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Pyramid Analytics expands AI-driven Decision Intelligence with new … – Yahoo Finance

The #1 ranked augmented analytics Decision Intelligence Platform adds deep integration of OpenAI into its 2023 release

LONDON & NEW YORK CITY & TEL AVIV, Israel, March 20, 2023--(BUSINESS WIRE)--Pyramid Analytics (Pyramid), a leading business analytics and decision intelligence provider, announced today at the Gartner Data & Analytics Summit in Orlando, Florida, that the Pyramid 2023 release extends its already category-leading, AI-driven augmented capabilities with the integration of GPT (generative pre-trained transformer) AI technology from OpenAIthe company behind ChatGPT and DALL-E 2throughout the platform, interoperating with its deep set of current AI technologies.

The release harnesses the new GPT AI engines to drive complex logic, data science, and machine learning code generation; AI-driven storytelling capabilities; and even AI-assisted design templates and colors. The effort extends Pyramids broader vision to enable and drive adoption across the enterprise by empowering all users to solve data-centric business problems through no-code and AI-assisted analytics and decision intelligence.

Key facts about Pyramids OpenAI integration

OpenAI is integrated throughout the Decision Intelligence Platformincluding the data preparation, data science, the business analytics and spreadsheet modules, and the storyboard and publication designer modules.

In data preparation: OpenAI can be used to generate SQL, DAX, and MDX code automatically for complex data extraction queries.

In data science: OpenAI can be used to generate Python and R code automatically to drive machine learning logic.

In spreadsheets: OpenAI can be used to build spreadsheet formulas for users constructing business models.

In storyboarding and publications: OpenAI can be used to generate designs for content and graphics.

Separately, OpenAI can be used with existing natural language querying (NLQ) engines to drive and enhance broader insights on enterprise-specific data, ultimately improving the existing tools for delivering automated storytelling and textual analysis.

Story continues

Market recognition

Pyramid has long been recognized as an innovator in the decision intelligence and analytics space. The companys Decision Intelligence Platform was ranked #1by leading analyst firm Gartnerfor "Augmented Analytics" in the 2022 Gartner Analytics and Business Intelligence (ABI) Critical Capabilities report.

Other leading analystssuch as 451 Research, Ventana Research, Dresner Advisory Services, and BARCrecognize Pyramid for its platform-based approach to no-code capabilities and AI/augmented analytics to enable all user types to drive sophisticated analytics easily. Critically, Pyramids existing augmented capabilities (NLQ, Chatbot, Smart Insights, Smart Model, Auto Discovery, Fill in the Blanks, Explain, etc.) uniquely operate directly on enterprise data without data duplication, custom models, proprietary data layers, or specialized data treatments.

Demos

Click here to schedule a demo of the Pyramid Decision Intelligence Platform and to learn more about OpenAI on the platform.

Quotes

Avi Perez, CTO and Co-Founder, Pyramid Analytics: "By integrating OpenAI throughout the Pyramid Decision Intelligence Platform, we are extending our existing AI and augmented capabilities with the latest generative AI tech, transformingand simplifyingthe decision-making experience further. As a no-code/low-code platform, Pyramid is designed to extend advanced analyticsfrom descriptive to predictive to prescriptivefor non-technical businesspeople, allowing them to make informed decisions that drive business outcomes."

Omri Kohl, CEO and Co-Founder, Pyramid Analytics: "At Pyramid, we believe the key to widespread adoption of data analytics requires an analytics experience that meets different peoples needs, regardless of their technical skills or analytics aptitude. By strategically integrating generative AI technologies like OpenAI, we are taking our AI vision to the next level."

About Pyramid Analytics

Pyramid Analytics is the next generation of decision intelligence. The award-winning Pyramid Decision Intelligence Platform empowers people with augmented, automated, and collaborative insights that simplify and guide the use of data in decision-making. Critically, the Pyramid Platform operates directly on any data, enabling governed self-service for any person; and meeting analytical needs in a no-code environment without data extraction, ingestion, and duplication. It combines data prep, business analytics, and data science into one frictionless platform to empower anyone with intelligent decision-making. This enables a strategic, enterprise-wide approach to business intelligence and analytics, from the simple to the sophisticated. Schedule a demo today.

Pyramid Analytics is incorporated in Amsterdam and has regional headquarters in global innovation and business centers, including London, New York City, and Tel Aviv. Our team lives worldwide because geography should not hinder talent and opportunity. Investors include H.I.G. Growth Partners, Jerusalem Venture Partners (JVP), Sequoia Capital, and Viola Growth. Learn more at Pyramid Analytics.

