A frustration for physicians and primary care providers alike is trying to balance listening to a patient and properly documenting the medical visit. This documentation is essential to making sure all the data is captured properly and that the patient was heard and treated correctly. Ravi Atreya and Pedro Teixeira, who met when they were in a joint M.D./Ph.D. program at Vanderbilt University, set out to solve the problem and eventually founded PredictionHealth, which uses artificial intelligence (AI) to help health providers complete documentation. On this episode of the Tennessee Voices podcast, the pair talked about their passion for medicine, computer science and data and how AI can be "game changing." The purpose behind their startup was helping create effective communication channels and reducing the frustration doctors and nurses may face at times with technology.

Congratulations to Tao Chen, Jie Xu and Pulkit Agrawal who have won the CoRL 2021 best paper award! Their work, A system for general in-hand object re-orientation, was highly praised by the judging committee who commented that "the sheer scope and variation across objects tested with this method, and the range of different policy architectures and approaches tested makes this paper extremely thorough in its analysis of this reorientation task". Below, the authors tell us more about their work, the methodology, and what they are planning next. We present a system for reorienting novel objects using an anthropomorphic robotic hand with any configuration, with the hand facing both upwards and downwards. We demonstrate the capability of reorienting over 2000 geometrically different objects in both cases.

Tech CEO Demis Hassabis is known for his role in DeepMind, an artificial intelligence company based in the United Kingdom and known as the subsidiary of Google's Alphabet. The CEO and his focus on the company have earned it one of the top recognitions in the world, and it is currently one of the top companies sought out with regards to AI. Demis Hassabis was born in London, England, on July 27, 1976, and has attended the University of Cambridge from 1995 to 1997 with top honors and a degree in Computer Science. Hassabis is also known as a chess master and is fond of gaming. He briefly joined Lionhead Studios before forming his own company, Elixir Studios are known for game development. Alongside this, he is also known for winning the World Series of Poker for six different seasons.

The thriving of artificial intelligence (AI) applications is driving the further evolution of wireless networks. It has been envisioned that 6G will be transformative and will revolutionize the evolution of wireless from "connected things" to "connected intelligence". However, state-of-the-art deep learning and big data analytics based AI systems require tremendous computation and communication resources, causing significant latency, energy consumption, network congestion, and privacy leakage in both of the training and inference processes. By embedding model training and inference capabilities into the network edge, edge AI stands out as a disruptive technology for 6G to seamlessly integrate sensing, communication, computation, and intelligence, thereby improving the efficiency, effectiveness, privacy, and security of 6G networks. In this paper, we shall provide our vision for scalable and trustworthy edge AI systems with integrated design of wireless communication strategies and decentralized machine learning models. New design principles of wireless networks, service-driven resource allocation optimization methods, as well as a holistic end-to-end system architecture to support edge AI will be described. Standardization, software and hardware platforms, and application scenarios are also discussed to facilitate the industrialization and commercialization of edge AI systems.

Robert Falck used to work at a Russian trucking factory by day, and by night, he built a nightclub guest list startup. He also collects old books, and once guessed that Chinese author Gao Xingjian would win the Nobel Prize in literature. He grew up on a farm, but has degrees in finance, economics and mechanical engineering. No, this isn't a game of two truths and a lie -- indeed, these are snippets from the life of a serial entrepreneur who harbors a vendetta against the carbon emissions produced by the world's trucking industry. Falck, now the CEO and founder of Swedish autonomous freight company Einride, also worked as the director of manufacturing engineering assembly at Volvo GTO Powertrain.

Who goes to a demonstration with a high-powered assault weapon? He planned on bringing his high-powered assault weapon to that demonstration with every intention of using it. He claims it was self-defense -- it was not. He was out for blood, his goal was to shoot and kill as many as possible and claim it was self-defense. Absolutely relieved that the jury in this case based their deliberations and ultimate not guilty verdict on the facts and didn't cower to the obvious intended intimidation of BLM, Antifa, the left-leaning liberal loonies, and last but not least, the lying fake media.

The research team behind Meta AI's Detectron project has recently been awarded the PAMI Mark Everingham Prize for contributions to the computer vision community. We first open-sourced the Detectron codebase five years ago as a collection of state-of-the-art algorithms for tasks such as object detection and segmentation. It has since evolved and advanced in important ways thanks to the contributions of both the open source community and many researchers here at Meta. In 2019, we released a ground-up rewrite of the codebase entirely in PyTorch to make it faster, more modular, more flexible, and easier to use in both research-first and production-oriented projects. Earlier this year, we released Detectron2Go, a state-of-the-art extension for training and deploying efficient object detection models on mobile devices and hardware, as well as significantly improved baselines based on the recently published state-of-the-art results produced by other experts in the field. Several members of the Detectron team sat down to discuss the project's origins, advances, and future.

Drones are remarkable things, nonetheless. The other day, a representative of the U.S. National Forest Service was reporting on their use for re-seeding incinerated forests in California, speeding the process at a vastly reduced cost. It occurred to me, though, that the same dark cloud/silver lining thinking applied. Imagine all the out-of-work foresters heading for the unemployment line in the shade of a flock of drones. It occurred to me, as well, that this replacement of "repetitive task" workers with artificial intelligence (AI) technology was fully expected. The first wave of AI pushed millions of such laborers out of the labor force.

This week, on the new-media platform Feral File, artist Refik Anadol presents Unsupervised, an exhibition of works created by training an artificial intelligence model with the public metadata of The Museum of Modern Art's collection. Spanning more than 200 years of art, from paintings to photography to cars to video games, the Museum's collection represents a unique data set for an artist who has worked with many different public archives. The AI-based abstract images and shapes in Unsupervised are interpretations of the Museum's wide-ranging collection, weighted toward the exhibition of new artworks at MoMA this fall. Starting with the exhibition opening on November 18, new artworks will be revealed and released over three days. Each work will be made available to collectors as nonfungible tokens, or NFTs. MoMA curators Paola Antonelli and Michelle Kuo sat down with Anadol and Casey Reas, the artist-founder of Feral File, to talk about the ecology of mobile images, art in the age of mechanical learning, and the question: What if a machine tried to create "modern art"? This conversation has been edited for length and clarity. Paola Antonelli: Refik, how did you start thinking of your Machine Hallucinations series, of which Unsupervised is a part? Refik Anadol: Five years ago, I was very fortunate to be one of the artists in residence at the Google Artists and Machine Intelligence program. This was the moment of DeepDream's development, the very first time we were witnessing AI algorithms making an impact on the art and technology communities.

Zest AI, a leader in software for credit underwriting, today announced it has been selected as an honoree in Fast Company's inaugural 2021 Next Big Things in Tech Awards. The awards recognize the companies and technologies that promise to redefine their industries and create a positive impact for consumers, businesses and society at large in the next five years. Specifically, Zest AI was recognized for its Fairness Kit, a set of software applications created in response to demand from banks and credit unions looking to reduce bias from consumer lending. Zest's patented machine learning-based solution automatically optimizes credit underwriting models for both accuracy and fairness, creating real options for the first time for lenders that want to close the racial approval rate gap in consumer credit. "We are honored to have our fair lending efforts recognized by Fast Company for this award," said Mike de Vere, CEO of Zest AI. "Traditionally, lenders have had to make trade-offs between accuracy in risk prediction and minimizing disparate impact. Through our technology, these lenders can make more accurate decisions and say yes to more people who might have struggled to get affordable credit. This award further endorses our mission of making fair and transparent credit available to everyone."