AI Technology & Industry Review
Technical review of the newest machine intelligence research.
On Fridays, Synced selects seven studies from the last seven days that present topical, innovative or otherwise interesting or important research that we believe may be of special interest to our readers.
This research demonstrated that deep learning can contribute to the traditional discipline with much better performance than existing methods.
Researchers from Facebook AI and the University of Maryland have introduced a 21st century version — sweatshirts printed with adversarial examples that make the wearer undetectable to the AI-powered object detectors in today’s public surveillance systems.
A Google researcher has released a deep neural network model that makes animating a VTube persona a little easier.
Researchers from The Chinese University of Hong Kong, Tencent AI Lab and University of Macau have proposed a new neuron interaction based representation composition for NMT.
Synced Global AI Weekly December 1st
Synced selects seven studies from the last seven days that present topical, innovative or otherwise interesting or important research that we believe may be of special interest to our readers.
Tencent Graph Computing (TGraph) officially announced the release of Plato, an open source high-performance graph computing framework that meets the ultra-large-scale graph computing requirement of billion-level nodes.
The collaboration produced a deep learning framework for the automatic detection of schools of herring from echograms that outperforms traditional hand-crafted machine learning algorithms on precision, recall, and F1-score metrics.
Rather than attempting to defend convolutional networks against them, the researchers introduce a novel enhanced adversarial training scheme, AdvProp, which treats adversarial examples as additional training examples to improve the accuracy of image classification models.
Researchers from the South Korea-based tech company Hyperconnect recently proposed a new framework, MarioNETte, which aims to reenact target faces in a few-shot manner (from even a single image) while preserving identity without any fine-tuning.
An interdisciplinary team of chemists, physicists, and computer scientists have developed a deep learning algorithm that leverages fundamental quantum mechanics equations to accurately predict the quantum mechanical wave functions of molecules.
Synced Global AI Weekly November 24th
Synced has surveyed last week’s crop of papers in the fields of machine learning, computer vision, computation and language, and beyond, and identified seven studies that we believe may be of special interest to our readers.
For decades machines have been able to understand simple musical features like beats per minute. Now AI is boosting their abilities to the point that they can not only figure out what particular genre of music is playing, but also how to appropriately dance to it.
Now, a team from Facebook AI Research, Inria, and Sorbonne Université have released CamemBERT, essentially a French version of Google AI’s game-changing pretrained language model BERT.
Although convolutional neural networks have reached Superman level on image classification tasks, adversarial examples remain the kryptonite that can mysteriously defeat even SOTA models.
It’s not as easy as one might imagine to train an AI model to accurately predict what a human will do next, even when they are interacting with a relatively simple object like a ball.
Microsoft’s new tunable gigaword-scale neural network DialogGPT is a virtual master of conversation that outperforms strong baseline systems in generating relevant and context-consistent responses and attains near human level performance in conversational response generation tasks.
Synced surveyed last week’s crop of machine learning papers and identified seven that we believe may be of special interest to our readers.
In an exclusive interview with Synced, the 56-year-old professor shared his thoughts on humanoids, human nature, human-robot interaction, knowledge and intelligence.
A team of researchers from Texas A&M University and Canada’s Simon Fraser University have open-sourced a toolkit called “RLCard” for applying RL research to card games.
Synced Global AI Weekly November 10th
As global AI development and deployment continues, the demand for AI talents is growing faster than ever. A number of industry leaders and reputable institutions offer AI residency programs designed to help nurture promising AI talents.
Synced invited Samuel R. Bowman, an Assistant Professor at New York University who works on artificial neural network models for natural language understanding, to share his thoughts on the “Text-to-Text Transfer Transformer” (T5) framework.
Exciting new research from Duke University introduces ProtoPNet, a deep learning network that can explain how it distinguishes a pigeon from a partridge in real time.
In a blog post today OpenAI today announced the final staged release of its 1.5 billion parameter language model GPT-2, along with all associated code and model weights.
Recognizing faces is as natural and habitual as can be for human beings. But what actually happens inside our brains during the process of recognizing a face? Can artificial intelligence learn to recognize faces the way humans do?
In a bid to improve object localization in less-than-ideal circumstances, an MIT and IBM research group has proposed a cross-modal auditory localization framework that can effectively locate objects using stereo sound.
The market opportunities for IIoT are massive. Markets & Markets reports the global IIoT market is expected to grow at a CAGR of 7.39 percent to reach US$91.4 billion by 2023, with the manufacturing industry holding the largest market share.
The ACM Symposium on Operating Systems Principles (SOSP) has a long history and a great reputation in Operating Systems (OS) research. This year SOSP was held in Huntsville, a charming town located in lake country, some 200km north of Toronto.
Much of the compute for such services is done on the cloud, but ideally these applications would be light enough to run directly on devices without an Internet connection.
Synced invited Graham Neubig, an Assistant Professor from Carnegie Mellon University to share his thoughts on Google’s universal neural machine translation (NMT) system trained on over 25 billion examples that can handle 103 languages proposed.
“We’ve made huge progress, much more than even my friends and I expected a few years ago. But (the progress) is mostly about perception, things like computer vision and speech recognition and synthesis of some things in natural processing. We’re still far from human capabilities.”
Now, a group of NLP researchers and enthusiasts, including graduates from Tsinghua University, Peking University, and Zhejiang University, have introduced ChineseGLUE, a benchmark designed to encourage the development and assessment of Chinese language models.
ICCV 2019 received 4,303 papers — more than twice the number submitted to ICCV 2017 — and accepted 1,075, for a reception rate of roughly 25 percent.
A new paper from researchers at the University of Bristol, Telecomm ParisTech and Sorbonne University introduces a multi-layer, silicone “SkinOn” membrane that mimics the layers of human skin.
In a new paper, researchers from the University of Texas at San Antonio (UTSA) design and implement attacks that leverage characteristics of the light emitted by modern smart bulbs to “steal” users’ private data and preferences from other nearby devices.
Synced Global AI Weekly October 27th
In what the company calls “the biggest leap forward in the past five years, and one of the biggest leaps forward in the history of Search,” Google today announced that it has leveraged its pretrained language model BERT to dramatically improve the understanding of search queries.