New York, April 19, 2021 (GLOBE NEWSWIRE) -- Reportlinker.com announces the release of the report "Artificial Intelligence In Medical Diagnostics Market Research Report by Technology, by Application - Global Forecast to 2025 - Cumulative Impact of COVID-19" - https://www.reportlinker.com/p06063085/?utm_source=GNW

Market Statistics:The report provides market sizing and forecast across five major currencies - USD, EUR GBP, JPY, and AUD. This helps organization leaders make better decisions when currency exchange data is readily available.

1. The Global Artificial Intelligence In Medical Diagnostics Market is expected to grow from USD 683.66 Million in 2020 to USD 1,414.56 Million by the end of 2025.2. The Global Artificial Intelligence In Medical Diagnostics Market is expected to grow from EUR 599.45 Million in 2020 to EUR 1,240.31 Million by the end of 2025.3. The Global Artificial Intelligence In Medical Diagnostics Market is expected to grow from GBP 532.91 Million in 2020 to GBP 1,102.64 Million by the end of 2025.4. The Global Artificial Intelligence In Medical Diagnostics Market is expected to grow from JPY 72,964.67 Million in 2020 to JPY 150,969.39 Million by the end of 2025.5. The Global Artificial Intelligence In Medical Diagnostics Market is expected to grow from AUD 992.77 Million in 2020 to AUD 2,054.12 Million by the end of 2025.

Market Segmentation & Coverage:This research report categorizes the Artificial Intelligence In Medical Diagnostics to forecast the revenues and analyze the trends in each of the following sub-markets:

Based on Technology, the Artificial Intelligence In Medical Diagnostics Market studied across Computed Tomography, Magnetic Resonance Imaging, Neuroradiology, and Radiology.

Based on Application, the Artificial Intelligence In Medical Diagnostics Market studied across Data Mining, Data Storage, Follow-up Plan, Image Acquisition, and Processing to Aided Reporting.

Based on Geography, the Artificial Intelligence In Medical Diagnostics Market studied across Americas, Asia-Pacific, and Europe, Middle East & Africa. The Americas region surveyed across Argentina, Brazil, Canada, Mexico, and United States. The Asia-Pacific region surveyed across Australia, China, India, Indonesia, Japan, Malaysia, Philippines, South Korea, and Thailand. The Europe, Middle East & Africa region surveyed across France, Germany, Italy, Netherlands, Qatar, Russia, Saudi Arabia, South Africa, Spain, United Arab Emirates, and United Kingdom.

Company Usability Profiles:The report deeply explores the recent significant developments by the leading vendors and innovation profiles in the Global Artificial Intelligence In Medical Diagnostics Market including Aidoc Medical Ltd., Arterys Inc., Butterfly Network Inc., Caption Health, Inc., Enlitic, Inc., Freenome Holdings, Inc., Gauss Surgical Inc., GE Healthcare Inc., General Vision, Inc., Google Inc., Health Fidelity, Inc., IBM Corporation, IBM Corporation, IDx Technologies Inc., Imagen Technologies, Inc., Intel Corporation, Johnson & Johnson Services, Inc., MaxQ AI, Ltd, Medtronic PLC, Microsoft Corporation, Qure.ai, Riverain Technologies, Riverain Technologies, Siemens Healthineers AG, SigTuple Technologies Private Limited, VUNO Inc, and Zebra Medical Vision Ltd.

Cumulative Impact of COVID-19:COVID-19 is an incomparable global public health emergency that has affected almost every industry, so for and, the long-term effects projected to impact the industry growth during the forecast period. Our ongoing research amplifies our research framework to ensure the inclusion of underlaying COVID-19 issues and potential paths forward. The report is delivering insights on COVID-19 considering the changes in consumer behavior and demand, purchasing patterns, re-routing of the supply chain, dynamics of current market forces, and the significant interventions of governments. The updated study provides insights, analysis, estimations, and forecast, considering the COVID-19 impact on the market.

FPNV Positioning Matrix:The FPNV Positioning Matrix evaluates and categorizes the vendors in the Artificial Intelligence In Medical Diagnostics Market on the basis of Business Strategy (Business Growth, Industry Coverage, Financial Viability, and Channel Support) and Product Satisfaction (Value for Money, Ease of Use, Product Features, and Customer Support) that aids businesses in better decision making and understanding the competitive landscape.

Competitive Strategic Window:The Competitive Strategic Window analyses the competitive landscape in terms of markets, applications, and geographies. The Competitive Strategic Window helps the vendor define an alignment or fit between their capabilities and opportunities for future growth prospects. During a forecast period, it defines the optimal or favorable fit for the vendors to adopt successive merger and acquisition strategies, geography expansion, research & development, and new product introduction strategies to execute further business expansion and growth.

