In the cybersecurity sector, artificial intelligence testing is crucial. This is because AI has the potential to help cybersecurity overcome some of its major obstacles. And there are many obstacles, including the incapacity of many organizations to stay on top of the numerous new risks and attacks that emerge as the internet and technological usage increase.

AI-powered cybersecurity is expected to change how we respond to cyber attacks. Because of its capacity to study and learn from enormous volumes of data, artificial intelligence will be crucial in identifying sophisticated threats. Moreover, AI testing is an all-in-one answer to safeguard these gadgets from malicious actors, as new technology and gadgets are always available.

This blog will walk you through the difficulties that the cybersecurity sector is now facing, the significance of employing Artificial Intelligence testing to overcome those difficulties and some of the drawbacks of doing so. Finally, we shall examine some actual applications of AI in this area before we conclude.

Cybersecurity describes the processes followed by people or organizations to safeguard their online-connected computer hardware and software against cyberattacks.

The proliferation of emerging digital technologies like the Internet of Things (IoT). The rising frequency and intricacy of cyberattacks and rigorous data protection laws for data security. An uptick in attacks that target software supply chains is the key driver of the cybersecurity market.

In addition, the COVID-19 pandemic has increased the incidence of malicious attacks on databases in large enterprises. They are necessitating tighter database protection and fostering the expansion of the cybersecurity industry. In healthcare, banking, insurance, manufacturing, and financial services, growth in adopting organization security solutions is provident.

You may be surprised to learn that human mistake accounts for 95% of cybersecurity breaches, according to a Google survey. These mistakes might include everything from downloading a virus-filled email attachment to using a weak password to access an unsafe website. According to studies, phishing attacks are among the most common cyber events, CEO fraud, stolen computers, and ransomware assaults. The effects of these attacks are stunning, even though they may seem easy to handle. In small and medium businesses (SMBs), data breaches cost, on average, $3.9 million. The top four are the top four: large-scale data monitoring, a slower turnaround, a lack of threat understanding, and organizational compliance standards.

Cybercrime is always changing, with hackers constantly refining their tactics to cause the most harm, complicating the issues outlined in the previous section. Malware that could modify its source to evade detection made up 93.67% of the malware observed in 2019. Additionally, within the same year, 53% of consumer PCs and 50% of commercial computers both relapsed the infection. To eradicate this virus from its source, action and awareness are vital.

We should all be aware of the following examples of the typical cybersecurity threats that clever hackers have cleverly created.

When a hacker uses the social engineering technique of phishing, they send you an email that contains a dangerous link. By clicking the link, you could give them access to your computer so they can infect it with a bug and steal all of your personal data.

If your systems hardware and software are not updated to the most recent versions, missing critical security updates can be a risk. It can be introduced to back doors or trojans and obtain access to the system.

Data going to and from a network endpoint can be hindered by malicious actors and decrypted. If they arent caught in time, they might alter it, tamper with it, or use it illegally.

Since more people are using private and public clouds, unencrypted data stored there is an open invitation to malicious hackers. Data saved in the cloud can also be composed due to unreliable interfaces or APIs, insufficient access control, and inadequate security architecture.

Mobile devices internal operating systems may become unreliable due to this dangerous malware, which could reduce their functionality. This frequently occurs as a result of URLs being insecure online. In addition, downloaded applications with security flaws also contribute to mobile virus problems.

One of the most common types of cyberattacks is ransomware, in which the attackers send a virus into peoples personal laptops and smartphones to access and use the data on those devices. They then want a ransom to give you access to it again.

A notable benefit of AI testing is that it significantly reduces some labor-intensive jobs known to be time-consuming, such as security monitoring, which is unquestionably a significant time-sink for IT security experts. AI testing can do this repetitious labor instead of humans having to keep an eye on numerous gadgets. To enforce proper cybersecurity, decrease attack surfaces, and detect malicious behavior, AI and machine learning testing need to be in collar.

Lets look at some additional crucial areas where AI testing proves to be of the utmost significance:

Each day, data of over 2.5 quintillion bytes are produced. Artificial intelligence (AI) technologies can assist in automating data processing. It makes sense of vast amounts of data that would be impossible for humans to understand in a usable manner. Security experts cannot evaluate and classify every piece of information because firms face millions of risks. As a result, it is tough for security specialists to foresee dangers before they destroy IT systems. Artificial intelligence testing can identify numerous cyber-security threats and issues without human analysts.

By analyzing how users typically interact with their devices, ML algorithms are intelligent enough to learn and create a pattern of user behavior.

AI testing flag the user as suspicious and possibly block them if it notices unexpected behaviors that are out of the ordinary. These actions include altering the users typing speed or attempting to access the system at odd times.

AI testing analyzes millions of events and detects a wide range of threats. These threats include malware that exploits zero-day vulnerabilities, phishing attempts, and malicious code downloads. As a result, AI and ML have emerged as essential information security technologies. Companies may better understand dangers and respond to them faster thanks to these insights. It also helps them adhere to the best security procedures.

Spam detection, as well as other types of social engineering aided by natural language processing(NLP), is a subfield of deep learning.

In general, NLP employs a variety of statistical techniques and extensively learns typical verbal and nonverbal communication patterns to identify and prevent spam content.

These systems can detect harmful network activity, guard against intrusions, and warn users of potential dangers. Systems using ID and IP frequently prove useful in addressing data breaches and improving the security of user information.

Furthermore, it is feasible to guarantee a more effective operation of ID/IP systems by utilizing deep learning, recurrent, and convolutional neural networks. The methods above will make it easier for security teams to distinguish between safe and risky network activity. In addition, it improves traffic analysis accuracy and decreases false alarm frequency.

When it comes to hacking networks, cybercriminals are becoming more skilled and quick. The use of cutting-edge technology, such as machine learning, makes it easier to detect cyberattacks. However, it is hard for humans to keep track of every connected system for every possible hazard. These data are used to educate AI-powered devices, which can then learn from real and digital world data.

Given the rising interest in AI in cybersecurity, its realistic to assume that in the future, well see even more sophisticated solutions capable of resolving difficulties in the business that is even more difficult and complex. By automating threat detection, artificial intelligence testing will strive to save cybersecurity and contribute to internet safety.

