Japanese Scientist Insists His Robot Twin Is Not Creepy
In an exclusive interview with Synced, the 56-year-old professor shared his thoughts on humanoids, human nature, human-robot interaction, knowledge and intelligence.
Category: Interview
Semantic Based Adversarial Examples Fool Face Recognition
Researchers have proposed a new adversarial attack approach, SemanticAdv, which generates adversarial perturbations by manipulating not pixels but rather an image’s semantic attributes.
Facebook AI Memory Layer Boosts Network Capacity by a Billion Parameters
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.
Harvard’s Tiny, Solar-Powered Flying Robot
Last month, Harvard Microrobotics Lab researchers introduced RoboBee X-Wing, a solar-powered micro-aerial vehicle that fits in the palm of your hand.
Yoshua Bengio on the Turing Award, AI Trends, and ‘Very Unfortunate’ US-China Tensions
On the occasion of 2019 International Conference on Machine Learning last week in Long Beach, California, Synced spoke with Dr. Bengio on the Turing Award, ICML, global AI trends, etc.
Peeking Inside DNNs With Information Theory
Deep learning model performance has taken huge strides, allowing researchers to tackle tasks which were simply not possible for machines less than a decade ago.
Google Brain NAS-FPN Outperforms SOTA Models for Object Detection
Current state-of-the-art convolutional architectures for object detection tasks are human-designed. In a recent paper, Google Brain researchers leveraged the advantages of Neural Architecture Search (NAS) to propose NAS-FPN, a new automatic search method for feature pyramid architecture.
Microsoft Research Asia: Past, Present, and Future of NLP
Microsoft Research Asia (MSRA) has been dubbed the “Whampoa Academy for AI” in reference the elite Chinese military school. MSRA is a bootcamp for NLP research and has trained more than 500 interns, 20 PhDs and 20 postdocs over the past two decades.
Google AI | Unsupervised Depth Estimation for Arbitrary Videos
Traditional methods used to estimate 3D structure and camera motion in videos rely heavily on manual assumptions such as continuity and planarity. Google researchers have now presented an alternative deep learning method which is able to obtain these assumptions from unlabelled video.
AutoML Mobile: Automated ML Model Design for Every Mobile Device
Designing accurate and efficient CNNs for mobile devices is challenging due to the large design space and expensive computational methods. Although many mobile CNNs are available for developers to train and deploy to mobile devices, existing CNN architecture may not be able to achieve the best results for some tasks on mobile devices.
Facebook Randomly Wired Neural Networks Outperform Human-designed for Image Recognition
Neural networks for image recognition have matured from simple chain-like models to structures with multiple wiring paths. The emergence of Neural Architecture Search (NAS) can optimize models with more elaborate wiring and operation types.
IBM Proposes Quantum-Enhanced Feature Space for ML
In a paper recently published in Nature, IBM researchers propose using two quantum algorithms based on superconducting processors to provide a novel solution to classification problems.
DeepMind TF-Replicator Simplifies Model Deployment on Cluster Architectures
DeepMind’s Research Platform Team has open-sourced TF-Replicator, a framework that enables researchers without previous experience with the distributed system to deploy their TensorFlow models on GPUs and Cloud TPUs. The move aims to strengthen AI research and development.
Google Brain SimPLe: Complete Model-Based Reinforcement Learning for Atari
Model-free reinforcement learning can be used to learn effective strategies for complex tasks such as Atari games, but it usually requires a large amount of interaction, which adds significant time and cost.
Google Open-Sources Lingvo Framework for Sequence-To-Sequence Modeling
Natural language processing has made significant progress in the past year, but few frameworks focus directly on NLP or sequence modeling. Google Brain recently released Lingvo, a deep learning framework based on TensorFlow. Synced invited Ni Lao, Chief Science Officer at Mosaix, to share his thoughts on Lingvo.
Google Brain Simplifies Network Learning Dynamics Characterization Under Gradient Descent
Machine learning models based on deep neural networks have achieved unprecedented performance on many tasks. These models are generally considered to be complex systems and difficult to analyze theoretically. Also, since it’s usually a high-dimensional non-convex loss surface which governs the optimization process, it is very challenging to describe the gradient-based dynamics of these models during training.
Oxford University AI Policy Researcher Says Trump’s AI Initiative Falls Short on Immigration and Ethics Issues
Last Monday US President Donald Trump signed the “American AI Initiative,” an executive order designed to spur US investment in artificial intelligence and boost the domestic AI industry. The initiative has five highlights: Investing in AI Research and Development (R&D), Unleashing AI Resources, Setting AI Governance Standards, Building the AI Workforce, International Engagement and Protecting our AI Advantage.
Yoshua Bengio On AI Priors and Challenges
Synced spoke with AI pioneer Professor Yoshua Bengio at the Computing in the 21st Century Conference in Beijing, where he discussed his recent research and the current state of AI.
AI Hasn’t Found Its Isaac Newton: Gary Marcus on Deep Learning Defects & ‘Frenemy’ Yann LeCun
Synced is proud to present Gary Marcus as the last installment in our Lunar New Year Project — a series of interviews with AI experts reflecting on AI development in 2018 and looking ahead to 2019. (Read the previous articles on Clarifai CEO Matt Zeiler and Google Brain Researcher Quoc Le.)
Google Brain Research Scientist Quoc Le on AutoML and More
The Synced Lunar New Year Project is a series of interviews with AI experts reflecting on AI development in 2018 and looking ahead to 2019. In this second installment (click here to read the previous article on Clarifai CEO Matt Zeiler), Synced speaks with Google Brain Researcher Quoc Le on his latest invention, AutoML, Google Brain’s pursuit of AI, and the secret of transforming lab technologies into real practices.
