Category Archives: Artificial Intelligence

A new cross-disciplinary research initiative at MIT aims to promote the understanding and use of AI across all segments of society. The effort, called Responsible AI for Social Empowerment and Education (RAISE), will develop new teaching approaches and tools to engage learners in settings from preK-12 to the workforce.

People are using AI every day in our workplaces and our private lives. Its in our apps, devices, social media, and more. Its shaping the global economy, our institutions, and ourselves. Being digitally literate is no longer enough. People need to be AI-literate to understand the responsible use of AI and create things with it at individual, community, and societal levels, says RAISE Director Cynthia Breazeal, a professor of media arts and sciences at MIT.

But right now, if you want to learn about AI to make AI-powered applications, you pretty much need to have a college degree in computer science or related topic, Breazeal adds. The educational barrier is still pretty high. The vision of this initiative is: AI for everyone else with an emphasis on equity, access, and responsible empowerment.

Headquartered in the MIT Media Lab, RAISE is a collaboration with the MIT Schwarzman College of Computing and MIT Open Learning. The initiative will engage in research coupled with education and outreach efforts to advance new knowledge and innovative technologies to support how diverse people learn about AI as well as how AI can help to better support human learning. Through Open Learning and the Abdul Latif Jameel World Education Lab (J-WEL), RAISE will also extend its reach into a global network where equity and justice are key.

The initiative draws on MITs history as both a birthplace of AI technology and a leader in AI pedagogy. MIT already excels at undergraduate and graduate AI education, says Breazeal, who heads the Media Labs Personal Robots group and is an associate director of the Media Lab. Now were building on those successes. Were saying we can take a leadership role in educational research, the science of learning, and technological innovation to broaden AI education and empower society writ large to shape our future with AI.

In addition to Breazeal, RAISE co-directors are Hal Abelson, professor of computer science and education; Eric Klopfer, professor and director of the Scheller Teacher Education Program; and Hae Won Park, a research scientist at the Media Lab. Other principal leaders include Professor Sanjay Sarma, vice president for open learning. RAISE draws additional participation from dozens of faculty, staff, and students across the Institute.

In todays rapidly changing economic and technological landscape, a core challenge nationally and globally is to improve the effectiveness, availability, and equity of preK-12 education, community college, and workforce development. AI offers tremendous promise for new pedagogies and platforms, as well as for new content. Developing and deploying advances in computing for the public good is core to the mission of the Schwarzman College of Computing, and Im delighted to have the College playing a role in this initiative, says Daniel Huttenlocher, dean of the MIT Schwarzman College of Computing.

The new initiative will engage in research, education, and outreach activities to advance four strategic impact areas: diversity and inclusion in AI, AI literacy in preK-12 education, AI workforce training, and AI-supported learning. Success entails that new knowledge, materials, technological innovations, and programs developed by RAISE are leveraged by other stakeholder AI education programs across MIT and beyond to add value to their efficacy, experience, equity, and impact.

RAISE will develop AI-augmented tools to support human learning across a variety of topics. Weve done a lot of work in the Media Lab around companion AI, says Park. Personalized learning companion AI agents such as social robots support individual students learning and motivation to learn. This work provides an effective and safe space for students to practice and explore topics such as early childhood literacy and language development.

Diversity and inclusion will be embedded throughout RAISEs work, to help correct historic inequities in the field of AI. We're seeing story after story of unintended bias and inequities that are arising because of these AI systems, says Breazeal. So, a mission of our initiative is to educate a far more diverse and inclusive group of people in the responsible design and use of AI technologies, who will ultimately be more representative of the communities they will be developing these products and services for.

This spring, RAISE is piloting a K-12 outreach program called Future Makers. The program brings engaging, hands-on learning experiences about AI fundamentals and critical thinking about societal implications to teachers and students, primarily from underserved or under-resourced communities, such as schools receiving Title I services.

To bring AI to young people within and beyond the classroom, RAISE is developing and distributing curricula, teacher guides, and student-friendly AI tools that enable anyone, even those with no programming background, to create original applications for desktop and mobile computing. Scratch and App Inventor are already in the hands of millions of learners worldwide, explains Abelson. RAISE is enhancing these platforms and making powerful AI accessible to all people for increased creativity and personal expression.

Ethics and AI will be a central component to the initiatives curricula and teaching tools. Our philosophy is, have kids learn about the technical concepts right alongside the ethical design practices, says Breazeal. Thinking through the societal implications cant be an afterthought.

AI is changing the way we interact with computers as consumers as well as designers and developers of technology, Klopfer says. It is creating a new paradigm for innovation and change. We want to make sure that all people are empowered to use this technology in constructive, creative, and beneficial ways.

Connecting this initiative not only to [MITs schools of] engineering and computing, but also to the School of Humanities, Arts and Social Sciences recognizes the multidimensional nature of this effort, Klopfer adds.

Sarma says RAISE also aims to boost AI literacy in the workforce, in part by adapting some of their K-12 techniques. Many of these tools when made somewhat more sophisticated and more germane to the adult learner will make a tremendous difference, says Sarma. For example, he envisions a program to train radiology technicians in how AI programs interpret diagnostic imagery and, vitally, how they can err.

AI is having a truly transformative effect across broad swaths of society, says Breazeal. Children today are not only digital natives, theyre AI natives. And adults need to understand AI to be able to engage in a democratic dialogue around how we want these systems deployed.

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Helping students of all ages flourish in the era of artificial intelligence - MIT News

The job of a college admissions officer is not an easy one. For any competitive higher learning institution, the admissions process used to hand pick each incoming student is one that has also drawn increased scrutiny over the years.

To ensure the ongoing success of an institution, admissions officers aresaddled with the nearly impossible task of efficiently evaluating thousands of applications each school year, with the expectation that their choices will reflect the institutions standards, grow diversity and that the students chosen will then be inspired enough to enroll and attend classes in the fall.

The process is a balancing act and one that is expected to proceed without gender-based or racial bias. The problem? Humans are inherently biased, and schools are now beginning to realize the faults in their traditional approach to admissions one that has placed an outweighed emphasis on test scores and transcripts and often fails to find the human factor in their applicants. The flaws in this system also tend to leave underprivileged groups behind and keep underrepresented demographics as anomalies.

Surprisingly, the solution to this issue to this lack of humanity might possibly be found through the utilization of artificial intelligence.

The mission of the organization is to bring a human aspect back into the admissions process,said Andrew Martelli, the chief technology officer at Kira Talent.

