AI Technology & Industry Review
Thanks to the CUDA architecture [1] developed by NVIDIA, developers can exploit GPUs’ parallel computing power to perform general computation without extra efforts. Our objective is to evaluate the performance achieved by TensorFlow, PyTorch, and MXNet on Titan RTX.
Respected AI pioneer and visionary Nils John Nilsson passed away early this morning at age 86.
At the recent NVIDIA GPU Technology Conference (GTC) 2019, Synced reported on a ‘magical brush’ app that could transform simple line drawings and sketches into realistic landscapes.
Synced Global AI Weekly April 21st
In February Chinese AI semiconductor maker Horizon Robotics raised US$600 million in Series B funding from SK China, SK Hynix and big auto groups, making it the first in its field to reach the staggering valuation of US$3 billion.
The Stanford ML Group led by Andrew Ng has released its MRNet Dataset, which contains more than 1000 annotated knee MRI Scans; and announced an associated public model competition.
Neural networks for image recognition have matured from simple chain-like models to structures with multiple wiring paths. The emergence of Neural Architecture Search (NAS) can optimize models with more elaborate wiring and operation types.
Researchers from Facebook, the National University of Singapore, and the Qihoo 360 AI Institute have jointly proposed OctConv (Octave Convolution), a promising new alternative to traditional convolution operations. Akin to a “compressor” for Convolutional Neural Networks (CNN), the OctConv method saves computational resources while boosting effectiveness.
At the Auto Shanghai 2019 Key Tech Forum yesterday Huawei Rotating Chairman Eric Xu unveiled the company’s plan to provide information and communication technology (ICT) to OEMs to help them build better vehicles.
Interactive movies are redefining cinema and storytelling and opening up a world of possibilities in the entertainment industry. There are no “spoilers” for films with no predetermined endings, whose characters and plots develop based on viewers’ real-time direction. Now, what if these viewers became characters?
In a YouTube video released today, Spot looks a lot more like a workhorse, harnessed up and hauling a box truck up a hill.
Held April 9 – 10, the conference welcomed AI leaders from industry and academia, who shared their AI experiences, insights, and analysis.
10 AI News You Must Know from April W 1 – W 2
The recent ReWork Deep Learning in Finance Summit in London, UK, featured 46 top scientists and professors from world-leading institutions, who presented their research progress and provided a glimpse into emerging trends in the field of artificial intelligence and fin tech.
Synced Global AI Weekly April 14th
After eight-months of development efforts, the “Open AI Five” exacted their revenge today against one of the world’s top teams in a highly anticipated best-of-three 5v5 Dota 2 showdown in San Francisco.
ccording to a Fuji Research Laboratory report, the Japanese smart home market is expected to top JP¥4.2 trillion (US$38 billion) in 2025, up 36.3 percent from 2017. The market is being driven by smart devices including smartphones, which already account for more than half the market and are continuing to grow due their ability to conveniently connect IoT devices.
Chinese technology giant Tencent has open-sourced its face detection algorithm DSFD (Dual Shot Face Detector). The related paper DSFD: Dual Shot Face Detector achieves state-of-the-art performance on WIDER FACE and FDDB dataset benchmarks, and has been accepted by top computer vision conference CVPR 2019.
This morning the NAACL 2019 conference committee announced its best paper awards. Synced has prepared a summary of the winning papers.
A collaboration between researchers from China’s Beihang University and Microsoft Research Asia has produced TableBank, a new image-based dataset for table detection and recognition built with novel weak supervision from Word and Latex documents on the Internet.
The idea of using machine learning to teach programs how to automatically write or modify code has always been tempting for computer scientists.
Artificial intelligence and machine learning have become powerful tools for tech giants looking to build the optimal cloud service platform. To catch up with rivals Amazon Web Services and Microsoft Azure, Google is accelerating the development of its own cloud services.
As robots take over industrial manufacturing, specific and accurate robot control is becoming more important. Conventional feedback control methods can effectively solve various types of robot control problems by capturing structures with explicit models such as motion equations.
A new math tool called “Snip” is creating a buzz on Twitter. Thousands of netizens are sharing the tool, which is being heralded as a “life changer” for scientific writing.
Facebook AI Research has announced it is open-sourcing PyTorch-BigGraph (PBG), a tool that can easily process and produce graph embeddings for extremely large graphs. PBG can also process multi-relation graph embeddings where a model is too large to fit in memory.
A year ago, Shenzhen-based self-driving start-up Roadstar.ai was cruising along promisingly. In May 2018 the company announced a US$128 million funding round led by Wu Capital and state-backed Shenzhen Capital Group — one of the largest autonomous driving investments ever in China.
Chinese AI unicorn Megvii Technology has proposed a new single-path, one-shot NAS design approach which makes various applications more convenient and achieves start-of-the-art performance on the large dataset ImageNet.
Synced Global AI Weekly April 7th
Now, China’s elite Central Conservatory of Music (CCOM) has announced it is recruiting PhDs for a new Music AI and Information Technology program. CCOM says prospective students should have a background in Computer Science, AI, or Information Technology; along with musical abilities (instrument playing or singing).
DeepMind trained and tested its neural model by first collecting a dataset consisting of different types of mathematics problems. Rather than crowd-sourcing, they synthesized the dataset to generate a larger number of training examples, control the difficulty level and reduce training time.
Ian Goodfellow — the research scientist who pioneered generative adversarial networks (GANs) — has left Google Brain and joined Apple to direct a special machine learning project, according to his Linkedln profile updated today and CNBC.
Google Brain researchers have proposed LAMB (Layer-wise Adaptive Moments optimizer for Batch training), a new optimizer which reduces training time for its NLP training model BERT (Bidirectional Encoder Representations from Transformers) from three days to just 76 minutes.
It’s a fanciful little one-piece in shimmering green and aquamarine with bold fuschia shoulder accents — perfect for a night out on the town. Is this a new dress from a Milan or Tokyo collection? Nope, it was designed by an AI-powered machine, and produced by a couple of MIT graduates.
In a paper recently published in Nature, IBM researchers propose using two quantum algorithms based on superconducting processors to provide a novel solution to classification problems.
“CityFlow,” a city-scale traffic camera dataset paper from NVIDIA researchers, has been accepted by CVPR 2019 as an Oral Session, earning two “Strong Accepts” and one “Accept” from reviewers.
10 AI News You Must Know from March W 3 – W 4
Today is April Fool’s Day, and despite Microsoft’s efforts to ban such pranks, many tech companies could not resist joining in the centuries-old spoofing tradition. However, given the already incredible achievements of cutting-edge AI technologies, some of today’s hoaxes actually look pretty convincing.
Chinese AI company iFLYTEK has bested the SQuAD2.0 challenge once again. The model “BERT + DAE + AoA” submitted by the joint iFLYTEK Research and HIT (Harbin Institute of Technology) laboratory HFL outperformed humans on both EM (exact match) and F1-score (fuzzy match) indexes to top the SQuAD2.0 leaderboard.
Synced Global AI Weekly March 31st
Business models that leverage location data from mobile devices are part of a growing, multi-billion dollar market. Where you are matters much more than you might think.