There you can buy not only our smart devices but also your desired mobile phone without a contract. But not only the functional development and manufacturing Our smart devices are important to us, but January 2019 Calendar To Print also your satisfaction as a customer. To make you feel comfortable with your product as a PHICOMM customer, we provide extensive technical support and cell phone service to you if you have a request.
"Smart grids" increase complexity, cost and vulnerability. The simulation softwareMYNTS (Multiphysical Network Simulator) of the Fraunhofer Institute for Algorithms and Scientific Research (SCAI) helps January 2019 Calendar Marathi to plan and operate complex electricity, gas or heating networks. It can be used, for example, to calculate how changes or even failures in subnetworks can affect the other network components or whether all compressor stations in a gas network can be operated in an energy-efficient manner.
January 2019 Calendar MarathiA new development looks at cross-sectoral networks and flexibility options.This makes the expansion more flexible and less expensive for network operators, relieves the burden on the environment and increases safety.www.scai.fraunhofer.de »DeepER«: Modern document analysisTechnologies for optical character recognition will benefit in the future from breakthroughs in the area of AI. This is what the research project calls "Deep learningbased optical character recognition" (DeepER). As part of the BMBF-funded project, the Fraunhofer Institute for Intelligent Analysis and Information SystemsIAIS is working with partners on new software for reliable document analysis. Intelligent learning systems should be based on deep learning methods for a significant technology progress. Optical Character Recognition (OCR) is used, among other things, in the digitization of library contents, newspaper archives or insurance documents.www.iais.fraunhofer. The "handle-in-the-box" experts at the Fraunhofer Institute for Production Technology and Automation IPA are working on machine learning procedures The optimization of the robot-based »handle-in-the-box«, ie the automated separation of unordered work pieces, is the starting point of the »DeepGrasping« project, which was carried out together with the University of Stuttgart. Previous solutions use recognizable features and fixed recognition methods for object recognition. Now, the necessary algorithms (for object recognition, position estimation, gripping, manipulation) should be autonomously optimized. A neural network learns from a high number of simulated handles and continuously improves its process knowledge and thus also calculation times, success rate and process reliability of the handles. For companies seeking guidance In a confusing digitized world, the American market research institute Gartner has the right list every year. Gartner's top 10 strategic technology trends have the potential to significantly impact a company and its long-term plans. "IT leaders need to incorporate these technology trends into their innovation strategies or risk losing touch with those who do." The trends are dominated by two meta-topics: artificial intelligence and machine learning. Virtual and Augmented RealitiesAlthough the demand for virtual and augmented reality solutions, such as eyewear, Gartner analysts currently see little value added beyond the games and film industry. To change that, companies January 2019 Calendar Marathi need to develop real-world scenarios in which employees and customers benefit from insight into virtual reality (VR) or augmented reality (AR). This could be a training environment, for example, the visualization of customer wishes as in Ikea or extensive design projects.
Thus, the Digital Twin is actually a test environment that keeps real damage by switching away. Clearly believes that industrial designers, city planners and healthcare January 2019 Calendar Singapore professionals in particular will benefit from this development. Job TeaserData ProcessingThe cloud, where all information is collected and processed at a fixed point, is complemented by distributed data processing.