The Canadian-founded company works with learning institutions around the world, in hopes of delivering a more holistic approach to reviewing candidates. Hopeful students applying to institutions that partner with Kira undergo a video interview process in which they will not encounter another live person. Instead, video- and text-based prompts lead you through a series of questions, and the applicants answers are then used to evaluate things like leadership potential, verbal and written communication skills, comprehension of key concepts, drives and motivations, and professionalism.

Martelli tells us that artificial intelligence (AI) has entered the picture in a beta phase: one that is used not to evaluate students, but rather the admissions officers and their possible biases.

It's almost more of a science experiment, to understand things like: are people accidentally or inadvertently introducing bias, he said. When schools express interest in it, they are presented with an AI-based tool that takes video data, and analyzes personality traits and behaviors. We take the very same footage that you view as an admissions person to get a sense of the applicant, and we have them run it through a series of algorithms. Schools are then able to run the algorithms, which give them AI-based data to then compare to what their human reviewers said.

The idea behind the technology is to help the human reviewer ask questions of themselves. Did I see these traits or qualities? Am I missing something? So the emphasis is not on using AI to replace the human aspect of the process. Our whole focus is on helping the human be a better evaluator of other humans.

Its those principles that the company utilized last year in their partnerships with schools like California State University (CSU) Fullerton. Members of the admissions committee were able to pre-record questions for the students to answer through video interviews.

Kira allowed us to bring our own personality, said Deanna Jung, Assistant Professor of Nursing and Coordinator of Pre-Licensure Programs. We have a diverse faculty, so there was a diverse group of individuals reading the questions. Students were able to watch those videos and think okay, there are faculty who teach here who are like me.

Automating bias

Not all AI systems are created equal, though, or without unconsciously programmed bias. At the end of the day, data scientists are still human, meaning that many of the subjective choices that they make as they create and refine training data can lead to racial bias in machine learning systems.

Human bias is an issue that pervades nearly every industry and facet of life, certainly not just in the process of college admissions. Over the last few years, society has become acutely more aware of how these human prejudices can affect peoples lives. These biases can slip into AI systems creating what is called algorithmic bias, taking various forms from gender bias to racial prejudice and age discrimination.

Weve already seen how algorithmic bias can lead to damaging consequences, like in 2016 when Microsoft released an AI-based chatbot on Twitter. Its goal was to interact with people through tweets and direct messages, but within hours of its release began replying to users with offensive and racist language. The chatbot, which was trained on anonymous public data and utilized a built-in internal learning feature, was targeted by hate groups to introduce racial bias into its system.

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Luckily, researchers are working daily to figure out how to mitigate the possibility of introducing racial bias into AI-based systems. One postgraduate researcher at the Massachusetts Institute of Technology, Joy Buolamwini, even founded the Algorithmic Justice League, with the objective to highlight the social and cultural implications of AI bias using both art and scientific research.

Combatting summer melt

A much more successful AI-based messaging experiment than Microsofts 2016 disaster was recently utilized by Georgia State University. The same year, the university introduced an AI chatbot called Pounce, whose objective was to reduce what schools refer to as summer melt.

Summer melt is what happens when enrolled students drop out during the summer, before their first fall semester even begins. According to the university, Pounce was able to reduce the occurrence of summer melt by an impressive 22 percent, which translated to an additional 324 students showing up for their first day of classes in the fall.

Realizing the power of communicating with their students through text message but not having the human power to implement it, Georgia State partnered up with the Boston-based education technology company AdmitHub.

More thanhalf of the universitys students hail from low-income backgrounds, and many of them are first generation college students a demographic that has shown the need for individual attention and financial aid, both of which aid enrolled students in showing up ready to start classes once the semester starts.

The admissions team worked with AdmitHub to identify these obstacles and fed information and answers into Pounce, which students could then direct their questions to at any time of the day or night by text message. In the first year of implementing Pounce, the AI-based system had answered more than 200,000 questions by incoming freshmen.

Every interaction was tailored to the specific students enrollment task, says Scott Burke, assistant vice president of undergraduate admissions at Georgia State, on the universitys website. We would have had to hire 10 full-time staff members to handle that volume of messaging without Pounce.

The future of AI and education

What experts seem to agree on is that the sole use ofAI will never be best practice for college admissions decisions, at least for now. Nevertheless, AI-based systems can serve an increasingly important purpose for schools, not only streamlining teams and processes, but also promoting education about unconscious biases amongst admissions officers.

I do believe that schools continuously look for ways to adjust their practices. I think COVID has also caused people to take a hard look at the processes that they use to try to find ways to make them more convenient, to make them more accessible, to make them safer because of the social distancing and other requirements, says Martelli.

I also think a lot of the social movements that we see in place today have asked for schools to take a harder look into their practices and the processes, and the ways they make these admissions decisions.

As far as the future of AI-based systems, Martelli preaches cautious optimism, saying that it has to be implemented in the right ways. Thechief technology officersaid that along with the promise that AI shows, there is a lot of danger as well. Experiments over the years have shown just how easy it is for algorithmic bias to make its way into an AI-based system, and Martelli says that a biased sample could only serve to perpetuate some of the problematic decision making of the past.

When you think about using those kinds of tools, we still think it needs a person at the heart of the whole system to make the judgment about another human, he says. Do I think there's promise there? For sure. Do I think we have to be careful about how we apply it? 100 percent.

A version of thisarticle can also be found on The Hill.

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How artificial intelligence can help us get back to the humanity of college admissions decisions | TheHill - The Hill

There seem to be a lot of articles about artificial intelligence in newspapers and magazines these days. Some of the other stuff in print makes me think that what we need is more regular intelligence,

Last week, the legislative branch of the 27-country European Union headquartered in Brussels announced plans to restrict the use of artificial intelligence. Its an attempt to head off abuse of artificial intelligence technology, instead of waiting for it to be a problem the way the United States does.

Artificial intelligencesimulates humanintelligencein computers that are programmed to think and act like human beings. (Hey, what could go wrong?)

Originally,artificial intelligence meant a machine doing something that would have previously needed human intelligence.From what Im reading these days, I worry that the artificial intelligence may be more intelligent than the human kind.

All of the major computer companies seem to offervirtual personal assistants (Microsoft Cortana, Apple Siri, Amazon Alexa and Google Assistant, for instance.)

Alexa, for another instance, can handle your e-mail, your shopping list, the radio and television, cooking, a wake-up call, communication with friends and family, and generally canrun your life.

Its hard to believe (at least for an old guy like me) to read about some of the things artificial intelligence can do.

For instance, some artificial intelligence systems can allow you todeposit checks in the bank from your living room, and, if necessary, some can decipher the handwriting on the check.

Artificial intelligence can also detect fraudulent use of a credit card by observing the users normal credit card spending patterns.

