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.
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.
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.
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 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.
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 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.
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.
Machine learning research resource Papers with Code last week introduced Sotabench, a free and open website created to benchmark and rate the performance of state-of-the-art open source models from GitHub.
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.
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.
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.
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.
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.
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.
Synced Global AI Weekly September 15th
For an AI system to acquire knowledge the way humans generally do it would need to interact with its surroundings and extract information through its own attention and analysis choices. That’s the idea behind a new paper from Microsoft Research, Polytechnique Montreal, MILA and and the University of Montreal.
More and more social apps are now leveraging AI technologies such as machine learning, deep neural networks and facial recognition to enable users to create highly-individualized emojis from selfies and photos.
To ramp up the robustness of neural networks, researchers from OpenAI have introduced a novel method that evaluates how well a neural network classifier performs against adversarial attacks that were not seen during their training.
In a recent interview with Synced, Shawe-Taylor spoke on his role at UNESCO, emerging AI trends and the tech’s unseemly side, human-centered AI research, and the progress of AI in Europe.
One of the world’s largest financial companies, Alibaba subsidiary Ant Financial, recently introduced Shared Machine Learning (SML) as their solution for data privacy.
Synced Global AI Weekly August 18th
Israeli research company AI21 Labs today published the paper SenseBERT: Driving Some Sense into BERT, which proposes a new model that significantly improves lexical disambiguation abilities and has obtained state-of-the-art results on the complex Word in Context (WiC) language task.
A team of researchers from the Georgia Institute of Technology, Facebook AI Research and Oregon State University has proposed ViLBERT (Vision-and-Language BERT), a novel model for visual grounding that can learn joint representations of image content and natural language.
In a bid to combine anime and cartoon culture with machine learning, a research team from China’s leading video streaming service iQIYI has introduced a novel large unconstrained cartoon dataset they call “iCartoonFace.”
Recently, Facebook AI Research (FAIR) researchers introduced a structured memory layer which can be easily integrated into a neural network to greatly expand network capacity and the number of parameters without significantly changing calculation cost.
Researchers at the Seattle Allen Institute for Artificial Intelligence (AI2) have proposed a Green AI initiative designed to make future AI research more energy efficient.
A research team from Julia Computing and the Massachusetts Institute of Technology propose that extensive scientific computing and machine learning domains both require linear algebra support on their underlying structures.