AI Technology & Industry Review
Technical review of the newest machine intelligence research.
While Poggio the teacher has taught some extraordinary leaders in AI, Poggio the scientist is renowned for his theory of deep learning, presented in papers with self-explanatory names: Theory of Deep Learning I, II and III.
Tencent today officially launched its first-ever smart speaker, Tencent Tingting (腾讯听听), which can send or receive voice messages via WeChat.
A Chatbot is information service interface done by a computer program, sometimes with the help of artificial intelligence (AI). Chatbot applications range from functional to fun, and have been growing quickly both in sophistication and popularity.
Ninety percent of AI-enabled devices shipped today are based on architecture developed by Arm, a leading UK-based chip intellectual property (IP) provider known for its CPU and GPU processors…
Sichuan pig farming corporation Dekon Group and pig feed supplier Tequ Group’s new partnership with Alibaba Cloud to apply its AI-powered “ET Brain” to pig farming. The trio are investing tens of millions of USD in the project, which was announced on February 6, 2018.
At the RE•WORK AI Assistant Summit San Francisco yesterday, research scientists and engineers from Amazon, Apple and Google spoke on how they are addressing challenges and evolving their conversational AI systems.
China has just released its “Artificial Intelligence Standardization White Paper.” The 98-page document was edited by the China Electronics Standardization Institute under the guidance of the National Standardization Management Committee Second Ministry of Industry.
The Montreal Institute for Learning Algorithms (MILA) recently launched ObamaNet — a photo-realistic lip-sync neural network that can make anyone appear to be saying anything.
To boost learning research aimed at endowing robots with better generalization capabilities, Yi Wu from UC Berkeley and Yuxin Wu, Georgia Gkioxari, and Yuandong Tian from Facebook AI research recently published the paper Building Generalizable Agents with a Realistic and Rich 3D Environment.
There are people who equate AI with Machine Learning (and to an extent, deep learning), this is a huge misunderstanding.
Whether you are a researcher, tech enthusiast, entrepreneur, investor, or student, this report will help you sort out the basics and provide you with the necessary background to move forward.
To combine the advantages of these two methods, the authors of this paper first adapts the multi-source NMT model, by employing different encoders to capture the semantics of the source language, then the decoder is used to generate the final output by the multiple context vector representations coming from the encoder.
Last month, Chinese internet giant Tencent released its Internet Technology Innovation Whitepaper.
The author uses a hard-attention (Viterbi alignment matrix) of the SMT (Statistical Machine Translation) to help learn a better alignment matrix in NMT during the training.
STN-OCR, a single semi-supervised Deep Neural Network(DNN), consist of a spatial transformer network – which is used to detected text regions in images, and a text recognition network – which recognizes the textual content of the identified text regions.
The author wants to run a musical experiment with Neural Networks to achieve the goal of making the neural translation of musical style.
Microsoft Reveals Azure IoT Edge; Google Launches Chatbot Analytics Platform Chatbase; Tesla Unveils An Electric Rival to Semi Trucks
In this paper, the authors build four classifiers which are the logistic regression, KNN, SVM, CNN by supervised machine learning to discriminate between criminals and non-criminals.
To boost CNN performance, industry leaders and startups alike are now racing to develop specialized AI chips.
Recently there are three papers on ArXiv that drew the author’s attention, all have focus on learning multi-model information.
This glossary currently includes a total of 743 specialized AI terms based on machine learning concepts and terminologies.
The success AI has achieved in image recognition has prompted tech companies to explore the new field of video understanding, in which machines are trained to answer questions like “Who is in this video?” or “What are the cats in the video doing?”
UC Berkley Professor David Wagner delivered a keynote speech to open the ACM Conference on Computer and Communications Security (CCS) 2017. The top tier computer security and privacy conference was held in Dallas, USA.
This paper gives a demonstration of using Bayesian LSTMs for classification of medical time series, which can improve the accuracy compared with standard LSTMs.
Today, the “Godfather of Deep Learning” Dr. Geoffrey Hinton published the paper Dynamic Routing Between Capsules on Arxiv. This is being hailed as a revolutionary work that could totally revamp computer vision research.
The author introduces the algorithm with a real-life story and then provides applications in four different fields to help beginners learn and know more about this algorithm.
Facebook AI Researcher Yuandong Tian says new AlphaGo Zero paper is destined to be a classic.
Synced tech analyst reviews the thesis “Tree Boosting With XGBoost – Why Does XGBoost Win ‘Every’ Machine Learning Competition”, which investigates how XGBoost differs from traditional MART, and XGBoost’s superiority in machine learning competition.
The objective of Voyage’s self-driving vehicles is to deliver fully functional autonomous taxis within five years.
YouTuber “TJWei” recently uploaded a “Face-off” video on YouTube. The four-minute split-screen clip sees two figures speaking and emoting simultaneously. Both look human, but one is an entity generated in real-time by an AI algorithm.
Researchers introduced a new object representation that allows the robots to identify three-dimensional objects with partially obscured geometry.
On the ICDAR2015 Incidental Scene Text benchmark, proposed method achieves F1-measure of 81%.
Before TensorFlow, PyTorch and Caffe; Theano was the major library for deep learning development. However, the library’s development and support will end after the upcoming Theano 1.0 release.
Attention is simply a vector, often the outputs of dense layer using softmax function.
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.
In applying the adversarial training, this paper adopts distributed word representation, or word embedding, as the input, rather than the traditional one-hot representation. The reason lies in the fact that the higher dimensionality the input has, the more likely it is to be disturbed by noise.
In this paper, the author aims to design a smart way to handle rare/unknown words in the bilingual training data during machine translation.
This paper is the implementation of ‘encoder-decoder reconstructor framework’ for neural machine translation for the English-Japanese translation task.
Recently NASA announced that their Frontier Development Laboratory (FDL) would cooperate with Intel to apply deep learning for space exploration.
In this paper, we present a survey on language models, which mainly consists of count-based and continuous-space language models.