Youre likely to run into that sort of electronic voodoo any time in these ever-increasing days of artificial intelligence.

The intelligence algorithms can detect and remove hate speech, faster than a human censor can. They are able to identify key words and phrases.

Google maps, Im told, not only tell you how to drive to a destination, but, thanks to an artificial intelligence algorithm, tell you what time youll get there, based on traffic conditions.

The Google app algorithm remembers the edges of buildings that have been fed into the system after the owner has manually identified them.

Another feature is the electronic (or possibly voodoo again) recognizing and understanding of handwritten house numbers.(On paper, I presume, not on the houses.)

The scary thing about the foregoing is that the people who devise, and write about, all this new technology claim that the field of artificial intelligence is still in its infancy. More programs are still to come, they tell us, that will much more accurately replicate human capabilities.

I wonder how long it will be before the computers tell us to just go home and take a nap, and theyll take care of everything.

Next thing you know, dear reader, weekly columns like this may be turned out by artificial intelligence, instead of the good old fashioned writers like me. Please dont tell me that you wont know the difference.

Originally posted here:

Of All Things: Artificial intelligence is real | News | montgomerynews.com - Montgomery Newspapers

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Last week, our trending stock lists collected a motley crew of companies ranging from biotech to regular tech to home entertainment tech. In general, there was just a lot of tech.

For the week of May 16, many of those same stocks hit our trending roundup again for good reason. From a 49 million square foot downgrade to a pilot program intended to put credit cards in the hands of the credit-less, heres an inside look at whats making the market pop.

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First up in our weekly trending list is International Business Machines, which closed up 0.35% on Friday to $144.68 with 2.7 million trades on the books. The stock is up almost 15% for the year.

IBM a repeat customer from last week, after announcing the week before that they had developed the worlds first 2nm chip-making technology. Now, IBM is trending, likely in part due to a slew of messages surrounding the future of the companys working arrangements.

CEO Arvind Krishna declared last week that IBM expects up to 80% of its 350,000 employees to opt for a hybrid office-remote work arrangement, with the remaining 20% keeping their position as fully remote employees. And while he cautioned that nobody should make firm plans for another two or three months, he also acknowledged that these arrangements will vary around the world to account for individual countries situations regarding the pandemic.

In anticipation of this massive workplace shift, IBM is planning to shed tens of millions of square feet of real estate. The company plans to move to the CrossPoint office complex in Lowell, Massachusetts, downsizing from almost 50 million square feet to a mere 150,608.

IBM 5-year performance

The downgrade will likely help IBMs bottom line as well as their employee working conditions something the company has surely considered. Although an operating income of $8.58 billion in the last fiscal year doesnt exactly put the company in hurting territory, this is a touch over half of their $13.2 billion operating income three years ago.

Plus, their mere 0.21% in revenue growth to $73.6 billion isnt quite up to snuff compared to their three-year-ago revenue of nearly $79.6 billion. Their EPS has fallen in the same timeframe, too, from $9.52 to $6.23, while their ROE has decline from 50.3% to 26.4%.

Still, when youre down, theres nowhere to go but up: the company is expected to see revenue growth of 0.57% in the next twelve months. And with a forward 12-month P/E of 12.8x, their stock shows plenty of room for growth, as well.

Our AI sees IBM as having above-average potential overall, as well, though it could be doing better in some areas. The company earned Cs in Technicals and Growth, and Bs in Quality Value and Low Volatility Momentum, setting them up for an optimistic future.

Netflix NFLX is a company that needs no introduction especially seeing as how it, too, appeared on last weeks trending lists. The streaming media giant remains a household name due to its invaluable services during the pandemic and a stock staple due to its overall history of turning out profits.

Although Netflix fell short 2 million subscribers in its most recent earnings report, it still closed up almost 1.4% on Friday to $493.37 per share, ending the week on a positive note with 2.88 million trades in the bank. Still, its stock remains down 8.8% YTD.

Netflix 5-year performance

Netflixs high stock prices are mostly supported by its underlying performance revenue grew almost 5.6% in the last fiscal year and 67% in the last three, bringing total revenue to $25 billion. Of this, the company netted $4.585 billion in operating income, almost triple their $1.6 billion operating income three years ago. And their EPS has risen 35.9% in the last year alone and 208% in the last three, seeing per-share earnings grow from $2.68 to $6.08.

And while you might think that a company this big has nowhere to go, youd be wrong: Netflixs revenue is expected to expand 3.33% in the next twelve months. At the same time, some analysts see the stock as overvalued (largely due to the inability to monetize their Netflix Originals via traditional methods), and their forward 12-month P/E of 47.53 appears to support this claim.

Still, our AI doubts that Netflix has reached its cap; far from it. In fact, Netflix earned an A in Growth, with Bs in Low Volatility Momentum and Quality Value though it did net a D in Technicals. Only time will tell if Netflix is able to grow as pandemic restrictions loosen at last and the broader economy reopens.

Last week was a roller coaster week for vaccine manufacturers after the Biden administration openly supported an initiative to waive Covid-19 vaccine patents in order to bolster global production. This announcement as well as Modernas MRNA announcement that it would funnel at least 34 million doses to struggling countries saw the stock trend twice last week.

Once again, Moderna makes our list of trending stocks as shares closed up 7.7% on Friday to $161.38 on volume of 6.5 million trades. While the stock has been falling over the past month, as indicated in the 22-day price average of $167 and change, the stock is still up almost 54.5% YTD.

Moderna can once again thank the government for its upward trend, as shares of the biotech company rose after an announcement from the CDC that individuals who are fully vaccinated can participate in indoor and outdoor activities, large or small, without wearing a mask or physical distancing. While Moderna cant claim full credit, distributing hundreds of millions of doses of their mRNA vaccine surely helped make this long-awaited declaration possible.

And in further good news, Australia last week noted that its in talks with Moderna to establish domestic production of messenger RNA vaccines. The company is also supposedly conferring with Samsung BioLogics Co Ltd to start production of the Moderna vaccine in South Korea (though no official decision has been made) after two expert panels recommended that Modernas vaccine be approved for emergency use.

Moderna 5-year performance

Moderna is one of those fortunate companies that benefitted from the pandemic more than it was hurt, as the biotech company saw their revenue expand 240% in the last fiscal year to $803 million, compared to $135 million three years ago. Their operating income almost doubled in the same time frame, from $413 million to $763 million, though per-share earnings plummeted from $4.95 to $1.96.

Moderna is expected to see revenue growth of 16.2% over the next twelve months. And with a forward-facing P/E of 5.84x, theres some indication that the company may be undervalued.

