Daily Archives: March 31, 2021

Its hard enough for people to categorize or discuss art, but its even more difficult for artificial intelligence. Several research groups have recently tried to apply machine learning to large databases of artworks to sort and describe them in a meaningful way.

First, researchers from Zhejiang University of Technology in Hangzhou, China, compared different neural networks to find out how well they perform at art classification. They used images from WikiArt and other digital collections to train the neural networks to learn what images of a certain art style look like. Then they asked the different neural network models to identify the art style of other images.

This is quite a tricky task, even for humans. Some art styles are easy to recognize from the way the image is created. Learning which artworks fall under the cubism genre wasnt a problem for the neural networks. But some genres are quite similar to each other and occurred around the same time. That made it difficult for the programs to learn which is which.

Vincent van Gogh's "Starry Night", seen here at an exhibit in Berlin, Germany, was one of the images ... [+] used in a study to categorize art using artificial intelligence. (Photo Sean Gallup/Getty Images)

The art classification neural networks also had trouble with tasks that humans wouldnt find very difficult at all, such as understanding the difference between cityscapes and landscapes. The difference between buildings and nature is obvious to us, but to a computer, they both look like images with similar elements of outside. It doesnt have a way of knowing that the clouds and sky in these images are not the key defining factor of these two categories.

For human art lovers, learning which style or category a piece of art falls in is a relatively straightforward and objective task. Like the neural networks, we can learn how to do that by looking at a lot of art and finding patterns. But theres something humans do that computers dont: we also form opinions about the art and can share in words how looking at it makes us feel. Computers cant do that yet - or can they?

Artificial intelligence is only as good as its training data, so to be able to teach an AI to form opinions and emotional statements about art, you need a vast collection of human-created descriptions of different artworks. Thats exactly what researchers from Stanford University, Ecole Polytechnique and King Abdullah University of Science and Technology have done. They created the ArtEmis dataset which includes over 400 thousand emotional attributes and descriptions for over 80 thousand images indexed in WikiArt.

To create ArtEmis, the team asked volunteers to share their main emotion about an artwork, and to explain that in a sentence. As you would expect, peoples reactions varied widely. One person might find a painting of a field peaceful while someone else finds it slightly ominous. In fact, having both positive and negative reactions to the same painting was so common, this happened to 61% of the images in the ArtEmis database.

So what does an AI make of all those human descriptions of art? When trained on the ArtEmis dataset, different systems started creating their own captions for given artworks. Some of them were very convincing, but others missed the mark. AI-generated descriptions of Rembrandts painting The Beheading of John the Baptist included the woman looks like she is having a good time and the man in the middle looks like he is in pain. Any human would recognize these descriptions as complete nonsense (or at the very least a major understatement) considering the scene in the painting.

An AI algorithm creating descriptions of images based on replicating human emotion said of ... [+] Rembrant's "The Beheading of John the Baptist" that the woman looks like she is having a good time and the man in the middle looks like he is in pain.

About half of the computer-generated descriptions passed the Turing test, which means that AIs can indeed learn to create new (and believable) descriptions of art, but its still far from perfect. Thats not surprising, considering its already a challenge to teach an AI whether a painting is a landscape or a cityscape.

Art can be hard to classify and peoples opinions about paintings are highly subjective, which makes it even harder for artificial intelligence to understand the patterns of our classifications and descriptions. But the experiments done in these two new studies show that computers are getting better at these tasks. Humans are still better at categorising and describing art, but AI programs are learning quickly.

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Artificial Intelligence Is Learning To Categorize And Talk About Art - Forbes

Boasting that it is on track to bring over 100 "AI-powered" improvements to Google Maps, Google has announced a series of updates that have been or are set to be released in the coming year.

The first is adding Live View, a feature that uses augmented reality cues -- arrows and accompanying directions -- to help point people in the right way and avoid the "awkward moment when you're walking the opposite direction of where you want to go".

According to Google Maps product VP Dane Glasgow, Live View relies on AI technology, known as global localisation, to scan "tens of billions" of Street View images to help understand a person's orientation, as well as the precise altitude and placement of an object inside a building, such as an airport, transit station, or shopping centre, before providing directions.

"If you're catching a plane or train, Live View can help you find the nearest elevator and escalators, your gate, platform, baggage claim, check-in counters, ticket office, restrooms, ATMs and more. And if you need to pick something up from the mall, use Live View to see what floor a store is on and how to get there so you can get in and out in a snap," Glasgow explained in a post.