January 2019 Calendar SingaporeThis solves some problems that will not be solved in the years to come - regrettable as it may be - connectivity problems, low bandwidths, long waiting times. Gartner therefore recommends that companies incorporate edge computing into their IT architecture. Event driven action Business-related events should be described more quickly and in more detail through artificial intelligence, the Internet of Things, cloud computing, and in-memory data management. The culture of leaders would have to change, planners and strategists would have to adapt to this event-driven character in their way of working. IT SecurityThis year they were called WannaCry and NotPetya, they attacked corporate and personal computers and caused immense damage. An IT security infrastructure that can continually adapt to new threat scenarios while remaining transparent to developers will be (again) one of the major technological challenges of the coming year. Gartner has developed a proprietary methodology that the company calls Carta ("continuous adaptive risk and trust assessment"). These were the technology trends for 2016. For your guidance, we have listed the ten most important technology trends for the year 2016. Take a look to what we expect in terms of machine learning and artificial intelligence in 2018. A year ago, market research and consulting firm Gartner called artificial intelligence (AI), machine learning (ML), and conversational AI (CAI) systems Three key strategic technology trends for 2017.]] In May of this year, SAP introduced the SAP Leonardo Machine Learning Portfolio at SAPPHIRE Now in Orlando to showcase its role in the league of great innovators. Now is the time to look back at the recent developments in these three trends and to give an outlook on the potential of intelligent technologies.Trend 1: Machine Learning PlatformsDeep Learning, Neural Networks, and Natural Language Processing (Natural Language Processing) NLP) have given machine learning a new status in the company. Sophisticated algorithms, higher computational power and the availability of huge amounts of data make machines intelligent and can handle unstructured data such as images, text or spoken language - often at superhuman levels. In addition, deep learning is now stable enough to potentially establish machine learning as a standard commodity in the global economy. Companies looking for customized and customized solutions need an ML platform such as the Leonardo Machine Learning Foundation to combine pre-packaged and out-of-the-box January 2019 Calendar Singapore services into their own, intelligent applications.Trend 2: Intelligent applicationsIntelligent applications automate routine activities that employees in the enterprise need Hindering the past by spending time coping with value-added activities can provide valuable insights into structured and unstructured enterprise data.
One technology that combines both worlds is mixed reality, in which Gartner also sees great potential for the economy. Voice Assistants Today, millions of people are using digital January 2019 Calendar Kalnirnay communication platforms to communicate with friends, as well as with businesses and customers. These platforms will change and not only provide the framework for communication, but also engage in discussions. Just like Alexa, Siri or Echo, today, more and more machines will be communicating with users and handling orders independently.
January 2019 Calendar KalnirnayThe challenge will be to develop sports assistants who understand the user when he mumbles or speaks colloquial language and can answer him as casually and fluently as a real person. This is exactly what Google's artificial intelligence works on.BlockchainThe blockchain not only fascinates the financial world, it also awakens longings in completely different areas. Because it represents a departure from the centralized transaction system and can promote disruptive digital business models in established companies and start-ups, according to Gartner. The company sees great potential in technology, such as health care, manufacturing, politics and media, logistics and identity identification. However, the products associated with the blockchain will be unripe for another two to three years. Artificial Intelligence Platform Self-learning and autonomous systems are finding their way into all sorts of areas. Gartner expects this technology to remain a major field of action for technology buyers and sellers by 2020. "Artificial intelligence technologies are evolving rapidly and organizations will have to invest significantly in knowledge, processes and tools to successfully exploit these techniques," said Gartner vice president David Caerley. What constitutes a machine learning developer and what he does all day explains Damian Borth from the German Research Center for Artificial Intelligence.Intelligent Apps and Analysis Artificial intelligence will be found everywhere, and so that people can still come along with it, intelligent apps will be available to them. They become the mediators between the worlds of machines and people. According to Gartner, they have the potential to bring a whole new look to every work environment and every workplace. "Augmented analytics is a strategic growth area that uses machine learning to automate data processing and empower business, operational, and data scientists," said Caerley. How engineers will work in 2030, we asked major industry associations .Intelligent Products By the term intelligent things, the analyst firm understands products that can interact with their environment. These include the Internet of Things, drones, autonomous vehicles and robots. "Autonomous vehicles are currently operating in controlled environments, but by 2022 we may see them on some roads - albeit on controlled and strictly defined sections," predicts Caerley. However, for the next five years, the analyst suspects, will always need to be a driver in the car to take the wheel in case of doubt. During this time, the automakers will continue to develop the January 2019 Calendar Kalnirnay autonomous systems, the policy will work with them on the legal framework and all together will seek to increase the social acceptance for self-driving cars.Digitaler twinThe digital doppelgänger is a digital image of a real object. Especially in the internet of things these digital pictures are supposed to record how the actual product or process would respond to system changes.
"Characteristic sounds and vibration patterns are often the only clues for an optimal separation process or necessary readjustment," says von Enzberg. INTELLIGENT DISTRIBUTION Centrifuges play an important January 2019 Calendar Telugu role in the industrial production of foodstuffs. Until now, the experience, hearing and intuition of a machine have been optimally adjusted Operator required. Now, it has been possible to transfer this knowledge to an expert system using neural networks.