The report provides insights on the following pointers:1. Market Penetration: Provides comprehensive information on the market offered by the key players2. Market Development: Provides in-depth information about lucrative emerging markets and analyzes the markets3. Market Diversification: Provides detailed information about new product launches, untapped geographies, recent developments, and investments4. Competitive Assessment & Intelligence: Provides an exhaustive assessment of market shares, strategies, products, and manufacturing capabilities of the leading players5. Product Development & Innovation: Provides intelligent insights on future technologies, R&D activities, and new product developments

The report answers questions such as:1. What is the market size and forecast of the Global Artificial Intelligence In Medical Diagnostics Market?2. What are the inhibiting factors and impact of COVID-19 shaping the Global Artificial Intelligence In Medical Diagnostics Market during the forecast period?3. Which are the products/segments/applications/areas to invest in over the forecast period in the Global Artificial Intelligence In Medical Diagnostics Market?4. What is the competitive strategic window for opportunities in the Global Artificial Intelligence In Medical Diagnostics Market?5. What are the technology trends and regulatory frameworks in the Global Artificial Intelligence In Medical Diagnostics Market?6. What are the modes and strategic moves considered suitable for entering the Global Artificial Intelligence In Medical Diagnostics Market?Read the full report: https://www.reportlinker.com/p06063085/?utm_source=GNW

About ReportlinkerReportLinker is an award-winning market research solution. Reportlinker finds and organizes the latest industry data so you get all the market research you need - instantly, in one place.

__________________________

Excerpt from:
Artificial Intelligence In Medical Diagnostics Market Research Report by Technology, by Application - Global Forecast to 2025 - Cumulative Impact of...

A few months ago, Generative Pre-Trained Transformer-3, or GPT-3, the biggest artificial intelligence (AI) model in history and the most powerful language model ever, was launched with much fanfare by OpenAI, a San Francisco-based AI lab. Over the last few years, one of the biggest trends in natural language processing (NLP) has been the increasing size of language models (LMs), as measured by the size of training data and the number of parameters. The 2018-released BERT, which was then considered the best-in-class NLP model, was trained on a dataset of 3 billion words. The XLNet model that outperformed BERT was based on a training set of 32 billion words. Shortly thereafter, GPT-2 was trained on a dataset of 40 billion words. Dwarfing all these, GPT-3 was trained on a weighted dataset of roughly 500 billion words. GPT-2 had only 1.5 billion parameters, while GPT-3 has 175 billion.

A 2018 analysis led by Dario Amodei and Danny Hernandez of OpenAI revealed that the amount of compute used in various large AI training models had been doubling every 3.4 months since 2012, a wild deviation from the 24 months of Moores Law and accounting for a 300,000-fold increase. GPT-3 is just the latest embodiment of this exponential trajectory. In todays deep-learning centric paradigm, institutions around the world seem in competition to produce ever larger AI models with bigger datasets and greater computation power.

The influential paper, On the Dangers of Stochastic Parrots: Can Language Models Be Too Big? by Timnit Gebru and others, was one of the first to highlight the environmental cost of the ballooning size of training datasets. In a 2019 study, Energy and Policy Considerations for Deep Learning in NLP, Emma Strubell, Ananya Ganesh and Andrew McCallum of University of Massachusetts, Amherst estimated that while the average American generates 36,156 pounds of carbon dioxide emissions in a year, training a single deep-learning model can generate up to 626,155 pounds of emissionsroughly equal to the carbon footprint of 125 round-trip flights between New York and Beijing.

Neural networks carry out a lengthy set of mathematical operations for each piece of training data. Larger datasets therefore translate to soaring computing and energy requirements. Another factor driving AIs massive energy draw is the extensive experimentation and tuning required to develop a model. Machine learning today remains largely an exercise in trial and error. Deploying AI models in real-world settingsa process known as inferenceconsumes even more energy than training does. It is estimated that 80-90% of the cost of a neural network is on inference rather than training.

Payal Dhar in her Nature Machine Intelligence article, The Carbon Impact of Artificial Intelligence, captures the irony of this situation. On one hand, AI can surely help reduce the effects of our climate crisis: By way of smart grid designs, for example, and by developing low-emission infrastructure and modelling climate-change predictions. On the other hand, AI is itself a significant emitter of carbon. How can green AI, or AI that yields novel results without increasing computational cost (and ideally reducing it), be developed?

No doubt, industry and academia have to promote research of more computationally efficient algorithms, as well as hardware that requires less energy. The software authors should report training time and computational resources used to develop a model. This will enable a direct comparison across models. But we need to have far more significant pointers to guide the future of AI. A strong contender for this role is the human brain.

Neuromorphic Computing is an emerging field in technology that understands the actual processes of our brain and uses this knowledge to make computers think and process inputs more like human minds do. For example, our brain executes its multi-pronged activities by using just 20 watts of energy. On the other hand, a supercomputer that is not as versatile as a human brain consumes more than 5 megawatts, which is 250,000 times more power than our brain does. Many challenges that AI is attempting to solve today have already been solved by our minds over 300-plus millennia of human evolution. Our brain is an excellent example of few-shot learning, even from very small datasets. By understanding brain functions, AI can use that knowledge as an inspiration or as validation. AI need not reinvent the wheel.