IT security professionals now utilize AI to reinforce sound cybersecurity procedures. It reduces the attack surface and tracks malicious activity. In addition, it evaluates and deals with massive volumes of data and assesses human behavior.

This is by no means a comprehensive list of its functions. Its preferable to embrace technology today and keep up with the times if you want to be more prepared for the AI-testing cybersecurity future.

Featured Image Credit: Provided by the Author; Thank you!

I am Timothy Joseph, a testing expert with over 10 years of experience in QASource. In a nutshell, a techie who enjoys studying the pinnacles of current technology & creativity!

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How Artificial Intelligence Testing is Changing the Cyberworld? - ReadWrite

Welcome to From Florida, a podcastthat showcases the student success, teaching excellence andgroundbreakingresearch taking place atthe University of Florida.

To thrive economically and be globally competitive, the U.S. needs to add many more workers who understand and have expertise in artificial intelligence. In this episode, David Reed, inaugural director of the Artificial Intelligence Academic Initiative Center explains how the University of Florida is taking a comprehensive approach to meet that need. Produced by Nicci Brown, Brooke Adams, James Sullivan and Emma Richards. Original music by Daniel Townsend, a doctoral candidate in music composition in the College of the Arts.

For more episodes of From Florida, click here.

Nicci Brown: Artificial intelligence is a part of so much of our day to day lives and it's spurring major societal and economic change. Because of this, the University of Florida is taking a unique approach to this technology. Instead of AI being a focus in only certain colleges or programs, UF is integrating artificial intelligence across the university, from instruction to research to university operations and in disciplines ranging from medicine to the arts.

I'm your host, Nicci Brown, and today on From Florida we are going to talk about the University of Florida's AI initiative and specifically the role of the Artificial Intelligence Academic Initiative Centerin carrying this work forward. Our guest today is David Reed, the inaugural director of the center. Welcome, David.

David Reed: Thank you very much. It's great to be with you today.

Nicci Brown: David, as I mentioned in the introduction, you are the Inaugural Director of the Artificial Intelligence Academic Initiative Center, AI Squared, as we call it. First of all, congrats and, second, what is the purpose of the center?

David Reed: Well, thank you. So, the purpose of the center is really to support all things artificial intelligence at the University of Florida and that's everything from marketing about what we do to enhancing the courses that we offer our students, getting faculty up to speed on artificial intelligence, adding it to their research repertoire if they don't use those techniques already and really just everything and anything related to artificial intelligence.

Nicci Brown: Quite a large role.

David Reed: It is.

Nicci Brown: Could you tell us more about the reasons UF made artificial intelligencea focal point for our campus?

David Reed: Absolutely. So, first of all, artificial intelligence is a big catchall term and we use it for all kinds of things. It's a technique to mine large amounts of data. It's a way to help computers make decisions. And so, when we talk about AI, we really are talking about a broad set of different kinds of things. But what we're finding and what industry partners are telling us is that artificial intelligence is now being used in one way or another in disciplines from A to Z. Everything imaginable. Anywhere you can collect large amounts of data, AI has the potential to really help you understand your business or your art or anything that you're doing. And so, because of that, we feel like it's important for all of our students to have the opportunity to learn how AI is already being used in their current discipline.

Nicci Brown: And so what does that look like as far as courses that are available and student enrollment in those courses?

David Reed: Well, we have over 200 courses in AI and data science already on the books here at UF that students can take and at the moment we have over 6,000 students taking those courses. So, we know that our students are engaged. They already understand the importance of artificial intelligence. But we've also erected things like an undergraduate certificate where an undergraduate can take three courses in AI and come away with really good skills about applying artificial intelligence right in their discipline.

Nicci Brown: Also, there are opportunities for staff at the university as well to learn more about AI.

David Reed: Indeed. We have a whole suite of professional development courses. These are meant to upskill workers who are already employed or people who want to become employed with artificial intelligence skills. They can take these courses and little-by-little they learn the ins and outs of artificial intelligence, but, more importantly, and this is true for our students as well, they learn how artificial intelligence is used right in the specific discipline that they're working in.

Nicci Brown: And I'll fess up, I've signed up for the courses. I've yet to get started. But one of the ones that I was really fascinated in learning more about was the ethics course.

David Reed: Indeed. So artificial intelligence done without an ethical framework often goes awry very quickly and so we require an ethics course for the undergraduate certificate. We also require it for the undergraduate major that we have in data science. It's critically important to understand how artificial intelligence can either be misused in malevolent ways or just misunderstood and used poorly. And the ethics course really helps people understand that.

Nicci Brown: So, we're hiring faculty with specialized expertise in AIto achieve this across-the-curriculum activity and they truly do cross all disciplines. We've heard about some of the courses. Can you tell us a little more about the research that's happening at UF?

David Reed: Sure. So, we've hired over 100 new faculty in artificial intelligence and they're spread across all 16 of the colleges that we have here at UF, and so they really are all over campus. So, for instance, we hired David Grant in the Department of Philosophy within the College of Liberal Arts and Sciences and he actually studies the ethics of artificial intelligence. Specifically, he studies how organizations use AI to make really high impact decisions.

But we have people in architecture. For instance, Vernelle Noel uses AIto study incredible designs of costumes at Trinidad's Carnival. So, there's just these wide uses of artificial intelligence. Joel Davis in business studies how executives and consumers incorporate AI advice into their decision-making process about buying or selling products. Nicolas Gauthier, an anthropologist at the Florida Museum, uses AI to study human-caused changes in the environment, whether it's in the past or the present or predicting the future, and that's really where the AI comes in. And then, lastly, Mickey MacKie in geology uses artificial intelligence to study glaciers. I mean, it just really is the applicability of artificial intelligence is so widespread.

Nicci Brown: Yeah, it's incredible when you think about, and we have had Mickey on the program before, this person who is studying at the University of Florida or researching at the University of Florida and also teaching and she's studying glaciers. It really is this broad range, for sure. What are some of the priority initiatives that you've developed for the center because this is an enormous task that you have and in an inaugural role you really have to set the playing field.