January 2019 Calendar TeluguFRAUNHOFER IEM25Complex sensors and intelligent data processingThe installation of sensors that make the drain technically more manageable, is complex and demanding, as they have to provide data of the machine continuously in the millisecond range, which additionally be measured at different places during the rotation. The research team at the Fraunhofer IEM has now mounted sensors not only on the housing and drainpipe, but also inside a rotating container - these can make and transmit up to 48,000 measurements per second. But the abundance of this data must also be processed quickly and intelligently, so that the centrifuge are controlled as real-time as possible can. »Aim of the intelligent data It's about understanding the perception and judgment of a human operator, "emphasizes von Enzberg. "Therefore, we rely on machine learning and have used neural networks and the number of data obtained to train one of our programmed systems. It can detect fault conditions and develop strategies for adjusting machine parameters to fine-tune the machine even during operation in fractions of a second. "This knowledge can also be applied to the handling of different centrifuges and tasks. This requires that the machines and systems are equipped with appropriate sensors and that the database is large enough. Once the learning process has been completed, centrifuges will in future also be able to work autonomously and remotely.www.iem.fraunhofer.de26 "MCube" microscopy system According to WHO estimates, around 214 million people worldwide were affected by malaria in 2015 - with approximately 438,000 deaths. The disease is caused by parasites of the genus Plasmodium, which can be detected by microscopic examination in blood smears. The microscopic examination, however, can be very time consuming if there are only a few exciters in the sample and a large number of fields of view are to be assessed manually. As part of a multidisciplinary project of the Fraunhofer Future Foundation, the Fraunhofer Institute for Integrated Circuits IIS is therefore developing a computer-aided microscopy system for the automatic recording of blood smears and detection of malaria pathogens based on Artificial Intelligence methods. Www.iis.fraunhofer.deTRENDS & PROJECTSView the Black Box Today's AI models and machine learning are large (gigabytes), complex - and thus energy hungry both execution. Consequently, the models can be executed on high-performance computers, but not on embedded devices, IoT devices or smartphones. The Fraunhofer Institute for Telecommunications, Heinrich Hertz Institute, HHI develops techniques to reduce the complexity of neural networks and to compress them without sacrificing performance . In machine learning in critical applications, methods are also developed to be able to study neural networks more deeply - for example, to verify that the solution path of the AI is meaningful and that it January 2019 Calendar Telugu comes to correct results on the right path: the so-called "black box" look .www.hhi. fraunhofer.de27 Optimized energy networks By 2020, thousands of kilometers of new grids are to be created in Germany in order to make use of renewable energies.
All of this is supposed to be a reliable way to control a computer or its software. But that will hardly work, who n They try to classify human intelligence algorithms with classical methods. They need January 2019 Calendar South Africa to take advantage of data-driven approaches such as deep learning. Impressive successes have been achieved here, especially when compared with classical logic-based systems. "Does not the hardware have its limits?" Keuper: Machines learn a wealth of information-driven data. The data mass required for this leads to the hitherto customary use of highendshared systems.