Computational neuroscience, a field of study in which mathematical tools and theories are used to investigate brain function at an individual neuron level, has given us lots of new knowledge on the human brain. According to V. Srinivasa Chakravarthy, author of Demystifying the Brain: A Computational Approach, This new field has helped unearth the fundamental principles of brain function. It has given us the right metaphor, a precise and appropriate mathematical language which can describe brains operation." The mathematical language of Computational Neuroscience makes it very palatable for AI practitioners.

AI has a significant role in building the world of tomorrow. But AI cannot afford to falter on its environment-friendly credentials. Go back to nature is the oft-repeated mantra for eco-friendly solutions. In similar vein, to build AI systems that leave a far smaller carbon footprint, one must go back to one of the most profound creations of naturethe human brain.

Biju Dominic is the chief evangelist, Fractal Analytics, and chairman, FinalMile Consulting

Subscribe to Mint Newsletters

* Enter a valid email

* Thank you for subscribing to our newsletter.

See the original post here:
The Achilles heel of AI might be its big carbon footprint - Mint

The Covid-19 pandemic, which since the beginning of last year has affected the entire planet with tragic effects and, due to inertial pressure, seems destined to continue for most of the current year, has not only had very severe effects in terms of general mortality (over 2.5 million deaths to date), but has also generated catastrophic economic and social consequences in many countries of the world, starting with Italy.

As soon as the pandemic crisis is finally over from the health viewpoint, the governments of all affected countries shall necessarily find the right instruments to set the economy again into motion by seeking new opportunities for development and recovery which, if properly seized and implemented, in the next decade could make us live in a better world than the one we left behind.

Last December a think tank of authoritative economists, co-chaired by Professor Mario Draghi, namely the Group of Thirty, published the results of a study entitled Reviving and Restructuring the Corporate Sector Post-Covid: Designing Public Policy Interventions.

The study starts from the observation that the epidemic has dramatically changed business paradigms worldwide, triggering a solvency crisis for companies in many countries.

This is now a structural crisis that requires politicians and governments to find financial support instruments for companies that can restart production and development.

The path indicated by the Group of Thirty is complex, but it starts from the need for politicians to immediately provide proactive support to the private sector companies which have already demonstrate actual resilience abilities, so that the scarce public resources are directed towards sectors that can recover quickly and drive the global economys relaunch.

In this regard, the Group of Thirty recommends that policymakers should carefully consider the allocation of resourceswhich should not be wasted on subsidies to sectors doomed to failure, but rather allocated to sectors that can recover from the crisis quickly and in a socially and economically acceptable manner.

The first sectors identified by the Group of Thirty as deserving immediate support because of their potential to drive recovery are digitalisation and the green economy.

It is therefore no coincidence that in the programme of the Italian government now led by Professor Draghi, the digital revolution and the green economy are top priorities for the strategic interventions to be implemented with the European Recovery Plan funds.

If appropriately matched by public support for smart, intelligent and effective forms of mutual interaction, digitalisation and the green economy can be decisive not only in the post-pandemic recovery, but can also deliver to our children a better, more efficient and healthier world than the one in which we lived before the coronavirus devastated our lives.

The pandemic, however, has hit the whole world regardless of borders, political tensions, regional problems, wars or riots.

It has affected the West and the East, the North and the South, without discrimination between rich and poor. The end of the crisis could therefore provide to politicians the chance for a new start, also under the banner of new forms of solidarity and international cooperation which, besides the Covid-19, will wipe away old-fashioned and anti-cyclical barriers that could severely damage the construction of a better world.

In this regard, it is no coincidence that Pope Francis first international commitment for the year 2021 was to visit the unfortunate Iraq not only to bring solidarity to the Christians persecuted and exterminated by the Caliphate, but above all to build a bridge towards Shiite and Sunni Muslims in the name of their common descent from Abraham.

The Popes meeting with Ayatollah Al Sistani, the highest religious figure in the Shiite world, shows that the possibility of opening up channels of dialogue between political and religious entities separated by centuries of enmity is concrete and feasible, even in view of the post-pandemic renaissance.

Pope Francis message should hopefully also reach the new Catholic President of the United States who, a few weeks after taking office at the White House, showed- in his initial foreign policy moves a superpowers aggressive and revanchist spirit that probably the Americans (and not only them) had hoped would be left behind with the end of Donald Trumps era.

The opening up to Iran matched by bombings of Iranian militias in Iraq, as well as chill in the relations with Saudi Arabia, and unmotivated aggressiveness towards China which has indeed shown the world it has been the first to emerge from the pandemic and has taken on the health support of many African countries are all moves that do not bode well for the search for realistic models of peaceful coexistence on the part of the worlds leading power, namely the United States.

If the worlds recovery from the pandemic is to be driven by science, as hoped by the Group of Thirty, it is precisely in this field that international collaboration should be closer and more effective (as has been the case in the research, production and distribution of vaccines).

A fundamental contribution to scientific progress will certainly come from progress in the field of Artificial Intelligence, a tool designed to support human intelligence, which will be able to accelerate and improve the processes of widespread digitalisation hoped for by many governments, starting with Italys, in the drive for productive recovery.