Uber AI’s Go-Explore Tackles Hard-Exploration Problems
Uber AI Lab has created a buzz in the machine learning community with the publication of a paper introducing a new reinforcement learning algorithm called Go-Explore. The algorithm is designed to overcome the challenges of intelligence exploration in reinforcement learning to improve performance on hard-exploration tasks.
David vs Goliath: Clarifai CEO Matt Zeiler Takes On the Tech Giants
This is the first installment of the Synced Lunar New Year Project, a series of interviews with AI experts reflecting on AI development in 2018 and looking ahead to 2019. In this article, Synced chats with Clarifai Founder and CEO Matt Zeiler on recent progress in computer vision and his company’s plans for the future. Founded in New York in 2013, Clarifai produces advanced image recognition systems.
Facebook BISON: An Alternative Evaluation Task for Visual-Grounding Systems
A cooperative research group from Facebook and the University of Southern California has introduced an alternative evaluation task for visual-grounding systems: BISON (Binary Image Selection).
AI in 2018 Review; What to Expect in 2019
To welcome 2019 with some fresh AI insights, Synced posed three questions to forty researchers and experts at last month’s NeurIPS 2018 conference in Montréal, Canada.
NeurIPS 2018 Best Paper Team: “Math Is Forever”
In an exclusive interview with Synced at NeurIPS, members of the University of Toronto and Vector Institute team led by Assistant Professor David Duvenaud discussed their winning submission Neural Ordinary Differential Equations — a math-based approach to designing deep learning models that is stimulating discussion across the machine learning community.
A Conversation With Quoc Le: The AI Expert Behind Google AutoML
A founding member of Google Brain and the mind behind AutoML, Quoc Le is an AI natural: he loves machine learning and loves automating things. Le used millions of YouTube thumbnails to develop an unsupervised learning system that recognized cats when he was a Stanford University PhD in 2011.
Baidu President Ya-Qin Zhang Talks AI Security
As Chinese Internet giant Baidu has expanded from search to mobile apps, cloud services, and emerging business sectors like autonomous driving and voice assistants, it has correspondingly beefed up its research efforts, particularly in AI, to keep pace with growing security threats.
MORE Health Co-Founder & UCSF Physician Robert Warren On AI in Health
Robert S. Warren, MD is a Professor of Surgery and a specialist in gastrointestinal and liver cancer. Dr. Warren joined UCSF Medical Center in 1988. Highly respected by his peers, Dr. Warren was named to the list of U.S. News “America’s Top Doctors,” a distinction reserved for the top 1% of physicians in the nation for a given specialty.
Where No Doctor Has Gone Before: AI Takes Telemedicine to Underserved Areas
MORE Health is a Silicon Valley-based company that provides access to top international physicians for patients faced with critical illnesses such as cancer or heart disease. The company was founded in 2013, and recently took a leap forward by partnering with Houston-based Melax Technologies…
Q&A With Microsoft Chief Speech Scientist Xuedong Huang
A performance boost of less than one percent may not seem like much to most people, but for Microsoft Global Technical Fellow and Chief Speech Scientist Xuedong Huang, it’s cause for celebration.
YITU CIO Hao Lu on AI Startups, Innovation, and Coming Home
While a Computer Science PhD candidate at the University of Washington, Hao focused on intelligent human-computer interaction research, and R&D and evaluation of intelligent systems and their tools.
Liulishuo’s AI App Is Teaching English to 70 Million People
Liulishuo is the AI English teacher on your phone. You don’t need to know how it works, yet it helps you learn English more efficiently than a human teacher,” says Yi Wang, Founder and CEO of Liulishuo — a Beijing-based “AI + language” company…
Program Lead Jake Lussier on Udacity’s New Flying Car Nanodegree
Online education platform Udacity thrilled flying car enthusiasts with its announcement of the world’s first flying car program.
Arm Accelerates its AI Efforts
Jem Davies, General Manager of the ARM Machine Learning Group, sat down with Synced to outline his company’s ambitious roadmap for machine learning development.
CES 2018 Just Got AI’ed
Algorithms are taking center stage at the Consumer Electronics Show (CES) 2018, as exhibitors strive to out “smart” each other with AI-powered gadgets and appliances.
Meet Voice Pioneer Dr. Mei-Yuh Hwang
Mobvoi hired Dr. Mei-Yuh Hwang as its Vice President of Engineering in 2016. A respected speech recognition researcher and former Principle NLP Scientist Manager at Microsoft, Dr. Hwang is a pioneer in voice recognition and machine translation.
30 Years of Devotion to Natural Language Processing Based on Concepts
We interviewed Mr. Qiang Dong, chief scientist of Beijing YuZhi Language Understanding Technology Co. Ltd. and learned more about their YuZhi NLU Platform that conducts its unique semantic analysis based on concepts rather than words.
Relearn the Linguistic World in “Arrival”: An Interview with Jessica Coon
Computer science and machine learning scholars are increasingly interested in languages, and natural language processing has shown great progress as a result.
Lethal Autonomous Weapons & Info-Wars: A Scientist’s Warning
“To pretend science is morally neutral, and that you can develop anything and have clean hands because it is someone else using it to kill people is extremely naive, and scientists should know that.” – UC Berkeley’s Dr. Stuart Russell
1960s-2010s: Humanistic Intelligence and History of Wearable Computing
Personal computers and mobile devices are in their heyday. Researchers are swarming standalone AI, focusing on how to automate self-learning intelligent systems. The interfaces for wearables meanwhile are evolving from smart screens to gesture commands, like those often seen in AR and VR commercials.