office with regard to taxes, insurance, and much, much more. “It’s a long way between the fictional super-intelligence of a Terminator and a simple assistant,” stresses Andrea Martin. The round-table participants view AI above all as a possibility to supplement human capabilities – not replace them. Consequently, Reinhard Karger also surmises optimistically: “Yes, Artificial Intelligence will change our lives – and that is terrific.”

The post Opportunities of Artificial Intelligence appeared first on Future Markets Magazine.

“AI is a fundamental existential risk for human civilisation, and I don’t think people fully appreciate that.”

Elon Musk, Entrepreneur and Investor

“The AI, big data is a threat to human beings. The AI and robots are going to kill a lot of jobs, because in the future, these will be done by machines.”

Jack Ma, CEO and Founder, Alibaba

“I fear that AI may replace humans altogether. If people design computer viruses, someone will design AI that improves and replicates itself. This will be a new form of life that outperforms humans.”

Stephen Hawking, Physicist

“One problem is that the term ‘killer robots’ makes people think of ‘Terminator’ which is still 50, 100 or more years away. But it is much simpler technologies, stupid AI and not smart AI that we need to worry about in the near future.”

Prof. Toby Walsh, University of New South Wales

“We live in a world that could become fraught with day-to-day hazards from the misuse of AI and we need to take ownership of the problems – because the risks are real.”

Dr Seán Ó hÉigeartaigh, Executive Director of Cambridge University’s Centre for the Study of Existential Risk

“It is time for an optimistic antidote to the doom and gloom we often hear regarding AI and the future of work. There is no passive forecast for the future of work – it will be what we make it, and that begins with imagination of what we want it to be.”

Martin Reeves, Director, BCG Henderson Institute

“AI is probably the most important thing humanity has ever worked on. I think of it as something more profound than electricity or fire. Artificial Intelligence will save us not destroy us.”

Sundar Pichai, CEO, Google

“Regulating AI can wait until we invent it. It’s not true that it will be too late by the time we create it. We have switches. They work.”

Reza Zadeh, CEO and Founder, Matroid

“If we want to close the demographic gap, we cannot leave anybody out. Robots, intelligent machines and software systems help people to work more productively.”

Dieter Spath, Co-Chair of Plattform Lernende Systeme, a digitalisation research venture launched by the German government

“AI promises to deliver benefits not only economically, but also in terms of business management: it enables employees to leave repetitive or hazardous tasks to computers and robots, and focus themselves on value-adding and interesting work.”

Harald Bauer, Senior Partner at McKinsey’s Frankfurt office

“Artificial Intelligence will change the way we live together, beyond a doubt. For our society, it is a case of welcoming the positive developments while preventing negative impacts.”

Hannes Schwaderer, President of Initiative D21, a network promoting the information society in Germany

“We must do everything we can to take advantage of AI’s potential for the digital society. It is not about an AI system coming to replace a police officer or a doctor. It is about intelligent systems doing work for them.”

Achim Berg, President of Bitkom, the German IT association

“AI is making advances in every aspect of our lives, such as health and well-being, transportation and education. However, there are also pressing concerns over the technology’s safety, trustworthiness, fairness and transparency that need to be addressed.”

Prof. Tony F. Chan, President, Hong Kong University of Science and Technology

The post Opinions on Artificial Intelligence appeared first on Future Markets Magazine.

What influence do you think Artificial Intelligence (AI) will have in the future on technology and our lives in general?

William Amelio: Futurists are saying that AI will have a bigger impact on society than the industrial and digital evolutions. We’re starting to see more concrete examples of what that might be like as the technologies needed to power AI systems are now becoming more affordable and open-sourced. Artificial Intelligence is already enabling more personalised medicine and treatment plans in healthcare. The vehicles on our roads are increasingly autonomous. Facial, voice and fingerprint recognition are becoming more commonplace as well. Nonetheless, AI is providing input to us and we’re still making the ultimate decision. Over time, these applications will be equipped to make more decisions on our behalf, in theory helping us devote more time to higher-level thinking.

As Artificial Intelligence evolves to other applications over the next few years, it will begin to have exponential impact, especially in areas such as employment. Enabling farmers to maximise the efficiency of their fields or automating repetitive office management tasks will dramatically influence how we manage our work. In turn, AI will create new public policy challenges. Though opinions vary on the scale and timing of its impact, AI does have the capability and potential to help us solve many of the complex problems that plague our society.

What role will AI technology play specifically for Avnet as an electronics distributor?

