AI Technology & Industry Review
Global machine intelligence updates.
Do you have two left feet? Do you avoid the dance floor out of fear of embarrassment? If you’ve ever secretly wished you could move your body like Joaquín Cortés — well, at least in a video — a new AI-powered 3D body mesh recovery module called Liquid Warping GAN can give you a leg up.
Synced Global AI Weekly October 13rd
In recent years frontier technologies such as AI, big data, IoT, and 3S technology (RS remote sensing technology, GIS geographic information systems, and GPS global positioning systems), have been aggressively deployed to accelerate the modernization of Chinese agriculture.
Inspired by OpenCV, Kornia is based on PyTorch and designed to solve generic computer vision problems.
The latest version, PyTorch 1.3, includes PyTorch Mobile, quantization, and Google Cloud TPU support. The release was announced today at the PyTorch Developer Conference in San Francisco.
Although the term “open source” conveys sentiments such as research sharing and community building, leading semiconductor IP provider Arm, which supports 95 percent of smartphone embedded processors, is not a fan.
The US chip giant now appears to be exploring the terrain beyond GPU architecture, raising the stakes on other dedicated electronic circuits.
For better or worse, AI can now figure out what you’re doing even without “seeing” you. The MIT Computer Science & AI Lab (CSAIL) has unveiled a neural network model that can detect human actions through walls or in extremely dark places.
In the paper ChipGAN: A Generative Adversarial Network for Chinese Ink Wash Painting Style Transfer, a team of researchers from Peking University and Tsinghua University propose an end-to-end GAN-based architecture that can transfer input photos into the style of Chinese ink wash paintings.
Researchers from the Huazhong University of Science and Technology and Huawei Noah’s Ark Lab have introduced TinyBERT, a smaller and faster version of Google’s popular large-scale pre-trained language processing model BERT.
Synced Global AI Weekly October 6th
Figures from nonprofit organization Mental Health America show the severe depression rate for US youth increased from 5.9 to 8.2 percent over the last five years. The numbers provide a sobering glimpse of the shortcomings in mental health care, and some researchers are suggesting AI might be able to address the problem.
Tech giant Google’s recent claim regarding quantum supremacy created a buzz in the computer science community and got global mainstream media talking about quantum computing breakthroughs.
NLP-focused startup Hugging Face recently released a major update to their popular “PyTorch Transformers” library which establishes compatibility between PyTorch and TensorFlow 2.0.
A research team from NVIDIA, Oak Ridge National Laboratory (ORNL), and Uber has introduced new techniques that enabled them to train a fully convolutional neural network on the world’s fastest supercomputer, Summit, with up to 27,600 NVIDIA GPUs.
DeepMind researchers are expanding GANs to audio, with a new adversarial network approach for high fidelity speech synthesis.
On September 22 about 300 artificial intelligence (AI) and deep learning enthusiasts gathered at the University of Toronto Bahen Centre for Information Technology for the AI Squared Forum 2019.
In a bid to help software developers and foster innovative code search research, GitHub last week announced the CodeSearchNet Challenge in a joint effort with California-based machine learning development tools startup Weights & Biases.
An R&D team from Japanese multinational conglomerate Hitachi has proposed a similar, sound-based technique for identifying malfunctioning industrial robots on a factory floor.
Google today announced the final release of TensorFlow 2.0. This follows the platform’s alpha release at the TensorFlow Dev Summit in June.
A multi-institute research group recently released the paper PSGAN: Pose-Robust Spatial-Aware GAN for Customizable Makeup Transfer, which proposes a novel method for transferring makeup styles from a reference picture to a user’s source image.
Synced Global AI Weekly September 29th
In an attempt to unlock the science behind hugs, a team of researchers from Arizona State University slapped wearable sensors on 33 humans and collected data on their more than 350 huggings with the humanoid remote-controlled robot “Baxter.”
Google’s new “ALBERT” language model has achieved state-of-the-art results on three popular benchmark tests for natural language understanding (NLU): GLUE, RACE, and SQuAD 2.0.
Chinese news outlet Caixin is reporting that UK-based chip designer ARM confirmed on Wednesday it will continue to license its chip design architecture to Chinese tech giant Huawei and the company’s chip unit HiSilicon Technologies despite a US trade ban.
Hugging Face, a startup specializing in natural language processing, today released a landmark update to their popular Transformers library, offering unprecedented compatibility between two major deep learning frameworks, PyTorch and TensorFlow 2.0.
A team of researchers have proposed a number of “recommendations to data providers, academic publishers, and the ML4H research community in order to promote reproducible research moving forward” in their new paper Reproducibility in Machine Learning for Health.
This summer Google Research extended BERT to video and introduced VideoBERT, a self-supervised learning model that can learn the relationship between videos and texts.
At the Alibaba Cloud (Aliyun) Apsara Conference 2019, Pingtouge unveiled its first AI dedicated processor for cloud-based large-scale AI inferencing. The Hanguang 800 is the first semiconductor product in Alibaba’s 20-year history.
Researchers from Intel AI and University of California at Santa Barbara have introduced a new generative hate speech intervention model, along with two large-scale fully-labeled hate speech datasets collected from Reddit and Gab.
The University of Cambridge has appointed Professor Neil Lawrence as its first DeepMind Professor of Machine Learning, a new position supported by Google-owned, UK-based AI research company DeepMind.
Researchers from Element AI, MILA (Montréal Institute for Learning Algorithms), and Université de Montréal have introduced a powerful transfer language model that can summarize long scientific articles effectively, outperforming traditional seq2seq approaches.
“Adversaries and strategic competitors probably will attempt to use deep fakes or similar machine-learning technologies to create convincing — but false — image, audio, and video files to augment influence campaigns directed against the United States and our allies and partners.”
Synced Global AI Weekly September 22nd
Cosmetic surgery companies are turning to big data, facial recognition, neural networks, adversarial learning and deep learning technologies that can assess the human face and generate outcomes for a specific procedures to guide patients to their best surgical options.
Chinese tech giant Huawei yesterday introduced the latest iteration of its flagship smartphone: Mate 30, Mate 30 Pro and Mate 30 Pro (5G).
At last week’s Re•Work AI in Finance Conference in New York, researchers and engineers from banks and academia alike shared their thoughts on current AI research and applications in the finance world.
The Re•Work AI in Insurance Summit in New York City was held September 5-6 and saw 60 speakers from insurance-related companies cover a wide range of topics — from detecting claims fraud to applying machine learning to underwriting and maximizing revenue.
DeepMind researchers have brought quantum Monte Carlo (QMC) to a higher level with the Fermionic Neural Network — or Fermi Net — a neural network with more flexibility and higher accuracy.
A new Adobe-developed AI tool significantly lowers the threshold for producing dynamic images with a framework that synthesizes a “3D Ken Burns effect” from a single image.