In the field of Artificial Intelligence, as in vaccine research, there should be no excessive room for the isolationist tendencies that have always damaged science and encouraged illegal espionage.

Electricity was discovered by Edison, but no one could keep it within the United States borders.

Industry has always outstripped politics in its ability to talk (and do business) across borders.

Yet, on March 1, the National Security Commission on Artificial Intelligence, established by President Trump two years ago, published its final report in which it essentially suggested that the President and Congress should use artificial intelligence research as a tool for surrogate warfare against China.

The National Security Commissions report reads as follows: We must engage in competition on artificial intelligence Competition will foster innovation and we must work with our partners to foster progress in this field as in the vaccine sector But we must win the Artificial Intelligence competition by intensifying the strategic confrontation with China. Chinas plans, resources and progress should be of great concern to all Americans. China is second to none in Artificial Intelligence and is even a leader in some of its applications. We recommend that Chinas ambition to overtake the United States in Artificial Intelligence research and become the leader in this field over the next decade be taken seriously.

Therefore, in the words and recommendations of these scientists, scientific progress should be instrumental to the competition for ranking first geostrategically.

Fortunately, serious scientists all over the world cooperate in common research much more than their governments might like, and the same holds true for the companies that are looking for work and growth opportunities even beyond the borders liked by politicians.

Let us take the case of research and development in renewable energy, a fundamental link in the green economy which, according to the suggestions of the Group of Thirty and the European and Italian Recovery projects, should receive public support and drive the economic recovery.

While the American dream of both Trump and Biden is to create a barbed wire fence around China, Europe and Italy have understood that they can and must cooperate with the Eastern giant, starting with the search for clean energy from wind, sun and sea.

Also thanks to the personal commitment of the young Chinese Minister for Energy Resources, Lu Hao, who a few months ago, at the inauguration of the Chinese Expo for Maritime Economy in Shenzhen, stated that China intended to promote the creation of a new development model that would make it possible to understand and manage the dialectic between the protection of the marine ecosystem and the use of the sea as an energy source, in recent weeks the foundations have been laid for collaboration in marine energy research and production between the Italian Eldor Corporation, supported by the International World Group, and the National Ocean Technology Centre in Shenzhen, through the development of devices to obtain energy from wave motion and the hydrogen contained in seawater. If these projects are adequately supported by the governments of Italy, Europe and China, they will provide a fundamental contribution to getting the world out of the crisis quickly and effectively.

With all due respect to those across the Atlantic who have not yet realised that the pandemic crisis also calls for a smart redefinition of the economic frontiers of geopolitics.

Related

Read this article:
Artificial intelligence and Renewables: The new frontiers of geopolitics during and after the pandemic - Modern Diplomacy

Our technology is conversational AI. Its basically composed of speech recognition technology that we have that is able to take the audio of your speech in a very noisy environment, said Hi Auto Chief Technical Officer Eyal Shapira.

The company specializes in voice recognition software used in cars and smartphones but has now moved their technology to the drive-thru with conversational artificial intelligence. The technology is able to extract your voice from traffic or other people talking in the car that could otherwise make it difficult to understand what a customer is ordering. The second half of the technology is understanding natural language and is able to get the meaning of what customers want exactly.

Doran said the Englewood location has been significantly impacted by the staffing hardships and would be a good location to adequately test the technology.

Its become increasingly difficult to have people want to work in restaurants for a variety of reasons. The obvious one is the pandemic and potential exposure and having to wear a face mask for eight to nine hours a day is another concern for a lot of people, he said.

With people still using caution when outside more people have opted for drive-thru restaurants to limit their interaction with people inside of businesses which can increase the wait time for customers. Number one expectation of customers when they enter a drive-thru is speed of service. So I viewed this as an opportunity to potentially address that issue, Doran said.

Implementing the technology wont cut hours or payroll for the location and if the employees and customers respond well to the technology Doran said they have plans to use it at at least four more locations.

Read the original here:
Lee's Famous Recipe using artificial intelligence at drive-thru to combat pandemic induced issues - dayton.com

On the opening day of Industrial Internet of Things (IIoT) platform provider Advantechs online conference, company representatives and other industry experts gathered to discuss new developments on the horizon for IIoT, artificial intelligence (AI), and industrial networking. In particular, many sessions focused on the hurdles that still remain if IIoT and associated Industry 4.0 technologies are to see ubiquitous adoption in the future.

The Advantech Connect conference continues online through May 6.

Perhaps the greatest take-away from the first day of the event was that, while the real bedrock of value provided by IIoT is to be found in the data it generates, nothing can be attained from it unless that data is effectively gathered, communicated, and analyzed. As such, several speakers spotlighted burgeoning technologies such as 5G wireless connectivity, intelligent sensors, and AI as the most consequential industry trends going forward. Through the improvements these technologies enable in data gathering, transmission, and analytics, Advantech envisions industry moving beyond IIoT and toward an Artificial Intelligence of Things (AIoT) that allows cloud-delivered applications to make real-time, autonomous decisions at the device level. Within this framework, cloud-based AI trained on large amounts of data can provide industry operators a means of more easily extracting value from their IIoT infrastructure in exchange for furnishing AIoT platforms with the datasets necessary to continue expanding their capabilities.