W. A.: AI will help us optimise our operations, increase customer and employee satisfaction and unearth new market opportunities. Today, we’re exploring using database models for personalised pricing, automating payments and both managing and anticipating customer needs. We’re piloting a project to automate repetitive tasks that don’t add value to our bottom line or to our employees’ happiness. AI can also help us make predictions and deliver more personalised offerings and services to customers, suppliers and to our employee base.

We’ll also be able to speed up and automate processes by offloading some decisions to machines. In particular, I think supply chains will go through a complete metamorphosis resulting from a combination of emerging technologies, including AI. Much of AI’s early promise comes down to better decision-making. This is also the area where AI will begin to significantly impact corporate leadership and culture.

“To get there, we’ll need to shape a new generation of leaders who understand how to work with AI.”

What influence is AI technology having on your products?

W. A.: AI is certainly beginning to create demand for new technologies, which is opening the door for new market opportunities. For example, our new Avnet MiniZed Zync SoC platform improves the performance of sound capture for AI applications. It leverages technologies from Xilinx and Aaware to provide faster, safer far-field voice interfaces. Among our major suppliers, we’re seeing AI drive both hardware and software products, including both FPGA kits and custom chips to hardcode AI neural networks. Many companies are also designing AI-specific chips. This reflects a larger trend of moving some intelligence to the edge instead of housing it all in the cloud, which solves latency and cost issues with the magnitude of processing power that these applications require. Not only are venture capitalists backing start-ups in this area, but large technology powerhouses such as Intel, Google, Apple and Microsoft are getting in on custom chips, too. Many of them are already on our linecard.

Will AI bring any other changes beyond that for Avnet?

W. A.: I mentioned earlier that AI will significantly impact corporate culture and leadership. This is because it will change how we work, how we make decisions and how we structure our business models. To get there, we’ll need to shape a new generation of leaders who understand how to work with AI. This means introducing a new set of skills and evolving some of our existing ones to truly understand the new advantages that AI introduces.

For example, AI systems can help anticipate employee satisfaction and balance workloads accordingly. We can also gain insight from customer surveys more quickly and regularly because we won’t need to go through such laborious data mining. But are the corporate systems and talent needed to enable HR and customer service departments to operate this way available today? Probably not.

AI can do a lot for us, but first we need to learn how to work with it. The way we do business is going to look very different in 10 years, and each of us is going to need to embark on a personal journey of change and continuous learning along the way.

Avnet is now using AI itself – on its “Ask Avnet” platform. Can you tell us briefly what “Ask Avnet” is and how your customers benefit from it?

W. A.: Ask Avnet is designed to deliver a better customer experience by leveraging a combination of AI and human expertise to create an intelligent assistant. Our customers benefit because it can help them address a wide variety of questions without having to jump through customer service hoops. Ask Avnet can move customers through our various digital properties seamlessly, too. Customers can still enjoy the same experience on each site while Ask Avnet keeps them connected to the resources available within our broader ecosystem. We’re already seeing promising results, such as reduced errors. As Ask Avnet learns over time, it will help us deliver a more scalable, efficient and pleasant customer experience.

More importantly, Ask Avnet is designed to understand the context of our customers’ needs and tailor its responses accordingly. It makes personalisation possible, and this adds significant value that will only grow with time. Because it can contextually understand which stage of the product development journey our customers are in, Ask Avnet can proactively identify information that they might need but are not necessarily on the lookout for, such as product maturity stage or anticipated lead time. It continuously learns from new queries and experiences over time, continually delivering the latest insights as needs, technologies and markets evolve.

“AI does have the capability and potential to help us solve many of the complex problems that plague our society.”

“Ask Avnet” also utilises the know-how of the hackster.io and element14 platforms. How important are those 2016 acquisitions to the “Ask Avnet” objective of shortening time to market for your customers?

W. A.: Ask Avnet is another way for customers to access the wealth of information available through the Avnet ecosystem, of which these communities are one important piece. Ultimately, it extends the mission of our communities while introducing more proactivity and personalisation. When you’re in our communities, you’re on an exploratory journey. When you’re using Ask Avnet, you have an AI-powered guide that brings you the information you need.

By combining Ask Avnet with our online communities, we’re helping shorten our customers’ time to market by making the resources they need to solve their challenges more readily available, easy to access and relevant.

The beta version of “Ask Avnet” went online in July 2017. What has been your customers’ experience with it so far?

W. A.: The customer experience continues to improve because the intelligent assistant learns from every query. Customers are finding greater value in the tool, as both usage and customer satisfaction are increasing. It’s able to hold more detailed and longer conversations as the kinds of questions that Ask Avnet is able to address have expanded significantly. It’s also now able to probe further into queries.