View source version on businesswire.com: https://www.businesswire.com/news/home/20230320005287/en/

Contacts

Pyramid AnalyticsPete VomocilSVP, Global Marketing, Pyramid Analyticspr@pyramidanalytics.com

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Unlocking computer vision and machine learning on highly efficient … – Imaging and Machine Vision Europe

Computer vision (CV) has been widely adopted in many Internet of Things (IoT) devices across various use cases, ranging from smart cameras and smart home appliances to smart retail, industrial applications, access control and smart doorbells. As these devices are constrained by size and are often battery powered, they need to wield highly efficient compute platforms.

One such platform is the MCU (microcontroller unit), which has low-power and low-cost characteristics, alongside CV and machine learning (ML) compute capabilities.

However, running CV on the MCU will undoubtedly increase its design complexity due to the hardware and software resource constraints of the platform.

Therefore, IoT developers need to determine how to achieve the required performance, while keeping power consumption low. In addition, they need to integrate the image signal processor (ISP) into the MCU platform, while balancing the ISP configuration and image quality.

One processor that fulfills these requirements is Arms Cortex-M85, which is Arms most powerful Cortex-M CPU to date. With vector extension of SIMD (single instruction, multiple data) 128-bit vector processing, Cortex-M85 accelerates CV alongside the overall MCU performance. For IoT developers, they can leverage Arms software ecosystem, ML embedded evaluation kit and guidance on how to integrate the ISP with the MCU in order to unlock CV and ML easily and quickly on the highly-efficient MCU platform.

As a first step, being able to run CV compute workloads requires improved performance on the MCU. Focusing on the CPU architecture, there are several ways to enhance the MCUs performance, including superscalar, VLIW (very long instruction word), and SIMD. For the Cortex-M85, Arm chose to adopt SIMD which is a single instruction set that can operate multiple data as its the best option for balancing performance and power consumption.

Figure 1: The comparison between VLIW and SIMD

Arms Helium technology, which is the M-Profile Vector Extension (MVE) for the Cortex-M processor series, brings vector processing to the MCU. Helium is an extension in the Armv8.1-M architecture to significantly enhance performance for CV and ML applications on small, low-power IoT devices. It also utilises the largest software ecosystem available to IoT developers, including optimised sample code and neural networks.

Supporting the Cortex-M CPUs, Arm has published various materials to make it easier to start running CV and ML. This includes the Arm ML embedded evaluation kit.

The evaluation kit provides ready-to-use ML applications for the embedded stack. As a result, IoT developers can experiment with the already-developed software use cases and then create their own applications. The example applications with ML networks are listed in the table below.

The Arm ML embedded evaluation kit

The ISP is an essential technology to unlock CV, as the image stream is the input source. However, there are certain points that we must consider when integrating ISP on the MCU platform.

For IoT edge devices, there will be a smaller image sensor resolution (<1-2MP; 15-30fps) and even lower frame rate. Also the image signal processing is not always active. Therefore, using a higher quality scaler within the ISP will drop the resolution to sub-VGA, which is 640 x 480, to, for example, minimise the data ingress to the NPU. This means that the ISP only uses the full resolution when needed.

ISP configurations can also affect power, area, and efficiency. Therefore, it is worth asking the following questions to save power and area.

Whether its for human vision, computer vision, or both?

What is the required memory bandwidth?

How many ISP output channels will be needed?

An MCU platform is usually resource-constraint with limited memory size. Integrating with an ISP requires the MCU to run the ISP driver, including the ISPs code, data, and control LUT (loop up table). Therefore, once the ISP configuration has been decided, developers need to tailor the driver firmware accordingly, removing unused code and data to accommodate the memory limitation on the MCU platform.

Figure 2: An example of concise ISP configuration

Another consideration when integrating the ISP with the MCU is lowering the frame rate and resolution In many cases, it would be best to consider the convergence speed of the 3As auto-exposure, auto-white balance and auto-focus. This will likely require a minimum of five to ten frames before settling. If the frame rate is too slow, it might be problematic for your use case. For example, this could mean a two to five second delay before a meaningful output can be captured and, given the short power-on window, there is a risk of missing critical events. Moreover, if the clock frequency of the image sensor is dropped too low, it is likely to introduce nasty rolling shutter artifacts.

Enabling CV and ML on MCU platforms is part of the next wave of the IoT evolution. However, the constraints of the MCU platform can increase the design complexity and difficulty. Enabling vector processing on the MCU through the Cortex-M85 and leveraging Arms software ecosystem can provide enough computing and reduce this design complexity. In addition, integrating a concise ISP is a sensible solution for IoT devices to speed up and unlock CV and ML tasks on low-power, highly efficient MCU platforms.