David Reed: Indeed. And because it's university-wide, the projects that we have really vary tremendously. We're trying to support faculty, for one, so we are inviting 40 faculty who study artificial intelligence to a communications workshop that lasts all year, its seven-day long sessions, that'll be starting this fall, where we can teach faculty how to talk about their research in artificial intelligence in new and basically concrete ways. Artificial intelligence can be hard to understand sometimes so we're helping them in their communications efforts. That's one thing.

We're also working with the Career Connection Center. If you're not familiar with them on campus, they are ranked No. 1 or No. 2 every year in career services helping our students get into meaningful jobs after they graduate. But we're working with them to better describe the skills that our students are learning in their courses so that it translates on their resume to jobs so that employers can really understand what it is that they've learned and how it's applicable in the jobs that they're applying for.

We're also trying to incentivize faculty to build out new artificial intelligence courses, and we're doing that in a number of different ways so that students have more opportunity to take courses in artificial intelligence.

And then, lastly, one of our projects coming up this fall is called AI Days and that's October 27 and 28. We're trying to get the whole campus engaged in artificial intelligence. And, for students, we have a pitch competition where they pitch a business idea. We also have a hackathon. And for those two events for students there's $50,000 in cash prizes for the winners of the pitch competition and the hackathon. So that event will be an opportunity for faculty, staff, and students to learn a whole lot more about artificial intelligence.

Nicci Brown: You mentioned a little bit earlier about industry and what you are hearing from partners and, certainly one of the things, particularly as a public institution, as a flagship for the state, we do talk about our service to the state of Florida and I think more broadly to the nation. How do you see that all intertwining? What are those kind of communications that you're having?

David Reed: Yeah, absolutely. So, the National Security Commission on Artificial Intelligence,a commission from the federal government, produced a final reportlast year that said that the United States is woefully behind in producing people who understand AI and can use it and that the United States is vulnerable both in terms of economic competitiveness but also in terms of defensive competitiveness. And so, they called for a better and larger AI workforce by 2025. And that's something that we've taken very seriously. That's why we're no longer teaching AI just in the College of Engineering but spreading that education across the full breadth of the university. So, what we're hearing from industry as well as federal partners and others is they need a skilled workforce immediately. And so, we've taken that to heart. We're the only university really doing this. We're really out in front of all of our competitors by trying to create an AI workforce, people who can apply AI specifically in their discipline, and we're going to be doing that within a year or so easily.

Nicci Brown: I've heard as well that some of the things that we're doing, particularly in the College of Ed, but also in the College of Engineering, is looking at K through 12 and how even if we have students who may not feel that university is for them they can become literate in what AI means and that will help them in their future as well.

David Reed: Yeah, absolutely. So those faculty that you've talked about here at UF are working with the Florida Department of Education to create the nation's first artificial intelligence curriculum for public schools. So, typically, in middle schools, but also in high schools, they're starting to teach the concepts of artificial intelligence and data science, and there are two reasons for that. That will prepare some students to come to university and be more prepared for what they experience here. But for those who don't, they're going to be much better citizens in a digital world if they understand the data that's being collected around them and how it's used and so forth. And so it really is important given the digital world that we live in, given how much artificial intelligence is being used around us all the time, the more literate we are about that, the better.

Nicci Brown: And I think there is something to be said in this range just in terms of democratization of information and access to knowledge and getting that available across all groups. What is the university doing as far as that's concerned?

David Reed: Yeah. That's a key component of what we're trying to do. There are many ways in which we're trying to democratize AI. One is we're teaching it across all disciplines here at UF. That's probably the most straightforward. It doesn't matter what your major is, we have courses designed for you to specifically learn artificial intelligence with no computer programming background required before you start or anything like that.

We're also working with public schools as we just talked about. We're also partnering with a number of other colleges and universities around the state to teach their faculty and their students about artificial intelligence. In particular, Miami-Dade College, which is a Hispanic-serving institution in Miami, we're helping their faculty learn about artificial intelligence so they can create new courses in AI. Also, getting their students to come to the University of Florida for graduate degrees.

In addition, we have FAMU in Tallahassee. We have a partnership with them where we're doing the exact same thing. One with Santa Fe College here in Alachua County and with Palm Beach State College in South Florida, where we're partnering with their faculty, learning together about how they can incorporate artificial intelligence into their courses and, by doing that, their students are also gaining this experience as well.

Nicci Brown: You mentioned those other organizations and other educational institutions. It sounds like what we are building here is a model that is transferable.

David Reed: Indeed. There's nothing special that we're doing here that no other college could do. Anyone could do this if they set their mind to it. We're really fortunate here at UF to have been gifted this incredibly large AI supercomputer and we use it in all kinds of incredible ways, but that's not absolutely necessary for teaching AI across-the-curriculum. This is something that any other college or any other university could do and we're trying to find as many partners who want to walk this road with us and do this with us as we can.

Nicci Brown: That sounds like it's intentional on your part.

David Reed: It is, very much so. When we think about it, we're trying to think of all of the potential ways that a learner might get on the path to learning AI. That includes K-12. It includes tech and vocational schools. It includes community colleges, universities even beyond the University of Florida, and the employees who are already working and need some professional development courses to learn how to use AI. And so, we really want to make this something that everybody can participate in.

Nicci Brown: When we think about AI, quite often the first thing that comes to mind for many people is this cold, dark, futuristic, very non-human approach to things. What would you say to people who have that in their mind?

David Reed: Yeah, I think it's a lot of fun reading science fiction and I like to, too, but the reality of artificial intelligence is it is around us all the time. It's there when you use facial recognition to turn on your iPhone, it's there when Amazon is recommending a product to you, and it isn't going to go away this time.

What we are doing with artificial intelligence, for example, it's not going to replace physicians, but what it can do is allow physicians as a tool to be able to find patients for clinical trials much faster than they would otherwise. It's not going to replace lawyers, for instance, but what it might do is help lawyers understand a wider array of potential case studies or precedents coming before that they can base approaches on in a legal system.

And so it really is the combination of experts in their field utilizing the tools of AI to try and do their work better or in some cases do their work faster. I don't think it's going to create autonomous robots that take over the world, but it is going to help you drive your car more safely and lots of other things, and that kind of work is happening right now. And so that's whats exciting about artificial intelligence

Nicci Brown: And for people who may fear that this is going to take their job, what would you say to them?

