This is of course very useful for practical purposes. If you think of companies that want to use AI for customer contacts, for example, simple functionalities, simple first-level answers, can already be provided by machines. "Neuronal Networks" is January 2019 Calendar Australia another keyword currently used in the AI environment Mouth is. What can one imagine under this? Wrobel: Neuronal networks are an original biology-inspired method of machine learning. We understand a sequence of functions that calculate from a certain amount of input over multiple layers of output.
Deep learning refers to neural networks with a greatly increased number of levels that could be used to penetrate new classes of problems.Blackbox, Graybox, WhiteboxBlackbox, Graybox, Whitebox Models differ in whether and to what extent the algorithm knows the January 2019 Calendar Canada physical model of the problem to be learned and incorporates it into its learning process. Whitebox models know this as closely as possible, but black box approaches do not consider the model.
January 2019 Calendar CanadaGreybox refers to combination approaches between the two. Neuromorphic chips Neuromorphic chips are microchips that replicate nerve-cell characteristics and architecture at the hardware level. These neuron-like components simulate the learning and association ability of the brain, which can particularly accelerate the recognition of patterns in images or in big-data structures.78 What is "Artificial Intelligence?" Wrobel: Intelligence is a central feature of human beings, which we usually only accord humans. If machines are now able to do things we would classify as intelligent, we call them artificial intelligence. It currently includes machines that, for example, are capable of interpreting images, of responding to linguistic utterances, and even of supposedly simple things like the digital assistants on our mobile phones. What do you think about the definition of machine learning? Wrobel: It was already at the beginning of Artificial Intelligence It's clear to AI pioneer AlanTuring that it's possible to program intelligent computer space by hand to every detail. "That means that human labor will be less extensive. And that we can train intelligent systems." He wrote as early as 1950 that there had to be a faster method - the machine learning. With these »STILL LONG AT THE END OF DEVELOPMENT« An interview with Prof. dr. Stefan Wrobel, Head of the Fraunhofer Institute for Intelligent Analysis and Information Systems IAIS and Professor of Computer Science at the University of Bonn, on Chances, Challenges and the Acceptance of Artificial Intelligence.INTERVIEW9 methods, computers are able to learn from observations, existing data and examples and thereby improve their behavior. Can one compare these intelligent computer systems with human intelligence? Wrobel: You can always compare two things, even if they have different character. A plane does not fly like a bird, a computer does not think like a human. We need to look at the achievements and then judge whether we classify this as equally intelligent, less intelligent, or as intelligent than what a human would do. Computers have already made big breakthroughs, not to mention winning the gameshow Jeopardy or cracking the game GO, not to speak of chess. Could one say: In topics such as strategy or image recognition, the AI now works human again or even better, but with the creative human being still has that Staff in hand? Wrobel: I do not think it's that easy anymore to say that flat-rate. It depends on whether an action by the computer is actually learned from examples. Can the necessary knowledge be modeled in advance? Whether or not a creative component is included in the execution is a deeper philosophical question. In interactions, the question arises: How long do I need to identify an AI? When it comes to customer January 2019 Calendar Canada service and support inquiries, it's quite common nowadays to have a Chat-Bot.Prof. Dr. Stefan Wrobel10Wrobel: We can not, in a philosophical way, create an artificial intel authenticity, merely the indistinguishability between human-to-human and human-to-human interactions.
Deep learning refers to neural networks with a greatly increased number of levels that could be used to penetrate new classes of problems.Blackbox, Graybox, WhiteboxBlackbox, January 2019 Calendar UK Graybox, Whitebox Models differ in whether and to what extent the algorithm knows the physical model of the problem to be learned and incorporates it into its learning process. Whitebox models know this as closely as possible, but black box approaches do not consider the model.