For now, the indoor Live View feature is available on Android and iOS in a number of shopping centres in the US across Chicago, Long Island, Los Angeles, Newark, San Francisco, San Jose, and Seattle, with plans to expand it to a select number of airports, shopping centres, and transit stations in Tokyo and Zurich. More cities will also be added, Glasgow confirmed.

See also:Google Maps turns 15: A look back on where it all began

Glasgow added commuters will be able to view the current and forecast temperature and weather conditions, as well as the air quality in an area through Google Maps, made possible through data shared by Google partners such as The Weather Company, AirNow.gov, and the Central Pollution Board. To be available on Android and iOS, the weather layer will be made available globally, while the air quality layer will launch in Australia, the US, and India, with plans to see it expanded in other countries.

On the environment, Glasgow also noted that Google is building a new routing model using insights from the US Department of Energy's National Renewable Energy Lab to help deliver more eco-friendly route options, based on factors like road incline and traffic congestion, for commuters in the US on Android and iOS. The model will be available later this year, with plans for global expansion at an unspecified later date.

Glasgow said the move is part of the company's commitment to reduce its environmental footprint.

"Soon, Google Maps will default to the route with the lowest carbon footprint when it has approximately the same ETA as the fastest route. In cases where the eco-friendly route could significantly increase your ETA, we'll let you compare the relative CO2 impact between routes so you can choose," he said.

In further efforts to meet its sustainability commitment, the tech giant also plans to introduce in "coming months" an updated version of Maps where commuters will have a view of all routes and transportation modes available to their destination, without toggling between tabs, while also automatically prioritising a user's preferred transport mode or modes that are popular in their city.

"For example, if you bike a lot, we'll automatically show you more biking routes. And if you live in a city like New York, London, Tokyo, or Buenos Aires where taking the subway is popular, we'll rank that mode higher," Glasgow said.

Also, within Maps, Google said it is teaming up with US supermarket Fred Meyer to pilot in select stores in Portland, Oregon a feature that has been designed to make contactless grocery pickup easier, including notifying commuters what time to leave to pick up their groceries, share the arrival time with the store, and allow customers to "check-in" on the Google Maps app so their grocery orders can be brought out to their car on arrival.

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Google Maps using artificial intelligence to help point people in the right direction - ZDNet

The robots are coming. If there is one thing we learned from the COVID-19 pandemic, its that when humans are sent home, machines keep working.

This doesnt mean that robots will take over the world. It does, however, mean that our technical landscape is changing.

Human history has a long and favorable track record of technological advancements, particularly when it comes to ideas that seem ludicrous at the time (Wright brothers, anyone?). The printing press, assembly line and personal computer have all helped move civilization forward by leaps and bounds over the last few centuries.

Imagine being one of the first people to replace glasses with contact lenses by putting them directly on their eyes, no less. Henry Ford replaced horses with the automobile as our main mode of transportation. The process of pasteurization changed the way we eat. Examples like these are endless, because throughout human history, there has been innovation and change.

Even as recently as the 1980s, there was no internet in peoples homes. The very means by which you are reading this article did not exist. Online school did not exist, at least not in the way we take college classes online now.

And while each technological advancement may have its detractors, its hard to argue with the benefits of technology as a whole. After all, thinking big got us to the moon, and gave us television, 3-D printing and a host of incredible advances in modern medicine.

So, are you wondering whats next? The future of technology lies squarely with machine learning and with artificial intelligence, known as AI.

Artificial intelligence is part of the field of data science. People who work in data science are skilled in developing mathematical algorithms to answer complex questions. When, for example, a company like Netflix wants to predict what movies a customer might want to watch next, a data scientist will create an algorithm based on that customers viewing history. Then, they will use that algorithm to offer a list of suggestions.

Machine learning is a branch of data science which involves using data science programs that can adapt based on experience, said Ben Tasker, technical program facilitator of data science and data analytics at Southern New Hampshire University. Take a weather predictor, for example. The more weather inputs there are, the better the prediction for what will come next.

While machine learning is useful, its important to note that there is no artificial intelligence involved in its functions. Machine learning involves rote mathematical or mechanical processes only.

Artificial intelligence then advances data science and machine learning even further.

Whereas machine learning can make predictions, artificial intelligence can make adjustments to its computations. In other words, AI can adjust a program to execute tasks smartly, Tasker said. For example, a fully autonomous, self-driving car is an example of something that would use full artificial intelligence.

These days, the idea of such a self-driving car is no longer science fiction. As the fields of science and engineering continue to advance, artificial intelligence is becoming a lot less artificial and a lot more intelligent, Tasker said.