However, our AI is wary of Moderna especially after a year of such rapid, and situation-specific, growth. The company scored its highest rating, B, in Growth, with Ds across the rest of the board in Technicals, Quality Value, and Low Volatility Momentum.

After making our trending list last week after Atlantic Equities downgraded the chipmaker to underweight, Intel INTC is back after closing up almost 2.5% to $55.35 on Friday with 28 million trades on the books. Though the stock has seen some losses in the last 10 days, its still up 11% YTD.

Intel 5-year performance

Intels struggles in chip manufacturing and delivery have been compounded in recent weeks during the global chip shortage, with the company still behind several nanometers in design not to mention grappling with the results of a $2.2 billion judgment by a federal jury in March over patent infringement. Still, the company managed to deliver strong Q1 results in April, driven by exceptional product demand.

However, Intels last year was not its best its numbers are roughly stagnant in the three-year timespan. Revenue is up 9.7% over the past three years, from $70.8 billion to $77.9 billion, though operating income barely ticked up from $23.2 billion to $23.9 billion. Its EPS has risen by around $0.50 to $4.94 in per-share earnings, with ROE down to 26% from 29%. All in all, Intel is trading with a forward 12-month P/E of 12.94x.

Our AI doesnt have much faith in Intel to turn its situation around anytime soon, either. The company earned below-average ratings across the board from our artificial intelligence, with Cs in Quality Value and Low Volatility Momentum, D in Growth, and F in Technicals.

Wells Fargo WFC closed up 1.2% on Friday to $46.96 on volume of 17 million trades. The company is up 55.6% YTD, despite waffling between $46 and $45 on its 10- and 22-day price averages.

Wells Fargo 5-year performance

Wells Fargo has been on a massive public rehabilitation campaign since 2018, wading through scandal after lawsuit due to deplorable business practices that damaged the credit of their members and tarnished their reputation (and bottom line). In the years since, despite some slip-ups, Wells Fargo has done their best to make a comeback and with their stock earnings approaching pre-pandemic numbers at last, the company may just be about to make it.

Later this year, Wells Fargo is set to join a number of companies including fellow financial giants US Bancorp USB and JPMorgan Chase JPM in a government-backed pilot program to put credit cards in the hands of credit invisible individuals. Under this program, banks will share applicant information regarding balances and overdraft histories to identify financially responsible individuals who havent previously built credit. If the initiative proves promising, the banks may move into other types of lending particularly auto loans for responsible credit invisible individuals, as well.

This program gives Wells Fargo a company that once hurt the credit of thousands of its members a chance to redeem itself and give members a financial foot forward. Thats something that the company has experienced itself in the last year, as the company saw a revenue increase of 9.3% to $58.3 billion (down from $84.7 billion three years ago), and operating income growth of 216% to $2.1 billion (down from $28.5 billion three years ago).

And while its EPS and ROE remain in the tank - $0.41 and 1.92%, respectively Wells Fargo maintains a forward 12-month P/E of 14.16x.

Still, our AI remains skeptical of Wells Fargo, rating the company just below average with a D in Quality Value and Cs in Technicals, Growth, and Low Volatility Momentum.

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Artificial Intelligence Identifies IBM And Netflix Among Trending Stocks This Week - Forbes

The pace of software releases has only accelerated, and DevOps is the reason things have sped up. Now, artificial intelligence and machine learning are also starting to play a role in this acceleration of code releases.

That's the word from GitLab's latest surveyof 4,300 developers and managers, which finds some enterprises are releasing code ten times faster than in previous surveys. Almost all respondents, 84%, say they're releasing code faster than before, and 57% said code is being released twice as fast, from 35% a year ago. Close to one in five, 19%, say their code goes out the door ten times faster.

Tellingly, 75% are using AI/ML or bots to test and review their code before release, up from 41% just one year ago. Another 25% say they now have full test automation, up from 13%.

About 21% of survey respondents say the pace of releases has accelerated with the addition of source code management to their DevOps practice (up from 15% last year), the survey's authors add. Another 18% added CI and 13% added CD. Nearly 12% say adding a DevOps platform has sped up the process, while just over 10% have added automated testing.

Developers' roles are shifting toward the operations side as well, the survey shows. Developers are taking on test and ops tasks, especially around cloud, infrastructure and security. At least 38% of developers said they now define or create the infrastructure their app runs on. About 13% monitor and respond to that infrastructure. At least 26% of developers said they instrument the code they've written for production monitoring -- up from just 18% last year.

Fully 43% of our survey respondents have been doing DevOps for between three and five years -- "that's the sweet spot where they've known success and are well-seasoned," the survey's authors point out. In addition, they add, "this was also the year where practitioners skipped incremental improvements and reached for the big guns: SCM, CI/CD, test automation, and a DevOps platform."

Industry leaders concur that DevOps has significantly boosted enterprise software delivery to new levels, but caution that it still tends to be seen as an IT activity, versus a broader enterprise initiative. "Just like any agile framework, DevOps requires buy-in," says Emma Gautrey, manager of development operations at Aptum. "If the development and operational teams are getting along working in harmony that is terrific, but it cannot amount to much if the culture stops at the metaphorical IT basement door. Without the backing of the whole of the business, continuous improvement will be confined to the internal workings of a single group."

DevOps is a commitment to quick development/deployment cycles, "enhanced by, among other things, an enhanced technical toolset -- source code management, CI/CD, orchestration," says Matthew Tiani, executive vice president at iTech AG. But it takes more than toolsets, he adds. Successful DevOps also incorporates "a compatible development methodology such as agile and scrum, and an organization commitment to foster and encourage collaboration between development and operational staff."

Then organizations aspects of DevOps tend to be more difficult, Tiani adds. "Wider adoption of DevOps within the IT services space is common because the IT process improvement goal is more intimately tied to the overall organizational goals. Larger, more established companies may find it hard to implement policies and procedures where a complex organizational structure impedes or even discourages collaboration. In order to effectively implement a DevOps program, an organization must be willing to make the financial and human investments necessary for maintaining a quick-release schedule."

What's missing from many current DevOps efforts is "the understanding and shared ownership of committing to DevOps," says Gautrey. "Speaking to the wider community, there is often a sense that the tools are the key, and that once in place a state of enlightenment is achieved. That sentiment is little different from the early days of the internet, where people would create their website once and think 'that's it, I have web presence.'"