January 2019 Calendar South Africamemory Multi-GPU systems for the calculation of a midsize PARADIGIN CHANGE: DEEP LEARNING SUPERCOMPUTERNDespite a multitude of trend-setting developments, machine learning has to undergo a paradigm shift - because the current need for data and computing power to calculate learning models is growing faster than the quality of the calculated solutions. Janis Keuper from the Fraunhofer Institute for Industrial and Industrial Mathematics ITWM. FRAUNHOFER ITWM23Models needs several days. The maximum achievable computing power in a local system can hardly keep up with the demands of machine learning. That's why machine learning algorithms are facing a fundamental change: we need to switch to a distributed computation on heterogeneous high-performance computers, HPC for short.This requirement focuses on learning per se? Keuper: Exactly. The computational effort always relates to the actual learning process at HPC. If something is learned, the software could run behind on your phone. But learning, for example, requires the automotive industry, which requires a variety of algorithms for its autonomous vehicles: for the driver himself, to recognize traffic signs or pedestrians, and so on. These models must be pre-trained, increasingly on mainframes. At the FraunhoferITWM we are working on methods for better and simpler use of HPC for deep learning. A central problem here is the question of how the vast amount of data can actually "pass through" the actual billing process, as it were. We are working in the range of 10 to 15 or even 10 to 20 arithmetic operations. Therefore, we try to get the necessary data transport under control on almost all levels - from mathematical models that calculate the amount of data down to the communication protocols down to the hardware with which we transport This is also the subject of projects such as the »High Performance Deep Learning Framework«, which we carry out on behalf of the Federal Ministry of Education and Research (BMBF). www.itwm.fraunhofer.de / mlDr. Janis Keuper24In industrial practice, things are much more difficult than in the classroom: Whether in the chemical industry, the pharmaceutical industry, or the food industry: necessary separations of different substances are often considerably more complicated than the scholastic separation of solids and liquids with maximum adjustable fluency - besides, tens of thousands of liters have to be processed per hour. "As a rule, there are several phases of separation here. When processing raw milk, for example, milk, cream and various solid substances have to be separated cleanly, "explains Sebastianvon Enzberg of the Fraunhofer Institute for Design Technology Mechatronics." If separators are not set exactly and adjusted continuously, January 2019 Calendar South Africa quality losses and product damage can result. "The correct setting of the separators was geared to a long time Flair and hearing of the respective centrifuge experts - usually the manufacturer or machine operator.
If technology becomes standard in five years' time, we need to be prepared.In terms of digital innovation, we are now in the midst of rapid growth. All draw attention to ever-expanding networking and automation - using technologies such as the Internet of Things (IoT), Big Data, Blockchain, Machine Learning, and Blank January 2019 Calendar Artificial Intelligence. People, businesses, and organizations are revolutionizing their processes, their entire production, and their work environments.
Blank January 2019 CalendarThese trends and developments provide tremendous benefits in terms of efficiency and connectivity, but they also present users with ever-increasing challenges, such as cybersecurity. Because data volumes and data complexity are sky-rocketing. Some security engineers and analysts are increasingly overwhelmed by an exponential increase in the number of cyber threats. Potential attackers are finding it increasingly easy to make malicious attacks on their chosen targets - they can resort to a variety of publicly available hacking tools and, with appropriate expertise, use countless third-party computers as so-called "bots" to conceal their practices or gain unauthorized access. Digitization and the Connected Industry 4.0 provide the foundation for complex applications and new business processes - while providing attack surfaces for IT-based attacks of all kinds. New machine learning skills help improve early detection and prevent catastrophic consequences of cyber-damage. THE AI FIGHT AGAINST CYBER ATTACKS AND ANOMALIENFRAUNHOFER AISEC21New Security through AI To meet the dangers of the networked world, it is becoming increasingly important to develop innovative security technologies. These must help to analyze and, in addition, understand potential threats and malicious behavior in cyberspace more efficiently - only in this way can safer systems and adequate protection mechanisms be provided in good time. To this end, the Fraunhofer Institute for Applied and Integrated Security AISEC uses intelligent technologies of cognitive security: Security researchers use complex artificial intelligence algorithms to continuously improve their current IT systems in both software and hardware security. By leveraging machine learning and neural network techniques, emerging cybersecurity systems can continually learn from data to dynamically adapt to changes in operational scenarios, reliably uncovering anomalies, for example. Cyber Attack Detection, Analysis, and Assessment Security engineers can use artificial intelligence to accomplish their daily tasks in this manner both on a large scale and in high complexity work. To this end, Fraunhofer AISEC designs and develops scalable security solutions for the detection, analysis and rapid assessment of attack activities on the Internet and offers direct solutions, new protection mechanisms and best-practice applications in the area of machine learning. Close cooperation and constant exchange with other renowned security expert concerns for the necessary development of AI-based security technologies lead to tailor-made solutions for the individual Blank January 2019 Calendar requirements of all customers. Machine learning has become a necessity since our demands on IT systems have increased immensely Think about self-driving cars that need to properly assess traffic situations, speech recognition, or "recognizing" the content of an image.