Because so much about the field of data science in general and AI in particular is new, there are many opportunities to make your own niche, especially now that many companies have started to invest in the idea of artificial intelligence, Tasker said. This creates a wealth of career opportunities for those who thrive on charting their own path. The future of AI is great.

Careers for computer information and research scientists are predicted to grow 15% between now and 2029, according to the U.S. Bureau of Labor Statistics (BLS). That is much faster than the national average for career growth. The median pay is a healthy $122,840 per year, BLS reported.

Some other top career options for machine learning and artificial intelligence include:

So, will robots replace humans moving forward? For some jobs or tasks, quite possibly. For all jobs or tasks? Not likely.

Of course, robots are already in the workplace, Tasker said. They are not intelligent, but they perform basic tasks. Car manufacturers use robots on assembly lines already and have for years.

Whether a company actively uses artificial intelligence or not, all industries will be impacted by it, whether intentionally or unintentionally, Tasker said. I do think that some industries will have a higher barrier of entry, so to speak, such as medicine, he said. Patients still prefer a human touch for things like receiving a diagnosis or test results.

As artificial technology continues to develop, humans will need to have an ethical debate about what robots can and cannot do, but yes, we will see more robots, said Tasker.

And as use of robots grows, without a doubt, ethics is going to play a much larger role as AI grows, said Tasker, or at least it should.

Careers in machine learning and artificial intelligence are still being defined, which creates generous opportunities to innovate and carve your own career path. If you like math, computer programming, coding, and technology in general, a career in data science, machine learning, or AI is definitely one to consider.

Having a strong foundation in math and STEM can help prepare you for a career in AI. Knowledge of psychology will be particularly helpful, too.

Also important: a large threshold for change. Data science [and AI with it] changes every year, Tasker said, so the people working in data science will need to change with it. You will always be learning new technologies, algorithms, and coding languages.

The more math, programming, and experience with cloud computing that you can get under your belt, the better.

And, as more and more adoption of artificial intelligence technologies occur, we will begin to see an ethical debate emerge about what AI should and should not be doing, Tasker said. That makes courses in ethics critical, because "as the field of AI grows, more ethical considerations will need to be applied."

Keep in mind that while a bachelors degreeis a great foundation on which to build a career in artificial intelligence, an advanced degree is likely necessary to advance to the highest levels in the field.

Most jobs in the field of artificial intelligence require a graduate degree, such as a master of science or even doctorate, so be ready to continually learn, said Tasker.

While no career is truly future-proof given the ever-changing technology landscape, there are some ways you can be best prepared to weather the change. By grounding yourself with a strong science, math, and engineering background and then being ready to drive change, you may enjoy a long and prosperous career in the field of artificial intelligence.

Of course, while having a strong academic background is important, being good at math and programming is not enough. To really thrive in this career-field, you also need good, old-fashioned grit. In fact, curiosity, grit, and being humble are key traits toward having a successful, long-term career in data science, and especially in artificial intelligence, said Tasker. These are traits that you cannot necessarily learn in the classroom, but are helpful to being successful in this field long-term.

We have actually been using AI for some time, and not just in factories and on assembly lines, or to design futuristic cars.

Have you ever filled out a job application and included key words so that the artificial job screening tool doesnt filter you out of contention? Thats artificial intelligence.

Some artificial intelligence programs can even scan how a resume is drafted to see personality traits of an applicant, said Tasker. Other programs use facial recognition, which scans your facial expressions in an interview to create personality profiles of applicants.

Likewise, if you have ever used a website and a chat bot popped up, saying How can I help you today? that is also artificial intelligence. If youve ever thought you were chatting with a real, live human only to be informed that youre chatting with a bot, you already know just how realistic artificial intelligence tools already are in the business and retail world.

Chat bots and virtual assistants are being routinely used to respond to easy emails, schedule appointments, and even take meeting notes for users, Tasker said. While at times, being on the receiving end of using a bot can be frustrating, many businesses use them because they can perform repetitive tasks that have some known outcomes, such as which department your query needs to be routed to when you contact customer service for a company.

There are limitations currently, though. While chat bots can accomplish a surprisingly large number of tasks, they cannot operate your Tesla, for example, said Tasker.

With high return-on-investment to using chat bots and interview bots, the use of artificial intelligence in commerce is not likely to go away anytime soon. If anything, the use of AI will continue to grow in new and innovative ways.

With an increased use in artificial intelligence comes an increase in the conversation about how it should be implemented. This is where a background in psychologycould be helpful for people working in this field. "Psychology is important because it teaches a student how the human brain works, which is complicated," said Tasker. "To really learn to program AI, learning how the brain works at some basic level would help as well."