January 2019 Calendar UKGreybox refers to combination approaches between the two. Neuromorphic chips Neuromorphic chips are microchips that replicate nerve-cell characteristics and architecture at the hardware level. These neuron-like components simulate the learning and association ability of the brain, which can particularly accelerate the recognition of patterns in images or in big-data structures.78 What is "Artificial Intelligence?" Wrobel: Intelligence is a central feature of human beings, which we usually only accord humans. If machines are now able to do things we would classify as intelligent, we call them artificial intelligence. It currently includes machines that, for example, are capable of interpreting images, of responding to linguistic utterances, and even of supposedly simple things like the digital assistants on our mobile phones. What do you think about the definition of machine learning? Wrobel: It was already at the beginning of Artificial Intelligence It's clear to AI pioneer AlanTuring that it's possible to program intelligent computer space by hand to every detail. "That means that human labor will be less extensive. And that we can train intelligent systems." He wrote as early as 1950 that there had to be a faster method - the machine learning. With these »STILL LONG AT THE END OF DEVELOPMENT« An interview with Prof. dr. Stefan Wrobel, Head of the Fraunhofer Institute for Intelligent Analysis and Information Systems IAIS and Professor of Computer Science at the University of Bonn, on Chances, Challenges and the Acceptance of Artificial Intelligence .INTERVIEW 9 methods, computers are able to learn from observations, existing data and examples and thereby improve their behavior. Can one compare these intelligent computer systems with human intelligence? Wrobel: You can always compare two things, even if they have different character. A plane does not fly like a bird, a computer does not think like a human. We need to look at the achievements and then judge whether we classify this as equally intelligent, less intelligent, or as intelligent than what a human would do. Computers have already made big breakthroughs, not to mention winning the gameshow Jeopardy or cracking the game GO, not to speak of chess. Could one say: In topics such as strategy or image recognition, the AI now works human again or even better, but with the creative human being still has that Staff in hand? Wrobel: I do not think it's that easy anymore to say that flat-rate. It depends on whether an action by the computer is actually learned from examples. Can the necessary knowledge be modeled in advance? Whether or not a creative component is included in the execution is a deeper philosophical question. In interactions, the question arises: January 2019 Calendar UK How long do I need to identify an AI? When it comes to customer service and support inquiries, it's quite common nowadays to have a Chat-Bot.Prof. Dr. Stefan Wrobel10Wrobel: We can not, in a philosophical way, create an artificial intel authenticity, merely the indistinguishability between human-to-human and human-to-human interactions.
The Industrial Data Space maintains the digital sovereignty of the owners of the data and at the same time forms the basis for smart services and innovative business processes. Artificial intelligence (AI), cognitive systems and learning machines play a crucial role in the future transformation of business and society. For the January 2019 Calendar USA international economy and industrial value chains, this means a fundamental structural change - because technical systems are adaptive and increasingly capable of transferring what they have learned to new situations.
