Category Archives: Artificial Intelligence

Do you have proven expertise in Artificial Intelligence and Machine Learning and an established international reputation within the field, both in industry and academia? Are you looking for a challenging role in an environment that is open, vibrant and welcomes new ideas? Then Be The Change, follow your passion and join the University of East London as Professor of Artificial intelligence and Machine Learning.

These are exciting times at the University as, under a brand new transformational 10-year strategy, Vision 2028, were committed to providing students with the skills necessary to thrive in an ever-changing world, includingincreasing the diversity of the talent pipeline, particularly for Industry 4.0 jobs. Our pioneering and forward-thinking vision is set to make a positive and significant impact to the communities we serve too, and inspire our staff and students to reach their full potential. This is your chance to be part of that journey.

Join us, and youll be a key member of our Computer Science & Digital Technologies departments School of Architecture, Computing and Engineering team. Your challenge? To raise the profile of the department and school, specifically in impactful applied research in disciplines that include Deep Learning, Computer Vision and Natural Language Processing. But thats not all. Well also rely on you to lead and develop the Schools work, both in relation to taught courses and in terms of research, consultancy, knowledge transfer and income generation. And, as a senior academic leader, youll be instrumental in shaping the Schools strategy for promoting research, learning & teaching and employability initiatives.

Playing a prominent role in obtaining funding for research and knowledge exchange activities in your area of expertise will be important too. Well also encourage you to contribute to other aspects of the Schools work too, such as staff development activities, mentoring and supporting the development of early career researchers and joint supervision of PhD students. Put simply, youll bring leadership, vision and inspiration for the future direction of research and teaching in AI.

To succeed, youll need a PhD in Computer Science or other relevant area and experience of teaching in higher education or training in a professional context and applying innovative and successful approaches to learning. Youll also need a proven ability to lead on the fusion of practice and theory in specific disciplines, in-depth experience of research & knowledge exchange projects and a record of significant research & knowledge exchange grant capture and/or income generation or equivalent. As comfortable developing and managing major research grant applications as you are communicating academic findings to policy and wider public audiences, you also have experience of PhD supervision as a Director of Studies and other research mentorship activities.

In summary, you have what it takes to act as a role model and ambassador to raise the Universitys profile and increasing its impact and influence and establish links with a variety of businesses, public and third sector organisations.

So, if you have what we are looking for and are keen to take on this exciting challenge, get in touch.

At the University of East London, we aim to attract and retain the best possible staff and offer a working environment at the heart of a dynamic region with excellent transport links. You can look forward to a warm, sincere welcome, genuine camaraderie and mobility in an institution led with passion, visibility and purpose. Your impact, resilience and sense of collegiality will directly contribute to the Universitys future and those of the students whose lives you will touch and change forever. We also offer a great range of benefits including pension, family friendly policies and an on-site nursery and gym at our Docklands Campus.

Closing date: 13 April 2021.

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Professor of Artificial intelligence and Machine Learning job with UNIVERSITY OF EAST LONDON | 249199 - Times Higher Education (THE)

Debating, held in high regard since the time of the Ancient Greeks (and even before that), has a new participant. Its not quite as eloquent and sharp as the likes of Socrates or Cicero, but it can hold its own against some debaters hinting at a future where AI can understand and formulate complex arguments with ease.

In 2019, an unusual debate was held in San Francisco. The topic of the debate was We should subsidize preschool, and it featured Harish Natarajan, a 2016 World Debating Championships Grand Finalist and 2012 European Debate Champion. His opponent was Project Debater, an autonomous debating system.

The structure of the debate was simple. Noam Slonim, an IBM researcher in Israel, explains how it worked: a four-minute opening statement, a four-minute rebuttal, and a two-minute summary.

The speech by Harish was captured via Watsons Speech to Text in real-time, which was then ingested by our algorithms in the Cloud to build the rebuttal, which took under a minute, Slonim explains.

Both contestants had about 15 minutes to prepare, which for Project Debater meant scouring its database for relevant arguments, although the topic of this debate was never included in the training data of the system, Slonim emphasizes.

We polled our live audience of around 800 attendees before and after the debate and then calculated the difference to see how many were persuaded to the other side, he notes.

The AI, it turns out, isnt able to stand up to the worlds best debaters yet, but it may be able to defeat the less prepared, and it could hold its own against even some experienced debaters. Its growth is also impressive: from zero to the current performance in a couple of years.

As the system matured it was very similar to watching a junior level debater grow up in front of your eyes, Slonim tells me in an email, his satisfaction betrayed by a smiling emoji. In 2016, during the first live debates we had with the system, and after nearly 4 years of research, it was still performing at the level of a toddler and was not making a lot of sense. Only three years later, it seems fair to say that the system achieved the performance of a decent university-level debater. So, from kindergarden to university in only three years, which was interesting to observe.

Slonim and collaborators went on to host several live debates which confirmed the AIs capability, showing that non-human debaters are ready to enter the stage. But the impact of their work goes way beyond that.

