Machine learning and automation are already widely welcomed as a … Growth in digital business is also driving interest in artificial intelligence, …

Language modeling is one of the interesting machine learning problems.

Artificial intelligence has been making waves in recent years, enabling us to solve problems faster than traditional computing could ever allow. Recently, for example, Google's artificial intelligence subsidiary DeepMind developed AlphaFold2, a program which solved the protein-folding problem. This is a problem which has had baffled scientists for 50 years. Advances in AI have allowed us to make progress in all kinds of disciplines – and these are not limited to applications on this planet. From designing missions to clearing Earth's orbit of junk, here are a few ways artificial intelligence can help us venture further in space.

Daniel Weimer heads up the AI Detroit unit and his team of software engineers and machine learning specialists are tasked with uncovering and …

As millions of tons of plastic wash into the ocean everyday, scientists have their work cut out for them in trying to keep tabs on its whereabouts, but they may soon have a useful new tool at the their disposal. Researchers at the University of Barcelona have developed an algorithm that can detect and quantify marine litter through aerial imagery, something they hope can work with drones to autonomously scan the seas and assess the damage. Taking stock of our plastic pollution problem is a tall order, with so much of it entering the ocean each day and being broken down into smaller fragments that are difficult to trace. The University of Barcelona team has taken aim at those pieces floating on the surface, hoping to improve on current methods of tracking their distribution, which involve surveying the damage from planes and boats. An interesting example of this is the work carried out by The Ocean Cleanup Project, which has ventured into the Great Pacific Garbage Patch with research vessels and flown over the top of it with aircraft fitted out with sensors and imaging systems.

Even if you can't name the tunes, you've probably heard them: from the iconic "dun-dun-dun-dunnnn" opening of Beethoven's Fifth Symphony to the melody of "Ode to Joy," the German composer's symphonies are some of the best known and widely performed in classical music. Just as enthusiasts can recognize stylistic differences between one orchestra's version of Beethoven's hits and another, now machines can, too. A Duke University team has developed a machine learning algorithm that "listens" to multiple performances of the same piece and can tell the difference between, say, the Berlin Philharmonic and the London Symphony Orchestra, based on subtle differences in how they interpret a score. In a study published in a recent issue of the journal Annals of Applied Statistics, the team set the algorithm loose on all nine Beethoven symphonies as performed by 10 different orchestras over nearly eight decades, from a 1939 recording of the NBC Symphony Orchestra conducted by Arturo Toscanini, to Simon Rattle's version with the Berlin Philharmonic in 2016. Although each follows the same fixed score -– the published reference left by Beethoven about how to play the notes -- every orchestra has a slightly different way of turning a score into sounds.

WSJ:What is the most exciting way AI and machine learning are being used to diagnose mental disorders and improve treatments?

Part of this fear stems from concerns about access. All countries are naturally trying to scientifically develop AI to benefit their populations.

Learn more about data science and artificial intelligence (AI) and how they can be used to better understand and utilise data your business.

AMS Healthcare: Compassion and Artificial Intelligence Small Grant. Sponsor. This program is offered as a partnership between the AMS Healthcare …