Just because a chat-bot can attend a meeting for an employee, does that mean that we should also make a bot that can perform medical exams? Where is the line? What about facilitating a classroom and teaching our children? Tasker asked. "What about fully autonomous truck driving?"

Is there a line between what we need versus what we can do? And where does focusing on the bottom line financially begin to cost us when it comes to our humanity?

These are big questions for which there are no easy answers. Yet by studying data science, math and STEM, and by embracing the change inherent in the field of machine learning and artificial intelligence, you just might be the next Wilbur or Orville Wright.

Marie Morganelli, PhD, is a freelance content writer and editor.

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The Future of AI: Careers in Machine Learning - Southern New Hampshire University

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Advances in artificial intelligence (AI) over the years has become foundational technology in autonomous vehicles and security systems. Now, a team of researchers at the University of Stanford are teaching computers to recognise not just what objects are in an image, but also how those images make people feel.

The team has trained an algorithm to recognise emotional intent behind great works of art like Vincent Van Goghs Starry Night and James Whistlers Whistlers Mother.

The ability will be key to making AI not just more intelligent, but more human, a researcher said in the study titled ArtEmis: Affective Language for Visual Art.

Also Read | Artificial Intelligence knows when you feel lonely

The team built a database of 81,000 WikiArt paintings and over 4 lakh written responses from 6,500 humans indicating how they felt about a painting. This included their reason for choosing a particular emotion. The team used the responses to train AI to generate emotional responses to visual art and justify those emotions in language.

The algorithm dissected the artists work into one of eight emotional categories including awe, amusement, sadness and fear. It then explained in written text what it is in the image that justifies the emotion.

Also Read | AI finds Bollywoods association of beauty with fair skin unchanged

The model is said to interpret any form of art, including still life, portraits and abstraction. It also takes into account the subjectivity of art, meaning that not everyone feels the same way about a piece of work, the team noted.

The tool can be used by artists, especially graphic designers, to evaluate if their work is having the desired impact.

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This is what happens when artificial intelligence meets emotional intelligence - The Hindu

PHILADELPHIA & STOCKHOLM--(BUSINESS WIRE)--Proscia, a leading provider of digital and computational pathology solutions, and Unilabs, a leading international provider of diagnostic services, have established a strategic partnership to accelerate the adoption of artificial intelligence (AI) in routine pathology practice. Through the collaboration, Unilabs will validate the efficacy of Proscias computational pathology applications and deploy them into its high-throughput workflows, improving diagnostic quality and reducing turnaround times to directly benefit patients and the physicians treating them.

Proscia will bring its experience building AI applications that perform across laboratory settings to the center of the partnership. It will collaborate with Unilabs to create de-identified data sets, using the latest technology to adhere with data protection regulations, for developing AI solutions that drive meaningful quality and productivity gains. Unilabs will also test the utility of Proscias computational applications, generating clinical and economic evidence on their capacity to achieve their intended purposes.

Unilabs will innovate its service offerings through the partnership by beginning to implement computational pathology into its routine workflows leveraging Proscias suite of AI applications. Unilabs will initially deploy DermAI, which classifies images of skin biopsies displaying more than 200 diagnosis with a high degree of accuracy, to study the applications impact on its high-throughput pathology operations.

At Unilabs, we pride ourselves on delivering accurate, timely diagnoses. Deploying Proscias AI solutions will enable us to provide better care to our patients and better serve our referring physicians, said Dr. Christian Rebhan, Chief Medical and Operations Officer at Unilabs. The adoption of AI is poised to make the biggest impact on pathology since the introduction of light microscopy over a century ago, and we are excited to chart our path in computational pathology with Proscia, said Claudio Silvestrin, Head of the AI Centre of Excellence at Unilabs.

In forming this strategic partnership, Unilabs joins the growing list of academic and commercial laboratories with which Proscia is working to accelerate the adoption of digital and computational pathology in clinical practice. Earlier this year, Proscia announced that LabPON has adopted its CE-IVD certified Concentriq Dx to scale its routine pathology operations amid a surge in demand for diagnostic services. In August 2020, Proscia established a Computational Pathology Center of Excellence with the University Medical Center Utrecht. The company also published the results of one of the largest and most comprehensive validation studies performed in pathology to date in support of its DermAI.

Proscia is committed to advancing the standard of care, and we will enable this change by driving adoption of computational pathology, said Julianna Ianni, VP of AI Research & Development. In partnering with Unilabs, we are working towards delivering real-world AI solutions that perform across multiple laboratory settings and demonstrating their implementation at scale.