January 2019 Calendar USAThey can plan processes, make predictions and even interact with people. The International Data Corporation expects $ 40 billion in global cognitive-solution spendouts by 2020. Using new technologies not only opens opportunities, it also challenges us all. For a lasting technological leadership in Germany in the field of AI not only technological solutions are in demand, but also the social dialogue. Fears and myths must be opposed to scientific knowledge. Machines will expand our circle of influence, but will not take over the leadership. The Fraunhofer-Gesellschaft develops key AI technologies and applications in fields such as robotics, image and speech processing, and process optimization. Machine learning processes for industry are as much part of this as the use of cognitive systems in cybersecurity and the need to explore artificial neuronal ones networks. Our research makes significant contributions to the theory and ethical design of AI, and is geared to "For 20 years, we have been regularly reading that the breakthrough of artificial intelligence is imminent. But now it really is true. "Sascha Lobo, author and blogger" The danger of artificial intelligence lies not in the fact that machines think more and more like humans, but that people are thinking more and more like machines. "Joseph Weizenbaum, computer scientist, cyberneticist and social critic» Evolution is more than the sum of all revolutions. "Gerald Dunkl, psychologist and aphorist." While they were researching, x-raying, filming, radiating, they themselves created the most delicious invention: the detour as the shortest link between two points. «Erich Kästner, writer» Artificial intelligence is always better than natural stupidity. «Hans Matthöfer, Former Federal Minister6The most important terms on the subject briefly explained: Cognitive Systems / MachinesCognitive systems / machines are technical systems that record digital information from sensor data and networks and turn it into B As a result of learning algorithms, conclusions, decisions and actions are derived and verified with their environment in dialogue and optimized. Machine LearningAs machine learning, processes are described in which an algorithm / machine learns by repetition of a task to perform it better with respect to a quality criterion. Artificial Intelligence Artificial Intelligence (Art. AI) is a branch of computer science that deals with equipping machines with skills that resemble intelligent (human) behavior. This can be achieved with preprogrammed rules or machine learning. Strong general AI refers to machines that can provide generalized intelligence and transfer services, and are thus not limited to very limited, predefined task areas. GLOSSARY7Neuronal Networks (Deep Learning) Artificial neural networks are a basis for machine learning based on neuronal networks in the brain. They consist January 2019 Calendar USA of data nodes and weighted connections between them. By changing various parameters in the network, machine learning techniques can be realized.
This raises the question of whether these now learned and conceptualized rules should not be used as a moral aspect in machines, "argues researcher Sütfeld." Personality recognition "for robotic people January 2019 Calendar With Holidays recognize gestures and interpret glances quickly and almost automatically. Computers and robots do not do that, so scientists around the world are working on ways to make human-computer collaboration more social, efficient and flexible.
January 2019 Calendar With HolidaysComputer scientists from Saarbrücken and Stuttgart have now reached an important milestone together with psychologists from Australia.The software system developed by them processes the eye movements of a person and calculates whether it is vulnerable, sociable, tolerable, conscientious or curious. "With our eyes, we not only capture the environment, they are also the window to our souls. Because they reveal who we are, how we feel and what we do, "explains Andreas Bulling, who heads the research group" Perceptual User Interfaces "in Saarbrücken at the Max Planck Institute for Informatics and the Cluster of Excellence of the Saarland University Bulling has trained scientists in Stuttgart and Australia to develop their own software system based on machine-learning algorithms so that they can evaluate eye movements and draw conclusions about their traits. To obtain the data for the training and the evaluation, the Flinders worked University in Australia took 50 students in. After arriving at the lab, the researchers equipped the students with a so-called "eye tracker," which filmed the subject's eye movements for about ten minutes people roamed the campus and bought coffee or other items in the campus store. Afterwards, the students were asked to take off their glasses and fill in special questionnaires to determine the personality and level of curiosity in a conventional way. "To analyze the recorded eye data, regardless of the duration of the recording, we have one slidable time frame, as it does not weaken any characteristics, "explains Bulling. From each of the resulting windows, the researchers gained 207 characteristics. These included statistics on gaze fixation as well as the blink rate. On the basis of this data and the information from the questionnaires, the researchers collected around 100 decision trees for each personality train and trained them for a classifier : The result: In the subsequent test with previously unused data, they were able to prove that the software system reliably recognizes traits such as emotional lability, sociability, compatibility and conscientiousness. "We also transfer this knowledge of nonverbal behavior to robots, so that they can how people behave. Such systems would then communicate with humans in a much more natural way and would therefore be more efficient and flexible in their use, "says researcher Bulling. International Data Spaces - Better data availability AI experts also see demand for data availability. . As already mentioned, in Germany there is a shortage of generally accessible, usable data worldwide. In order to create incentives to generate and share such data, professionals recommend that data creators retain control and sovereignty over their data, but share it for mutual benefit. Models such as the International Data Spaces January 2019 Calendar With Holidays and especially the Industrial Data Space are exemplary in this context. The Industrial Data Space is a virtual data room that enables the secure exchange of data and the simple linking of data in business ecosystems based on standards and with the help of collaborative governance Models supported.
