AI Technology & Industry Review
Technical review of the newest machine intelligence research.
n the new paper Adversarial Examples Are Not Bugs, They Are Features, a group of MIT researchers propose that adversarial examples’ effectiveness can be attributed to non-robustness: “Adversarial vulnerability is a direct result of our models’ sensitivity to well-generalizing features in the data.”
Google AI yesterday released its latest research result in speech-to-speech translation, the futuristic-sounding “Translatotron.”
Current state-of-the-art convolutional architectures for object detection tasks are human-designed. In a recent paper, Google Brain researchers leveraged the advantages of Neural Architecture Search (NAS) to propose NAS-FPN, a new automatic search method for feature pyramid architecture.
NVIDIA has opened a fun online AI platform (https://nvlabs.github.io/FUNIT/petswap.html) that can swap pet faces onto other animals. Simply upload a photo of your Spot or Sylvester, draw a rectangle around its head, click on “Translate” and voila!
Researchers from the University of Washington, MIT, and Facebook Realty Lab recently proposed the novel deep representation method “DeepSDF” to study 3D object generation.
DeepMind and Google researchers have proposed a powerful new graph matching network (GMN) model for the retrieval and matching of graph structured objects.
Microsoft Research Asia (MSRA) has been dubbed the “Whampoa Academy for AI” in reference the elite Chinese military school. MSRA is a bootcamp for NLP research and has trained more than 500 interns, 20 PhDs and 20 postdocs over the past two decades.
Traditional methods used to estimate 3D structure and camera motion in videos rely heavily on manual assumptions such as continuity and planarity. Google researchers have now presented an alternative deep learning method which is able to obtain these assumptions from unlabelled video.
UK-based national research organization The Alan Turing Institute has released a new machine learning toolbox, Machine Learning in Julia (MLJ), which provides a uniform interface enabling users to easily train, evaluate, and tune machine learning models.
Although machine learning has achieved huge advances in speech recognition, gaming and many other applications, some critics still regard it as little more than glorified “curve fitting” that lacks high-level cognitive abilities and reasoning skills.
Researchers from the Sri Lanka’s University of Moratuwa and the University of Sydney in Australia have proposed a technique for generating new handwritten character training samples from existing samples.
The Seventh International Conference on Learning Representations (ICLR) kicked off today. One of the world’s major machine learning conferences, ICLR this year received 1591 main conference paper submissions — up 60 percent over last year — and accepted 24 for oral presentations and 476 as poster presentations.
Designing accurate and efficient CNNs for mobile devices is challenging due to the large design space and expensive computational methods. Although many mobile CNNs are available for developers to train and deploy to mobile devices, existing CNN architecture may not be able to achieve the best results for some tasks on mobile devices.
Google today announced the release of a new and improved landmark recognition dataset. Google-Landmarks-v2 includes over 5 million images, doubling the number in the landmark recognition dataset the tech giant released last year. The dataset now covers more than 200 thousand different landmarks, a seven times increase over the first version.
“AI is the best bot to keep people safe on our platforms,” Facebook Director of Artificial Intelligence Manohar Paluri told the F8 audience, adding that an effective way to achieve that goal is enabling Facebook’s AI system to “understand content and work effectively with less labeled training data.”
A group of Google researchers led by Quoc Le — the AI expert behind Google Neural Machine Translation and AutoML — have published a paper proposing attention augmentation. In experiment results, the novel two-dimensional relative self-attention mechanismfor image classification delivers “consistent improvements in image classification.”
The non-profit organization behind the popular worldwide library of computer vision programming functions, OpenCV (Open Source Computer Vision), is launching a kickstarter campaign to raise funds for a series of summer 2019 AI courses.
New research from Harvard Medical Group shows AI-powered autonomous device navigation is possible in minimally invasive surgical procedures, and even in heart surgery.
San Francisco research company OpenAI has developed Sparse Transformer, a deep neural network which outperforms current state-of-the-art techniques for predicting long-sequence data in text, image and sound.
If we ask one of today’s AI-powered voice assistants like Alexa and Siri to tell a joke, it might very well come up with something that puts a smile on our face. If however we then asked “Why do you think that joke is funny?” the bot would be stuck for a response. AI researchers want to change that.
Everyone, however, sleeps. And Synced has found a simple way to challenge cutting-edge facial recognition security scans: just point a camera at the unaware subject while they are sleeping.
Advanced machine learning techniques and the widespread deployment of surveillance cameras have dramatically improved the efficiency and accuracy of human detection systems in airports, train stations, and other sensitive public places. Is this the end of anonymity?
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
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.
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.
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.
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.