That's where the organization as a whole needs to be engaged, and this comes to fruition "with build pipelines that turn red the moment an automated test fails, and behavioral-driven development clearly demonstrating the intentions of the software," says Gautrey. "With DevOps, there is a danger in losing interaction with individuals over the pursuit of tools and processes. Nothing is more tempting than to apply a blanket ruling over situations because it makes the automation processes consistent and therefore easier to manage. Responding to change means more than how quickly you can change 10 servers at once. Customer collaboration is key."

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Artificial intelligence taking over DevOps functions, survey confirms - ZDNet

European Union (EU) lawmakers have introduced new rules that will shape how companies use artificial intelligence (AI). The rules are the first of their kind to introduce regulation to the sector, and the EUs approach is unique in the world.

In the US, tech firms are largely left to themselves, while in China, AI innovation is often government-led and used regularly to monitor citizens without too much hindrance from regulators. The EU bloc, however, is taking an approach that aims to maximise the potential of AI while maintaining privacy laws.

There are new regulations around cases that are perceived as endangering peoples safety or fundamental rights, such as AI-enabled behaviour manipulation techniques. There are also prohibitions on how law enforcement can use biometric surveillance in public places (with broad exemptions). Some high-risk cases also face specific regulatory requirements, before and after entering the market.

Transparency requirements have also been introduced for certain AI use cases, such as chatbots and deep fakes, where EU lawmakers believe risk can be mitigated if users are made aware that they are interacting with something that is not human.

Companies that do not comply with these new rules face fines of up to 6% of their annual revenue higher penalties than those that can be levied under the General Data Protection Regulation (GDPR).

Like many other firms in the AI sector, we are in favour of this type of legislation. For far too long, there have been too many cases where biased datasets have been used by companies to develop AI that discriminates against the society it is meant to serve. A good example was when Goldman and Apple partnered to launch a new credit card. The historical datasets used to run the automated approval process for the cards were biased and favoured male applicants over women, shutting out millions of prospective users.

These negative outcomes are a wake-up call for companies, and proof that they must seriously consider algorithm interpretability and testing. New, robust legislation puts a renewed sense of responsibility on those developing and implementing AI to be transparent and call out biases in datasets. Without legislation, companies have no incentive to put in the extra resources required to overcome such biases.

We believe that legislation can enforce ethics and help to reduce the disturbing amount of bias in AI especially in the world of work. Some AI recruitment tools have been found to discriminate against women because they lean towards favouring employees similar to their existing workforce, who are men.

And it does not stop at recruitment. As ProPublica unveiled a few years ago, a criminal justice algorithm deployed in Broward County, Florida, falsely labelled African-American defendants as high risk at nearly twice the rate that it mislabeled defendants who were white.

Beyond the problematic issues of bias against women and minorities, there is also the need to develop collectively agreed legal frameworks around explainable AI. This describes humans being able to understand and articulate how an AI system made a decision and track outcomes back to the origin of the decision. Explainable AI is crucial in all industries, but particularly in healthcare, manufacturing and insurance.

An app might get it wrong when recommending a movie or song without many consequences. But when it comes to more serious applications, such as a suggested dental treatment or a rejected application for an insurance claim, it is crucial to have an objective system for developing more understanding around explainable AI. If there are no rules around tracing how an AI system came to a decision, it is difficult to pinpoint where accountability lies as usage becomes more ubiquitous.

The public is arguably growing more suspicious of an increasingly widespread application of biometric analysis and facial recognition tools without comprehensive legislation to regulate or define appropriate use. One example of a coordinated attempt to corral brewing collective discontent is Reclaim Your Face, a European initiative to ban biometric mass surveillance because of claims that it can lead to unnecessary or disproportionate interference with peoples fundamental rights.

When it comes to tackling these issues, legislation around enforcing ethics is one step. Another important step is increasing the diversity of the talent pool in AI so that a broader range of perspectives is factored into the sectors development. The World Economic Forum has shown that about 78% of global professionals with AI skills are male a gender gap triple the size of that in other industries.

Fortunately, progress is being made on this front.

A welcome number of companies are coming up with their own initiatives to counteract biases in their AI systems, especially around the area of career recruitment and using machine learning to automate CV approval processes.

In the past, traditional AI applications would be trained to stream resums and if there were any biases in the datasets, then the model would learn them and discriminate against candidates. It could be something like a female-sounding name on a CV that the system is streaming. Subsequently, the system would not permit the hiring of that potential candidate as an engineer because of some implicit human bias against that name, and the model would therefore discard the CV.

However, there are standard ways to prevent these biased outcomes if the data scientist is proactive about it during the training phase. For example, giving an even worse score if the prediction is wrong for female candidates or simply removing data such as names, ages and dates, which shouldnt influence hiring decisions. Although these countermeasures may come at the cost of making the AI less accurate on paper, when the system is deployed in a place that is serious about reducing bias, it will help move the needle in the right direction.

The fact that more innovations and businesses are becoming conscious of bias and using different methods such as the abovementioned example to overcome discrimination is a sign that we are moving in a more optimistic direction.

AI is going to play a much bigger part in our lives in the near future, but we need to do more to make sure that the outcomes are beneficial to the society we aim to serve. That can only happen if we continue to develop better use cases and prioritise diversity when creating AI systems.

This, along with meaningful regulations such as that imposed by the EU, will help to mitigate conscious and unconscious biases and deliver a better overall picture of the real-world issues we are trying to address.

Shawn Tan is CEO of global AI ecosystem builder Skymind

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Why new EU rules around artificial intelligence are vital to the development of the sector - ComputerWeekly.com

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Tech stocks declined today following last weeks sell-off partly fueled by Elon Musk doing what he does best on Twitter with the Nasdaq NDAQ composite hitting losses of 1% in the early afternoon. Though prices may be dropping, we here at Q.ai cant think of a better time to go all-in on this weeks thematic screen: the tech Top Buys for the month of May.

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Activision Blizzard ATVI , the famous videogame company responsible for the popular Call of Duty franchise, bumped down 0.07% on Friday to $93.35 with 3.6 million trades on the books, though it remains up over 4.3% YTD.

The company peaked in Q1 following strong performance in their CoD franchise, spurred on by the introduction of mobile play that brought their active monthly user base to 150 million. Success from their King Digital and Blizzard Entertainment divisions saw games like Candy Crush and World of Warcraft prop up their performance and stock prices although the stock has trended down from their most recent high.

Activision 5-year performance

Activisions fiscal 2020 was a busy one: the company saw revenue increase by 6% to $8 billion, with operating income popping 6.7% to $2.8 billion almost a $1 billion increase over the last three years. EPS rose almost 5% to $2.82, though ROE fell from 17.7% to 15.7% in the three-year period. Currently, Activision is trading with a forward earnings ratio of 25x.