The application potential of intelligent data analysis methods for monitoring and optimizing test data, ECUs and test benches in the automotive industry is, according to the partners, "extraordinary". For example, a state-of-the-art engine control unit has more than 50,000 setting parameters that govern performance, January 2019 Calendar PDF consumption, wear, and overall engine performance. Deep learning technologies, or more precisely the use of neural networks in the control unit, can autonomously "learn" how to optimally set the input variables.
January 2019 Calendar PDFThe use of such networks in the time series analysis of engine test data also enables new approaches for "predictive health monitoring" the prediction of wear and maintenance cases can be improved. Such procedures should be researched and developed in the new research laboratory. At the same time, the FLaP will also work on new visualization options for the diverse measurement data from the neural networks. It is planned to create a toolbox of AI tools that can be used intuitively by automotive engineers.Automotive: The PostBus plans its own routeAutonomous driving and electric driving are top priorities at the Deutsche Post DHL Group. For this purpose, the logistics group will set up a test fleet of autonomous and purely electric delivery vehicles. Partner is the automotive supplier ZF - because the "Postautos" are equipped with the control box ZF ProAI, which developed the ZF Friedrichshafen AG together with NVIDIA. The light, electrical and intelligent delivery vehicles can above all the future requirements on the "last mile" Customers who are currently very complex and costly due to the flexibility expectations in e-commerce and the requirements of the disposition. The Deutsche Post DHL Group currently has a fleet of 3400 street scooter delivery vehicles. These can be equipped with ZF sensor technology - camera, lidar and radar sensors - whose information is processed by the control box ZF ProAI. Thanks to AI, the vehicles can later "understand" their immediate surroundings, plan a safe route - or reschedule at short notice -, track the route and park the vehicle independently. This makes deliveries more accurate, safer and cheaper.Quo vadis Driver Assistance Systems? Autonomous DrivingQuo vadis Driver Assistance Systems? 15.05.18 - Autonomous driving is on everyone's lips. But the essential components required for the self-driving automobile are already part of modern driver assistance systems: they automate key aspects of driving. "The example of autonomous delivery vehicles shows how strongly AI and deep learning are affecting the commercial vehicle industry," said Jensen Huang, founder and CEO of NVIDIA , "As online shopping continues to grow, but the number of truck drivers is limited, KI-enabled autonomous vehicles are becoming a key player in future 'last mile' logistics. " To develop these AI delivery vehicles , the Deutsche Post DHL Group has already equipped its data center with the supercomputing chip NVIDIA DGX-1, thus training its artificial neural network. As the January 2019 Calendar PDF vehicle continues to develop, these deep learning algorithms are later transferred to the vehicle control boxes on the NVIDIA Drive PX platform. In a prototype presented at the NVIDIA developer conference "GPU Technology Conference" (GTC) in Munich, six cameras, one radar and two lidar systems provide the AI with data. Logistics
The young company helps buyers use artificial intelligence to find new suppliers and to optimize their supplier relationships. But what about Artificial Intelligence? What is currently being researched? What's in the pipeline? Machines can (but) act morallyMachines can soon mimic people's moral behavior. Scientists at the January 2019 Calendar Excel University of Osnabrück are convinced of this. The reason is autonomous driving, because self-driving automobiles are the first generation of intelligent robots that share everyday life with people.
