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How IBM Watson Overpromised and Underdelivered on AI Health Care

After its triumph on Jeopardy!, IBM’s AI seemed poised to revolutionize medicine. Doctors are still waiting

16 min read
Conceptual photo-illustration imagining IBM’s AI Watson as a concerned doctor, with the Watson logo standing in for the doctor’s face.
Illustration: Eddie Guy

In 2014, IBM opened swanky new headquarters for its artificial intelligence division, known as IBM Watson. Inside the glassy tower in lower Manhattan, IBMers can bring prospective clients and visiting journalists into the “immersion room," which resembles a miniature planetarium. There, in the darkened space, visitors sit on swiveling stools while fancy graphics flash around the curved screens covering the walls. It's the closest you can get, IBMers sometimes say, to being inside Watson's electronic brain.

One dazzling 2014 demonstration of Watson's brainpower showed off its potential to transform medicine using AI—a goal that IBM CEO Virginia Rometty often calls the company's moon shot. In the demo, Watson took a bizarre collection of patient symptoms and came up with a list of possible diagnoses, each annotated with Watson's confidence level and links to supporting medical literature.

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When Gamers Get Nasty

Researchers grapple with subjectivity as they develop aIgorithms to detect toxicity in online gaming

2 min read
A man wearing a headset is seen in a dark room playing video games
Getty Images

Online gaming is a chance for players to come together, socialize and enjoy some friendly competition. Unfortunately, this enjoyable activity can be hindered by abusive language and toxicity, negatively impacting the gaming experience and causing psychological harm. Gendered and racial toxicity, in particular, are all too common in online gaming.

To combat this issue, various groups of researchers have been developing AI models that can detect toxic behavior in real-time as people play. One group recently developed a new model, which is described in a study published May 23 in IEEE Transactions on Games. While the model can detect toxicity with a fair amount of accuracy, its development demonstrates just how challenging it can be to determine what is considered toxic—a subjective matter.

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Quantum Computing for Dummies

New guide helps beginners run quantum algorithms on IBM's quantum computers over the cloud

3 min read
An image of the inside of an IBM quantum computer.
IBM

Quantum computers may one day rapidly find solutions to problems no regular computer might ever hope to solve, but there are vanishingly few quantum programmers when compared with the number of conventional programmers in the world. Now a new beginner's guide aims to walk would-be quantum programmers through the implementation of quantum algorithms over the cloud on IBM's publicly available quantum computers.

Whereas classical computers switch transistors either on or off to symbolize data as ones or zeroes, quantum computers use quantum bits, or "qubits," which because of the peculiar nature of quantum physics can exist in a state called superposition where they are both 1 and 0 at the same time. This essentially lets each qubit perform two calculations at once. The more qubits are quantum-mechanically linked, or entangled (see our explainer), within a quantum computer, the greater its computational power can grow, in an exponential fashion.

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Modeling Microfluidic Organ-on-a-Chip Devices

Register for this webinar to enhance your modeling and design processes for microfluidic organ-on-a-chip devices using COMSOL Multiphysics

1 min read
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Comsol

If you want to enhance your modeling and design processes for microfluidic organ-on-a-chip devices, tune into this webinar.

You will learn methods for simulating the performance and behavior of microfluidic organ-on-a-chip devices and microphysiological systems in COMSOL Multiphysics. Additionally, you will see how to couple multiple physical effects in your model, including chemical transport, particle tracing, and fluid–structure interaction. You will also learn how to distill simulation output to find key design parameters and obtain a high-level description of system performance and behavior.

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