Allan Yang, chief technology officer at Advantech, stressed the need for a platform approach if AIoT is to be realized in a timely and cost-effective manner. AIoT is cross-disciplinary. It requires edge computing, cloud platforms, data know-how, and domain expertise in many specific areas. No one company can do this alone successfully. However, we have seen many companies that are still trying to build their essential technology modules in-house, rather than adopting a platform approach, he said. This takes a lot of time and involves a lot of trial and error. We strongly encourage all companies, regardless of their size, to evaluate the possibility of collaborating or engaging in a partnership to speed up adoption.

The Future of IIoT

The Advantech event also explored why IIoT adoption rates have not yet met projected expectations, with Dirk Finstel, deputy managing director at Advantech Europe, noting that although 50 billion IIoT devices were expected to be in operation by 2020, only 8.5 billion have been deployed in reality. According to Finstel, much of this can be attributed to shortcomings in the associated infrastructure needed to make large-scale IIoT a reality. He believes that the high speed and bandwidth capacity of 5G networking will improve the feasibility of many IIoT technologies that rely on cloud computing in the near future.

Advances in edge computing are also expected to play a larger role in IIoT deployments by easing the burden of sending large quantities of data in and of out of plants via cloud computing applications, said Jerry OGorman, associate vice president at Advantech North America. Not only does OGorman see edge computing reducing costs and accelerating adoption, but by extending cloud-native software to the edge, latency can be reduced and less bandwidth will be required for data transmission. In fact, he estimated that by extending cloud-native software to the edge, up to 75% of data generated may never need to be sent to the cloud.

He also noted how Software as a Service (SaaS) models are likely to grow in prominence as 5G allows complex applications to be rapidly delivered to the edge. OGorman perceives that this could greatly reduce costs for end-users, making increasingly sophisticated AIoT applications easily accessible even to small-and-medium sized enterprises.

Business considerations

Though AI promises to offer impressive new functionalities, end-users shouldnt expect it to solve all issues surrounding IIoT deployment and integration, said William Webb, author of The Internet of Things Myth, during his presentation at the Advantech event.

Theres a number of promising new developments in this field, but they need to be treated with caution and used in the right way. AI only works when youve got the data in the first place, and that means it can only enhance an IIoT system thats already there and working well, Webb said. Until youve got an IIoT system in place delivering all of the data, you cant really use AI to make sense of that data.

According to Webb, approaching IIoT projects with an eye toward harmoniously adjusting overall business processes may be the best way to ensure success. In numerous early IIoT technology deployments, it was not uncommon for operators to put new systems in place without fully realizing the degree to which they would need to alter their overall operations to efficiently act on insights derived from their data, Webb noted. For example, even when equipment had been outfitted with IIoT technology to allow failures to be predicted in advance, this information could only be used to yield productivity gains once new processes were designed to efficiently allocate labor to maintenance on machines that needed it and redirect it to other valuable activities when they didnt. So, while predictive maintenance is more efficient in theory, without proper systems support, fixed and regular maintenance schedules are more simplistic and easier to keep to in practice.

Of course, operators are shaking out these kinks, and predictive maintenance is now one of the most common applications for IIoT technology. Still, Webb stressed that it is challenges like these that highlight the importance of viewing IIoT projects not only as technological installations, but initiatives that also require cultural, workforce, and business-oriented changes within an organization.

Access registration for future Advantech Connect sessions here.

Here is the original post:
Advantech and the Artificial Intelligence of Things - Automation World

MOL's 300,000 dwt Brasil Maru bulk carrier (Mitsui O.S. K. Lines)

By The Maritime Executive 02-10-2021 05:39:48

Efforts are progressing to harness emerging technologies to improve the efficiency of shipping operations. Japans Mitsui O.S.K. Lines announced that it is expanding its efforts with artificial intelligence to achieve greater efficiency with routing which will also contribute to lower emissions from their ships.

Building on a partnership that began in 2019, MOL is working with Bearing, a Silicon Valley-based AI technology startup, to improve efficiencies within the maritime industry. Together the two companies are developing a range of products that combine MOL's maritime expertise and Bearing's AI technology infrastructure.

Bearing, according to MOL, is building technologies using highly-accurate ship performance models built off of a diverse set of real-world data points. These AI-powered models with some historical voyage data for certain vessels such as vessel speed, trim, main engine operation, weather, and sea condition allow Bearing to predict metrics like fuel consumption with state-of-the-art accuracy even without vessels' design parameters.

Through various trials and intensive discussions concerning ship modeling, MOL announced that it has developed an AI-powered Smart Routing Engine. This application automatically analyzes multiple potential routes for a given voyage and recommends prudent, efficient routing through the use of optimal main engine output and propeller RPM profiles.