January 2019 Calendar ExcelConsequently, it is essential to develop rules and expectations for autonomous systems that define how they should behave in critical situations. The Institute for Cognitive Science at the University of Osnabrück has now published a study in "Frontiers in Behavioral Neuroscience", i e shows that human-ethical decisions can be implemented in machines and autonomous vehicles will soon face moral dilemmas in traffic. Politically, the debate on the modeling of moral decisions is accompanied by an initiative of the Federal Ministry for Transport and Digital Infrastructure (BMVI). This has formulated 20 ethical principles. The Osnabrück study now provides the first empirical scientific data. "In order to be able to define rules or recommendations, two steps are necessary. First of all, you have to analyze and understand human moral decisions in critical situations. The second step is to statistically describe human behavior in order to derive rules that can then be used in machines, "explains Prof. Dr. med. Gordon Pipa, one of the leading scientists in the study. To realize both steps, the authors used a virtual reality to observe the behavior of subjects in simulated traffic situations. The participants of the study drove on a foggy day through the streets of a typical suburb. In the course of the experiments, there were inevitable and unexpected dilemma situations in which people, animals or objects stood as obstacles in the lanes. In order to avoid the obstacles in one of the two tracks, a moral balance was necessary. The observed decisions were then evaluated by a statistical analysis and translated into rules. The results indicate that, in the context of these unavoidable accidents, moral behavior can be explained by a simple valence of life, for every person, every animal, and every object. Leon Sutfeld, the principal author of the study, explains this: "The human moral Behavior can be explained or predicted with considerable precision by comparing the valence of life associated with each person, animal or object. This shows that human moral decisions can be described in principle with rules and that these rules could be used as a consequence of machines. "Basically, the findings of Osnabrück researchers contradict the eighth principle of the BMVI report (see above) based on the assumption that moral decisions can not be modeled But can this fundamental difference be explained? Algorithms can be described either by rules or by statistical models that relate several factors to each other. So laws are rule-based. By contrast, humans and modern artificial intelligent systems are more likely to use a complex statistical balance. This balance allows humans and the modern AI to assess new situations that January 2019 Calendar Excel humans and AI have not been exposed to. Sütfeld's scientific work has now used such data-like methods of human behavior. "Therefore, the rules do not have to be formulated abstractly at the desk by a human, but derived from human behavior and learned.
The algorithm replaces the dispatcher the sign of digitization fundamental change and always job profiles are under pressure to adapt. A good example of this is the dispatcher. His main task is traditionally in the January 2019 Calendar Word optimization of transport and in pricing. Both tasks are already supported by computers today. Digital forwarding companies such as FREIGHT ROOM immediately backfill the entire business model with self-learning algorithms.
January 2019 Calendar WordFrom this perspective, it is clear to the Berlin-based company that the role of humans in logistics planning will change dramatically as a result of better and better working algorithms: from the planning and optimization of a transport to the care and management of the persons involved Logistics is subject to many factors of varying dynamics. In addition to weight and distance of the transport, holidays and bridging days, the availability of the requested truck type, charge exchange or seasonal peak demand, factors such as the short-term booking request and the current fuel price are also included. The selection of more than 100 parameters, the dispatchers at the Determining a transport price shows how complex and thus error-prone this process is. This is one of the reasons why the large logistics companies work with regional branches, as dispatchers can only guarantee this information density for a regionally limited space. Only there does the complexity of the scheduling process remain manageable. For this reason, FRACHTRAUM relies on a machine learning-based algorithm. This is able to include all relevant parameters within a few seconds and to determine on this basis quasi ad-hoc a binding price - for each type of transport. At the same time, the quality of the solution improved improves with every transport carried out "automatically" increases the available amount of data on the basis of which the price is calculated. And what about the dispatcher? This will be seen more than ever in the role of the human link between driver and shipper. Already one year after entering the market, FRACHTRAUM carries out around 3000 transports automatically every month on the basis of self-learning algorithms. Chatbot assists the purchaser. Natural language processing and artificial intelligence make shopping faster, more intuitive and more pleasant. One of them is convinced of Basware. The Finnish software company presented Basware Assistant, a new Chatbot feature within its electronic procurement solution, at AP & P2P Conference & Expo in the spring of 2018. The Chatbot acts as a virtual assistant that helps buyers find order requests and orders they have access to. The Basware Assistant uses natural language processing and artificial intelligence to create a new and simplified way of interacting with Basware's e-procurement solution to accomplish. Buyers can communicate with the Basware Assistant, as with a flesh-and-blood person, to search for orders, purchase inquiries, supplier and product names, and ID and document numbers. The verbal communication with the sourcing solution eliminates the need to navigate through a series of screens as before to get to the desired "process." Another example of AI use in the procurement area is the Würzburg-based company Scoutbee, which helps buyers Assisting Artificial Intelligence in finding new suppliers and optimizing their supplier relationships. Only recently, Scoutbee's founders were able to prevail against 118 competitors in their business plan competition for January 2019 Calendar Word northern Bavaria.KI: Scoutbee ranked first in business plan competitionArtificial intelligenceKI: Scoutbee ranked first in business plan competition16.07.18 - Ranked 1st in business plan competition in northern Bavaria landed the Würzburg start-up Scoutbee.