Artificial Intelligence algorithms can already do a lot of things, but debating (or analyzing complex arguments) is one of the fields considered to be AI-proof.

The study of arguments has an academic pedigree stretching back to the ancient Greeks, and spans disciplines from theoretical philosophy to computational engineering. Developing computer systems that can recognize arguments in natural human language is one of the most demanding challenges in the field of artificial intelligence (AI), writes Chris Reed in a News and Views article that accompanied the study.

Since the 1950s, AI research has greatly progressed, being able to compete against humans in a number of games. First, algorithms conquered chess, and more recently, they even conquered the game of Go, thought to be impossible until recently.

But in the new paper, Slonim and colleagues argue that all these games lie within the comfort zone of AI, based on several simple observations. Debates are a whole new ballgame.

First, in games there is a clear definition of a winner, facilitating the use of reinforcement learning techniques. Second, in games, individual game moves are clearly defined, and the value of such moves can often be quantified objectively, enabling the use of game-solving techniques. Third, while playing a game an AI system may come up with any tactic to ensure winning, even if the associated moves could not be easily interpreted by humans. Finally, for many AI grand challenges, massive amounts of relevant data e.g., in the form of complete games played by humans was available for the development of the system.

All these four characteristics do not hold for competitive debates. Thus, the challenge taken by Project Debater seems to reside outside the AI comfort zone, in a territory where humans still prevail, and new paradigms are needed to make substantial progress.

To overcome these challenges, Project Debate scans through an archive of 400 million newspaper articles and Wikipedia pages, looking to form opening statements and counter-arguments. Its able to debate on varied different topics, scoring high on opening statements.

While the authors conclude that debating humans is still out of the AI comfort zone, its an important proof of concept and once again, AIs are ready to rise up to new challenges.

These new challenges, researchers say, could be quite important.

The broad goal of this new AI was to help people make unbiased, informed decisions. As is often the case with pioneering AI algorithms, though, the scope reaches beyond what has already been accomplished. In this case, an AI that can present arguments and counter-arguments is very useful as an adviser.

Whether you are a politician or a CEO you are likely to make decisions based on instinct and experience, which may be vulnerable to blind spots or a bias. So the question is, what if AI could help you see data to eliminate or reduce the bias? You still may ultimately make the same decision, but at least you are better informed about other opinions. This also addresses the echo chamber or social media bubble challenge that we see currently, particularly around the COVID vaccine and whether people should get it or not, Slonim says.

Already, the technology is being put to work. The Project Debater API was made freely available for academic use, including two modules called Narrative Generation and Key Point Analysis.

When given a set of arguments, Narrative Generation constructs a well-structured speech that supports or contests a given topic, according to the specified polarity. And Key Point Analysis is a new and promising approach for summarization, with an important quantitative angle. This service summarizes a collection of comments on a given topic as a small set of key points, and the prominence of each key point is given by the number of its matching sentences in the given data, he explains.

A lot of ideas can build on this existing model. Already, technologies built by the Project Debater team were recently used on a TV show called Thats Debatable and this week its being used during the Grammy Awards to allow fans to debate on pop culture topics, Slonim tells me

The idea that you can comb through thousands of arguments made by other people and compile and summarize can be very useful in a number of scenarios. The approach can also eliminate bias, or at least, reduce it to the bias present in the voice of the crowd.

Think of a company that would like to collect feedback about a service or a product from thousands of clients; about an employer who would like to learn the opinions of thousands of employees; or a government, who would like to hear the voice of the citizens about a policy being examined. In all these cases, by analyzing peoples opinions, our technology can establish a unique and effective communication channel between the decision-maker, and the people that might be impacted by the decision.

Project Debater is a crucial step in the development of argument technology, and given the deluge of misinformation were faced with on a daily basis, it couldnt come soon enough.

Project Debater tackles a grand challenge that acts mainly as a rallying cry for research, it also represents an advance towards AI that can contribute to human reasoning, Reed concludes in the News & Views article.

You can watch an entire debate below.

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Artificial Intelligence can debate and its pretty good at it (but not as good as the best humans) - ZME Science

AI governance touches many functional areas within the enterprise data privacy, algorithm bias, compliance, ethics, and much more. As a result, addressing governance of the use of artificial intelligence technologies requires action on many levels.

It does not start at the IT level or the project level, says Kamlesh Mhashilkar, head of the data and analytics practice at Tata Consultancy Services. AI governance also happens at the government level, at the board of directors level, and at the CSO level, he says.

In healthcare, for example, AI models must pass stringent audits and inspections, he says. Many other industries also have applicable regulations. And at the board level, its about economic behaviors, Mhashilkar says. What kinds of risks do you embrace when you introduce AI?

As for the C-suite, AI agendas are purpose-driven. For example, the CFO will be attuned to shareholder value and profitability. CIOs and chief data officers are also key stakeholders, as are marketing and compliance chiefs. And thats not to mention customers and suppliers.