For example, at launch, Ask Avnet would respond to a query with a list of recommendations. Today, Ask Avnet would respond with more relevant questions to help clarify your specs and narrow down options before providing recommendations. It can also include contextually relevant information, such as how-to projects from our communities, price and stock information or lead times. As it learns, Ask Avnet is providing more information and holding more high-quality conversations.

Will there be more projects with Avnet processes using AI in the future?

W. A.: Without a doubt. We’re currently focused on those that create the highest possible value for stakeholders, including both front-office and back-office projects. We’re looking at demand management, supply chain optimisation and are continuing work to enhance our customers’ experience with Ask Avnet and other projects. The technology is really applicable anywhere where there’s an opportunity to improve efficiency, reduce boredom and help our employees create more value.

How will AI influence our lives in the future?

W. A.: Just when you think innovation is waning, a new trend like AI takes hold. It’s clear to me that the economic and social value AI has to offer is just at the beginning of its “S-curve”. Whichever argument sways you, we all can agree that AI is fundamentally going to change the nature of how we live and work. This means that we need to explore new business models, hiring practices and skill sets. Start-ups, makers, tech giants and oldline companies are all in the game. Competition will drive new and innovative AI ideas and applications, and I’m excited to see the next chapter in this story.

From initial sketch to mass production

Avnet supports its customers through every phase of the product life cycle – from initial idea to design, from prototype to production. As one of the world’s largest distributors of electronic components and embedded solutions, the company offers a comprehensive portfolio of design and supply chain services in addition to electronic building blocks. Its acquisition of the online communities Hackster.io and Element14 in 2016 furthermore shows how Avnet is building bridges between the maker and manufacturer. Hackster.io is committed to helping fledgling companies develop hardware for IoT designs. The network engages with some 90 technology partners and includes close to 200,000 engineers, makers and hobbyists. Element14 is an engineering community with more than 430,000 members. By acquiring both platforms, the company is taking an important step towards achieving its goal of helping customers get their ideas first to market. In this respect, Avnet can call on a closely-knit global network of leading technology companies dating back almost a century.

Avnet has its headquarters in Phoenix, Arizona. The company was founded in 1921 by Charles Avnet, starting out as a small retail store in Manhattan specialising in the sale of components for radios. Today Avnet has a workforce of more than 15,000 employees and is represented in 125 countries in North America, Europe and Asia.

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Could our entire life simply be a computer simulation, like “the Matrix” from the Hollywood blockbuster of the same name? According to Marvin Minsky, this is entirely conceivable: “It’s perfectly possible that we are the production of some very powerful complicated programs running on some big computer somewhere else. And there’s really no way to distinguish that from what we call reality.” Such thoughts were typical of the mathematician, cognition researcher, computer engineer and great pioneer of Artificial Intelligence. Minsky combined science and philosophy scarcely any other, questioned conventional views – but always with a strong sense of humour:

“No computer has ever been designed that is ever aware of what it’s doing; but most of the time, we aren’t either.”

Born in 1927 in New York, Minsky studied mathematics at Harvard University and received a PhD in mathematics from Princeton University. He was scarcely 20 years old when he began to take an interest in the topic of intelligence: “Genetics seemed to be pretty interesting because nobody knew yet how it worked,” recalled Minsky at the time in an article that appeared in the “New Yorker” in 1981. “But I wasn’t sure that it was profound. The problems of physics seemed profound and solvable. It might have been nice to do physics. But the problem of intelligence seemed hopelessly profound. I can’t remember considering anything else worth doing.”

Great intelligence is the sum of many non-intelligent parts

Back then, as a youthful scientist, he laid the foundation stone for a revolutionary theory, which he expanded on during his time at the Massachusetts Institute of Technology (MIT) and which finally led to him becoming a pioneer in Artificial Intelligence: Minsky held the view that the brain works like a machine and can therefore basically be replicated in a machine too. “The brain happens to be a meat machine,” according to one of his frequently quoted statements. “You can build a mind from many little parts, each mindless by itself.” Marvin Minsky was convinced that consciousness can be broken down into many small parts. His aim was to identify such components of the mind and understand them. Minsky’s view that the brain is built up from the interactions of many simple parts called “agents” is the basis of today’s neural networks.

Together with his Princeton colleague John McCarthy, he continued to develop the theory and gave the new scientific discipline a name at the Dartmouth Conference in 1956: Artificial Intelligence. Together McCarthy and Minsky founded the MIT Artificial Intelligence Laboratory some three years later – the world’s most important research centre for Artificial Intelligence ever since. Many of the ideas developed there were later seized on in Silicon Valley and translated into commercial applications.