MOL says that it continuously monitors the condition of its fleet to ensure optimum operational efficiency which is being further aided by combining the technologies of Bearing as well as other existing and new solutions. Through the addition of AI technology to the existing voyage routing systems, MOL expects that it will be able to further enhance the operations of its fleet which currently numbers approximately 800 ships in operation.

MOL says that it understands the transformative potential of AI and looks forward to leveraging Bearings AI expertise and background in building scalable AI technology products to further advance operating efficiencies.

Follow this link:
Artificial Intelligence to Improve the Shipping Industry's Efficiency - The Maritime Executive

Stockholm, Sweden, Feb. 10, 2021 (GLOBE NEWSWIRE) -- Logical Clocks announces three new research projects part of the European Union (EU) Horizon 2020 research and innovation programme that will benefit from Hopsworks artificial intelligence (AI) capabilities to scale deep learning and enhance research focused on understanding environmental changes and improving healthcare in Europe. Hopsworks is the worlds first and most advanced managed Feature Store with an end-to-end AI platform for the development and operation of AI applications at scale.

The European Union leads the world when it comes to leveraging AI for the benefit of the environment and public health comments Jim Dowling, CEO at Logical Clocks and Associate Professor at KTH Royal Institute of Technology in Sweden. Research is part of our DNA and we are proud to be one of the few AI companies leading projects that will ultimately enhance quality of life, not just in the European Union, but around the world.

AI Applications to Improve HealthcareThe Human Exposome Assessment Platform (HEAP) is building a research platform, leveraging AI capabilities, to reveal the influence of environmental factors on human health, such as the link between airborne particles and predisposition to late-onset disease such as cancer. The project received 11 million funding from the European Union for 11 partners from 6 European countries to combine machine learning with computational statistics and develop powerful statistical modelling tools. With Hopsworks metadata mechanisms, which makes large volumes of data easily searchable, accessible and shareable, the HEAP platform will not only unlock new insights but it will also facilitate sharing data in a secure environment, becoming an open resource for the research communities as well as policy-makers across the world.

AI Applications to Predict Climate ChangesThe DeepCube project tackles, through AI, urgent problems caused by climate change in Europe and the whole Mediterranean region, such as forecasting of localized extreme drought and deadly heat impacts in Africa. The project is part of a consortium formed by 9 organizations from 6 European countries that will combine cutting-edge technologies, such as the Hopsworks platform for machine learning, the Earth System Data Cube, and an advanced visualization tool, to extract meaningful information from a large volume of data and to develop data-driven AI models. Funded with 4 million million by the European Union, the project will develop AI applications by extracting extract data from the Copernicus Earth Observation programme which already produces annually more than 3 petabytes of free, open and high quality data from satellites and from non-conventional data sources, such as social network data, industry-specific data, and sensor data.

AI Applications to Improve Food Security and Navigation SafetyThe ExtremeEarth project focuses on the most concerning issues of food security, such as water availability for irrigation of vegetation growth for the former. Currently 20 percent of the agricultural areas of the world are irrigated, producing 40 percent of the global food. The project is also dedicated to developing near real-time automated sea mapping, positively impacting the maritime sea navigation and safety, thus improving the life of 4 million people living in the Arctic. Currently, sea ice information is available either as ice charts or as satellite data, a practice that requires time consuming expert analysis to produce and, consequently, leads to less frequent updates than desired. With support of 11 organizations, the project is implementing state-of-the-art technologies such as Hopeworks Deep Learning and big data processing of massive amounts of data. ExtremeEarth received 6 million funding from the European Union and it is generating key insights for the development of sustainable practices with high significant financial impacts.

The Hopsworks platform will play a major role in going beyond the current state of the state-of-the-art of AI technologies, especially when addressing large volumes of data and scale-out deep learning, while remaining open source. We will continue to make Hopsworks available for free to researchers across the world to bring answers to problems that concern all of us, comments Dowling.

About Logical ClocksLogical Clocks was founded by the team that created and continues to drive Hopsworks Feature Store, the worlds first and most complete feature store with an end-to-end machine learning platform. With offices in Stockholm, London and Palo Alto, Logical Clocks aims to simplify the process of refining data into intelligence at scale.

Read the original here:
Tech for Good: Artificial Intelligence Applications that will Improve the Environment and Healthcare in the EU - GlobeNewswire

As the demand for products such as fitness trackers and wearable technology increases, so does the need for smart textile and smart apparel. According to a recent market report, the global elegant textile market size is expected to reach USD 5.55 billion by 2025.

The rise of new technologies such as Artificial Intelligence (AI) and the Internet of Things (IoT) has transformed the once labor-intensive textile industry. Computerized machinery is now found in most textile factories, and these machines are far more efficient at creating specific designs on a massive volume than human workers.

New smart apparel products are being created every day. By implementing AI along with technologies such as Bluetooth Low Energy (BLE), edge computing, and cloud data, smart textiles can monitor and communicate the wearers information, including biometric data such as blood pressure, heart rate, perspiration, temperature, and more.

This article will examine how AI is impacting the textile industry, some new use cases, and why ultra-low-power (ULP) technologies are a must to fully unleash AI at the endpoints.