Not all companies will need to take action on all fronts in building out an AI governance strategy. Smaller companies in particular may have little influence on what big vendors or regulatory groups do. Still, all companies are or will soon be using artificial intelligence and related technologies, even if they are simply embedded in the third-party tools and services they use.

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AI governance: Reducing risk while reaping rewards - CIO

Researchers are working on combining the technologies to create realistic 2D avatars of people who can interact in real time, showing emotion and making context-relevant gestures. A Samsung-associated company called Neon has introduced an early version of such avatars, though the technology has a long way to go before it is practical to use.

Such avatars could help revolutionize education. Artificial intelligence researchers are already developing A.I. tutoring systems that can track student behavior, predict their performance and deliver content and strategies to both improve that performance and prevent students from losing interest. A.I. tutors hold the promise of truly personalized education available to anyone in the world with an Internet-connected device provided they are willing to surrender some privacy.

Having a visual interaction with a face that expresses emotions, that expresses support, is very important for teachers, said Yoshua Bengio, a professor at the University of Montreal and the founder of Mila, an artificial intelligence research institute. Korbit, a company founded by one of his students, Iulian Serban, and Riiid, based in South Korea, are already using this technology in education, though Mr. Bengio says it may be a decade or more before such tutors have natural language fluidity and semantic understanding.

There are seemingly endless ways in which artificial intelligence is beginning to touch our lives, from discovering new materials to new drugs A.I. has already played a role in the development of Covid-19 vaccines by narrowing the field of possibilities for scientists to search to picking the fruit we eat and sorting the garbage we throw way. Self-driving cars work, theyre just waiting for laws and regulations to catch up with them.

Artificial intelligence is even starting to write software and may eventually write more complex A.I. Diffblue, a start-up out of Oxford University, has an A.I. system that automates the writing of software tests, a task that takes up as much as a third of expensive developers time. Justin Gottschlich, who runs the machine programming research group at Intel Labs, envisions a day when anyone can create software simply by telling an A.I. system clearly what they want the software to do.

I can imagine people like my mom creating software, he said, even though she cant write a line of code.

Craig S. Smith is a former correspondent for The Times and hosts the podcast Eye on A.I.

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A.I. Is Everywhere and Evolving - The New York Times

Artificial intelligence and machine learning have moved from the backrooms of computer science into the mainstream. Their impact is being felt in everything - from how we shop through to finance markets and medical research, as well as the agriculture and manufacture industries.

That's according to AI firm Appier, who has released its AI Predictions and Trends to Watch in 2021.

According to the company, larger models have been trained in separated modality. For instance, GPT-3 is the first 100-billion-parameter model for natural language processing (NLP). Recently, a-trillion-parameter model (T5-XXL) has also been trained. They can be used to write articles, analyse text, perform translations and even create poetry.

"In parallel, we've seen models used for image recognition and generation greatly improved as they have also been trained with more data sets," Appier says.

"What we are seeing emerge is the power that can come from combining two or more AI models without changing these large models.

"In this way, combining these large models becomes affordable. That will allow us to use AI to interpret text and generate a completely new image."

The following are the current observations and predictions of AI applications in five major fields:

The E-Commerce Boom Is AI-Driven

Over the last year, online commerce has grown significantly and is expected to continue to increase. COVID-19 restrictions have resulted in people spending much more time online -- not just shopping but in online meetings, playing games, accessing social media and using apps.

The growing digital journeys undertaken by people have generated more data that can be used to understand human behaviour. However, more data also brings a greater complexity.

Today, there's no single, most effective channel for reaching customers. Reaching the right customer on the right channel at the right time is complicated for humans, but that complexity can be overcome through the use of AI.

AI gives marketers a way to influence customer's behaviour at a pace and scale previously thought impossible. AI not only finds the right customers, but also accesses the often-forgotten long tail of customers. It can also effectively generate creatives and develop customised content for different customers, and test the performance for different creatives to increase user engagement.

Data-Driven Finance Relies on AI

The main application of AI in finance has been in high-frequency trading where transactions are conducted between machines faster than people can communicate. This will continue in both traditional finance and in the world of cryptocurrencies, where we see different AIs engage in 'warfare'.

Investors have been using AI to make long-term predictions -- which has required systems that can understand investors' long-term targets. These were typically centred around measures such as revenues, incomes and profits.

While high-frequency trading strategies are important, there is another factor to show that cryptocurrencies are far more challenging to predict. Much of what we see in cryptocurrency markets is driven by 'human madness'. While AI models struggle with this today, we can expect the AI models of the future to evolve and do a better job of predicting this behaviour through closely monitoring trends in media and social networks.

AI in Healthcare and Biomedical Research

The prototype of messenger RNA (mRNA) COVID-19 vaccines was developed in days thanks to the digitisation tools of genetic code sequencing and the transcription tools of making mRNA from genetic code sequence.