David Reed: Yeah, I think the prognosticators who love to talk about this and who probably know vastly more than I do, they do say that there will be some jobs that are lost as a result of automation. And that's been true for a very long time, all the way back to the first industrial revolution. But it's also creating jobs at the same time where the skills and the decision making that the human possesses, think of creativity, for one, that's really required for a particular process, is always going to be necessary. So, if you're doing something that can be fully automated, then that may take those jobs. But I think for the vast majority of people who learn this technique or these skills, they're going to have opportunities to expand their employment opportunities quite greatly.

Nicci Brown: One of the areas that I've been particularly interested in learning more about is in the applications when it comes to agriculture. And, of course, with IFAS, we are so strong here at the University of Florida and it's such a large part of what we do. Could you share a little bit more about some of the ways it's being applied there?

David Reed: Oh, absolutely. Yeah, so precision agriculture is a way to use decision making as well as lots of data to try and be smarter about the ways in which you're trying to, say, grow plants. And so, for instance, you can send drones over agricultural fields and the drones can capture so much data, visual data, as they pass over, but it takes an enormous amount of human effort and human time to then download and look at those videos. And it's only so much information that a human could get from those images, but if you use artificial intelligence, they can mine through that data much faster and do things like find areas that are over watered or underwater. They can also find areas where there's crop damage due to pests.

And so, in thinking about precision agriculture, just the fact that you can fly drones over an agricultural field and pull from that massive amounts of data that can then be analyzed pretty quickly to make very specific changes to the agricultural process, those kinds of things are now getting to be widespread in their use in agriculture. And there are many more examples of how artificial intelligence is being used in agriculture alone.

Nicci Brown: And connected to that, of course, we're very mindful of our environment and preserving our environment and protecting our environment. I would imagine that AI also has some applications in that realm as well.

David Reed: Absolutely. Here at UF, we have the Center for Coastal Solutions where they monitor water quality and air quality. They have a monitoring station, for instance, in Charlotte Harbor in Southwest Florida and they collect massive amounts of data very, very quickly from these monitoring stations and from satellites and other things. And so with that, the company, SAS, it's a statistical analysis software company, they've partnered with the Center for Coastal Solutions to create a data model that we can then apply artificial intelligence to. Just how you store the data is critically important to the process of artificial intelligence. But what they'll be able to do is use that to monitor real time events like predicting red tides, for instance, and then also, in partnering with UF Health, be able to warn people who might be at risk of the effects of red tide, respiratory illness, for instance, in elderly populations before the red tide actually occurs. And so, whether it's environmental or health or agriculture, AI is really being applied in so many different domains.

Nicci Brown: You mentioned earlier about the courses that our students are signing up for. Could you give us a sampling of some of the names of these courses or what they're focused on?

David Reed: Yeah, absolutely. So, one of the things I've said a couple of times is you get to learn about artificial intelligence right in your discipline. So, for the undergraduate certificate, the students would start out with two required courses, one's called Fundamentals of AI, and it's the one that really allows you to wade into the AI pool from the shallow end.

You don't have to have any prior experience to take this course. And then there's the required ethics course, which is fantastic. But once you take those two, the third course in that series is something that's within your major. So, for instance, there's AI in Media and Society. If you care about how artificial intelligence is used in marketing and communications and media and so forth.

There's one for students who are interested in design and construction. It's called AI in the Built Environment. There's one for agriculture and life sciences called AI and Agriculture and Life Sciences. And there are many of these spread across the full breadth of the university, AI and the social sciences and on and on. So, there are lots of these different courses that are diving in and learning how artificial intelligence is applied right in your major.

Nicci Brown: And for those of us who are in the workforce and want to learn more, what are the options there?

David Reed: We have a series of seven different courses that you can take. There's a one-hour teaser, if you will, that you can listen to. It's free to go to that and you can find these on ai.ufl.edu. But these one-hour courses just give you a flavor of what you would learn. For a small amount of money, there's also a four-hour bite size chunk that you can take. Or you can actually sign up for a faculty led course that's a total of 15 contact hours where you do a much deeper dive. And you can learn about the fundamentals of AI, you can learn about AI ethics, but then you can also learn about AI in these different applications. Agriculture is one of them. Health and medicine is coming online soon. Business is already developed and a couple of others. And so it gives you the opportunity to really learn about AI, both the fundamentals, the ethics and how it applies in your area.

Nicci Brown: I can only imagine how busy you are and some of the things that you come in contact with. Is there anything about your work recently that has surprised you and even you were like, "Wow, this is just beyond anything I imagined?

David Reed: Well, yeah. The first thing that really surprised me was, we did a tally to see how many students were engaged in artificial intelligence courses, and I was really hoping it would be 1,000 or maybe 2,000 at the most. But to see that we had 6,000 students already taking AI and data science courses when we had really not started any direct marketing to students to tell them about what we were doing, I was very relieved. That was a wonderful sight and it just tells you the students here at UF are obviously in touch with what they're going to need in their professional lives and so they were already seeking out these courses. And that was just great to see.

Nicci Brown: Are there any other partners that you'd like to mention that you're working with right now that people might be interested in knowing about?

David Reed: Absolutely. We've talked about some of the other colleges that we're working with. We've talked about the fact that we're working with the Florida Department of Education on K-12. Those are really important partnerships.

But we also have partnerships with industry too. Our partnership with NVIDIA is one that has even predated our artificial intelligence initiative. They gifted us this incredible AI supercomputer, but they also put on campus an AI Technology Center where two of their engineers are embedded on our campus with our faculty to help them do their research better on HiPerGator AI, the AI supercomputer. We also have a great partnership with IBM where they made their full suite of artificial intelligence software, including Watson, available to our faculty and staff for free.

We also have partnerships with companies like L3Harris. We did professional development for them. Our faculty at the College of Engineering trained some of their trainers on how to train employees about artificial intelligence and data science, and then turned all of that material over to them. And so we've had a wonderful partnership with them. And we're looking for many other industry partners who might want to partner with us in terms of capstone courses for our seniors who have taken a deep dive into artificial intelligence already. That could give those students the ability to solve some real world problems with real world data and really prepare them for the workforce in a deep and meaningful way.