Due to its excellent performance and potential for expansion with such popular franchises as Call of Duty, our AI thinks fondly of Activision, rating the company As in Technicals and Low Volatility Momentum and Cs in Growth and Quality Value, bringing the videogame developer to Top Buy status for the month of May.

Qualcomm closed up 2.4% on Friday to $130.15 per share, banking 9.3 million trades by EOD. The semiconductor, software, and wireless technology services company is down almost 12% for the year.

Qualcomm 5-year performance

Qualcomms woes this month are not entirely their own the company is trending downward due to repeat rumblings that Apple AAPL is looking to release their own 5G modem by 2023, despite the iPhone makers licensing agreement with Qualcomm that extends through April of 2025. While this shouldnt be a surprise to investors (given that Apple bought their modem business from Intel way back in 2019), the market appears wary that this future problem could pose risks to Qualcomms bottom line.

But investors neednt worry. Qualcomm had a banner 2020 heading into the new fiscal year, with revenue up 25% to $23.5 billion and operating income exploding 43.2% to $6.23 billion. Their EPS also grew by 54.5% to $4.52 in per-share earnings, with ROE tripling to 94% from 31% three years ago.

Qualcomm is expected to experience modest revenue growth of 4.8% in the next twelve months, and is currently trading with a forward 12-month P/E of 16.15. Our AI believes that this is a company worth your investment dollars: Qualcomm, Inc QCOM is rated Top Buy for the month of May, with As in Quality Value and Growth and Cs for Technicals and Low Volatility Momentum.

Cirrus Logic, Inc CRUS closed up 1.6% on Friday, closing out the week at $74.55 per share and 354,000 trades. Though Friday ended the week on a good note, Cirrus Logic is still down 11.4% YTD, due in part to the semiconductor manufacturers fourth-quarter earnings that fell short of Wall Street estimates two weeks ago. The stock has been declining since on news that Q4 sales dropped 5%, with Q1 revenue guidance set 8% below Wall Street projections.

Cirrus Logic 5-year performance

But the company has a strong future with new opportunities upcoming, including a new integrated circuit that is likely to be a cornerstone of the flagship Apple phones in fall 2021. Cirrus Logic is also expecting a boost from their collaboration with Elliptic Labs, a global AI software company using Cirrus to certify and optimize their AI Virtual Smart Sensor Platform for smartphone, PC, and IoT customers.

Furthermore, Cirrus Logic experienced a solid 2020 despite the pandemic, with revenue up 5.8% to $1.28 billion. Their operating income grew by 25% in the same period to $195 million, though this is down from their $262 million operating income three years ago. All told, Cirrus Logix experienced per-share earnings growth of 27.5% to $2.64, with ROE ticking down to 13.46%.

Cirrus Logic, Inc. has been bolstered by their strong performance, climbing demand, and brand partnerships. With a forward 12-month P/E of 16.11, our AI sees good things in store for them, rating the semiconductor company Top Buy with As in Growth and Low Volatility Momentum and Bs in Technicals and Quality Value.

Keysight Technologies KEYS is one of those companies that doesnt crop up in common parlance often, but they perform a critical role: manufacturing the electronics test and measurement equipment and software that clears your favorite tech to be delivered to your doorstep. The company is slated to report second quarter fiscal 2021 results on 19 May and in anticipation of their expected favorable performance, we thought wed take a look at what their last year has brought to the table.

Keysight Technologies 5-year performance

Keysight Technologies closed up 1.3% on Friday to $139.85, bringing YTD gains to 6.6%. Their last year saw revenue growth of 2% to $4.2 billion, with operating income resting at $777 million a total rise of 4.6% over the fiscal twelve months.

Though EPS experienced slower growth in the last year, not even scratching 2%, the last three years have seen per-share earnings quadruple from $0.86 to $3.31, with ROE tripling to 19.9%. Keysight Technologies is currently trading with a forward 12-month P/E of 24.23.

Keysight Technologies robust 2020 performance benefited from continued momentum in smartphone processors, high-performance data center growth, and high-speed networking needs. These, combined with acceleration in chip design activity, are expected to positively contribute to their performance. And as remote work and online learning proliferate (with IBM planning to downscale its 50 million square foot building to a mere 150,608 on anticipation of permanent changes), Keysight has also bolstered their software testing capabilities.

Once again, our AI sees solid growth and possible chances for investor gains in Keysight Technologies, rating the company Top Buy for the month of May with Bs in Technicals and Growth and Cs in Low Volatility Momentum and Quality Value.

KLA Corporation KLAC closed up 3.33% on Friday, ending the week at $305.75 per share with 1.5 million trades on the books. The capital equipment company is up 18% YTD, despite recent declines in stock prices after reporting solid fiscal 2021 Q3 earnings two weeks ago, with total earnings up $1.8 billion.

Said President and CEO Rick Wallace at the time, KLAs March quarter results demonstrate strong momentum. We have seen a sharp increase in business levels in each of our major end markets, driven by secular demand trends across a broad range of semiconductor markets and applications.

KLA Corporation 5-year performance

KLA Corps positive 2021 Q3 earnings report followed a robust fiscal 2020, which saw the company increase revenue by 11% to $5.8 billion, with operating income growth topping out at 26% to almost $1.76 billion. Expansions in their bottom line also extended to per-share earnings, which ballooned 54.7% in the last fiscal year alone to $7.70. And though their ROE fell in the last three years, it remains around a hefty 45%.

KLA Corp is expected to continue this upward trend in future earnings reports, with forward revenue growth of 12.6% predicted over the next year. The company is currently trading with a forward 12-month P/E of 18.35.

With a year of growth behind them and a bright future going forward, our AI rates KLA Corp a Top Buy for May, with an A in Low Volatility Momentum, Bs in Growth and Quality Value, and D in Technicals.

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Artificial Intelligence Selects Activision Blizzard As A Thematic Stock Highlight This Week - Forbes

Artificial intelligence (AI) is more accessible than ever and is increasingly used to improve business operations and outcomes, not only in transportation and logistics management, but also in diverse fields like finance, healthcare, retail and others. An Oxford Economics and NTT DATA survey of 1,000 business leaders conducted in early 2020 reveals that 96% of companies were at least researching AI solutions, and over 70% had either fully implemented or at least piloted the technology.

Nearly half of survey respondents said failure to implement AI would cause them to lose customers, with 44% reporting their companys bottom line would suffer without it.

Simply put, AI enables companies to parse vast quantities of business data to make well-informed and critical business decisions fast. And, the transportation management industry specifically is using this intelligence and its companion technology, machine learning (ML), to gain greater process efficiency and performance visibility driving impactful changes bolstering the bottom line.

