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GPUs have long been the standard hardware used for performing machine learning. To train today’s large deep learning models, practitioners and researchers often use GPUs, which require additional specialized knowledge to utilize for training models. The need for GPUs to train deep learning models has increased the barriers to performing research and creating products for those who do not have access to such specialized hardware. But Neural Magic, a startup created by MIT professor Nir Shavit, wants to change that. The startup, which recently released its first line of products, redesigned the deep learning software to run more efficiently on a CPU, achieving the same speed that a GPU would by avoiding the need to ferry data on and off the GPU. While Shavit thinks that CPUs will come to be “the actual fabric for running machine-learning algorithms,” MIT research scientist Neil Thompson is less sure, stating that while Neural Magic can squeeze more performance out of existing hardware, “fundamental hardware advancements will still be the only way to drive computing forward.”
NeurIPS, the world’s biggest and most recognizable AI conference, has made the news frequently. Recently, NeurIPS announced a requirement for a “societal impact” statement that would require authors to consider positive and negative impacts of their work. In another drastic shift, the organizers announced that the 2020 conference would be completely virtual and that tickets would be considerably cheaper. Indeed, NeurIPS’ shift towards inclusivity does signal its reckoning with the shortcomings of a less inclusive past. NeurIPS has reflected the field of AI’s demographics–mostly male and white–with the high cost of attendance and visa denials aiding homogeneity. In addition to the significantly reduced registration fee, a virtual conference will not require travel and lodging costs. Since NeurIPS has also removed the attendance cap, the conference will become more accessible to those who have not been able to attend in the past.
Advances & Business
This AI tool helps people with speech difficulties to communicate - A new AI tool can help people with speech difficulties to communicate by reducing the number of keystrokes they need to type.
Artificial intelligence makes blurry faces look more than 60 times sharper - This AI turns blurry pixelated photos into hyperrealistic portraits that look like real people. The system automatically increases any image’s resolution up to 64x, “imagining” features such as pores and eyelashes that weren’t there in the first place.
AI creates realistic faces from crude sketches - Back in the Sixties, one of the hottest toys in history swept America. It was called Etch-A-Sketch, and its popularity was based on a now-laughably simple feature.
AI recreates the painting techniques of famous artists - You can’t go back in time to see how Monet or Van Gogh made their masterpieces, but AI might give you the next best thing.
Experimental New AI Can Autocomplete Images With the Same Technology as Predictive Text - That was the finding of a new experiment from research group OpenAI, which trained a version of its hyper-sophisticated text generator, GPT-2, on millions of images to prove that it could generate coherent patterns of pixels in the same manner that it does sentences.
Google builds AI agent that learns to generalize to new environments by ignoring distractions - In a study earlier this year accepted to the Genetic and Evolutionary Computation Conference (GECCO) 2020, Google researchers investigate the properties of AI software agents that employ self-attention bottlenecks.
Boston Dynamics’ Spot Robot Dog Now Available for $74,500 - You can now order a Spot robot from the Boston Dynamics online store. Spot costs US $74,500, shipping included.
Why Training Matters - And How Adversarial AI Takes Advantage of It - The following is an excerpt from our recently published whitepaper, “Self-Supervised Learning - AI for Complex Network Security.”
Chinese AI researchers based overseas sweep top awards at leading computer vision conference CVPR - At this year’s Conference on Computer Vision and Pattern Recognition (CVPR), which kicked off on Tuesday, the two papers that clinched the top awards at the event shared one thing in common–both were led by Chinese artificial intelligence researchers.
Concerns & Hype
Amazon Can’t Make Facial Recognition Go Away - Amazon, IBM, and Microsoft have generated a lot of excitement by announcing that they will, at least for a while, stop selling facial recognition software to police departments. Municipalities have imposed moratoriums.
How is Face Recognition Surveillance Technology Racist? - If police are authorized to deploy invasive face surveillance technologies against our communities, these technologies will unquestionably be used to target Black and Brown people merely for existing.
Where are all the robots? - We were promised robots everywhere - fully autonomous robots that will drive our cars end-to-end, clean our dishes, drive our freight, make our food, pipette and do our lab work, write our legal documents, mow the lawn, balance our books and even clean our houses.
Analysis & Policy
Breaking Down AI’s Role In Cybersecurity - Today’s cybersecurity threats are incredibly smart and sophisticated. Security experts face a daily battle to identify and assess new risks, identify possible mitigation measures and decide what to do about the residual risk.
Baidu Breaks Off an AI Alliance Amid Strained US-China Ties - Chinese search giant Baidu has left The Partnership on AI (PAI), a US-led effort.
Expert Opinions & Discussion within the field
The U.S. Is Catching Up With China in Technology Adoption, AI Pioneer Kai-Fu Lee Says - The U.S. has started to catch up to China on the adoption of Artificial Intelligence technology, says AI expert Kai-Fu Lee. When Lee–the chairman and CEO of Sinovation Ventures–wrote his book AI Superpowers in 2018, he argued that China was faster in implementing and monetizing AI technology.
AI And Machine Learning In Healthcare: Garbage In, Garbage Out - Much proselytizing has occurred regarding the value and future of artificial intelligence (AI) and machine learning in healthcare. The industry is burgeoning.