Nicci Brown: It sounds like this approach is inclusive in every sense of the word.

David Reed: It is in that it covers all of our students. It's graduate and undergraduate and professional and we really are trying to make sure that anybody who wants to be included in this can be.

Nicci Brown: David, could you tell us more about the partnership with the SEC?

David Reed: Oh, absolutely. So, in the work that we're doing trying to teach AI across the curriculum, we're trying to find as many partners who will do that alongside us as we possibly can. The Southeastern Conference, what we typically think of as an athletic conference, also partners on academic missions, too, and the latest one is artificial intelligence. And so we've had a working group that have met, all of the schools of the SEC have had a representative at this meeting over the last year where we've talked about what we're doing in the AI and data science space.

For instance, we've heard from faculty at other institutions about AI centers that they have. We've talked about our ability to teach AI across-the-curriculum here at UF. And at this point we're exchanging ideas and discussing best practices for how we can educate our students in artificial intelligence and create a regional center of excellence in the southeastern United States.

Nicci Brown: David, thank you so much for joining us today. It's been a real pleasure speaking with you.

David Reed: Oh, the pleasure was mine. Thank you very much.

Nicci Brown: Listeners, thank you for joining us. Our executive producer is Brooke Adams, our technical producer is James Sullivan and our editorial assistant is Emma Richards. I hope youll tune in next week.

Continued here:
The U.S. is falling behind in artificial intelligence. Here is what one university is doing about it . - University of Florida

CSU professor says artificial intelligence can be good atmospheric science teachers.

FORT COLLINS, Colo. The science of weather prediction improves every year but there are still so many mysteries to solve.

Colorado State University (CSU) professor Elizabeth Barnes believes that some of those answers might come from artificial intelligence (AI) also known as machine learning. Essentially thats when a computer program makes a prediction based on patterns that it finds in huge amounts of data.

"It can sort through data much faster than we can and in most cases it can also do it better," said Barnes. "And sometimes it might even find relationships that we didn't know were there. We can learn new science."

Barnes said she is often impressed with the accuracy of an AI-driven climate forecast but she is more interested in learning how the machine got that answer in the first place.

What Barnes and her collages are working on at CSU is called Explainable Artificial Intelligence (XAI). Barnes said it's like cracking the lid of the so called black box that seals the methods behind the machine.

We take that forecast or that prediction, and the idea is that you push that information back through your machine learning model," said Barnes. "And it gives you a map of what was important for it to make its decision. What were the ingredients it used.

Barnes said that road map of information has already led to a new understanding of how the ocean conditions impact long-range weather more than a month in advance.

"It's also helping us learn more about our climate models," Barnes said "In the insides of the models, pieces are actually being replaced with machine learning algorithms to do a better job."

Barnes said one of the beauties of machine learning is that you can keep the rules very simple and can almost use any type of data, even maps, words and images instead of just numbers and statistics.

It's a straight data driven approach to prediction modeling; AI doesn't need any equations to find a solution. Unlike numerical weather forecast models which are a more physical approach. Those models use things like Newtonian and Thermodynamic equations to make a weather prediction.

Machine learning tools allow us to be creative about how we do science," said Barnes. "This has allowed me to think about how I ask questions and what kinds of questions I ask, without barriers in the way I think a lot of climate science had in the past.

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CSU hopes artificial intelligence can teach us more about the atmosphere - 9News.com KUSA

Violin-shaped buildings in the style of Gaudi produced by AI art tool Midjourney, from a prompt by Evrim Yazgin.

AI art tools like Craiyon (formerly DALL-E mini) and Midjourney have been making waves on the internet over recent months. But are these artificial intelligence tools exhibiting creativity, or just clever mimics? How will AI art impact artists themselves? And how can machine learning be effectively used in artistic, creative and design endeavours most effectively?

Cosmos science journalist Evrim Yazgin tackles these questions and speaks with AI expert Professor Jon McCormack, Director of Monash Universitys SensiLab, in the article Creativity and AI in Cosmos Magazine #96.

At this years Colorado State Fairs annual art competition awarded its prize to an AI-generated piece entitled Thtre Dopra Spatial by Jason M. Allen. But Allen didnt paint or sculpt the work it was generated by AI art tool Midjourney.

While Allen was open about the pieces origins, submitting it under the name Jason M. Allen via Midjourney, that the prize was awarded to a piece created by a machine learning tool has enraged some artists.

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Impressive and controversial as tools like Midjourney are, they represent only the tip of the AI art iceberg.

AI expert Professor Jon McCormack, Director of Monash Universitys SensiLab says AI should not be thought of as intelligent, creative or artistic. These systems are kind of statistical mirrors on broad aspects of human culture, McCormack explains.

McCormack stresses that AI is best used as an aid to human creativity.

In Cosmos Magazine #96 McCormack shows Evrim Yazgin around SensiLab, where AI researchers are creating design and art pieces. Of note are a mirror which writes a poem based on the onlookers expression, a machine which can learn from human drummers how to make a beat, and a tapestry drawing on the stories of female convicts in Australia.

Cosmos Magazine #96 is available now at all good newsagents or Subscribe at comosmagazine.com and save up to $35.

Cosmos is a quarterly science magazine. We aim to inspire curiosity in The Science of Everything and make the world of science accessible to everyone.

Theres never been a more important time to explain the facts, cherish evidence-based knowledge and to showcase the latest scientific, technological and engineering breakthroughs. Cosmos is published by The Royal Institution of Australia, a charity dedicated to connecting people with the world of science. Financial contributions, however big or small, help us provide access to trusted science information at a time when the world needs it most. Please support us by making a donation or purchasing a subscription today.

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AI Art: Proof that AI is creative? - Cosmos

Far from being a futuristic concept relegated to the realms of science fiction, the use of artificial intelligence (AI) in the workplace is becoming more common. The benefits of using AI are often cited by reference to time and productivity savings. However, the challenges of implementing AI into HR practice and procedures should not be underestimated.

AI technologies are already being used across a broad range of industries, at every stage in the employment cycle. From recruitment to dismissal, their use has significant implications. In recent months, incidents at Meta, Estee Lauder and payment service company Xsolla have hit the headlines for utilising AI when dismissing employees.

