AI Technology & Industry Review
Technical review of the newest machine intelligence research.
To promote fairer ML systems, the team introduced a collaborative causal theory formation that incorporates diverse stakeholder perspectives for discovering and considering societal context.
DeepMind researchers call attention to another “fundamentally novel” development in AI research — deep reinforcement learning (deep RL) — which they believe also has vital implications for neuroscience and deserves more attention from neuroscientists.
A team of researchers proposed a novel three-stage learning framework that includes scene context to generate long-term 3D human motion prediction when given a single scene image and 2D pose histories.
Researchers propose a neuro-symbolic hybrid approach to address the challenge of creativity in generative art.
Organizers of the 58th Annual Meeting of the Association for Computational Linguistics (ACL) today announced their Best Paper Awards.
Researchers from the Shenzhen Institutes of Advanced Technology (SIAT) of the Chinese Academy of Sciences and their collaborators from Beihang University developed a novel vision-based algorithm to track the 6-DOF pose of a multi-rigid-body spacecraft in real time.
Researchers introduce a novel Physical Scene Graphs (PSG) approach designed to obtain a better structured understanding of visual scenes.
The proposed method generalizes well across various degrees of eye openness, different identities, and combinations of eye and lower facial expressions.
Interactive sensors and actuators, with the “intelligence” of sensing the environment and responding accordingly, are essential for human-machine interaction. However, it remains a critical challenge for a long time.
There are one trillion synapses in a cubic centimeter of the brain. If there is such a thing as General AI, it would probably require one trillion synapses.
Organizers of the 37th International Conference on Machine Learning (ICML) have announced this year’s Test of Time award, which goes to a team from the California Institute of Technology, University of Pennsylvania, Saarland University.
Facing a shortage of seasonal workers and rising labour costs, kiwifruit growers may get some relief from robots equipped with a new AI-powered fruit detection system.
NLE is a procedurally generated environment for testing the robustness and systematic generalization of RL agents.
Synced presents 13 comprehensive case studies and 74 use cases in five main application scenarios to demonstrate how AI has assisted and can continue to assist in efforts to roll back COVID-19.
A team of researchers from Princeton, DeepMind and New York University have introduced a new method that extracts symbolic representations from deep learning models by introducing strong induction biases.
Researchers have addressed the challenge of comprehensive, dynamic manipulation of particles and cells in a microchannel by integrating acoustofluidics, physics and fabrication of phononic crystals on the microscale.
This paper presents a novel contrastive framework for unsupervised graph representation learning.
The researchers introduce sinusoidal representation networks (SIRENs) as a method for leveraging periodic activation functions for implicit neural representations.
DeepMind researchers released several new models and a tutorial for their dm_control software stack for physics-based simulation and reinforcement learning environments using MuJoCo physics.
Researchers have proposed the use of Fourier feature mapping with MLPs in order to learn high-frequency functions in low-dimensional problem domains.
Google Brain in Zürich and DeepMind London researchers believe one of the world’s most popular image databases may need a makeover.
A research group from the Shenzhen Institutes of Advanced Technology (SIAT) of the Chinese Academy of Sciences has developed a “smart” contact lens that can show real-time changes in moisture and pressure by altering colors.
Apple CEO Tim Cook made the announcement today during his keynote speech opening the Apple Worldwide Developers Conference (WWDC 2020).
Following on the February release of its contrastive learning framework SimCLR, the same team of Google Brain researchers guided by Turing Award honouree Dr. Geoffrey Hinton has presented SimCLRv2, an upgraded approach that boosts the SOTA results by 21.6 percent.
Researchers from the University of Washington, Salesforce Research and Allen Institute for Artificial Intelligence have introduced a graph-based method that retrieves reasoning paths to boost multi-hop open-domain question answering.
GitHub recently introduced a series of free and open-source GitHub Actions that merge data science and machine learning workflows with a software development workflow.
Large transformer-based language models trained on pixel sequences can generate coherent images without the use of labels.
Cruciform Thin-film Microrobot (CTM) could realize double-modal motion and environmental adaptive functions through a programmable external magnetic field.
A team of researchers from Google Brain have proposed a rethink of the dominant computer vision paradigm of pre-training.
Researchers have proposed a novel framework that learns fast and dynamic character interactions.
The 2020 IEEE Conference on Computer Vision and Pattern Recognition (CVPR) has announced its best paper awards.
Covariant last month secured a US$40 million Series B funding round led by Index Ventures to push its total funding to US$67 million.
Researchers from Fudan University and Microsoft have proposed a novel seq2seq architecture that generates dance sequences for music clips running a minute or longer.
A team of researchers from Facebook and UC Berkeley has proposed a new paradigm for computer vision.
Researchers from the University of Tokyo and Google Research have proposed a new metric for RL performance and novel BREMEN algorithm designed to manage the costs and risks of new policy deployment.
In a recent Google AI team blog post, researchers report on recent efforts and progress in the field of language translation, especially with resource-poor languages.
Neuropod, an open-source library that provides a uniform interface for running deep learning (DL) models from multiple frameworks in C++ and Python.
How AI is helping fight COVID-19?
DeepMind researchers have developed EATS, a generative model trained adversarially in an end-to-end manner that achieves performance comparable to SOTA models.
ACM SIGGRAPH has honoured MIT CSAIL postdoctoral researcher Li Tzu-Mao with its 2020 Doctoral Dissertation Award for his PhD thesis Differentiable Visual Computing.