AI Technology & Industry Review
Global machine intelligence updates.
This paper carefully engineers artificial-language learning experiments to replicate sources of information infants learn from and under what conditions.
NVIDIA researchers propose a novel vid2vid framework that utilizes all past generated frames during rendering.
Microsoft announced it would spin off its chatbot business XiaoIce, with all associated technologies licensed to a newly formed independent company.
NeurIPS desk-rejects (papers passed over without review) has become “a super noisy process,” complains a post in the Reddit Machine Learning group.
Researchers launched the ProtTrans Project, which provides an outstanding model for protein pretraining.
PLATO-2, a open-domain chatbot model, can talk about anything in Chinese and English and engage in deep conversations.
TaBERT-powered neural semantic parsers showed performance improvements on the challenging benchmark WikiTableQuestions and demonstrated competitive performance on the text-to-SQL dataset Spider.
Researchers proposed a Taylor Expansion Policy Optimization (TayPO) framework that combines two leading algorithmic improvement methods.
Insilico Medicine announced a spin-off of its aging biomarker and deep aging clock business.
The acceptance rate of 21.8 percent is slightly lower than 2019’s 22.6 percent (774 accepted papers from 3,424 submissions).
DeepMind introduced a new approach designed to improve the generalizability and efficiency of algorithms represented by neural networks.
Microsoft today announced it will divest its XiaoIce business into an independent company, with Harry Shum appointed as the Chairman of the board.
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.
The post highlights perceived peer-review problems, the reproducibility crisis, and ethics and diversity issues.
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 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.
The paper looks at the New Generation Artificial Intelligence (NGAI) Development Plan of China (2015– 2030), which was published in 2017 as a blueprint for the rapid construction of a complete Chinese AI ecosystem.
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.
Leading US universities engaged in AI research have joined tech giants in backing legislation aimed at establishing a roadmap for the creation of a national AI research cloud.
NLE is a procedurally generated environment for testing the robustness and systematic generalization of RL agents.
Turing Award Winner and Facebook Chief AI Scientist Yann LeCun has announced his exit from Twitter after getting involved in a long and often acrimonious dispute regarding racial biases in AI.
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.
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.