All three companies used algorithms as part of their selection process. For Meta and Xsolla, the algorithms used analysed employee performance against key metrics to identify those who were unengaged and unproductive. These employees were subsequently dismissed.

Similarly, Estee Lauder used an algorithm when making three makeup artists redundant, which assessed employees during a video interview. The software measured the content of the womens answers and expressions during interview and evaluated the results against other data about their job performance.It led to their dismissal.

Where algorithms are used in place of human decision-making, they risk replicating and reflecting existing biases and inequalities in society.

An AI system is created by a variety of participants, from those writing the code, inputting the instructions, those supplying the dataset on which the AI system is trained and those managing the process. There is significant scope for bias to be introduced at each stage.

If, for example, a bias towards recruiting men is included in the dataset, or women are under-represented, this is likely to be replicated in the AI decision. The result is an AI system making decisions that reproduces inherent bias. If unaddressed, those biases can become exaggerated as the AI learns becoming more adept at differentiating using those biases.

To mitigate this risk, HR teams should test the technology with comparison between AI and human decisions looking for bias. This is only going to be effective in combating unconscious bias if the reviewers comprise a diverse group themselves. If bias is discovered, the algorithm can and should be changed.

AI systems are increasingly being viewed by employers as an efficient way of measuring staff performance. While AI may identify top performers based on key business metrics, they lack personal experience, emotional intelligence and the ability to form an opinion to shape decisions. There is a danger that low-performing staff could be disregarded solely on an assessment of metrics. Smart employees are likely to find ways to manipulate AI to their advantage in a way that might not be so easy without technology.

It is tempting to trust AI to limit legal risks by using it for decision-making. Superficially, this may be right, but the potential unintended consequences of any AI system could easily create a lack of transparency and bias equivalent to that of its human creators.

When AI systems are used, there is an obligation to consider how these might impact on fairness, accountability and transparency in the workplace.There is also a risk of employers exposing themselves to costly discrimination claims, particularly where the policy of using AI disadvantages an employee because of a protected characteristic (such as sex or race) and discriminatory decisions are made as a result.

Until AI develops to outperform humans in learning from mistakes or understanding the law, its use is unlikely to materially mitigate risk in the meantime.

Catherine Hawkes is a senior associate in the employment law team at RWK Goodman.

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Artificial intelligence in the workplace - ComputerWeekly.com

WINTERTHUR, Switzerland October 6, 2022 The Rieter Group is constantly expanding its technology leadership. Together with the Johann Jacob Rieter Foundation, the company is therefore supporting a new Endowed Professorship for Industrial Artificial Intelligence (AI) at the Zurich University of Applied Sciences (ZHAW) School of Engineering. The Professorship is dedicated to teaching and research in the field of industrial applications of Artificial Intelligence and will be announced later this year.

The new Endowed Professorship will be established at the Center for Artificial Intelligence (CAI) of the ZHAW in Winterthur. It will focus, in particular, on the application of machine learning methods and knowledge-based systems in connection with processes in production and service. The use of artificial intelligence in industry is becoming increasingly important, especially with regard to the potential of data for evaluation and control of complex processes. The support of the Johann Jacob Rieter Foundation and the Rieter Group will allow us to further expand AI research in the field of industrial applications, explains Prof. Dr. Dirk Wilhelm, Director of the ZHAW School of Engineering.

For Rieter, the commitment is related to the implementation of its technology leadership strategy. The use of Artificial Intelligence will make a significant contribution to automation and process optimization, and thereby advance sustainability in the textile industry. This makes it an important element of the leading technology that Rieter offers, emphasizes Rieter CEO Dr. Norbert Klapper.

The contribution of the Johann Jacob Rieter Foundation to sponsoring the Professorship is in line with the Winterthur Cluster Initiative. The increasing digitalization of production processes opens up new perspectives for Winterthur as a business location. The Smart Machines cluster is growing in importance, says Thomas Anwander, member of the Foundation Board, and adds: The Endowed Professorship for Industrial AI at the ZHAW aims to promote Winterthur as a technology location by pooling locally available strengths in mechanical engineering and Industry 4.0.

The Endowed Professorship will serve to build expertise in the field of Industrial AI and will oversee a group that will focus on teaching and research pertaining to trustworthy machine learning. This involves, for example, the deployment of artificial intelligence with the aim of optimizing production processes in relation to the use of raw materials and energy, and making expert knowledge more readily available.

In addition to research, for the purpose of knowledge transfer, the new professorship will also be active in teaching, in the bachelors degree programs in Computer Science and in Data Science, in the Master of Science in Engineering, and in continuing education.

The annual commitment of CHF 300 000 over a period of six years will be financed equally by the Rieter Group and the Johann Jacob Rieter Foundation.

Posted: October 6, 2022

Source: The Rieter Group

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Rieter And The Johann Jacob Rieter Foundation Sponsor Professorship For Artificial Intelligence At The Zurich University of Applied Sciences (ZHAW) -...

SAN FRANCISCO, Oct. 5, 2022 /PRNewswire/ --The global artificial intelligence in cybersecurity market size is estimated to reach USD 93.75 billion by 2030, expanding at a CAGR of 24.3% from 2022 to 2030, according to a new study by Grand View Research, Inc. An unprecedented spike in cyber incidents has fostered the demand for AI, cloud, and machine learning for seamless operations, data safety and prompt response to cyber threats. Some factors, such as soaring internet penetration, expanding footfall of connected devices, and escalating data protection concerns, have triggered the need for advanced cybersecurity solutions.

Grand View Research Logo

Key Industry Insights & Findings from the report:

In terms of type, the cloud security segment will contribute notably toward the global market in the wake of the rising prominence of AI and machine learning.

Based on vertical, the BFSI sector will exhibit profound demand for AI in cybersecurity to resist cyberattacks and prevent data leaks.

North America AI in cybersecurity market share will be pronounced due to threats to mobile devices and soaring penetration of IoT and 5G in the region.