Answerable for halting research

What is interesting is that the father of Artificial Intelligence was responsible for research into the area being halted for many years: Minsky had experimented himself with neural networks in the 1960s, but renounced them in his book “Perceptrons”. Together with his co-author Seymour Papert, he highlighted the limitations of these networks – and thus brought research into this area to a standstill for decades. Most of these limitations have since been overcome, and neural networks are a core technology for AI in the present day.

However, research into AI was by far not the only work area that occupied Marvin Minsky. His Artificial Intelligence Laboratory is regarded as the birthplace for the idea that digital information should be freely available – a theory from which open-source philosophy later emerged. The institute contributed to the development of the Internet, too. Minsky also had an interest in robotics, computer vision and microscopy – his inventions in this area are still used today.

Problems of mankind could be resolved

Minsky viewed current developments in AI quite critically, as he felt they were not focused enough on creating true intelligence. In contrast to the alarmist warnings of some experts that intelligent machines would take control in the not too-distant future, Minsky most recently advocated a more philosophical view of the future: machines that master real thinking could demonstrate ways to solve some of the most significant problems facing mankind. Death may also have been at the back of his mind in this respect: He predicted that people could make themselves immortal by transferring their consciousness from the brain onto chips. “We will be immortal in this sense,” according to Minsky. When a person grows old, they simply make a backup copy of their knowledge and experience on a computer. “I think, in 100 years, people will be able to do that.”

AI-Pioneer Minsky only temporarily dead

Marvin Minsky died in January 2016 at the age of 88. Although perhaps only temporarily: shortly before his death, he was one of the signatories of the Scientists’ Open Letter on Cryonics – the deep-freezing of human bodies at death for thawing at a future date when the technology exists to bring them back to life. He was also a member of the Scientific Advisory Board of cryonics company Alcor. It is therefore entirely possible that Minsky’s brain is waiting, shock-frozen to be brought back to life at some time in the future as a backup on a computer. 

The post AI-pioneer Minsky: Temporarily dead? appeared first on Future Markets Magazine.

Connected Cars for Everyone

In the form of Chris, the start-up German Autolabs provides an assistant designed specifically for motorists, which easily and conveniently provides access to their smartphone via smart speech recognition and gesture control, including while driving. Chris can be integrated with any vehicle, regardless of its model and year of manufacture. The aim is to make connected car technology available to all through the combination of a flexible and scalable assistant software and hardware for retrofitting.

www.hellochris.ai

Make Your Own Voice Assistant

Snips is developing a new voice platform for hardware manufacturers. The service, based on Artificial Intelligence, is intended to allow developers to embed voice assistance services on any device. At the same time, a consumer version is due to be provided over the Internet, running on Raspberry Pi-powered de­vices. Privacy is at the forefront of this, with the system sending no data to the cloud and operating completely offline.

www.snips.ai

Realistic Simulation for Autonomous Driving Systems

Automotive Artificial ­Intelligence offers a virtual 3D platform which realistically imitates cars’ driving environment. It is intended to be used as a means of testing software for fully automated ­driving, helping to explore the systems’ limits. ­Self-learning agents ­provide the reality needed in the virtual platform. ­Aggressive ­drivers turn up just as often as overcautious ones, and there are arbitrary lane changes just as there are unforeseeable braking manoeuvres from other (simulated) vehicles that are part of the traffic.

www.automotive-ai.com

Feeding Pets More Intelligently

With SmartShop Beta, Petnet provides a digital marketplace that guides dog and cat owners towards suitable food for their pets using Artificial Intelligence ­­–
­depending on their breed and specific needs. The start-up has itself also developed the Petnet SmartFeeder for the feeding pets. This allows the pets to be automatically supplied with individual portions. The system gives notifications for successful feeds and when food levels are low. An automatic repeat order can also be set up in the SmartShop.

www.petnet.io

Smart Water Bottle

Bellabeat has already successfully brought Healthtracker to market in the form of women’s jewellery. Building on this, the start-up has developed an intelli­gent water bottle with Spring. By way of sensors, its system can record how much water the user drinks, how active she is, how much she sleeps, or her stress sensitivity levels. An app, with the assistance of ­special AI algorithms, is used to ­analyse users’ individual hydration needs and give a ­recommendation for fluid intake.

www.bellabeat.com

Drone for the Danger Zone

Hivemind Nova is a ­quadrocopter for law enforcement, first responder and security applications. The drone learns from experience how to negotiate restricted ­areas or hazardous environments. Without a pilot remote-controlling, it autonomously explores dangerous buildings, tunnels, and other structures before people enter them. It transmits HD video and a map of the building layout to the user live. Hivemind Nova learns and continuously improves over time. The more it is used, the more capable it becomes.