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Darwin AI Evolving the Islands of Automation – SMT 007

When Canadian artificial intelligence company Darwin AI was founded in 2017, machine learning and deep learning were still relatively new terms. In the past five years, CEO Sheldon Fernandez and his team have been working with this technology to develop some foundational IP to simplify implementation. About a year ago, Sheldon took a part happenstance, part deliberate opportunity to develop a vertical offering for EMS manufacturing. Heres what happened.

Sheldon, its nice to meet you. Would you briefly introduce your company?

Sheldon Fernandez:Were based out of Waterloo, Ontario, Canada. We're organically connected to the University of Waterloo, which is kind of like Canada's MIT. Two of our co-founders are professors at the institution, including Professor Alexander Wong, Canadas Research Chair in AI and Medical Imaging.

Weve been working on foundational machine learning and deep learning technology for the past five years. A couple of years ago, our large industrial and aerospace clients were telling us about their supply chain challenges during the pandemic and reshoring sensitive electronics manufacturing work back to North America, specifically printed circuit boards (PCB). We thought that created an opportunity for us.

When we looked at PCB manufacturing, it became apparent that while the SMT placement workflow was highly automated, there was a need in automating back-end production and final assembly. This laborious part of the process was where EMS companies and OEMs were still employing manual inspection. These inspection tasks are tough to crack from a traditional machine vision perspective, and we wondered, Can AI bring anything to bear on this problem? We spent about a year developing a hardware and software solution which fits into the typical assembly line for PCB manufacturing. It also does post-assembly analysis, and what's really fascinating is how quickly an operator can program our product.

We often hear that AOIs are good at what they do but are laborious to program and maintain. With our system, theres not a lot of manual work. You give the system a good (i.e., golden) boardor a couple of good boards if there's a union of different componentsand our AI system creates a map of where components should be in less than a minute; away you go. You can tweak it after that, and its striking how quickly you can configure the product.

We brought our mini system to IPC APEX EXPO, and the response was fascinating. So many companies were intrigued by finally automating back-end production, and we're really excited about becoming a part of the community.

To read this entire conversation, which appeared in the March 2023 issue of SMT007 Magazine,click here.

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What is artificial intelligence and how does it affect banking? – Santander

15/03/2023

To learn, reason and solve problems are some of the skills associated with humans. Today there are computer applications capable of performing such tasks through artificial intelligence. The rapid expansion of this technology brings about a series of opportunities in different fields. In the banking sector it can be used to improve customer service, optimise loan approval processes and prevent non-performing loans, among other applications. At the same time, it is important to be aware of the many challenges that artificial intelligence poses.

A few years ago, artificial intelligence (AI) might have seemed very futuristic. Nowadays it's common to find tools and applications that are based on AI algorithms in different areas of our everyday life and with different purposes: content generation (known as generative AI and employed in chatbots such as Microsoft's Chat GPT and Google's Bard); computers that play chess and are capable of beating humans; digital personal assistants, navigation assistants that tell you the best route and thousands of other examples.

In general, AI is the development of systems capable of learning, planning or resolving problems in a way similar to humans. For an electronic device or software to have artificial intelligence, it needs data and algorithms that are capable of making decisions. It can receive the former via the internet, big data applications, or by connecting directly to other devices to exchange information. The latter, meanwhile, are a series of instructions with which they are programmed in order to create behaviours or patterns based on the different data they receive.

The growth in artificial intelligence is being driven mainly by disruptive technology such as machine learning, deep learning, big data and quantum computing. What sets AI apart from a standard IT program is that it can improve its own processes autonomously. In other words, it learns from previous tasks, without the need for human intervention. This is known as machine learning.

Imagine you have a robot vacuum. It is programmed to go around your house every day. It follows a map that it generated and stored using its integrated navigation system on day one (previous tasks). However, a few weeks later you decide to move some furniture around. The robot starts bumping into them, prompting it to automatically activate its navigation system to update the map (it makes a decision using the data received). That way since it has designed a new route it won't bump into the furniture next time.

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Lessons in leadership: Removing barriers to get more women in tech – McKinsey

For all the talk of the need for more women in tech, data suggests that meaningfully moving the needle requires better innovation. Thirty-five years ago, women earned roughly a third of computer science degrees. By 2016, that share had fallen to less than 20 percent. Although that number appears to have marked the bottomin 2021 women were earning 22 percent of computing degreesclosing the gender gap in tech, especially for women of color, still has a long way to go.

But Judith Spitz has landed on a promising approach to accelerate progress. After 30 years at Verizon, where she rose through the ranks to become its chief information officer, she left in 2016 to oversee a City University of New York initiative that led to a 94 percent increase in undergraduate women enrolled in computer science classes. In 2020, she built on that success by founding Break Through Tech, a nonprofit housed at Cornell Tech, which works with academia and industry to get more undergraduate women into computer science and connect them with companies that might not otherwise find them.