McKinsey research reveals that 61% of executives report decreased costs and 53% report increased revenues as a direct result of introducing AI into their supply chains. For supply chains, lower inventory-carrying costs, inventory reductions and lower transportation and labor costs are some of the biggest areas for savings captured by high volume shippers. Further, AI boost supply chain management revenue in sales, forecasting, spend analytics and logistics network optimization.

For the trucking industry and other freight carriers, AI is being effectively applied to transportation management practices to help reduce the amount of unprofitable empty miles or deadhead trips a carrier makes returning to domicile with an empty trailer after delivering a load. AI also identifies other hidden patterns in historical transportation data to determine the optimal mode selection for freight, most efficient labor resource planning, truck loading and stop sequences, rate rationalization and other process improvement by applying historical usage data to derive better planning and execution outcomes.

The ML portion of this emerging technology helps organizations optimize routing and even plan for weather-driven disruptions. Through pattern recognition, for instance, ML helps transportation management professionals understand how weather patterns affected the time it took to carry loads in the past, then considers current data sets to make predictive recommendations.

The Coronavirus disease (COVID-19) put a tremendous amount of pressure on many industries the transportation industry included but it also presented a silver lining -- the opportunity for change. Since organizations are increasingly pressed to work smarter to fulfill customers expectations and needs, there is increased appetite to retire inefficient legacy tools and invest in new processes and tech tools to work more efficiently.

Applying AI and ML to pandemic-posed challenges can be the critical difference between accelerating or slowing growth for transportation management professionals. When applied correctly, these technologies improve logistics visibility, offer data-driven planning insights and help successfully increase process automation.

Like many emerging technologies promising transformation, AI and ML have, in many cases, been misrepresented or worse, overhyped as panaceas for vexing industry challenges. Transportation logistics organizations should be prudent and perform due diligence when considering when and how to introduce AI and ML to their operations. Panicked hiring of data scientists to implement expensive, complicated tools and overengineered processes can be a costly boondoggle and can sour the perception of the viability of these truly powerful and useful tech tools. Instead, organizations should invest time in learning more about the technology and how it is already driving value for successful adopters in the transportation logistics industry. What are some steps a logistics operation should take as they embark on an AI/ML initiative?

Remember that the quality of your data will drive how fast or slow your AI journey will go. The lifeblood of an effective AI program (or any big data project) is proper data hygiene and management. Unfortunately, compiling, organizing and accessing this data is a major barrier for many. According to a survey conducted by OReilly, 70% of respondents report that poorly labeled data and unlabeled data are a significant challenge. Other common data quality issues respondents cited include poor data quality from third-party sources (~42%), disorganized data stores and lack of metadata (~50%) and unstructured, difficult-to-organize data (~44%).

Historically slow-to-adopt technology, the transportation industry has recently begun realizing the imperative and making up ground with 60% of an MHI and Deloitte poll respondents expecting to embrace AI in the next five years. Gartner predicts that by the end of 2024, 75% of organizations will move from piloting to operationalizing AI, driving a five times increase in streaming data and analytics infrastructures.

For many transportation management companies, accessing, cleansing and integrating the right data to maximize AI will be the first step. AI requires large volumes of detailed data and varied data sources to effectively identify models and develop learned behavior.

Before jumping on the AI bandwagon too quickly, companies should assess the quality of their data and current tech stacks to determine what intelligence capabilities are already embedded.

And, when it comes to investing in newer technologies to pave the path toward digital transformation, choose AI-driven solutions that do not require you to become a data scientist.

If youre unsure how to start, consider partnering with a transportation management system (TMS) partner with a record of experience and expertise in applying AI to transportation logistics operations.

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Artificial Intelligence and Machine Learning Drive the Future of Supply Chain Logistics - Supply and Demand Chain Executive

Assisting, not replacing: AI can amplify the work of officials but the webinar panellists agreed that it should not displace them. Image by Pixabay

Nothing better illustrates the need for governments to harness artificial intelligence (AI) than the challenge faced by Germanys Ministry of Labour and Social Affairs. In the next 15 years, 30% of its staff will retire and become users of the agencys pension system instead. This twin dynamic of staff retrenchment and greater demand for services sums up why governments across the world are so keen to embrace technology: how else to deliver more with fewer resources?

The demand that is really driving the diffusion of AI is demographic change, Michael Schnstein, head of strategic foresight and analysis at the ministrys Policy Lab Digital, told a Global Government Forum webinar in April.

Rather than following a predetermined set of rules, AI algorithms learn how to achieve their mission by identifying connections in large data sets. At its best, AI can revolutionise service delivery scanning a patent application to make an instantaneous adjudication without the need for human intervention, for example.

But the risks are also substantial. It can be hard to ensure that services are fully accountable and transparent if highly-complex, fast-evolving algorithms lie at their heart. Development can be costly, requiring the assembly and standardisation of huge quantities of data, and any biases in that data can be reproduced in faulty decision-making. As a result, many senior civil servants are understandably nervous about adoption.

In Germany, Schnstein has been able to launch some services that are completely AI-driven: a bot that uses text, image and speech recognition to help businesses register new employees for the countrys social security system, for example. But there are limits to how fast he can move, he commented.

In many cases, German legislation requires a signature to be applied before a government decision can be taken, limiting where AI can be applied. Works councils and trades unions must approve any new services in the areas of pensions and social security, complicating sign off of proposed deployments. And even for processes where AI has been applied, a human confirmation step may still be required.

As a result, 80-90% of AI deployments by the Ministry of Labour involve the improvement of individual steps within existing administrative processes, Schnstein said. The largest single field of experimentation has involved the existing child benefit application process, rather than any greenfield services.

This approach made sense to the other panellists, who argued that governments should move forward cautiously and by delivering practical, measurable improvements to existing services often assisting human decision-making, rather than replacing it entirely.

Very often, when we see a [new] technology stack such as AI, its very alluring to just start playing with it and make predictions and all kinds of awesome recommendations, said Dr Vik Pant, chief scientist and chief science advisor at Natural Resources Canada. But really the question [should be]: how does this map to the priorities and plans of our department?

Pant leads an accelerator within Natural Resources Canada. These institutions, borrowed from the world of startups and venture capital, involve interdisciplinary teams coming together to push forward a promising idea as fast as possible.

That might sound like the antithesis of gradual, pragmatic change. But Pant is keen to point out that the accelerator team work closely with the operational and frontline civil servants whose problems theyre trying to solve co-creating solutions alongside subject matter experts. This ensures both that the AI tool will closely match the requirement, and that service managers and elected leaders are familiar with its operation and characteristics.