Some major players, such as IBM Corporation, Cylance Inc. (BlackBerry), Acalvio Technologies, Inc, Intel Corporation, Amazon Web Services, Inc., FireEye, Inc., LexisNexis, Fortinet, Inc., Micron Technology, Inc., and Darktrace are poised to boost their portfolios in the coming years.

Read 200-page full market research report, "Artificial Intelligence In Cybersecurity Market Size, Share & Trends Analysis Report By Type (Cloud Security, Network Security), By Offering, By Technology, By Application, By Vertical, By Region, And Segment Forecasts, 2022 - 2030", published by Grand View Research.

Artificial Intelligence In Cybersecurity Market Growth & Trends

Artificial intelligence (AI) in cybersecurity has leveraged a faster response to breaches and propelled the efficiency of cyber analysts. AI is likely to be sought for vulnerability management, threat hunting, and boosting network security. In doing so, emphasis on natural language processing, machine learning, deep learning, and neural networks could gain ground during the assessment period. For instance, deep learning has become trendier to track transactions, logs, and real-time data to detect threats. AI is highly sought-after to secure cloud services and on-premises architecture and spot abnormal user behavior.

Story continues

Natural language processing could remain a value proposition to foster the penetration of AI technologies in cyberspace. The trend for natural language inference, sentiment analysis, and text summarization will bode well for major companies gearing to reinforce artificial intelligence in the cybersecurity market share. Prominently, NLP has received impetus for fake news detection, clickbait detection, and rumor detection. Leading companies are likely to bank on NLP to detect malicious language and domain names produced for phishing scams.

Stakeholders predict North America to witness investments galore, on the heels of the high footprint of connected devices, IoT, and 5G. Moreover, the possibility of DDoS attacks and the growing prominence of IoT-enabled activities have prompted major players to bank on cutting-edge technologies to deter cyber incidents. To illustrate, in August 2019, Microsoft was reported to have alleged Russian hackers using IoT devices to breach enterprise networks. Industry participants expect bullish investments in machine learning platforms, threat hunting, and advanced analytics. Besides, Microsoft Security blocked over 35.7 billion phishing and malicious emails and more than 9.6 billion malware threats in 2021.

The competitive landscape alludes to an increased emphasis on organic and inorganic growth strategies, including mergers & acquisitions, product offerings, technological advancements, collaborations, and innovations. For instance, in July 2022, Darktrace rolled out Darktrace PREVENT to assist organizations in pre-empting cyber-attacks. Meanwhile, in August 2022, it was reported that Thoma Bravo was contemplating acquiring Darktrace. In February 2019, BlackBerry completed the acquisition of Cylance to bolster its footprint in AI cybersecurity.

Artificial Intelligence In Cybersecurity Market Segmentation

Grand view research has segmented the global artificial intelligence in cybersecurity market in terms of type, offering, technology, application, vertical, and region:

AI In CybersecurityMarket - Type Outlook (Revenue, USD Billion, 2017 - 2030)

Network Security

Endpoint Security

Application Security

Cloud Security

AI In CybersecurityMarket - Offering Outlook (Revenue, USD Million, 2017 - 2030)

AI In Cybersecurity Market - Technology Outlook (Revenue, USD Billion, 2017 - 2030)

AI In CybersecurityMarket - Application Outlook (Revenue, USD Billion, 2017 - 2030)

Identity and Access Management

Risk and Compliance Management

Data Loss Prevention

Unified Threat Management

Fraud Detection/Anti-Fraud

Threat Intelligence

Others

AI In CybersecurityMarket - Vertical Outlook (Revenue, USD Billion, 2017 - 2030)

AI In CybersecurityMarket - Regional Outlook (Revenue, USD Billion, 2017 - 2030)

List of Key Players of Artificial Intelligence In Cybersecurity Market

Acalvio Technologies, Inc

Amazon Web Services, Inc.

Cylance Inc. (BlackBerry)

Darktrace

FireEye, Inc.

Fortinet, Inc.

IBM Corporation

Intel Corporation

LexisNexis

Micron Technology, Inc

Check out more related studies published by Grand View Research:

IT & Telecom Cyber Security Market - The global IT & telecom cyber security market size is expected to reach USD 82.64 billion by 2030, expanding at a CAGR of 12.1% from 2022 to 2030 according to a study conducted by Grand View Research, Inc. Expansion of telecom networks, emerging BYOD trend, and the emergence of 5G technology are anticipated to increase the network traffic and create loopholes, thereby increasing the risk of cyber-attacks.

Artificial Intelligence In Fintech Market - The global artificial intelligence in fintech market size is expected to reach USD 41.16 billion by 2030, growing at a CAGR of 16.5% from 2022 to 2030, according to a new report by Grand View Research, Inc. Artificial intelligence (AI) is widely used in financial organizations to improvise their precision levels, enhance their efficiency and instant query resolving through digital banking channels. AI technology like machine learning can help organizations raise their value by improving loan underwriting and eliminating financial risk.

Artificial Intelligence Market - The global artificial intelligence market size is expected to reach USD 1,811.8 billion by 2030, according to a new report by Grand View Research, Inc. The market is anticipated to expand at a CAGR of 38.1% from 2022 to 2030. Artificial Intelligence (AI) denotes the concept and development of computing systems capable of performing tasks customarily requiring human assistance, such as decision-making, speech recognition, visual perception, and language translation.

Browse through Grand View Research's Next Generation Technologies Industry Research Reports.

About Grand View Research

Grand View Research, U.S.-based market research and consulting company, provides syndicated as well as customized research reports and consulting services. Registered in California and headquartered in San Francisco, the company comprises over 425 analysts and consultants, adding more than 1200 market research reports to its vast database each year. These reports offer in-depth analysis on 46 industries across 25 major countries worldwide. With the help of an interactive market intelligence platform, Grand View Research Helps Fortune 500 companies and renowned academic institutes understand the global and regional business environment and gauge the opportunities that lie ahead.