Spitz recently sat down with Sarah Gitlin, an associate partner in McKinseys Washington, DC, office, to talk about one of Break Through Techs foundational programsSprinternshipsand how it is helping to launch undergraduate women from underrepresented backgrounds into tech careers.

This interview has been edited for clarity and brevity.

Sarah Gitlin: When you founded Break Through Tech in 2020, what was your North Star?

Judith Spitz: We had two. Number one, I believed thenand I believe nowthat every student should be exposed to computer science in their undergraduate years. This should be considered basic literacy in the digital age. You may never write a line of code, but you are certainly going to be impacted by people who do, working with people who do, and trying to conceive of solutions that require writing code. I believed, and research shows, that if you teach that introductory class in a way thats inclusive and more mission-drivenlearning how to write code to solve a problem that were passionate about, as opposed to an end unto itselfsignificantly more of the 58 percent of the undergraduate population who are women will be interested in studying computer science.

Second, we wanted to open the floodgates between the incredible talent pool of undergraduate women who go to nontop-ranked schools and all the companies, large and small, that say theyre looking for them. These companies say they want more women; Black, Latina, and Native American women; first-generation college students; and students from low-income households. They want them, but theyre looking in the wrong placesbecause the vast majority of those women are going to schools other than the ones that most companies are recruiting from.

Sarah Gitlin: How did you get started on the first of those north stars?

Judith Spitz: We found that women coming into these undergraduate schools werent necessarily looking for computer science classesbecause nobody had coached them or told them that this was a real possibility for them. So, we created something called The Guild. It was a program for entering freshman and rising sophomores who hadnt yet chosen a major. The goal was to get them interested in taking that first class, by teaching them enough code to get them excited and having them work on a real-world project with company advisers to give them a sense of empowerment from solving a real problem.

We discovered that magic happens when you get company advisers together with these students. It was eye-opening on both sides. The students were incredibly excited to see how they could use this technology to do real things. And the companies were completely blown away by these studentsbecause they dont normally see them.

Sarah Gitlin: Beyond those company advisers, what else did you do on the second North Star? How did you build a bridge between company recruiters and women studying computer science at schools that arent top-ranked?

Judith Spitz: We wanted to connect our students to paid summer internships. All the research shows that the single largest predictor of a student landing a job within six months of graduating is whether they had a paid tech internship. We sent rsums to companies, but fewer than 4 percent of those students were offered a summer internship. When we went back to the companies, they said, Look, these students have nothing on their rsums. They didnt participate in hackathons on the weekends. They dont have apprenticeships.

What it boiled down to is that all those things are the result of the privilege of free time, when youre not working one or more jobs as you go through college to support yourself, sometimes to support your family. In essence, the companies were looking for things on rsums that were more attributes of privilege than they were of potential. So, we literally sat down with some industry partners and we said, How are we going to crack this nut? And from those discussions, we landed on Sprinternships.

the companies were looking for things on rsums that were more attributes of privilege than they were of potential.

Sarah Gitlin: How exactly do Sprinternships work?

Judith Spitz: Think sprint. Its a three-week, paid (by the companies) microinternship thats designed to create an experience that gives these students a rsum credential that will make them competitive when they apply for regular summer internships. There are two programs a yearone in January and one in Mayduring an academic break.

Its not a substitute for an internship. Think of it as a preinternship that gives our students some rsum juice. It gives them a project and experience they can talk about when they apply for a summer internship. And it also gives them confidence.

Sarah Gitlin: How has the program evolved?

Judith Spitz: Theres some secret sauce that we have iterated on since we launched the program. First, we put the students into a host company in a cohort together, rather than one student at a time. We do that because theyre not ready to work by themselves and because theres power in numbers. They do better as a group. Its also easier for the companies. Its much easier for them to say, OK, the five of you go off into that conference room and work on this project, than it is to come up with a challenge project that can be done alone.

Students are not interviewed. Theyre matched with companiesbecause it would take companies longer to interview them than [the students] would be there, and because we know that theres interview bias. We also prep the students beforehand, to make sure theyre ready to walk in the door and hit the ground running, whether its virtual or otherwise.

We did a pilot the first year, placing five students in one company. At the end of the three weeks, [the company] offered all five a summer internship. And we thought, OK, were onto something here.

Sarah Gitlin: What kind of results have you seen as the program has scaled?

Judith Spitz: Were now running the program in four cities. Over 150 companies have participated to date, and the results are consistent. About 60 percent of the Sprinterns land a paid summer tech internship.

Sarah Gitlin: So, its gone from 4 percent before the Sprinternships to 60 percent?