Kurt Bettenhausen, chairman of the interdisciplinary VDI panel Digital Transformation, who presented the results of the survey at the Hannover Messe 2018, stated that the December 2018 Calendar Kalnirnay USA was a leader in basic research, but also in the use of AI for the evaluation of unstructured consumer data, due to stricter data protection regulations such as new DSGVO in Germany and Europe is only conditionally possible.
December 2018 Calendar KalnirnayThe Siemens manager, who has been active in the USA for years, sees this as a "chance and risk" at the same time. "According to the VDI study, the requirements in China are also completely different from those in this country China's centralized structures are part of the economic plan is investing heavily in AI, with the national target of becoming the # 1 artificial intelligence in the world by 2030. Bettenhausen: "China has taken a breathtaking pace as part of the Digital Transformation and is leapfrogging some of the development that has been going on Machine learning happens either through training on a record of known outputs (monitored), or algorithms need to recognize patterns in data themselves (unsupervised), learning through reward and punishment (reinforced ), in which the algorithm independently recognizes whether the learning component belongs to the entire system m uses (reward) or not (punishment). The data are either structured, for example in tabular form, or unstructured as text, image or language - as in e-mails or social media posts. Machine Learning can handle all the data, which is a big advantage. Source: SAPChina: Data and IT are in abundance. China has another advantage: huge market and access to a vast amount of data. That makes "much easier", as Bettenhausen emphasized in Hannover, compared to Europe, where there is a data shortage due to data protection. In addition, there are a large number of people in China who deal with IT and with it big data and artificial intelligence - casually speaking, there is a huge pool of natural intelligence in the Middle Kingdom that other countries do not have on that scale sees VDI expert Bettenhausen Germany in the AI basic research by no means "suspended". In principle questions one h This country is even quite well positioned. However, the still inadequate digital penetration of production prevents the use of AI technologies on a larger scale. The statement "We lack the prerequisites for digitally networked production (Industry 4.0) in order to use AI technologies efficiently." In the VDI survey around two-thirds of the surveyed members agreed or "rather" agreed. Only 13.9 percent felt differently and expressed the opinion that their company was sufficiently prepared for the "fourth industrial revolution". "We did not expect that to happen in this way", emphasized Bettenhausen at the press conference at the Hannover Messe 2018. To make matters worse, there was often a lack of the skills required for December 2018 Calendar Kalnirnay the beneficial use of AI methods. Professionals who are proficient in KI methods are scarcely available in the companies and hardly available on the job market. Consequently, the practical use of artificial intelligence in German industry is still in its infancy.
Outlining the benefits of AI and the associated opportunities to reinvent its own products with digital technologies.2. Develop a vision on how existing offers can be complemented by AI.3. Provide the resources needed to develop AI-based products.4. Implementing their vision and concrete initiatives to enable December 2018 Calendar Spanish large-scale digital reinvention of products. If the companies studied are classified by industry and up-to-date for use in specific clusters, the level of maturity in the Artificial Intelligence industry is demonstrated to industry is very different.