AI Technology & Industry Review
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
Simulation systems can play a valuable role in identifying and testing evacuation plans to enable individuals to promptly leave a dangerous area via the safest and fastest route.
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
E-commerce is a fast-growing industry. In 2017, global retail e-commerce sales reached US$2.3 trillion, and e-retail revenue is expected to grow to US$4.88 trillion in 2021.
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.
In fact, the accuracy of results in few-shot learning, both with and without labeled data, is very high.
In an effort to benchmark deep learning on smartphones in the Android ecosystem, researchers from the ETH Zurich Computer Vision Lab last year developed an AI Benchmark application to measure the AI readiness of more than 200 Android devices and 100 mobile SoCs collected in the wild.
Synced Global AI Weekly November 17th
Although Japan’s declining and aging population has done little to stimulate the domestic fashion industry, AI is getting very positive reviews from the country’s still massive JP¥9 trillion (US$83 billion) apparel market.
Precup discussed the latest developments in the field: “Reinforcement learning allows autonomous agents to learn how to act in a stochastic, unknown environment, with which they can interact.”
Featuring 100+ models, new mobile inference engine, and frameworks for graph & federated learning
The new Intel products strengthen the company’s growing portfolio of AI solutions, which is expected to generate more than US$3.5 billion in revenue in 2019.
Microsoft Executive Vice President Harry Shum (Shen Xiangyang), the head of Microsoft AI and Research, will leave the tech giant in early 2020.
AAAI-20 welcomes submissions on mainstream AI topics and related areas and reported a record-high number of over 8,800 submissions — a thousand more than last year.
The Synced Machine Intelligence Awards 2019 focus is “the power of industry” and the selection process will key in on AI companies’ products, application cases and industry landings — with the most noteworthy companies chosen based on real and objective industry performance.
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.
The message from Microsoft is clear: the company is investing in knowledge, which it believes will become one of the most important assets of any organization.
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.
“You’ll see AI infused into all our products and services across the company, from tools to help people be more productive at work, to Azure services that give our customers the flexibility to deploy AI capabilities in any environment,” said Microsoft Communications Corporate Vice President Frank Shaw.
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?