www.shield.ai

Detecting Wear Ahead of Time

Konux combines smart sensors and analysis based on Artificial Intelligence. The solution is used on railways to monitor sets of points, for example. Field data, already pre-processed by sensor, is wirelessly transmitted to an analysis platform and combined with other data sources such as timetables, meteorological data, and maintenance logs. The data is  then analysed using machinelearning algorithms to detect ­operational anomalies and critical wear in advance.

www.konux.com

Greater Success with Job Posts

Textio is an advanced writing platform for creating highly ­effective job advertisements. By analysing the hiring outcomes of more than 10 million job listings per month, Textio predicts the impact of a job post and gives instructions in real time as to how the text could be ­improved. To do this, the ­company uses a highly sophisticated predictive engine and makes it usable for anyone – no training or IT ­integration needed.

www.textio.com

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Systems with Artificial Intelligence require a wide range of electronic components. This is an area where EBV already has a vast variety of components in its product portfolio, from sensors to FPGAs. However, the new technology poses a challenge for the electronics distributor, as Antonio Fernandez, Vice President of Technical Development at EBV, told us. In order to provide customers with expert assistance when it comes to software development and technical support, the company has joined important manufacturers in developing a common AI roadmap. It is also investing in specialised software support.

AI is making its way into more and more applications. What does that mean for you as an electronics distributor?

Antonio Fernandez: For us, Artificial Intelligence represents both a huge business opportunity and an unprecedented challenge in terms of technical support. That’s our chance to stand out, demonstrating the value of our partnership to our customers.

Is your product portfolio changing?

A.F.: Artificial Intelligence can be deployed in the cloud, at the edge of the network, or most commonly in a combined scenario between edge and cloud. We already have FPGAs, MPSoCs and processors capable of implementing AI in the different application scenarios and a promising roadmap with our key manufacturers and partners of dedicated AI hardware and software.

Alongside AI chips, which components are important for supporting customers in the development of AI systems?

A.F.: That starts with sensors for collecting all the variables that affect a process, then also includes processors to effectively implement the sensor fusion and communication protocols, security chips to safeguard the communications, and much more. Then, to transfer the data, wireless connectivity transceivers – for instance, for Wi-Fi, Bluetooth, Thread or LTE – and various network products are also needed.

Does this also present challenges in consulting and other services offered by EBV?

A.F.: Sure, but our technical specialisation and close collaboration with our manufacturer partners and AI cloud service preferred third parties enable us to take on the challenge.

In particular, AI is also a software topic. How can EBV support customers here?

A.F.: EBV continues to invest in specialised software support resources and our manufacturing partners are developing specific software-development kits that will significantly accelerate the adoption of machine learning in multiple applications. A good example is the Xilinx “reVISION” stack for edge machine learning in embedded vision applications.

AI solutions are also becoming increasingly interesting for companies that have so far had little or no contact with the world of electronics. Can you also support companies like those, and if so, how?

A.F.: Our customers develop and manufacture electronics systems and cover all kinds of applications. When integrators approach us, we try to understand their needs and refer them to some experienced customers, design houses, and contract manufacturers that can solve their requirements and deliver a final product.

What technology trends in AI are you currently seeing among your suppliers, the electronics manufacturers?

A.F.: There are several interesting developments here. For instance, AI specific functions and peripherals are being integrated into the MCUs. This allows small microcontroller-based nodes to interact more intelligently with deep neural networks. Another observation would be an increase in the power of the processors and MPSoCs to implement edge inference engines with very low latency. In addition, the manufacturers are currently investing very heavily in software libraries for sensor fusion and machine learning.

In what areas do you see need for further development in electronic components for AI?

A.F.: Sensors are a critical area for the development of Artificial Intelligence. We still do not have commercial sensors for smell or taste, for instance … Artificial Intelligence is a very complex topic, so specific development kits and training will be required to bring its benefits to the mass market.

In your view, which applications are currently especially interesting or offer particularly high potential for AI systems?

A.F.: Embedded vision, autonomous systems, predictive maintenance, natural-language human-machine interface, robotics, measurement and diagnostics.

Elon Musk is often quoted as saying that AI is one of the biggest risks facing humanity. What is your opinion on this?

A.F.: Artificial Intelligence can enable disruptive innovations that could represent a significant benefit for humanity, increasing our productivity and quality of life; but there is a risk of machines replacing people, which could increase unemployment, the risk of losing privacy with Big Brother controlling everything, and of systems taking unsupervised decisions and doing more harm than good. As usual, it all depends on the use of the technology and we most probably need new rules to regulate the ethical use of Artificial Intelligence.

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