With the help of AI to predict new mutations in the Sars-Cov-2 virus, the process of developing mRNA vaccines will be even faster. AI can also be used as a diagnostic tool to read x-rays, based on the sound of someone coughing and indicate whether the patient is likely to be suffering from COVID-19 or some other illness.

In the biomedical domain, sequences of codes, such as DNA or amino acid, are commonly used. Since sequences of codes can be treated as a type of language with hidden structure, the architecture used in NLP models can be potentially used to understand and generate sequences of codes in the biomedical domain as well.

One example in early 2021 is that biomedical researchers used language model architecture to predict virus mutations and to understand protein folding -- a key challenge in the creation of some of the vaccines now available. This finding is actually adapting the architecture of one model to solve problems in the biomedical domain.

Machine learning and AI don't replace clinicians and researchers; they allow these professionals to work faster and rapidly test hypotheses.

Instead of waiting for cell cultures to grow in the physical world, they can use these models to understand what will happen much faster in the digital simulation.

As more and more people wear devices that can monitor heart rate, body temperature, blood pressure and other critical factors, the data can be used to give doctors greater insight into a patient's condition. It also aids accuracy when making diagnoses as doctors and other clinicians are no longer reliant on patient recollections.

The Future of Education

Curricula and textbooks have typically been developed to serve large populations of 'average' students. These materials include content designed for a wide gamut of different abilities.

However, experts, such as Sir Ken Robinson, point out that the 'conveyor belt' model of education doesn't take into account the individual abilities and needs of students. Therefore, we have seen AI being used to revolutionise the way curricula is created and delivered.

It can be used to provide more personalised curricula or personal problem sets for students. Instead of every student working through the same set of problems or questions, they receive a set that are customised to their specific level.

For example, a student may be very strong with fractions in mathematics, but have a problem with trigonometry. Instead of putting the student through the standard curriculum, he or she would spend less time on fractions and more time on trigonometry. As a student proceeds through a course, AI will monitor his progress and self-modify to meet the specific needs of that student.

With so much content now available online, cheating and plagiarism has become a huge issue. While detecting plagiarism is quite easy -- there is already AI that can detect direct copying and similar text where just a few words or the tense are altered -- there are other challenges. For example, a student may take content from one language and translate it to another. This is harder to detect, but AI is being developed to solve this problem. Similarly, image interpretation AI is being developed to find instances where arts students copy or imitate a design.

Smart Farming and Factories

Factories and farms are using data in innovative ways too. However, they differ from many other AI applications as they don't focus on end-users. Instead, they focus on products, produce and machines. This requires an investment in sensors, robots and automation, and the optimisation of operations.

The biggest development we are seeing in this area is in the generalisation of findings between different areas. For example, if AI is being used to increase yields in an apple crop, can those AI models be reapplied for the growing of other fruits such as bananas or peaches? Similarly, if a factory is manufacturing LCD panels and has found ways to increase their yield rates, can those tools and lessons be applied to other manufacturing processes and factories?

Perhaps the biggest prediction to make about AI in 2021 and beyond can be summarised in one word: leverage, Appier says.

"Using existing AI model architecture, combining well developed models and finding ways to generalise existing models to other applications will continuously increase the impact of AI along with accelerated digital transformation across many domains."

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Artificial intelligence felt in everything we do - report - IT Brief Australia

SAN FRANCISCO--(BUSINESS WIRE)--Today, the AI Infrastructure Alliance (AIIA), a non-profit organization with 25 global members officially launched with the mission to create a robust collaboration environment for companies and communities in the artificial intelligence (AI) and machine learning (ML) space. This global Alliance brings together top technologists across the AI spectrum and includes a wide range of member companies. Together, these companies and communities provide a glimpse into the future where AI creates real value for everyday businesses and not just big tech powerhouses.

Partnerships in the Alliance will help create a Canonical Stack for AI, by driving strong engineering standards and creating seamless integration points between various layers of the AI infrastructure ecosystem. Canonical means "a set of rules, standards and principles by which something is judged, and a Canonical Stack (CS) for AI will set the standard for how enterprises develop and design machine learning models at scale. It will let data scientists and data engineers move up the stack to solve more complex, higher order problems, instead of reinventing the wheel on every data science project.

The AI and ML space currently lacks a standard set of tools and solutions, blocking data science teams from sharing their work and collaborating across the world. Rather, there is wild proliferation of proprietary, cloud lock-in solutions that benefit individual companies, but not the data scientists and engineers building the AI applications of today and tomorrow. The Alliance came together to help those data science teams break out of lock-in so they can build on top of a standardized, open platform that works across all of their environments.

"Time and again, I've seen development teams get excited about the potential of AI to transform their business and applications, only for them to get stopped dead in their tracks by a fragmented and confusing array of technologies with little to no integration," said Dan Jefferies, Director of the AIIA. "Despite a massive surge of partial solutions, no single tool exists that lets teams leverage the true power and potential of AI. The AI Infrastructure Alliance will help create clarity in this confusing space by building a cohesive framework and bringing together leaders and innovators to help set the standard for how data science teams build models now, and into the future."