Judith Spitz: Correct. And theres more. This past year, 80 percent of the Sprinterns who applied for a summer internship at their host company received an offer. Theres no recruitment event, no job fair, no conference companies can go to where they get to interview somebody for five minutes and have that kind of return on investment, in terms of meeting a student, making an offer, and having the student accept the offer. The flip side of it is that about 64 percent of our students who get offers get an offer someplace other than their Sprinternship hostwhich says to me theyve got a hugely valuable rsum credential they can shop around.

Sarah Gitlin: What kind of feedback have you gotten from the employers who participate in Sprinternships?

Judith Spitz: The feedback is almost universally consistent. They are incredibly surprised by what these students can accomplish in three weeks, and they think theyre terrific. Without the Sprinternship, the employers would simply never meet these students. This is the problem were solving. The best estimates show that more than 90 percent of women studying computer science in this countryand 97 percent of Black, Latina, and Native American women studying computer scienceare going to colleges other than the top 25. They are spread out all over the country, and its not economical for industry recruiters to try and recruit from hundreds, if not thousands, of different colleges.

Without the Sprinternship, the employers would simply never meet these students.

Sarah Gitlin: What are the demographics of the participants in the Sprinternship program?

Judith Spitz: There is a small percentage of men in the program, from underrepresented communities in tech. But between 90 and 94 percent of them are women. Sixty to 70 percent of them are from underrepresented communities, which we define as Black, Latina, and Native American, or first-generation college students, or students from low-income households.

Sarah Gitlin: How many students have gone through Sprinternships at this point?

Judith Spitz: Just over 1,500. But we are starting to make a pivot now. We have a company thats taking 100 Sprinterns this year because they are positioning this program as a strategic part of their tech-talent recruitment plan. They know how many interns they want, and they know how many Sprinterns itll take to get the pull-through into their hiring process. And were expecting to scale up from there once we go to what we call a direct-to-student model.

Sarah Gitlin: How does that model work?

Judith Spitz: As an example, we had spots for about 50 Sprinterns for one of our companies in a geography where we dont have a specific university partnership. We put out minimal direct marketing, calling all interested students, and we got 250 applications for it. So, we filled 50 spots with virtually no marketing.

We know that this thing can and will scale. And thats also part of my heritage. You grow up at a company like Verizon, and you do everything at scale. We think this is a programmatic intervention that isnt just for a few companies and isnt targeted at just a few schools. It can scale across the industry and enable systemic change in how companies recruit diverse tech talent.

We know that this thing can and will scale.

Sarah Gitlin: Could you ever see a Sprinternship model applying beyond tech?

Judith Spitz: Absolutely. The City University of New York, which is the first place we started, is very interested in doing just that. You need the right ground elements to make this work, which means it would have to be an industry thats having persistent diversity problems. What this is solving for is an industry where theres what I call a feeding frenzy at a small number of schools and an unwillingness or an inability to tap into talent outside of that.

Sarah Gitlin: Turning to a slightly less rosy topic As we know, tech talent was in short supply, and now were seeing a wave of layoffs. Are you considering any changes to the Sprinternship program to adapt to these shifting labor market dynamics?

Judith Spitz: Most of the announced layoffs are by the companies often called Big Tech. But those are not the only companies that have really outstanding tech organizations with great career opportunities. I am a firm believer in the adage Every company is a tech company. And it doesnt matter whether youre talking about the Fortune 50, 100, 500 companies; they all have large tech organizations, and most are not overstaffed. There are still huge opportunities in all those other companies. These organizations have super-cool tech organizations that are doing really interesting things.

I am a firm believer in the adage Every company is a tech company.

Sarah Gitlin: Does Break Through Tech have other programs that complement Sprinternships?

Judith Spitz: We work with our partner universities on curriculum innovations, and to clear barriers students often face trying to get into computer science classes. Theres our Guild program, and Guild students often become Sprinterns. We also have a new programBreak Through Tech AIthat focuses specifically on underrepresented undergraduate women from institutions employers typically overlook, and who have a specific interest in machine learning and AI data science.

We asked our industry partners what they are looking for on student rsums for entry-level machine learning engineering jobs. And they said three things: they need to know some industry tools, they need to have a portfolio of things theyve built, and they need the wherewithal to get through a tech interview. Most students who have those things are getting them outside a standard university curriculum. They are learning the industry tools on their own. Theyre getting portfolio projects during their free time because they have a connection, and they can work on something without getting paid. And of course, those experiences give them the training and confidence to get through an interview.

So, we created this program that has those three elements. We give participants a stipend to attend a nine-week summer course specifically focused on machine learning industry tools. Not theoryindustry tools. Then in the fall, we match them to an industry machine learning project with an industry adviser. Its like a Sprinternship program, only its done over the course of a semester. We have about 160 women in the program now. The target is 1,500 women a year.

