Fake AI vs. Real AI
The AI boom has seen countless companies scrambling to jump on the bandwagon — even if their products have little to do with AI.
Tag: Machine Learning
Machine Teaching A New Paradigm for Building Machine Learning Systems
This paper laid out the position of Machine Teaching, a universally accessible, easy to manage, and fast discipline proposed by Microsoft Research, and articulated the fundamental machine teaching principles.
Best Time Ever for AI Startups?
While tech giants like Google and Amazon are setting the pace in AI R&D these days, startups can also find success by targeting niche markets
What AI Talent Are Companies Hungry For?
As more companies bet on AI, computer scientists with AI expertise are coming into demand on the job market.
Is AI Advancing Too Quickly or Too Slowly?
Last month, it was widely reported that two Facebook chatbots had been shut down after communicating with each other in an unrecognizable language.
Pittsburgh’s Pivot to Artificial Intelligence
Synced meets the people transforming a former steel town into a metropolis powered by artificial intelligence and robotics.
System-Aware Distributed Optimization for Machine Learning
The goal of this report is to inspire our readers in the field of distributed machine learning and invite more to join our discussion to exchange knowledge and contribute to our intellectual community.
Learning to Guide Task and Motion Planning Using Score-Space Representation
This paper proposes a learning algorithm to speed up search in Task and Motion Planning problems (TAMP), and to solve three challenges in order to improve planning efficiency.
Deep Learning in Real Time – Inference Acceleration and Continuous Training
In this report, we will touch on some of the recent technologies, trends and studies on deep neural network inference acceleration and continuous training in the context of production systems.
Andrew Ng Unveils Deeplearning.ai – New DL Courses on Coursera
Andrew Ng, one of the top minds in deep learning, loves teaching. And so, the Stanford University professor decided toContinue Reading
CVPR 2017: The Fusion of Deep Learning and Computer Vision, What’s Next?
CVPR 2017 conference covered topics in: Machine Learning, Object Recognition & Scene Understanding – Computer Vision & Language, 3D Vision, Human Analyzing, Low- & Mid- Level Vision, Image Motion & Tracking: Video Analysis, Computational Photography, Applications.
Kullback-Leibler Divergence Explained
Minimization of the KL-divergence can be thought of as maximizing the likelihood ratio, which appears in numerous applications.
Using Human Brain Activity to Guide Machine Learning
Instead of investigating what steps the brain takes to process information, the authors of this paper link brain activity directly to the learning process.
Tensorflow Programs and Tutorials
This repository did some toy experiments based on Tensorflow in order to introduce some deep learning concepts which are used for image recognition and language modeling.
Customer Success with Machine Learning (Google Cloud NEXT’17)
The reason why TensorFlow is so widely used is due to its automatic derivation of functions and distributed computing capability. This increase in interest can also be found in commercial applications.
Exploring Sparsity in Recurrent Neural Networks
In order to deploy Recurrent Neural Networks (RNNs) efficiently, we propose a technique to reduce the parameters of a network by pruning weights during the initial training of the network.
Word2vec: Google’s New Leap Forward on the Vectorized Representation of Words
Word2vec is an open source tool developed by a group of Google researchers led by Tomas Mikolov in 2013. It describes several efficient ways to represent words as M-dimensional real vectors, also known as word embedding, which is of great importance in many natural language processing applications
Basics of Computational Reinforcement Learning
Intelligent behavior arises from the actions of an individual seeking to maximize its received reward signals in a complex and changing world”. Meanwhile, reinforcement learning is the way to realize AI.
Representations for Language: From Word Embeddings to Sentence Meanings
This talk was recently given by Prof. Christopher Manning at Simons Institute, UC Berkeley. It is an introductory tutorial without complicated algorithms.
Big Picture Machine Learning: Classifying Text with Neural Networks and TensorFlow
TensorFlow is one of the most popular open source AI libraries. Its high in computing efficiency, and the rich development resources make it widely adopted by companies and individual developers.
Interview with Tencent AI Lab- Four Core Research Fields:Computer Vision, Speech Recognition, Natural Language Processing and Machine Learning
Synced recently conducted a special interview with the Director of Tencent AI Lab Tong Zhang, to discuss about the strategic position and research focuses in Tencent.
Neural Networks for Beginners
This review will introduce and compare the three commonly used machine learning frameworks: Matlab Neural Network Toolbox, Torch and Tensorflow.
Tencent Cloud’s Huang Ming on its New DI-X Deep Learning Platform
On March 28, Tencent Cloud launched its machine learning platform DI-X, with a goal of providing a one stop shop for its machine learning and deep learning customers.
Canada’s Future Bets on AI
Canada unveiled a budget of $125 million to launch Pan-Canadian Al Strategy, a new independent institute for AI, Vector Institute.
ArtGAN – Artwork Synthesis with Conditional Categorical GANs
ArtGAN can generate images with abstract information like images with a certain art style.
Why AI Must Be Biased, and How We Can Respond
AI must be biased because the knowledge we used in the training process contains traces of our history, including our prejudices.
Deep Learning in Industry with NVIDIA/Fine-grained Emotional Profiling
This talk is focused on the future potential of deep learning with NVIDIA Deep Learning SDK and GPU hardware families.
Label-Free Supervision of Neural Networks with Physics and Domain Knowledge
The recipient of this year’s Outstanding Paper Award utilizes prior domain knowledge to constrain output space to a specific learning structure rather than a simple mapping from input to output
Interview with Andrew Ng：Many Leading AI Technologies were First Deployed in China
Synced had a special interview with Ng to learn more about the progress of AI research at Baidu, why and how he became an AI expert.
Richard Sutton: The Future of Artificial Intelligence Belongs to Search and Learning
The future of AI belongs to scalable methods, search and learning; as presented by Richard Sutton in seminars at University of Toronto