Neither temperatures, vibrations, mechanical movements nor radiations are allowed to act from outside. This requires very low temperatures, vibration-free suspensions and sometimes laser. That sounds January 2019 Calendar Cute very expensive. What Advantages Do Quantum Computers Have Over Classic Computers? Prof. Dr. Christian Bauckhage18Bauckhage: A qubit can have two states. Two qubits can have a total of four states. Three qubitsight states, four 16s and so on.
January 2019 Calendar CuteThis is similar in digital computers. Four bits can represent a total of 16 numbers - but only one of these 16 numbers at a time. However, four quantum bits represent the 16 numbers simultaneously. If understood mathematically, one is able to solve exponentially difficult problems in so-called polynomial times. The classic example is encryption: if the encryption numbers are large enough, a digital computer would take billions of years to crack an encryption, because it has to go through an incredible number of combinations bit by bit. A quantum computer, on the other hand, tests all of these combinations simultaneously. Instead of billions of years, this calculation takes only a few seconds. Quantum computing will change everything. No banking transaction over the internet will be more secure. You see a potential for danger? "Bauckhage: The potential danger is not that we can use quantum computers, but that our encryption algorithms may not be sufficient in the future In machine learning, algorithms solve problems by evaluating a great deal of data. Will quantum computers thus accelerate this process? Bauckhage: Machine learning is statistics. The parameters of statistical models are optimally adapted to data. On classical computers, these optimization problems are cumbersome and expensive. Thanks to strong, conventional computers we have nevertheless made great progress in the field. Quantum computers, however, are predestined to solve these optimization problems very quickly. Within a short time, computers will learn processes for which they need FRAUNHOFER IAIS19 today. Where isolated special programs are needed today, for example, for image recognition, for speech recognition, for process planning, a single program will soon be enough. Today's condition can be multiplied by a thousand. Much more complex problems are solved and then sold. We will see dramatic advances in artificial intelligence. Quantum computers will initially be reserved for large companies. These in turn sell problem solutions as a service based on their systems? Bauckhage: Exactly. And that will be a big challenge for us. For example, we will be experiencing problems in computer science education and the IT labor market. For people who have studied theoretical physics, the changes will be good, for everyone else it will be difficult. Because quantum computation requires other algorithms and a very complex mathematics. So far, there are hardly any people in Germany who are adequately trained to work with technology. Are there already initiatives in Germany dealing with quantum computing? Bauckhage: In terms of research, January 2019 Calendar Cute Germany has always been in a good position, even in this case. For example, the Federal Ministry of Education and Research for the Promotion of Quantum Technologies in Germany has decided to set up the national initiative "Quantum Technology Fundamentals and Applications (QUTEGA)". Research at the Fraunhofer-Gesellschaft also plays a major role here. Personally, I deal with the topic of quantum computing for machine learning.
These are qualities of people who have no advantage in medical diagnoses. Computers help people to make safer January 2019 Calendar Templates decisions of large amounts of data. They process information much faster, more reproducibly, and most of the time demonstrably better when it comes to simple cognitive tasks. In this sense, computers help doctors to bring the positive human qualities into everyday clinical practice. January 2019 Calendar Templates For example, by allowing the AI to do monotonous work and give the doctor time to listen to patients with empathy and orientation based on his broad medical knowledge and compassionate experience in a psychologically distressing situation "When it comes to life and death, AI has no business." Wrong: Especially where quick decisions are needed, KIverwertigen helps. Wherever the informational situation is complex, where there is a great deal of time pressure or where the general conditions are unfavorable, most human errors occur. An AI system that serves as a second pair of eyes and indicates that something has been overlooked is very useful. It sorts the information according to importance and supports the doctor. Www.mevis.fraunhofer.de 16COMPANTERCOMPUTER: DRAMATIC PROGRESS IN ARTIFICIAL INTELLIGENCE Quantum computers will soon be on everyone's lips. What is different from conventional computers? Bauckhage: In conventional digital computers, the minimum unit of information representation is the bit, which has either the value 0 or 1. In a quantum computer, on the other hand, individual ones become Electrons are manipulated-and the calculations are based on the principles of quantum mechanics. A so-called quantum bit is 0 and 1 at