Sarah Gitlin: What is next on the horizon for Break Through Tech?

Judith Spitz: Our big focus right now is how to scale even more. Were not talking about a couple of thousand, but about tens of thousands. And we think the way to get to real scale is to have a direct-to-student model, where we can invite and welcome students who go to any university. So, the program will have to switch to being more hybrid.

Were also trying to figure out how to pivot companies from thinking about this as a social-good engagement to a strategic solution to their diversity pipeline problem. Some companies are no longer requiring a college degree and, instead, are looking at skilled-based hiring or apprenticeships to try to diversify their numbers. And thats good. But what theyre doing is going outside the higher education universe, and they are missing out on an incredible opportunity pool of amazing students who are doing exactly what society has told them to do. Theyre getting their four-year degrees. Theyre studying computer science. Theyre doing everything the companies are saying they should. Its just that theyre off the recruitment radar screen.

Sarah Gitlin: Youve found a way to put them on the companies radar.

Judith Spitz: Exactly. What we want to do is help companies see that while no college degree required is one way to achieve diversity in your tech organization, there are about 170,000 women studying computing at 4-year institutions today. And more than 150,000 of them are going to schools that are off of many companies radar.This is an opportunity pool just waiting to be tapped.

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Lessons in leadership: Removing barriers to get more women in tech - McKinsey

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High School Programming Contest Shows Promise for Future … – University of Arkansas Newswire

University of Arkansas

Dean Needy presenting the first place award.

High school students from across Arkansas gathered in March at the U of A for the annual High School Programming Contest, hosted by the Department of Computer Science and Computer Engineering after a two-year hiatus due to COVID-19.

More than 70 students on 28 teams squared off in a test of programming and problem-solving throughout the day. The event was sponsored by CGI and supported by volunteers from the Association for Computing Machinery at the U of A as well as the Computer Science and Computer Engineering Department.

Professor Kevin Jin led the event for the first time this year after being passed the torch by Professor Wing Ning Li after his retirement in 2022.

"For future students to come here with excited faces and focused faces I'm very excited," Jin said.

Staff in the Department of Computer Science and Computer Engineering put countless hours toward planning and running this event. Jenna Stacey, ASCENT program manager, was one of many at the forefront of planning.

"This was an excellent event with a great turnout. It was so exciting to see the future generation working so hard. We are grateful to our sponsor for helping make this happen, and we look forward to next year's high school programming contest. We are thrilled with the turnout this year!" Stacey said.

Students who completed the most questions in the least amount of time were awarded trophies for first place, second place, third place and most creative. All competitors were given free food, T-shirts and the opportunity to win door prizes such as a Nintendo Switch, Raspberry Pi, Blue Yeti microphone, Amazon gift card, gaming keyboard, gaming headset and more!

The awards ceremony took place at the end of the day with a special appearance from Kim Needy, dean of the College of Engineering.

The winners were:

First Place

Second Place

Third Place

Most Creative

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LBCC budget cuts will eliminate criminal justice and computer … – KEZI TV

ALBANY, Ore. Linn-Benton Community College will be dropping some of its programs at the end of the 2024-25 academic because it does not have the funds to continue to offer them, college officials said.

Linn-Benton Community College (LBCC) officials said that its criminal justice and computer science programs will be eliminated at the end of the 2024-25 school year due to budget cuts. An emphasis in criminal justice or computer science for an Associate of Arts Oregon Transfer will no longer be an option, the college said.

LBCC officials also said that the LBCC Board of Education approved a 6% tuition increase for the 2023-24 school year.

Students currently enrolled have the next two years to complete their degrees in either program, LBCC said. Options include an associate or applied science degree in computer science or systems administration, an applied science degree in criminal justice, or a one-year certificate in juvenile corrections, the college said.

LBCC also said library staffing will be reduced in June but the library will remain open, the college said.

College officials also said that its Adult Basic Skills programs budget will be reduced with division staff overseeing the program, grant management and related support services.

There are also six open positions at LBCC that officials said will not be filled, but will be re-evaluated in the fall.

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Grant Will Help Break Down Barriers in Access to Technology in … – University of Connecticut

A collaborative effort between the Research on Resilient Cites, Racism, and Equity (RRCRE) initiative at UConn Hartford, and the Computer Science and Engineering Department in the UConn School of Engineering has resulted in the institution receiving a federal grant that will help provide technology and internet access to traditionally underserved students in the Hartford area.

UConn is one of 61 college and universities from around the country to receive this grant from the Department of Commerces National Telecommunications and Information Administration. UConn is receiving approximately $2.86 million over a two-year period to launch a pilot program.

