Lifeboat Foundation

Virtual assistants and robots are becoming increasingly sophisticated, interactive and human-like. To fully replicate human communication, however, artificial intelligence (AI) agents should not only be able to determine what users are saying and produce adequate responses, they should also mimic humans in the way they speak.

Researchers at Carnegie Mellon University (CMU) have recently carried out a study aimed at improving how virtual assistants and robots communicate with humans by generating natural gestures to accompany their speech. Their paper, pre-published on arXiv and set to be presented at the European Conference on Computer Vision (ECCV) 2020, introduces Mix-StAGE, a new model that can produce different styles of co-speech gestures that best match the voice of a speaker and what he/she is saying.

“Imagine a situation where you are communicating with a friend in a virtual space through a virtual reality headset,” Chaitanya Ahuja, one of the researchers who carried out the study, told TechXplore. “The headset is only able to hear your voice, but not able to see your hand gestures. The goal of our model is to predict the hand gestures accompanying the speech.”

“For the first time ever, we have direct experimental evidence that an external quantum efficiency above 100% is possible in a single photodiode without any external antireflection,” says Hele Savin, associate professor of Micro and Nanoelectonics at Aalto University in Finland. The results come just a few years after Savin and colleagues at Aalto University demonstrated almost unity efficiency over the wavelength range 250–950 nm in photodiodes made with black silicon, where the silicon surface is nanostructured and coated to suppress losses.

Noticing some curious effects in the UV region, Savin’s group extended their study of the devices to focus on this region of the electromagnetic spectrum. UV sensing has multiple applications, including spectroscopy and imaging, flame detection, water purification and biotechnology. While annual market demand for UV photodiodes is expected to increase to 30%, the efficiency of these devices has been limited to 80% at best. To Savin’s surprise, closer analysis of their device’s response to UV light revealed that the external quantum efficiency could exceed 130%. Independent measurements at Physikalisch Technische Bundesanstalt (PTB) verified the results.

A team of researchers at Stanford University has created an artificial intelligence-based player called the Vid2Player that is capable of generating startlingly realistic tennis matches—featuring real professional players. They have written a paper describing their work and have uploaded it to the arXiv preprint server. They have also uploaded a YouTube video demonstrating their player.

Video game companies have put a lot of time and effort into making their games look realistic, but thus far, have found it tough going when depicting human beings. In this new effort, the researchers have taken a different approach to the task—instead of trying to create human-looking characters from scratch, they use sprites, which are characters based on video of real people. The sprites are then pushed into action by a computer using artificial intelligence to mimic the ways a human being moves while playing tennis. The researchers trained their AI system using video of real tennis professionals performing; the footage also provided imagery for the creation of sprites. The result is an interactive player that depicts real professional tennis players such as Roger Federer, Serena Williams, Novak Jovovich and Rafael Nadal in action. Perhaps most importantly, the simulated gameplay is virtually indistinguishable from a televised tennis match.

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Take a sneak peek at our agenda: https://go.nasa.gov/31JrSyi?fbclid=IwAR1QTlNK9Q2QjgbHR5GYaCw…4ECrtpbCDM

OpenAI’s new language generator #GPT-3 is shockingly good—and completely mindless: https://bit.ly/3kphfsX

By Will Douglas Heavenarchive page from MIT Technolgy Review

#AI #MachineLearning #NeuralNetworks #DeepLearning

Continue reading “OpenAI’s new language generator GPT-3 is shockingly good—and completely mindless” »

Network neuroscience could revolutionize how we understand the brain—and change our approach to neurological and psychiatric disorders.

Individual frequency can be used to specifically influence certain areas of the brain and thus the abilities processed in them — solely by electrical stimulation on the scalp, without any surgical intervention. Scientists at the Max Planck Institute for Human Cognitive and Brain Sciences have now demonstrated this for the first time.

Stroke, Parkinson’s disease and depression — these medical illnesses have one thing in common: they are caused by changes in brain functions. For a long time, research has therefore been conducted into ways of influencing individual brain functions without surgery in order to compensate for these conditions.

Scientists at the Max Planck Institute for Human Cognitive and Brain Sciences in Leipzig have taken a decisive step. They have succeeded in precisely influencing the functioning of a single area of the brain. For a few minutes, they inhibited exactly the area that processes the sense of touch by specifically intervening in its rhythm. As a result, the area that was less networked with other brain regions, its so-called functional connectivity, decreased, and thus also the exchange of information with other brain networks.

NR and NMN are popular ways to try to boost levels of NAD+, but that approach hasn’t worked every time in human studies. One reason for that may involve CD38, which degrades both NR and NMN. With the goal of boosting NAD+ levels during aging, why does CD38 increase with age, and what can be done about it? All that and more in this video!