The AI Infrastructure Alliance provides a range of benefits to member companies including opportunity to:

Creating a place for top AI companies to work together will speed development of the infrastructure that businesses really need to make the promise of AI a reality, said Joey Zwicker, Co-Founder of Pachyderm, a founding member of the AIIA. As the Canonical Stack comes together, it will vastly reduce time to value for any company, in any industry, thats leveraging AI across their business.

Core founding members include Pachyderm, Seldon, Determined AI, Algorithmia, Tecton, ClearML by Allegro AI, Neu.ro, ZenML by Maiot, DAGsHub, TerminusDB, WhyLabs, YData, Superb AI, Valohai, Superwise.ai, cnvrg.io, Arize AI, CometML, Iguazio, UbiOps, and Fiddler. These companies have raised over $200M in collective venture capital funding from top firms including Andreessen Horowitz, Sequoia Capital, GV, Benchmark, NorWest Venture Partners, Madrona Venture Group and Gradient Ventures.

About the Artificial Intelligence Infrastructure Alliance

The Artificial Intelligence Infrastructure Alliance (AIIA) is a consortium of leading artificial intelligence startups with a mission to help every company realize the infinite potential of AI. Formed in February 2021, the Alliance is focused on tying together the complex web of existing AI technologies into a single Canonical Stack, providing the infrastructure on which any companyfrom tiny startups to global enterprisescan run impactful AI projects. Founding members include Pachyderm, Seldon, Determined AI, Algorithmia, Tecton, ClearML by Allegro AI, Neu.ro, ZenML by Maiot, DAGsHub, TerminusDB, WhyLabs, YData, Superb AI, Valohai, Superwise.ai, cnvrg.io, Arize AI, CometML, Iguazio, UbiOps, and Fiddler. To learn more about the AIIA or to become a member, visit https://ai-infrastructure.org/.

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The AI Infrastructure Alliance Launches With 25 Members to Create the Canonical Stack for Artificial Intelligence Projects - Business Wire

BEIRUT In two Gulf countries focused on advancing artificial intelligence to boost their economies, experts expect military AI technology to progress quickly and extend the reach of the nations armed forces.

Saudi Arabia and United Arab Emirates also are carving a niche in the defense export market by adding AI capabilities and pursuing emerging technologies, said Jean-Marc Rickli, head of global risk and resilience at the Geneva Centre for Security Policy.

Both adopted Vision 2030 development strategies, which have data and AI at their core to help the countries move beyond oil-based economies, Rickli said.

Their militaries will realize benefits from the emphasis on AI.

In the military, technology increasingly has the potential to become a surrogate in warfare. It allows smaller powers and also non-state actors, to use technology as a force multiplier across all dimensions of the battlefield and beyond, Rickli said.

For example, with the limited size of UAEs armed forces, increasing integration of AI in the military, such as in weapons or C4ISR systems, allows defense tasks to be performed increasingly autonomously and thus reducing economic and human costs, he said.

UAE leads the way in AI developments in the Gulf countries, Rickli noted. It was the first country to appoint AI minister and founded Mohamed bin Zayed University of Artificial Intelligence.

Last fall, the Saudi Data & AI Authority launched the countrys National Strategy for Data and Artificial Intelligence to make it a global AI leader by 2030. One effort has been to track data from COVID-19 infections to help with the countrys response and precautions.

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Artificial intelligence likely will have the most powerful effect on the countries financial sectors, but it is in the domains of defense, intelligence, and counterterrorism where the use of AI will probably grow the fastest, said Giorgio Cafiero, CEO of Gulf State Analytics, a Washington, D.C.-based consulting firm that assesses risks and opportunities among Gulf Cooperation Council states.

Regarding the advancement of AI, there will be major consequences for the Saudi military as well as the kingdoms security, especially when one considers the extent to which autonomous agents will play important roles in the future of Middle Eastern warfare, Cafiero said.

A spot in the defense market

Previously, neither country has had the capabilities or workforce to invest in vast research and development for expensive weapons programs, but emerging technologies could provide a niche.

As Turkey has developed a niche in the drone industry by producing drones (Kargu) that display semiautonomous features. Similarly, Israel has invested in this market (Harop and Harpy) in addition to air defense systems (Iron Dome) and cyber security. The UAE and KSA seem to adopt a similar path, to provide a niche in the defense market through emerging technologies, Rickli said.

Though it is costly for these technologies to mature, once they have reached maturity, their diffusion is very rapid. It is almost impossible to prevent the proliferation of codes. Furthermore, algorithms can also be repurposed, i.e. used or applied in a way that they were not intended, he explained.