For textile manufacturers, AI is reshaping their entire production process and the way they conduct business. AI can access and collect historical and real-time operational data, providing insights that can improve operational efficiency. When you have a clear view of your operations, it is easier to tweak processes to magnify human workers capabilities.

Whether it is product cost, textile production, quality control, just-in-time manufacturing, data collection, or computer integrated manufacturing, AI leaves an imprint on every part of the process. Some commonly integrated AI applications for textile production include defect detection, pattern inspection, and color matching.

The use of AI has enabled smart apparel, or smart clothes that leverage IoT and electronic sensors to create a better user experience. By leveraging these technologies, smart clothes can offer a more comfortable experience and a more healthcare-focused experience. Below, we will examine some of these new possibilities in the textile industry.

Much like how fitness trackers can help their users live a healthier and more attentive lifestyle, smart apparel combined with electronic sensing technology can do the same. However, since your clothes have a larger area of contact with your body than something like a smartwatch, smart apparel can potentially provide more types of physiological signal measurements.

Smart clothing can enable continuous monitoring of important biometrics, such as our heart rate. With long-term monitoring more feasible, physicians can better identify or diagnose potential cardiac diseases. Smart clothing helps patients collect complete and comprehensive heart-related data, track long-term heart disease, and enhance the detection and diagnosis of heart issues through regular monitoring over an extended period.

Following the COVID-19 outbreak, consumers have emphasized healthcare and medical attention in their wearable products, which is now extending to smart apparel. Clothes embedded with BLE technology can feel, sense, and regulate data, and the development of fabric-based sensors should only improve the overall wearing experience.

Artificial Intelligence isnt the only technology driving forward the textile industry. Cloud data, edge compute, accurate sensors, and ultra-low-power technologies are also necessary components. Especially for smart clothes that rely on BLE and IoT technologies, a long-lasting energy source from their embedded battery must provide a satisfactory and useful consumer experience.

The rest is here:
How Artificial Intelligence Is Transforming the Textile Industry - IoT For All

Nancy Shemwell, COO, Trilogy Networks, USA; Young-Kai Chen, program manager, Microsystems Technology Office, Defense Advanced Research Projects Agency (DARPA), USA; and Yiqun Cai, vice president, Alibaba Group, China will present compelling technical content on groundbreaking initiatives. The talks will cover edge cloud support and applications in rural territories, advances in photonics and artificial intelligence, and the evolution of networking driven by cloud computing. The plenary program is scheduled for Tuesday, 08 June 2021, 08:00 PDT, UTC-04:00.

"The OFC 2021 plenary will demonstrate the impressive work of leaders in our field who are driving innovations that will inspire our community and benefit society-at-large," said Jun-ichi Kani, OFC General Chair. "Nancy Shemwell, Young-Kai Chen and Yiqun Cai are behind the revolutionary applications of technologies that are rapidly changing communications and computing. We are privileged to have them as headliners for an engaging plenary program, which is always a highly anticipated segment of our international conference and exhibition."

In her presentation titled "Industrial Revolution 4.0 Gone Country," Nancy Shemwell, COO, Trilogy Networks, USA, will describe the Rural Cloud Initiative, the deployment of distributed edge cloud support and applications across rural America to help close the "digital divide." The initiative will bring the technology platforms required to run advanced solutions software and hardware to create an ecosystem.

Young-Kai Chen, program manager, Microsystems Technology Office at DARPA, USA, will discuss the "Symbiotic Perspective of Photonics and Artificial Intelligence" in his talk. Tremendous advances in photonics and artificial intelligence over the past decades have enabled the next generation of communications and computing.

A veteran in the networking industry, Yiqun Cai, vice president, Alibaba Group, China, will explore how cloud computing became the foundation of the company's infrastructure. In his talk titled "Hammers and Nails: How Technologies and Applications Drive the Evolution of Networking in Alibaba," Cai will share the company's experience building networks to enable the transition to this technology.

Registration Information

Conference registration opens in early 2021. Credentialed media and analysts who wish to cover OFC 2021 can find registration and other essential information in the OFC media room.

About OFC

The 2021 Optical Fiber Communication Conference and Exhibition (OFC) is the premier conference and exhibition for optical communications and networking professionals. For more than 40 years, OFC has drawn attendees from all corners of the globe to meet and greet, teach and learn, make connections and move business forward.

OFC includes dynamic business programming, an exhibition of global companies, and high impact peer-reviewed research that, combined, showcase the trends and pulse of the entire optical networking and communications industry. OFC is co-sponsored by The Optical Society (OSA), the IEEE Communications Society (IEEE/ComSoc), and the IEEE Photonics Society and managed by OSA. OFC 2021, a blended in-person and virtual event, will take place 06 10 June 2021 at the Moscone Center in San Francisco, California, USA. Follow @OFCConference, learn more at OFC Community LinkedIn, and watch highlights on OFC YouTube.