The essence of the idea is to reach out to students in Hartford that have little or no access to internet or computer equipment and create an opportunity for these folks, says associate professor of sociology and Africana studies David Embrick, who also oversees the RRCRE at UConn Hartford. We want to create a realistic pipeline for students who are interested in fields of engineering and computer science, and even those that dont even realize that they have that interest.

The UConn program will focus on students in Hartford entering high school, those at the end of the high school career, and students just starting college at UConn.

The grant will help fund internet access at home for these students, and provide them with basic computer equipment and support, such as workshops and instruction.

The success of Dr. Embrick and UConn Hartfords Research on Resilient Cities, Racism, and Equity highlights the strength of conducting research in collaboration with community organizations, says Mark Overmyer-Velzquez, the director of UConn Hartford. This grant will provide access to high impact learning opportunities for our UConn students and support Hartford schools to attain vital access to broadband technology and related education.

Embrick says faculty members in the Department of Computer Science and Engineering learned about the grant opportunity and approached him about a joint effort for applying. Embrick thought it would be a perfect fit for UConn Hartford, and went to work with professor Laurent Michel, associate professor Zhijie Jerry Shi, and assistant professor Qian Yang, in the School of Engineering, along with UConn Hartford Director of Finance and Operations Cynthia Miranda-Donnelly in the application process.

There is a shortage of talent in the computer engineering field on both a national and state basis, says Laurent. However, there are many people from different walks of life who have the capabilities to be successful at it. Very often, the more privileged ones get so much more exposure at a young age and can recognize that they have this talent. The others dont have these opportunities, so we want to nurture that natural inclination that exists in these groups, but right now is untapped. We want to give them access to these resources for them to reach their potential, and follow career paths that are very rewarding both intellectually and financially.

Embrick says that young scholars who dont have internet access readily available can lack the capacity to see what career paths are truly available to them. The level of inequities, just based on lack of access to the internet, is just immense, especially in this day and age.

The cooperative effort that resulted in earning the grant will continue in its practice. The computer science faculty members will be creating workshops to help and guide the students by providing them ways to navigate the internet and offer them practical skills which they can use in their future studies.

We will be in charge of the budget and managing the operations and evaluations of the program here at UConn Hartford to make sure there is long-term success, says Embrick. The School of Engineering will be building the program and workshops for the students themselves, so together its a powerful force. Its a good illustration of a strong collaboration in the way UConn wants it to be.

While the grant is only for two years, there are long-term goals beyond that timeframe for this program to continue by offering students guidance and resources in all parts of their lives to develop successful careers. There are also long-term goals of hiring three IT staff members and server equipment to benefit the program.

Laurent says the group will monitor cohorts in the program as their time progresses from early high school through college.

As a land-grant institution, UConn has the responsibility to the people of Connecticut, and UConn Hartford, as an urban campus, has a specific responsibility to the people of Hartford, says Embrick. There are real needs to do community engagement in a way that not just facilities one-way conversation between academic and the community. It must be done in a way that engages the community and builds upon the mission of the Research on Resilient Cities, Racism, and Equity initiative.

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Computer science alum reflects on his role in building the Internet in … – Dal News

Dan MacKay (BCS89) remembers New Years Day, 1983 well. He was in the Sculpture Court at the Dalhousie Arts Centre and about to make history by helping bring Nova Scotia online for the first time.

The usual ceremonial flourishes wouldnt do for such a special occasion.

We had our equipment set up in the Sculpture Court, and the premier was there, and instead of cutting a ribbon, I had him connect two pieces of ethernet together an old kind of ethernet called 10base2, recalls MacKay, who was a key player on the technical team that built the Internet in Nova Scotia and across Canada.

While the day the team officially connected Nova Scotia to the transcontinental network stands out as a highlight in MacKays mind, there were many exciting and challenging moments during the project.

Every day there was a new challenge, the Faculty of Computer Science alum says. We were building and improving the speed of the internet across Canada, and I got to talk to tech people at schools, libraries and businesses all across the province about exciting new installations and improvements.

MacKay also played a role in developing the technological process that syncs time across every clock, computer and watch connected all over the world.

MacKay pictured in 1991 during an Internet hookup at Park View school in Bridgewater, N.S.

Theres no wonder MacKay was involved in building the internet. From a young age, he was immersed in the world of technology thanks to his two older brothers, one of whom graduated a member of the Class of '75 with a degree in physics.

By the time I was 5 years old, I had a home physics, chemistry and engineering lab to play with, says MacKay. When I was just barely a teen, I got to try out programming on paper tape on the new Intel 8080 chip in my brother Michaels lab.

