Zume was the darling of fast food automation until it nearly went bust. Now the brand is disrupting packaging.
A new technique compares the reasoning of a machine-learning model to that of a human, so the user can see patterns in the model’s behavior. In machine learning, understanding why a model makes certain decisions is often just as important as whether those decisions are correct.
Speedcam Anywhere allows anyone to submit evidence of drivers speeding
When artificial intelligence is tasked with visually identifying objects and faces, it assigns specific components of its network to face recognition — just like the human brain. The human brain seems to care a lot about faces. It’s dedicated a speci
First-of-its-kind survival predictor detects patterns in heart MRIs invisible to the naked eye. A new artificial intelligence-based approach can predict, significantly more accurately than a doctor, if and when a patient could die of cardiac arrest.
For individuals who communicate using a single switch, a new interface learns how they make selections, and then self-adjusts accordingly. In 1995, French fashion magazine editor Jean-Dominique Bauby suffered a seizure while driving a car, which left
MIT AI Hardware Program launches with five inaugural companies to advance AI technologies for the next decade. The MIT AI Hardware Program is a new academia and industry collaboration aimed at defining and developing translational technologies in hardware and software for the AI and quantum age.
While machine learning in ad tech won't replace humans, it can free marketers from tedious tasks and empower them to be superhuman.
Will the big tech companies dominate AI applications? Experts weighed the pros and cons in a recent online conference.
MLops is still an emerging field, so it may be tempting to write it off as just another techy buzzword, but its track-record proves that when designed the right way and targeted at the proper goal: to maximize model performance and improve ROI, it pays off.
Predicting how climate and the environment will change over time or how air flows over an aircraft are problems too complex even for the most powerful supercomputers to solve. Scientists rely on models to fill in the gap between what they can simulate and what they need to predict.
By itself, data is like a bicycle with no wheels. It can’t go anywhere. That’s where the power of analytics comes in. Similar to the wheels of a bike, analytics powers data to reveal meaningful trends and insights, enabling organisations to make key business decisions.
By itself, data is like a bicycle with no wheels. It can’t go anywhere. That’s where the power of analytics comes in. Similar to the wheels of a bike, analytics powers data to reveal meaningful trends and insights, enabling organisations to make key business decisions.
Almost 75 years ago, U.S. Air Force pilot Chuck Yeager became the first person to fly faster than the speed of sound. Engineers have been pushing the boundaries of ultrafast flight ever since, attaining speeds most of us can only imagine.
Kirigami is the Japanese art of paper cutting. Likely derived from the Chinese art of jiǎnzhǐ, it emerged around the 7th century in Japan, where it was used to decorate temples. Still in practice today, the kirigami artist uses one piece of paper to cut decorative designs, like birds and fish or the more intricate and popular snowflake.
Data meshes and data fabrics have become hot topics of conversation as enterprises look to improve their data analytics operations.
Lilt is staking its claim in the $23.8 billion global language services and technology industry. The company offers translation technology and services through a human-in-the-loop AI approach. This branch of AI creates machine learning (ML) models from both human and machine intelligence.
Deep learning models have proved to be very effective for analyzing large amounts of data and accurately predicting future events. This makes them advantageous for a wide range of applications, including weather forecasting.