Ensuring full line of sight for our departmental decision-makers into the rationales, the way we make choices, the way we make decisions, how we evaluate projects, [means] we can get buy-in from all of the leadership within our department, Pant told the online audience.

Nadun Muthukumarana, a data analytics partner at the events knowledge partner, consultancy Deloitte, was equally adamant that technologists must collaborate closely with policy and service managers rather than building AI products in splendid isolation. A lot of applications of AI fail [because] somebody is doing it as a proof of concept or an experiment, but when you try to scale it up to delivering services to millions of citizens it doesnt work, he said.

He advises his public sector clients to only consider using AI where enterprise tooling exists, ensuring that algorithms can be embedded in software able to process the extremely high volumes of transactions required in many government services. And Muthukumarana also emphasised the need for civil servants to cooperate across organisational boundaries, assembling data sets of sufficient scale and quality to support the effective use of AI.

In the United States, elected representatives have the resources and structures to hold the executive arm of government to account and this has led to heightened scrutiny of the use of AI. Taka Ariga, chief data scientist and director of the Innovation Lab at the US Government Accountability Office (GAO), explained that hes leading investigations into a number of cases where AI has already been deployed by American agencies.

He compared the current capabilities of AI unfavourably to those of a small child: Google Translate can help him navigate museums and restaurants in Paris, he noted, but remains unaware of the context of conversations meaning that its translations lack nuance. These constraints, he argued, should limit both AIs deployment and the weight put on its results. In many conversations with government digital professionals, he recalled, hes been assured that their models have been designed to squeeze out bias. But in his view, its still not clear how you operationalise do no evil creating systems that can both guarantee and demonstrate equity in outcomes. From a GAO perspective, we are in the business of verification, said Ariga. We would love to trust those AI implementations, but as an oversight entity, we want to see evidence.

Generating this evidence is becoming easier as the technology advances, commented Pant. People always talk in terms of black boxes, he said: algorithms whose operation has evolved to the point where decision-making becomes opaque to the systems managers. But just as much as there have been these advances in algorithms and models, there have been commensurate improvements also in explainability; in interpretability. So even as AI systems become more complex, their developers are finding new ways to maintain oversight of how individual decisions are being made.

Pants staff already produce documents explaining AI systems to senior civil servants and decision makers, he added, and these could also be distributed to regulators.

Regulation looks set to dominate the debate around AI for some time, and there is some concern that premature and overly-prescriptive rules could dampen innovation. When Schnstein recruited a specialist technology team and came up with proposals for several areas where AI implementations could be explored, he recalled, that immediately made our political leadership a little bit nervous.

The German government had already signed up to guidelines from global organisations governing the ethical use of AI, and his superiors were worried the proposed experiments might run counter to those. So Schnsteins team ended up working on two projects simultaneously developing guidelines on how to develop systems that comply with those standards, even as they built new AI systems for use within government. Wed have liked to do these sequentially, in an ideal world, he said.

Schnstein suggested that in many cases it will be sufficient to apply existing laws to AI, rather than passing new legislation focusing on the emerging technology. Youre not meant to discriminate when you hire people. Thats already the law, [so] what we need is to make sure the current law is applied when you use an AI-enabled recruitment system, he said.

But regulators worry that technological changes will render existing governance frameworks obsolete, said Ariga. Too often, oversight entities are playing catch-up, he commented. Theres plenty of examples out there where we wait until a certain maturity of technology before we dive into the accountability implications.

One way forward, said Muthukumarana, may be to vary regulatory scrutiny and compliance requirements between industrial sectors tailoring oversight to the risk involved. Self-driving cars, which make thousands of life-or-death decisions every day, might need greater scrutiny than an AI deployed to produce transcripts of conferences, he commented.

I think different industries will have domain-specific frameworks, said Muthkumarana. There might be some universal truths that can be incorporated. But a lot of these things will be developed on a domain-by-domain basis.

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Being smart with artificial intelligence: deploying AI in the public sector - Global Government Forum

SUNNYVALE, Calif.--(BUSINESS WIRE)--With the help of next generation technology, passengers at William P. Hobby Airport HOU, will get an upgrade to their travel experience, which includes live journey and wait times for passenger and social distance monitoring.

We want our passengers to feel empowered by the technology we implement throughout their travel experience, Houston Airport Director IT Program Management Diego Parra said. This technology not only helps passenger know what to expect at certain points in their journey, but it also provides us with valuable information to keep them safe. When we see a congested area that needs greater social distancing, we can respond.

The technology is powered by advanced artificial intelligence and machine learning through LiveReach Media (LRM), a comprehensive motion analytics and digital out-of-home marketing platform. The motion analytics system integrates into Houston Airports existing technology infrastructure to measure passenger throughput and provide accurate live wait times at TSA and immigration checkpoints. Existing or new monitors can also display live journey times to restaurants and retail locations inside the airport.

Airports, especially award-winning ones such as Houston, clearly see the need of becoming more data driven but widespread adoption of motion analytics has been limited due to the lack of scalability or the large upfront capital investment associated with traditional solutions. Weve democratized analytics for all airports, large and small, with our single-click integration or our easy-to-deploy sensing options. Abhi Jain, Co-Founder of LiveReach Media

Airports across the United States, including Des Moines International and El Paso International, have selected LiveReach Medias system due to its premium performance and simple deployment and most recently, in April of 2021, LiveReach Media was selected by Philadelphia International to provide Queue Management and Content Management Services via a public bidding process.

This is just the start, Parra said. Houston Airports is looking to expand LiveReach Medias comprehensive analytics and advanced artificial intelligence to become the airport system of the future.

About Houston Airports

Houston Airports is the City of Houstons Department of Aviation. Comprised of George Bush Intercontinental Airport (IAH), William P. Hobby Airport (HOU) and Ellington Airport (EFD) / Houston Spaceport, Houston Airports served nearly 25 million passengers in 2020 and nearly 60 million passengers in 2019. Houston Airports forms one of North America's largest public airport systems and positions Houston as the international passenger and cargo gateway to the South-Central United States and as a primary gateway to Latin America. Houston is proud to be the only city in the Western Hemisphere with two Skytrax rated 4-star airports.

About LiveReach Media

Trusted by large grocery chains, transportation hubs, and retail stores around the world, LiveReach Medias comprehensive motion analytics and digital out-of-home marketing platform helps venues operate more effectively, engage with their customers at scale, and create better and safer customer experiences. LiveReach Media is headquartered in Sunnyvale, California with several offices globally.

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Airport of the Future: Houston's Hobby Airport Uses Artificial Intelligence to Provide a Next Gen Travel Experience - Business Wire