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Category: robotics/AI

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The machine learning models that can detect our face and movements are now part of our daily lives with smartphone features like face unlocking and Animoji. However, those AI models can’t predict how we feel by looking at our face. That’s where EmoNet comes in.

Researchers from the University of Colorado and Duke University have developed the neural net that can accurately classify images in 11 emotional categories. To train the model, researchers used 2,187 videos that were clearly classified into 27 distinct emotion categories including anxiety, surprise, and sadness.

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What if neither distance nor language mattered? What if technology could help you be anywhere you need to be and speak any language? Using AI technology and holographic experiences this is possible, and it is revolutionary.

Microsoft has created a hologram that will transform someone into a digital speaker of another language. The software giant unveiled the technology during a keynote at the Microsoft Inspire partner conference this morning in Las Vegas. Microsoft recently scanned Julia White, a company executive for Azure, at a Mixed Reality capture studio to transform her into an exact hologram replica.

The digital version appeared onstage to translate the keynote into Japanese. Microsoft has used its Azure AI technologies and neural text-to-speech to make this possible. It works by taking recordings of White’s voice, in order to create a personalized voice signature, to make it sound like she’s speaking Japanese.

Microsoft has shown off holograms of people before, but the translation aspect is a step beyond what has been possible with HoloLens. This looks like it’s just a demonstration for now, and you’d need access to a Mixed Reality capture studio to even start to take advantage of this. Microsoft’s studios are equipped with lighting rigs and high-resolution cameras to capture a fully accurate digital hologram of someone, which isn’t something that can be done easily at home with a smartphone just yet.

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Stand by to start space mining – not on an asteroid, but aboard the International Space Station (ISS). Delivered to the station by an unmanned Dragon cargo ship on July 27, an experimental mining kit developed by a team led by the University of Edinburgh will use bacteria to study how microorganisms can be used to extract minerals and metals from rocks on asteroids, moons, and planets.

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Understanding of repair outcomes after Cas9-induced DNA cleavage is still limited, especially in primary human cells. We sequence repair outcomes at 1,656 on-target genomic sites in primary human T cells and use these data to train a machine learning model, which we have called CRISPR Repair Outcome (SPROUT). SPROUT accurately predicts the length, probability and sequence of nucleotide insertions and deletions, and will facilitate design of SpCas9 guide RNAs in therapeutically important primary human cells.

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To tackle this environmental catastrophe, U.S. companies and researchers are developing AI-assisted robotic technology that can work with humans in processing plants and improve quality control. The goal is to have robots do a better job at sorting garbage and reduce the contamination and health hazards human workers face in recycling plants every day. Sorting trash is a dirty and dangerous job. Recycling workers are more than twice as likely as other workers to be injured on the job, according to a report at the University of Illinois School of Public Health. The profession also has high fatality rates.

The U.S. is facing a recycling crisis that is burying cities and towns in tens of millions of tons of garbage a day. The problem began last year when China, the world’s largest recyclable processor, stopped accepting most American scrap plastic and cardboard due to contamination problems, and a glut of plastics overwhelming its own processing facilities. Historically, China recycled the bulk of U.S. waste.

Contamination in the U.S. is high since recyclables are often dumped into one bin instead of multi-streamed or separated from the source. Now China has strict standards for recycling materials it will accept, requiring contamination levels in a plastic bale, for example, contain one-tenth of 1%.

The situation is dire for many local economies as recycling costs skyrocket. It’s forced many cities and some small communities to stop recycling all together. Now more waste is ending up in landfills and incinerators.

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But that always looked like a tall order when faced with stiff competition from tech giants like Google, IBM, and Amazon, all happy to pour billions into AI research. Faced with that reality, OpenAI has undergone a significant metamorphosis in the last couple of years.

Musk stepped away last year, citing conflicts of interest as his electric car company Tesla invests in self-driving technology and disagreements over the direction of the organization. Earlier this year a for-profit arm was also spun off to enable OpenAI to raise investment in its effort to keep up.

A byzantine legal structure will supposedly bind the new company to the original mission of the nonprofit. OpenAI LP is controlled by OpenAI’s board and obligated to advance the nonprofit’s charter. Returns for investors are also capped at 100 times their stake, with any additional value going to the nonprofit, though that’s a highly ambitious target that needs to be hit before any limits on profiteering would kick in.

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For decades, computer programmers have been trying to beat multiplayer games by finding reliable patterns in data.

Researchers at Facebook and Carnegie Mellon University published a whitepaper in Science Journal in July that flips this switch. Their software embraces randomness, and it is reliably beating humans at games.

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