Rickli pointed to the example of how UAEs Edge defense conglomerate is building automation and AI into some products. Edge ranked 22nd of the list of the top 25 arms-producing and military services companies in the world, according to the Stockholm International Peace Research Institute Arms Industry Database.

Last year, Edge subsidiary ADASI unveiled its first UAE-made vertical-takeoff-and-landing drone, Garmousha, that incorporates technology using AI algorithms.

UAE with Edge has set the foundation to compete in the global defense market, and investments in AI automation offers huge growth potential, Rickli said.

And the state-owned Saudi Arabian Military Industries recently acquired Advanced Electronics Co., a step forward in building its defense electronics capabilities. Plus, the deal lines up with Saudi Vision 2030 directives to increase in-country defense manufacturing.

Internal experts, international partnerships

Experts noted that automation and increased productivity from artificial intelligence could reduce the nations need for foreign workers.

Through NSDAI [National Strategy for Data and Artificial Intelligence], the Saudis seek to lure roughly USD 20 billion in investment, both from abroad and from within the kingdom, in the next nine years and to train approximately 2,000 Saudis to become AI specialists before 2030, Cafiero said.

The two countries still hire AI specialists from the West and increasingly from China to fill workforce needs, Rickli said. But they also set up academic institutions UAEs Mohamed Bin Zayed University of Artificial Intelligence and the Artificial Intelligence Initiative at King Abdullah University of Science and Technology in Saudi Arabia to develop local talent, he noted.

With a new diplomatic agreement between UAE and Israel, theres a good chance that their AI collaboration will increase. When it comes to AI, the knowledge acquired by Israel in the field, notably in the defense sector, is very appealing for the UAE, Rickli said. Hence, it is very likely that cooperation will develop further in this field between the two countries.

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AI militarization will be 'force multiplier' for UAE, Saudi Arabia - C4ISRNet

Phoenix, Arizona--(Newsfile Corp. - February 22, 2021) - The Stock Day Podcast welcomed Artificial Intelligence Technology Solutions (OTC Pink: AITX) ("the Company"), an innovator in the delivery of artificial intelligence-based solutions that empower organizations to gain new insight, solve complex challenges and fuel new business ideas. CEO of the Company, Steve Reinharz, joined Stock Day host Everett Jolly.

Jolly began the interview by asking about the Company's background and current projects. "It was 2017 when I did the reverse merger into the public company that I then renamed 'Artificial Intelligence Technology Solutions'," explained Reinharz, after elaborating on his experience in the artificial intelligence space.

"What are your revenue goals moving forward and what markets are you hoping to penetrate?" asked Jolly. "As far as revenues go, we've had double-digit percent growth month-over-month, which is fantastic. That kind of exponential growth is going to be one of our goals for the foreseeable future," said Reinharz, noting that the Company has also been working to improve the Company's financials. "We had a situation where sales were outpacing our ability to produce, so we moved into a new assembly location in California, and recently it looks like we have been outgrowing that facility, which will accelerate our plans to move into a much larger facility in Michigan presumably before the end of this year."

"From a sales growth standpoint, I couldn't be happier. From a market acceptance standpoint, we've got a long way to go. We're just scratching the surface," said Reinharz. "We have a platform-style solution that applies across a variety of markets," he continued. "We have five products in the market right now," said Reinharz. "We have a very focused road map for 2021 and 2022 from a development standpoint. So, we're just going to continue to build and grow," he shared. "Our mission is to be the incumbent in this new space that we are creating, which we call the 'Autonomous Remote Services' space."

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"For the Robotic Assistance Devices (RAD), what is the price point from the lowest to the highest?" asked Jolly. "It is going to be from about $700 to $6,000 per month," explained Reinharz, noting that the Company's solutions drastically reduce the cost of traditional manned security services.

The conversation then turned to a recent advertisement released by the Company. "We wanted to participate in a positive messaging piece," said Reinharz. "It's called 'America Renewed' on USA TODAY," he added. "We wanted to be a part of the story of how we are protecting ourselves and staying healthy using technology and autonomous systems to do it," explained Reinharz. "We had paid participation by all of the dealers on the ad," he shared, noting that the advertisement represented both a low-cost and high-visibility opportunity for the Company.

To close the interview, Reinharz encouraged listeners to consider the future and potential of the artificial intelligence space as workplace roles continue to evolve and embrace technology. Reinharz also expressed his gratitude for the opportunity to reach listeners and shareholders, and encouraged listeners to take a closer look at the Company's current projects and new developments.

