Scientists at the Massachusetts Institute of Technology have stumbled upon an interesting problem with machine learning and image classification. This problem, if not solved, could be harmless or could be deadly, depending on what the system is being used for. Simply put, a model could look at an image and make a prediction based on information that we humans can't make sense of, and it could be wrong. Image classification is used in both medical diagnostics and autonomous driving. The aim is to train a neural network to understand an image in a similar way that a human does.

Imagine a highly sophisticated body armor that is a tough as it is flexible, a shield that consists largely of water, but remains strong enough to prevent mechanical penetration. Now imagine that this armor is not only strong, but also soft and stretchy, so much so that the wearer is able to move their body parts with ease, whether they're swimming in water, walking across the ground or rushing to escape danger. That description might sound like a suit worn by a fictional hero in the DC Comics franchise, but it actually describes portions of a lobster's exoskeleton. Researchers at the Massachusetts Institute of Technology and Harvard believe the soft membrane covering the animal's joints and abdomen ---- a material that is as tough as the industrial rubber used to make car tires and garden hoses ---- could guide the development of a new type of flexible body armor for humans, one designed to cover joints like knees and elbows. The researchers' findings appeared in a recent edition of the journal Acta Materialia.

Norman, developed by MIT Media Lab, serves as an example of how the data used to train artificial intelligence matters deeply. That's because Norman is a "psychopath" powered by artificial intelligence and developed by the MIT Media Lab. Norman is an algorithm meant to show how the data behind AI matters deeply. MIT researcherssay they trainedNorman using the written captions describing graphic images and video about death posted on the "darkest corners of Reddit," a popular message board platform. The team then examined Norman's responses to inkblots used in a Rorschach psychological test.

That's because Norman is a "psychopath" powered by artificial intelligence and developed …

Norman always sees the worst in things. That's because Norman is a "psychopath" powered by artificial intelligence and developed by the MIT Media Lab. Norman is an algorithm meant to show how the data behind AI matters deeply. MIT researchers say they trained Norman using the written captions describing graphic images and video about death posted on the "darkest corners of Reddit," a popular message board platform. The team then examined Norman's responses to inkblots used in a Rorschach psychological test.

Want to watch this again later? Need to report the video? This feature is not available right now. It is an algorithm-based piece of artificial intelligence, or AI, created by a team of researchers at CSIRO and the Massachusetts Institute of Technology (MIT) that spontaneously generates zombie faces out of human ones and transforms images of places into visions of the inferno. Audio: At the Foot of the Sphinx 04:29 At the Foot of the Sphinx by Twin Musicom is licensed under a Creative Commons Attribution license (https://creativecommons.org/licenses/...) Artist: http://www.twinmusicom.org/

Just in time for Halloween and the presidential election, MIT scientists have created an AI that makes images spooky. Think of it like filter app Prisma, but with a more sinister spin. A three-person team created an algorithm called Nightmare Machine that generates Halloween-inspired images from pictures of faces and places. It's not the first creepy AI -- Google's Deep Dream has been creating nightmares since June -- but some early results are promising. The algorithm is still a work-in-progress, however.

Scientists at Massachusetts Institute of Technology (MIT) claim they have created an AI that can detect 85% of cyber attacks -- albeit with the help of humans. The "AI2" algorithm, developed by MIT's Computer Science and Artificial Intelligence Lab (CSAIL) and machine learning startup PatternEx, can reportedly detect cyber attacks three times more effectively than today's current systems. AI2 has been tested on 3.6 billion pieces of data, known as "log lines," which were created over a three month period by millions of people. In order to predict attacks, AI2 scans sets of data and identifies suspicious activity. It does this by clustering the data into meaningful patterns using unsupervised machine-learning, according to MIT.

Scientists at Massachusetts Institute of Technology (MIT) claim they have created an AI that can detect 85% of cyber attacks -- albeit with the help of humans. The „AI2" algorithm, developed by MIT's Computer Science and Artificial Intelligence Lab (CSAIL) and machine learning …

Donald Trump's speeches are nothing like that, according to Brad Hayes, a MIT scientist who programmed a Twitter bot to sound like him. Called DeepDrumpf, it uses an artificial intelligence algorithm based on Trump's language in hundreds of hours of debate transcripts. Hayes told Tech Insider he has learned a lot over the last few weeks about how Trump talks. Here is how he describes Trump's language, which differs dramatically from past presidential candidates. Trump often uses short, imperative sentences, Hayes says.