the same time. It does not commit itself until mapped. As long as no physical measurement is performed on a qubit system, one can only say with a certain probability whether it is 0 or 1. That sounds bizarre and in no way matches our everyday experience. But nature at the subatomic level works that way. We have to rely on mathematics, which is extremely complex in this case. But since the 1930s, humanity has been able to describe these processes mathematically. How far is research today? Are quantum computers being used? What sounds like science fiction may already be everyday in a few years. Initial companies have already developed quantum computer models and are working hard to bring them to market. Prof. Dr. Christian Bauckhage of the Fraunhofer Institute for Intelligent Analysis and Information Systems IAIS explains the background.FRAUNHOFER IAIS17Bauckhage: A Canadian company producing quantum computers has sold it to NASA, the NSA and Google for $ 15 million. VW Research leased these systems following the paradigm of adiabatic quantum computation. At the same time, IBM has its own quantum computers, which in turn follow the quantum gate computing paradigm. This is essentially the attempt to transfer logic circuits of digital computers - that is, "AND", "OR" and "NOT" - into quantum mechanics. January 2019 Calendar Templates Intel and Microsoft also work on such models. Google announced a quantum computer with 49 quantum bits for the end of 2017, which achieved the so-called quantum supremacy, so much faster than a classical computer.
In addition, systems in the field of autonomous driving, chat bots, are particularly visible to the public and user interfaces - for example, the greatly improved ability of computers to handle speech.What is the current state of research January 2019 Calendar Printable on AI? Wrobel: In recent years, we have been limited in the possibilities of very parameter rich, deep neural networks that can actually be trained We are far from the end of development. January 2019 Calendar Printable It will be important in the next few years to reconnect with other knowledge-based techniques in the field of AI. This is a focal point of research, which we are also focusing on at Fraunhofer. "In the next few years, it will be important to re-integrate other knowledge-based techniques in the area of AI." INTERVIEW13 In medicine, for example However, in the industry, a small business would not have millions of posts from a video or image service, but only 500 or 1000 individual classifications made in-house. This is going to be a big and important development. What do you think companies should do best in AI? Wrobel: Of course, companies should look at the current opportunities of AI and look at examples - and think about it: how can we take advantage of these opportunities? This must be done from the very top, because it affects the basic design of your own business model and your own positioning. I can not become a company using Artificial Intelligence unless I'm also a data-driven, data-driven, digitized company. If the data is the key resource I want to work with, then that data must be secure. If they are even an asset, a trump card I want to be in the market with, then I have to consider: Who can I share this data with, with whom do I build these business models? Which data can and may I collect? How is cybersecurity ordered? To that extent the simple message: "Start now". Invest now, build up your skills, find the right partner. Therefore, at Fraunhofer, we also support the support of KI in our advice on digitization or big data - because these questions are closely related. Www.iais.fraunhofer.de 14 »AI creates artificial Brains. "We do not build artificial brains or artificial people. Neither does an aircraft manufacturer try to build an artificial bird. He just wants to construct something that flies. We build machines that do elementary cognitive tasks that require intelligence. Such machines or mechanisms have already reached our everyday lives: there are devices that understand car steering, translate our language or translate it simultaneously. But even if we teach a machine some ability to be better at it than human beings - such as lip reading - one does not end up talking about an intelligent device. "AI system decisions are more neutral and objective." That's not right. AIs have no intrinsic motivation, no self-interest to be neutral or objective. They depend on the training material and the intention of the trainer. Finally, the machine is trained to process an input and deliver an output. An example from the medical field: If a machine is trained to detect malignant changes in the liver in CT scans, it is not capable of malignant changes in the spleen, kidney, or lung Find. We need people to review and take responsibility for machine-based decisions. ORDER: MYTHBUSTINGDr. Hans January 2019 Calendar Printable My and Dr. Markus Wenzel from the Fraunhofer Institute for Image-Assisted Medicine MEVIS puts myths and clichés to artificial intelligence to the test.FRAUNHOFER MEVIS15 »KI makes medicine cold and impersonal.« On the contrary. Nobody wants to lose the so-called "human factor" in medicine. But what is this human? For example, volatility, ignorance, misjudgment.