To hear the entire interview with Steve Reinharz, follow the link to the podcast here: https://audioboom.com/posts/7805851-artificial-intelligence-technology-solutions-discusses-the-potential-of-its-robotic-assistance-de

Investors Hangout is a proud sponsor of "Stock Day," and Stock Day Media encourages listeners to visit the company's message board at https://investorshangout.com/

CAUTIONARY DISCLOSURE ABOUT FORWARD-LOOKING STATEMENTS

This release contains "forward-looking statements" within the meaning of Section 27A of the Securities Act of 1933, as amended, and Section 21E the Securities Exchange Act of 1934, as amended and such forward-looking statements are made pursuant to the safe harbor provisions of the Private Securities Litigation Reform Act of 1995. Statements in this news release other than statements of historical fact are "forward-looking statements" that are based on current expectations and assumptions. Forward-looking statements involve risks and uncertainties that could cause actual results to differ materially from those expressed or implied by the statements, including, but not limited to, the following: the ability of Artificial Intelligence Technology Solutions to provide for its obligations, to provide working capital needs from operating revenues, to obtain additional financing needed for any future acquisitions, to meet competitive challenges and technological changes, and other risks. Artificial Intelligence Technology Solutions undertakes no duty to update any forward-looking statement(s) and/or to confirm the statement(s) to actual results or changes in Artificial Intelligence Technology Solutions expectations.

About Artificial Intelligence Technology Solutions (AITX)

AITX is an innovator in the delivery of artificial intelligence-based solutions that empower organizations to gain new insight, solve complex challenges and fuel new business ideas. Through its next-generation robotic product offerings, AITX's RAD and RAD-M companies help organizations streamline operations, increase ROI and strengthen business. AITX technology improves the simplicity and economics of patrolling and guard services, and allows experienced personnel to focus on more strategic tasks. Customers augment the capabilities of existing staffs and gain higher levels of situational awareness, all at drastically reduced cost. AITX solutions are well suited for use in multiple industries such as enterprises, government, transportation, critical infrastructure, education and healthcare. To learn more, visit http://www.aitx.ai and http://www.roboticassistancedevices.com, or follow Steve Reinharz on Twitter @SteveReinharz.

ContactsInvestor Relations Contact The Waypoint Refinery, LLC(845) 397-2956www.thewaypointrefinery.com

Steve Reinharz (949) 636-7060

About The "Stock Day" Podcast

Founded in 2013, Stock Day is the fastest growing media outlet for Nano-Cap and Micro-Cap companies. It educates investors while simultaneously working with penny stock and OTC companies, providing transparency and clarification of under-valued, under-sold Micro-Cap stocks of the market. Stock Day provides companies with customized solutions to their news distribution in both national and international media outlets. The Stock Day Podcast is the number one radio show of its kind in America.

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To view the source version of this press release, please visit https://www.newsfilecorp.com/release/75058

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Artificial Intelligence Technology Solutions Discusses the Potential of Its Robotic Assistance Devices (RAD) with The Stock Day Podcast - Yahoo...

DALLAS, TX / ACCESSWIRE / February 22, 2021 / According to a new market report published by Lucintel, the future of the global artificial intelligence market looks attractive with opportunities in the healthcare, security, retail, automotive, manufacturing, and financial technology (fintech) sectors. The global artificial intelligence market is expected to decline in 2020 due to global economic recession led by COVID-19. However, market will witness recovery in the year 2021 and it is expected to reach an estimated $70 billion by 2025 with a CAGR of 21% from 2020 to 2025. The major drivers for this market are increasing demand for virtual assistance for easy accessibility of services and growing adoption of cloud-based technology.

To download report brochure, please go to https://www.lucintel.com/artificial-intelligence-market.aspx and click "report brochure" tab from the menu.

In this market, different types of artificial intelligence such as machine learning, natural learning processing, and others are used as technology. On the basis of comprehensive research, Lucintel forecasts that the machine learning technology will remain the largest segment and it is also expected to witness the highest growth over the forecast period due to increasing adoption of this technology in the autonomous applications and growing consumer preference for IoT-enabled devices.

Within the artificial intelligence market, media and advertising will remain the largest application due to an increasing adoption of customer-centric marketing strategies and increasing use of social platform for advertisements. The healthcare segment is expected to witness the highest growth over forecast period due to advancements in clinical research and growing demand for electronics-based medical equipment and sensors in the healthcare applications.

APAC will remain the largest region and it is also expected to witness the highest growth over the forecast period due to the growing adoption of IoT (internet of things), increasing installation of smart home devices, and growing industrial automation in countries, such as China, India, and Taiwan.

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Emerging trends, which have a direct impact on the dynamics of the artificial intelligence industry, include growing adoption of artificial intelligence in IoT applications and increasing demand for AI-enabled processors. Intel, IBM, Amazon, Facebook, NVIDIA, Apple, Microsoft, General Electric, and NEC Corporation and others are among the major artificial intelligence manufacturers.