Building the Internet in a time before it was widely available came with its own set of challenges.

Everything was new, he says. The very first routers we started working with were built in Burnside using very experimental software and had all kinds of serious problems that made them unusable. The next batch was from the USA but had software built in Ontario which had never been connected to the Internet before. The tools we had for diagnosing problems with the internet were very primitive they still are and so we got really good at reading the nuances of what tools we had."

When asked how the Internet has changed since those early days, he replies: "It would be easier to document the things that havent changed! That is e-mail and the underlying protocol, TCP/IP."

MacKay says the biggest revolutions to the Internet since its inception are the development of the World Wide Web and advances in Internet-wide search engines.

Recommended reading:Dal computer science students hack their way to national competition

This past January, MacKay held a party in the Goldberg Computer Science Building to mark the 40th anniversary of bringing Canada online.

The event inspired MacKay to work on a project documenting the history of local public, free, subsidized, and egalitarian access to the Internet through organizations like The Chebucto Community Net and C@P and a piece of software called C-Suite.

When asked about the future of the Internet and its evolution, MacKay sees some major new shifts underway.

"That answer has changed drastically in the last few months, and it will continue to do so. It seems a great deal of our lives will be mediated by artificial intelligence which will vary from administration tasks to advanced medical consultations.

While the Internet continues to evolve, one thing is certain: MacKays contributions to the tech industry and connecting Nova Scotia to the internet will always be remembered and celebrated.

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Uncovering the unheard: Researchers reveal inaudible remote … – UTSA

"The technically interesting thing about this project is that the defense solution is simple; however, in order to get the solution, we must discover what the attack is first, said Xu.

The most popular approach that hackers use to access devices is social engineering, Chen explained. Attackers lure individuals to install malicious apps, visit malicious websites or listen to malicious audio.

For example, an individuals smart device becomes vulnerable once they watch a malicious YouTube video embedded with NUIT audio or video attacks, either on a laptop or mobile device. Signals can discreetly attack the microphone on the same device or infiltrate the microphone via speakers from other devices such as laptops, vehicle audio systems, and smart home devices.

If you play YouTube on your smart TV, that smart TV has a speaker, right? The sound of NUIT malicious commands will become inaudible, and it can attack your cell phone too and communicate with your Google Assistant or Alexa devices. It can even happen in Zooms during meetings. If someone unmutes themselves, they can embed the attack signal to hack your phone thats placed next to your computer during the meeting, Chen explained.

Once they have unauthorized access to a device, hackers can send inaudible action commands to reduce a devices volume and prevent a voice assistants response from being heard by the user before proceeding with further attacks. The speaker must be above a certain noise level to successfully allow an attack, Chen noted, while to wage a successful attack against voice assistant devices, the length of malicious commands must be below 77 milliseconds (or 0.77 seconds).

This is not only a software issue or malware. Its a hardware attack that uses the internet. The vulnerability is the nonlinearity of the microphone design, which the manufacturer would need to address, Chen said. Out of the 17 smart devices we tested, Apple Siri devices need to steal the users voice while other voice assistant devices can get activated by using any voice or a robot voice.

NUIT can silence Siris response to achieve an unnoticeable attack as the iPhones volume of the response and the volume of the media are separately controlled. With these vulnerabilities identified, Chen and team are offering potential lines of defense for consumers. Awareness is the best defense, the UTSA researcher says. Chen recommends users authenticate their voice assistants and exercise caution when they are clicking links and grant microphone permissions.

She also advises the use of earphones in lieu of speakers.

If you dont use the speaker to broadcast sound, youre less likely to get attacked by NUIT. Using earphones sets a limitation where the sound from earphones is too low to transmit to the microphone. If the microphone cannot receive the inaudible malicious command, the underlying voice assistant cant be maliciously activated by NUIT, Chen explained.

Research toward the development of NUIT was partially funded by a grant from the Department of Energy National Nuclear Security Administrations (NNSA) Minority Serving Institutions Partnership Program (MSIPP). The $5 million grant supports research by the Consortium On National Critical Infrastructure Security (CONCISE) and allows the creation of certification related to leveraging Artificial Intelligence (AI) and block-chain technology to enhance critical infrastructure cybersecurity posture.

UTSA is a nationally recognized leader in cybersecurity. It is one of few colleges or universities in the nation and the only Hispanic Serving Institution to have three National Centers of Academic Excellence designations from the U.S. Department of Homeland Security and National Security Agency.

Additionally, the university is home to five cybersecurity research centers and institutes the Cybersecurity Manufacturing Innovation Institute, the National Security Collaboration Center, the Institute for Cyber Security, the Center for Infrastructure Assurance and Security and the Cyber Center for Security and Analytics.

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