If you are looking for an answer to the question What is Artificial Intelligence? and you only have a minute, then here's the definition the Association for the Advancement of Artificial Intelligence offers on its home page: "the scientific understanding of the mechanisms underlying thought and intelligent behavior and their embodiment in machines."
However, if you are fortunate enough to have more than a minute, then please get ready to embark upon an exciting journey exploring AI (but beware, it could last a lifetime) …
Machine Learning, Data Science, and Predictive Analytics techniques are in strong demand. That's why since its launch, IBM Watson Studio has proven to be very popular with academia. Thousands of students and faculty have been drawn to Watson Studio for its powerful open source and code-free data analysis tools. Now, this all-in-one platform for data science is free to students and faculty with unlimited use with Watson Studio Desktop. Watson Studio Desktop, with unlimited compute, is now available for free to students and faculty for teaching and learning purposes via a 1 year subscription.
MIT's Computer Science and Artificial Intelligence Lab has developed a new deep learning-based AI prediction model that can anticipate the development of breast cancer up to five years in advance. Researchers working on the product also recognized that other similar projects have often had inherent bias because they were based overwhelmingly on white patient populations, and specifically designed their own model so that it is informed by "more equitable" data that ensures it's "equally accurate for white and black women." That's key, MIT notes in a blog post, because black women are more than 42 percent more likely than white women to die from breast cancer, and one contributing factor could be that they aren't as well-served by current early detection techniques. MIT says that its work in developing this technique was aimed specifically at making the assessment of health risks of this nature more accurate for minorities, who are often not well represented in development of deep learning models. The issue of algorithmic bias is a focus of a lot of industry research and even newer products forthcoming from technology companies working on deploying AI in the field.
"We can run these simulations in a few milliseconds, while other'fast' simulations take a couple of minutes," says study co-author Shirley Ho, a group leader at the Flatiron Institute's Center for Computational Astrophysics in New York City and an adjunct professor at Carnegie Mellon University. The speed and accuracy of the project, called the Deep Density Displacement Model, or D3M for short, wasn't the biggest surprise to the researchers. The real shock was that D3M could accurately simulate how the universe would look if certain parameters were tweaked--such as how much of the cosmos is dark matter--even though the model had never received any training data where those parameters varied. "It's like teaching image recognition software with lots of pictures of cats and dogs, but then it's able to recognize elephants," Ho explains. "Nobody knows how it does this, and it's a great mystery to be solved."
Eyes are more than the "windows to the soul." As such, ocular health and neurological health are intertwined. The most skilled ophthalmologists can read ocular scans to not only look for eye disease, but also traces of a host of neurological disorders. Voxeleron is using artificial intelligence and machine learning to, as they put it, "democratize expertise." Their algorithms hold the promise of delivering expert-level diagnostic capabilities to any lab with a scanning device.
While today's deep learning systems are able to natively analyze video, the large file sizes of high resolution movies present unique challenges in terms of storage space and computational requirements. Sampling them into sequences of still images not only allows for real-time processing of unlimited-length videos but opens the door for creative new applications like "video ngrams." The most straightforward way to sample a video into a sequence of still images is to use a fixed-rate time-based mechanism such as one frame per second. This kind of sampling is supported natively by most tools like ffmpeg and provides a simplistic and robust workflow. At the same time, it is highly inefficient, especially for videos where there is a lot of repetition.
TTEC Holdings, Inc., a leading digital global customer experience technology and services company focused on the design, implementation and delivery of transformative customer experience for many of the world's most iconic and disruptive brands, will be showcasing Associate Assist and other innovative technology solutions for AI-enhanced training, omnichannel interactions and journey orchestration during Customer Contact Week, June 24-27, in Las Vegas. TTEC creates employee experiences that increase engagement and designs, builds and operates customer experiences that deliver results. TTEC uses Intelligent Virtual Assistants (IVAs) to empower employees and deliver seamless service experiences that enable hyper personalization, increase response time and improve accuracy. Associate Assist augments associates by monitoring conversations between associates and customers and scanning through data to deliver the suggested next best action or response to the associate, in real-time. In addition, the solution establishes a closed loop, AI-enhanced, self-training knowledge base that is used not only to train new associates but also improve associate accuracy, efficiency and consistency.
A team of MIT researchers is making it easier for novices to get their feet wet with artificial intelligence, while also helping experts advance the field. In a paper presented at the Programming Language Design and Implementation conference this week, the researchers describe a novel probabilistic-programming system named "Gen." Users write models and algorithms from multiple fields where AI techniques are applied -- such as computer vision, robotics, and statistics -- without having to deal with equations or manually write high-performance code. Gen also lets expert researchers write sophisticated models and inference algorithms -- used for prediction tasks -- that were previously infeasible. In their paper, for instance, the researchers demonstrate that a short Gen program can infer 3-D body poses, a difficult computer-vision inference task that has applications in autonomous systems, human-machine interactions, and augmented reality.
Our increasing fascination with the hyper-performance of machines, smart software and AI is casting a shadow over our elusive and ephemeral'human-only skills.' As our working environments shift dramatically it's time for a change in our performance metrics, too. My recommendation comes in the form of'Key Human Indicators,' designed to protect and encourage human agency in our future workforces. The current dialogue around the future of work is dominated by digitisation, cognification, automation and what I describe as the '10 Megashifts' in my recent book Technology vs Humanity. The conversation, however, rarely considers the humans in this equation.
About Hanson Robotics Limited Hanson Robotics is an AI and robotics company dedicated to creating living, intelligent machines that enrich people's lives. The company develops renowned robot characters, such as Sophia, the world's first robot citizen, which serve as AI platforms for scientific research, education, healthcare, sales and service, entertainment, and other research and service applications. Hanson Robotics' scientists, artists, roboticists, and engineers strive to bring robots to life as true friends who deeply understand and care for people, and collaborate with us in pursuit of ever-greater good for all. For more information please visit www.hansonrobotics.com.