About Proscia

Proscia is a software company that is changing the way the world practices pathology to transform cancer research and diagnosis. With the companys Concentriq digital pathology platform and pipeline of AI-powered applications, laboratories are leveraging new kinds of data to accelerate discoveries and improve patient outcomes. Proscias team of technologists, scientists, and pathologists is bringing a fresh approach to an outdated industry, helping the world to keep pace with the increasing demand for pathology services and fulfill the promise of precision diagnostics. For more information, visit proscia.com.

About Unilabs

Unilabs is one of Europes largest and fastest-growing diagnostics companies. It offers a complete range of laboratory, pathology and imaging services for patients all around the world. With 12,000 employees across 110 imaging centers and 250 labs in 17 countries, we perform close to four million lab tests a week saving lives every single day. Its digitized pathology services from accredited laboratories span 12 countries across Europe, Latin America and Middle East, with a subspecialist network of more than 200 pathologists, providing timely and actionable reports. The Unilabs AI Centre of Excellence is continuously searching for and evaluating the latest AI solutions, to provide Unilabs patients and physicians with the best possible service & care. For more information, visit unilabs.com.

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Proscia and Unilabs Enter Strategic Partnership to Advance the Use of Artificial Intelligence in High-Throughput Diagnostic Workflows - Business Wire

Could artificial intelligence reduce the need for human therapists?

Websites, smartphone apps and social-media sites are dispensing mental-health advice, often using artificial intelligence. Meanwhile, clinicians and researchers are looking to AI to help define mental illness more objectively, identify high-risk people and ensure quality of care.

Some experts believe AI can make treatment more accessible and affordable. There has long been a severe shortage of mental-health professionals, and since the Covid pandemic, the need for support is greater than ever. For instance, users can have conversations with AI-powered chatbots, allowing them to get help anytime, anywhere, often for less money than traditional therapy.

The algorithms underpinning these endeavors learn by combing through large amounts of data generated from social-media posts, smartphone data, electronic health records, therapy-session transcripts, brain scans and other sources to identify patterns that are difficult for humans to discern.

Despite the promise, there are some big concerns. The efficacy of some products is questionable, a problem only made worse by the fact that private companies dont always share information about how their AI works. Problems about accuracy raise concerns about amplifying bad advice to people who may be vulnerable or incapable of critical thinking, as well as fears of perpetuating racial or cultural biases. Concerns also persist about private information being shared in unexpected ways or with unintended parties.

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Can Artificial Intelligence Replace Human Therapists? - The Wall Street Journal

Pune, India, March 30, 2021 (Wiredrelease) Prudour Pvt. Ltd : The New Report Artificial Intelligence-based Security Market posted through MarketResearch.Biz, covers the market panorama and its growth possibilities over the upcoming years. The report also offers leading players in this market. The research comprises in-depth insight of the worldwide share, size, and developments, in addition to the growth rate of the Artificial Intelligence-based Security Market to estimate its development throughout the forecast period. Most importantly, the report in addition identifies the historical, current, and future developments which might be predicted to persuade the improvement ratio of the Artificial Intelligence-based Security market. The research segments the market on the premise of offering, deployment type, security type, solution, technology, industry vertical, and region. To provide extra readability concerning the Artificial Intelligence-based Security industry, the report takes a more in-depth study the contemporary fame of different factors along with however now no longer confined to deliver chain management, area of interest markets, distribution channel, trade, deliver, supply and manufacturing functionality regionwise.

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Business Segmentation Research and Study

SWOT Analysis and Porters Five Forces Evaluation

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The Artificial Intelligence-based Security market objective examine are:

Artificial Intelligence-based Security Overview Market Status and Future Forecast 2021 to 2031

Artificial Intelligence-based Security Market report mentioned product developments, partnerships, mergers and acquisitions, RD tasks are mentioned

Artificial Intelligence-based Security Market Details on Opportunities and Challenges, Restrictions and Risks, Market Drivers, Challenges.

General aggressive scenario, along with the principle market players, their growth targets, expansions, deals.

In-depth Description of Artificial Intelligence-based Security Market Manufacturers, Sales, Revenue, Market Share, and Latest Developments for Key Players.

To examine and research the Artificial Intelligence-based Security market through offering, deployment type, security type, solution, technology, industry vertical, and region

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What are the principal elements that take this market to the top level?

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Artificial Intelligence-Based Security Market Key Factor Drive Growth Is Increasing Adoption of Internet of Things - WV News