About The Optical Society

Founded in 1916, The Optical Society (OSA) is the leading professional organization for scientists, engineers, students and business leaders who fuel discoveries, shape real-life applications and accelerate achievements in the science of light. Through world-renowned publications, meetings and membership initiatives, OSA provides quality research, inspired interactions and dedicated resources for its extensive global network of optics and photonics experts. For more information, visit osa.org.

SOURCE The Optical Fiber Communication Conference and Exhibition (OFC)

https://www.ofcconference.org

Follow this link:
Evolution of Networking, Photonics and Artificial Intelligence and Deployment of Edge Cloud for Rural Among Topics for OFC 2021 Plenary - PRNewswire

The GREENTECH FESTIVAL and Audi as one of the founding partners of the sustainability platform created by Sven Krger, Marco Voigt, and Nico Rosberg awarded the GREEN FUTURE award together for the first time as part of the world premiere of the Audie-tronGT. The prize is part of the GREEN AWARDS of the festival and distinguishes projects and persons that promote environmentally compatible urbanization while making an important contribution to improving the quality of life and urban infrastructures at the same time. The award went to Tel Avivbased start-up Zencity, which developed an algorithm that collects and analyzes social media posts and local news from cities.

The UN already predicted that more than two thirds of people will live in cities by the middle of this century in its World Urbanization Prospects study in 2018. Already in 2030, the United Nations expect that there will be 43 megacities worldwide. Making life in cities as environmentally friendly and socially just as possible is therefore one of the major tasks of this decade. By initiating an award precisely for this endeavor, the GREENTECH FESTIVAL and AUDIAG aim to draw attention to this challenge and promote innovative solutions, support founders in the early stages of their projects, and encourage public dialogue.

Nominees included projects from the fields of energy, water, mobility, construction and living, digitalization, safety and security, and resources. The jury was comprised of representatives of the WWF, Deutsche Bahn, the German Institute for Economic Research (DIW), and the fashion label of rap artist Marteria Green Berlin, who are also members of the GREEN AWARDS jury of the sustainability platform. The jury evaluated the projects in terms of their contribution to environmental protection, scalability, technical innovation, and future viability. The GREENFUTURE Award is a special prize that is part of the GREEN AWARDS of the festival and highlights the opportunities of sustainable technologies for the cities of the future.

As part of the digital world premiere of the latest electric car from Audi, the Audie-tronG, two of the founders of the GREENTECH FESTIVAL, Nico Rosberg and Marco Voigt, CEO Judith Khn and Henrik Wenders, Senior Vice President Audi Brand, handed the award to Assaf Frances, Director Urban Policy & Partnerships of Zencity in a live ceremony. Nico Rosberg: Time is a critical factor when it comes to climate change, and we need to act now. Start-ups like Zencity provide us with the necessary tools. We need technologies like Zencitys AI to live up to our responsibility and put a stop to the destruction of our environment. With this special award, we are demonstrating what todays technology is already capable of when it comes to shaping our near future in urban areas that is sustainable and offers quality of life. We made a conscious decision to award the GREEN FUTURE Award in a different setting today, so as to reach as many new people as possible and spark their enthusiasm for a sustainable lifestyle. Henrik Wenders, SVP Audi Brand: Audi stands forVorsprung our aim is to use technology to contribute to a sustainable future and to shape urban mobility in such a way that the main focus is on the people. As an active partner of the GREENTECH FESTIVAL, we want to provide real added value and do our part to find answers to the pressing questions of the future.

Zencity was developed by Eyal Feder-Levy and Ido Ivri as an intuitive AI tool for local administrations. It uses an algorithm to find social media posts, websites, local news, and other online sources that contain information referring to the cities in which the people making these posts live. Advanced artificial intelligence and machine learning allow millions of user data points from the defined area, such as within a citys limits, to be processed and to generate informative findings on this basis. Customers of Zencity include municipal authorities that can use this data as a basis for understanding the needs of their inhabitants and making them a reality. This method conserves resources and replaces expensive and time-consuming face-to-face surveys, citizen hotlines, and committee meetings. This way, the tool helps all inhabitants of a city to gain the attention of political decision-makers and does so in an automated way, without complex reporting processes or bureaucratic obstacles. Zencity is already in use in 160cities, including Chicago, Ottawa, and Tel Aviv.

Other nominees included Strabag and its CIAir project and Sensoneo with its solution for intelligent waste management. The clean asphalt from Strabag reduces noise emissions by up to 35percent as compared to conventional asphalt. The gritting material used for the asphalt consists of ultra-high performance concrete (UHPC) mixed with titanium dioxide. When exposed to sunlight, it breaks down nitrogen oxides bound in the air and converts them into harmless nitrates. The material is incorporated directly into the hot asphalt surface. Sensoneo offers intelligent waste disposal solutions for cities and companies. They range from plant tracking forcontainers and all the way to an automated on-demand solution for more efficient collection planning. This way, three solutions for smart waste management are combined: asset management, waste monitoring, and route planning.

SOURCE: Audi

View original post here:
Artificial intelligence for greater sustainability and quality of life in cities: GREENTECH FESTIVAL and Audi give GREEN FUTURE Award to Zencity -...