Lucintel, a leading global strategic consulting and market research firm, has analyzed the global artificial intelligence market by end use industry, technology, product and service, and region and has come up with a comprehensive research report entitled "Growth Opportunities in the Global Artificial Intelligence Market 2020-2025: Trends, Forecast, and Opportunity Analysis." The Lucintel report serves as a catalyst for growth strategy as it provides a comprehensive data and analysis on trends, key drivers, and directions. The study includes a forecast for the global artificial intelligence market by end use industry, technology, product and service, and region as follows:

By End Use Industry [ $B shipment analysis from 2014 to 2025]:

By Technology [$B shipment analysis from 2014 to 2025]:

By Product and Service [$B shipment analysis from 2014 to 2025]:

By Region [$B shipment analysis for 2014 to 2025]:

North America

United States

Canada

Mexico

Europe

United Kingdom

France

Germany

Asia Pacific

The Rest of the World

This 206-page research report will enable you to make confident business decisions in this globally competitive marketplace. For a detailed table of contents, contact Lucintel at +1-972-636-5056 or click on this link helpdesk@lucintel.com.

About Lucintel

Lucintel, the premier global management consulting and market research firm, creates winning strategies for growth. It offers market assessments, competitive analysis, opportunity analysis, growth consulting, M&A, and due diligence services to executives and key decision-makers in a variety of industries. For further information, visit http://www.lucintel.com.

Brandon FitzgeraldLucintelDallas, Texas, USAEmail: brandon.fitzgerald@lucintel.comTel. 972.636.5056Cell: 303.775.0751

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SOURCE: Lucintel

View source version on accesswire.com: https://www.accesswire.com/630968/Opportunities-for-The-Global-Artificial-Intelligence-Market-to-Reach-70-Billion-By-2025

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Opportunities for The Global Artificial Intelligence Market to Reach $70 Billion By 2025 - Yahoo Finance

Stock Market SymbolsGIB (NYSE)GIB.A (TSX)www.cgi.com/newsroom

LONDON, Feb. 22, 2021 /PRNewswire/ -CGI (NYSE: GIB) (TSX: GIB.A) was awarded by the European Space Agency (ESA) a contract to develop a new wildfire mapping service that combines recent advances in Earth Observation (EO), Artificial Intelligence(AI) and cloud computing to help better map and monitor the impact of wildfires.

CGI and its project partner, the University of Leicester, is working with nationally mandated user organisationsfrom Australia (Geoscience Australia) and France (ONF France) to implement and demonstrate EO services based on their requirements for improved wildfire risk management. The consortium will evaluate a variety of AI algorithms that could help meet these requirements. It is expected that combining the machine learning capabilities of these AI algorithms with the increased availability of frequent, high quality satellite observations will allow better burnt area mapping products to be generated where and when users want them.

The resulting AI-enabled wildfire mapping service will be made available to Geoscience Australia and ONF France, as well as the wider environmental community, through the EO4SD Lab portal. This online data portal, which has been developed by CGI for ESA, utilises cloud computing to provide free access to a range of EO data, tools and services to the sustainable development and wider environmental community.

The recent extensive fire disasters in the USA, Southern Europe and Australia have shown both the environmental and human cost of wildfires. Climate change is contributing to more frequent wildfires, with studiesfinding a 19% increase in global mean fire weather season length between 1979 to 2013. Better monitoring and analysing of burnt areas is important to improve land management and help mitigate the impact.

Tara McGeehan, President at CGI in UK & Australia said: "We are excited to be part of this cutting edge project that brings to bear the potential of AI to help the scientific and environmental community to better understand the extent and impact of damaging wildfires throughout the world. Our ongoing partnership with ESA for EO and Thematic Exploitation Platforms is enabling rapid progress in monitoring the Earth's environment to support scientific research and government policy."

Kevin Tansey, Professor of Remote Sensing and Principal Investigator at the University of Leicester said: "After 20 years of research into the use of satellite data to measure burned area and severity from local to global scales, the opportunity to work with CGI and agency partners to develop new wildfire services is very exciting. I am further delighted that this project will be one of the first to be delivered out ofSpace Park Leicester, our new state-of-the-art, high-tech facility for research, development and manufacturing.".

CGI has been delivering complex, mission-critical spacesoftware systems for clients across Europe, Australia, Asia and North America for over 40 years, supporting satellite navigation, communications and operations, to space enabled applications. CGI's partner, the University of Leicester, have a wealth of experience within EO domain and are one of the leading academic institutions with the UK.CGI is a partner in the Manufacturing, Engineering, Technology and Earth Observation Centre (METEOR) at Space Park Leicester.

About CGIFounded in 1976, CGI is among the largest independent IT and business consulting services firms in the world. With 76,000 consultants and other professionals across the globe, CGI delivers an end-to-end portfolio of capabilities, from strategic IT and business consulting to systems integration, managed IT and business process services and intellectual property solutions. CGI works with clients through a local relationship model complemented by a global delivery network that helps clients digitally transform theirorganizations and accelerate results. CGI Fiscal 2020 reported revenue is C$12.16 billion and CGI shares are listed on the TSX (GIB.A) and the NYSE (GIB).Learn more atcgi.com

SOURCE CGI Inc.

http://www.cgi.com

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European Space Agency selects CGI to develop services combining Artificial Intelligence and Earth Observation for Wildfire Mapping - PRNewswire