Contact:Sherry JamesCorporate Sales Specialist, USAGrand View Research, Inc.Phone: 1-415-349-0058Toll Free: 1-888-202-9519Email: sales@grandviewresearch.comWeb: https://www.grandviewresearch.comGrand View Compass| Astra ESG SolutionsFollow Us: LinkedIn | Twitter

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Artificial Intelligence (AI) in Cybersecurity Market to be Worth $93.75 Billion by 2030: Grand View Research, Inc. - Yahoo Finance

Danny Olivas

John Daniel Danny Olivas, former NASA astronaut and current member of the NASA Advisory Council, has joined the staff of the Visual Intelligence and Multimedia Analytics Laboratory (VIMAL) of USCs Information Sciences Institute (ISI) as Co-Director for AI Initiatives in Space.

Olivas brings considerable experience to VIMAL, ISI and USC. A veteran of space shuttle missions in 2007 and 2009, he is the recipient of two NASA Space Flight Medals and the NASA Exceptional Service and Exceptional Achievement Medals. Olivas completed five space walks totaling over 34 hours outside of the International Space Station. His expertise in space is rivaled only by his passion for it, and he brings both to his new role.

Olivas said, I am excited about the opportunity to help expand USCs footprint in space, for researchers and students alike.

VIMAL which is led by Wael AbdAlmageed, research director at ISI and research associate professor of electrical and computer engineering has a noble and straight-forward mission: to empower students to use artificial intelligence to make the world a better place, one day at a time. With Olivas on the team, VIMAL is now able to look beyond Earth to do this.

Olivas and AbdAlmageed met in July 2022, when they were both invited to Renaissance Weekend, a prestigious, non-partisan, invite-only retreat for innovative thinkers across disciplines held this year in Banff,Canada. They quickly realized they had a lot in common. AbdAlmageed said, Danny [Olivas] and I come from very similar mindsets and backgrounds. We believe in working hard on hard problems, without giving up, for a long period of time. We believe that is enough to make things happen.

Interested in each others area of expertise, the two discussed how to harness their collective grit and work together. A month later, Olivas visited ISI for the day to learn about VIMAL and ISI, and present his thoughts on opportunities for AI in space.

Olivas astronaut background and exposure to space provides a valuable new perspective on new areas for data analysis. Since the beginning of the [NASA] program, NASA has produced more data than has been analyzed, he noted. He added that this data is ripe for analysis through artificial intelligence and machine learning.

One application is climate, which AbdAlmageed called an area of growth for VIMAL.

NASA has instruments that can see things like water vapor in the upper atmosphere, Olivas said. All these kinds of things can not only be analyzed in their individual silos of monitoring, but you can now start to integrate data across the different instruments to build a much more robust picture of how climate changes are affecting a certain region.

Ozone and CO2 in the atmosphere, temperature trends across the planet, drought prediction, sea level detection, deforestation, planet population changes these are just some of the areas where NASA has useful historical data, according to Olivas.

This data has been available by NASA for many, many years, he added, and (they) provide an opportunity to take pieces of this information and start to integrate them together and allow computational technologies to take over where human beings have had to digest this information in the past, to try to make sense of it.

As NASA prepares for a future in which humans will travel to Mars, new and exciting AI applications will emerge. There are some specific robotic applications that are very unique to NASAs space program, Olivas said. For example, a robot that can check the mood of an astronaut based on their facial expressions or voice intonations something that will be increasingly important for mental health as missions extend from months to years with Mars exploration.

Exploration rovers are another area where Olivas sees room for more AI, again, with Mars as the example: It takes about twenty minutes to be able to send a command from Earth to Mars. By the time you get the photograph that your rover is marching over a cliff, its probably the wrong time to send the command to stop moving. So you want to have more intelligence being built on the platform to allow the rover to make decisions for itself.

Climate data, robots and rovers these are areas Olivas might take VIMAL in the future. However, the first problem Olivas and AbdAlmageed plan on tackling is trash, specifically orbital debris.

NASA defines orbital debris as any non-functional human-made object in orbit around the Earth. Think: spacecraft, satellites, rockets or what youd get if any of those collided or exploded. Debris ranges in size from sub-microns all the way to several meters from a paint chip to a school bus with hundreds of thousands of estimated pieces orbiting Earth.

The trouble comes from the fact that this debris travels at orbital velocities that are dangerous to NASAs missions picture that paint chip or school bus traveling at 16,000 mph! Olivas said, its that hyper-velocity impact that causes all sorts of problems, not only with the space station or human spacecraft, but also with satellite technology. It is a serious threat to astronauts, spacecraft and space exploration in general.

The VIMAL team will be looking at ways to use their sensing, computer vision and AI expertise to identify pieces of debris and track them for long periods of time as they orbit Earth.

Olivas extends a strong legacy of innovation in space exploration at USC. He joins fellow former NASA astronauts Paul Ronney and Garrett Reisman, who also serve as faculty at USC Viterbi, which is one of a core group of top schools with a distinct astronautical program. This wont be the first time Olivas and Reisman have worked together, they were classmates in the NASA astronaut program.

To date, school researchers have created innovations in spacecraft propulsion, space science, space environment, space communications, satellites and materials. Astronaut Neil Armstrong was a USC Viterbi alumnus, and the school has a dedicated Space Engineering Research Center at ISI.

USC Viterbi maintains strong connections with pioneering space organizations and alumni who design and build rockets and space launchers, communications and direct broadcasting satellites, navigational systems, crewed space vehicles and planetary probes.

At the end of the day, space is a human endeavor, said Olivas, who pointed out that part of being an astronaut involves looking out for one another. He seemed impressed by this aspect of the work done by VIMAL.

One thing that Ive come to appreciate at VIMAL is the inclusive nature of the collaborations; it is really inspirational, he said.

AbdAlmageed has very intentionally fostered the collaborative environment of VIMAL. Im proud that weve created a culture in the lab where everybody feels a sense of ownership and partnership. He continued, I couldnt have done something like hire Danny [Olivas] without the significant contributions of everyone in VIMAL who do the work day in and day out. This was a team effort. I am also very grateful to Dr. Craig Knoblock, ISI Executive Director, for supporting our ambitious initiatives and pursuits.

Olivas certainly seems excited to join the team, I look forward to sharing, learning and seeing where those opportunities might be with VIMAL, concluded the astronaut.

Published on October 3rd, 2022

Last updated on October 3rd, 2022

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Artificial Intelligence in Space - USC's Information Sciences Institute is on a Mission - USC Viterbi | School of Engineering - USC Viterbi School of...