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"Instead, the new work shows our brains rely on the kind of maths that an algorithm might use to perform the task. In fact, Tsao and her colleague, Steven Le Chang, stumbled on their discovery while working on computer vision. The pair had initially set themselves the challenge of coming up with a way of reliably converting facial images into a numerical representation."

"It is the first time scientists have created sentences from brain activity linked to handwriting and paves the way for more sophisticated devices to help paralysed people communicate faster and more clearly. The man, known as T5, who is in his 60s and lost practically all movement below his neck after a spinal cord injury in 2007, was able to write 18 words a minute when connected to the system. On individual letters, his "mindwriting" was more than 94% accurate."

"Imagine having a digital twin that gets ill, and can be experimented on to identify the best possible treatment, without you having to go near a pill or a surgeon's knife. Scientists believe that within five to 10 years, "in silico" trials - in which hundreds of virtual organs are used to assess the safety and efficacy of drugs - could become routine, while patient-specific organ models could be used to personalise treatment and avoid medical complications. Digital twins are computational models of physical objects or processes, updated using data from their real-world counterparts. Within medicine, this means combining vast amounts of data about the workings of genes, proteins, cells and whole-body systems with patients' personal data to create virtual models of their organs - and eventually, potentially their entire body"

"AI tool GNoME finds 2.2 million new crystals, including 380,000 stable materials that could power future technologies Modern technologies from computer chips and batteries to solar panels rely on inorganic crystals. To enable new technologies, crystals must be stable otherwise they can decompose, and behind each new, stable crystal can be months of painstaking experimentation. Today, in a paper published in Nature, we share the discovery of 2.2 million new crystals - equivalent to nearly 800 years' worth of knowledge. We introduce Graph Networks for Materials Exploration (GNoME), our new deep learning tool that dramatically increases the speed and efficiency of discovery by predicting the stability of new materials."

"Researchers showed detectors can be defeated by inserting inputs called adversarial examples into every video frame. The adversarial examples are slightly manipulated inputs which cause artificial intelligence systems such as machine learning models to make a mistake. In addition, the team showed that the attack still works after videos are compressed."