Microsoft India announced this morning that it’s launching a new research group, the Microsoft Intelligent Network for Eyecare, to bring data-driven eyecare services to India.
Whereas DeepMind’s swing at ophthalmology targeted the UK, Microsoft’s ambitions are a considerably more global. The tech company is working alongside researchers from the United States, Brazil, Australia and, of course, India to train machine learning models that can identify conditions that can lead to blindness.
Microsoft’s key strategic partnership is with the L V Prasad Eye Institute in Hyderabad, India, one of the most prestigious hospitals in the country. The company is focusing heavily on children, with ambitions to predict outcomes for refractive surgery and the rate of change of myopia in children. Read more…
This morning, Google announced that it was open sourcing its data visualization tool, Embedding Projector. The tool will help machine learning researchers to visualize data without having to install and run TensorFlow.
For a significantly more complex model with thousands of dimensions, traditional tools start to break down. That’s where Google’s Embedding Projector comes in. Read more
Microsoft has published a list of major tech changes its researchers expect to see in the next ten years. They range from improved language translators and advances in deep learning to the prediction that traditional app search boxes will become obsolete.
A frequently cited reason for this divide is the lack of female role models for girls interested in STEM subjects. In an attempt to counteract this, Microsoft asked 17 women working in its global research departments for their opinions on what’ll change in technology between 2017 and 2027.
One of the most intriguing developments was suggested by distinguished scientist Susan Dumais. According to Dumais, the search box “will disappear” from interfaces in the next ten years. It will be replaced by automatic search functionality that’s more “ubiquitous, embedded and contextually sensitive.” This is already becoming evident as devices like the Amazon Echo and Google Home let you start a voice search in your home through barely any effort. Read more…..
TensorFlow is an open source software library for numerical computation using data flow graphs. The flexible architecture allows you to deploy computation to one or more CPUs or GPUs in a desktop, server, or mobile device with a single API. TensorFlow v0.12.0 RC0 was released yesterday and it comes with major improvements including the support for Windows.
TensorFlow now builds and runs on Microsoft Windows (tested on Windows 10, Windows 7, and Windows Server 2016). Supported languages include Python (via a pip package) and C++. CUDA 8.0 and cuDNN 5.1 are supported for GPU acceleration. Known limitations include: It is not currently possible to load a custom op library. The GCS and HDFS file systems are not currently supported. The following ops are not currently implemented: DepthwiseConv2dNative, DepthwiseConv2dNativeBackpropFilter, DepthwiseConv2dNativeBackpropInput, Dequantize, Digamma, Erf, Erfc, Igamma, Igammac, Lgamma, Polygamma, QuantizeAndDequantize, QuantizedAvgPool, QuantizedBatchNomWithGlobalNormalization, QuantizedBiasAdd, QuantizedConcat, QuantizedConv2D, QuantizedMatmul, QuantizedMaxPool, QuantizeDownAndShrinkRange, QuantizedRelu, QuantizedRelu6, QuantizedReshape, QuantizeV2, RequantizationRange, and Requantize.
Machine learning is no longer exclusive to digital companies: Businesses in every industry are utilizing this technology to improve processes.
The NFL uses machine learning to gather deep insights into player movements, positions, and passes to reorganize play style. In the medical sector, machine learning analyzes patients and predicts the likelihood of their returning. Even hiring and talent management in most companies is now handled by algorithms that dig out desired characteristics and, hopefully, remove biases.
Machine learning’s data-driven intelligence is permeating every corner of every industry, and it’s starting to disrupt the way we do business globally. As Google’s Eric Schmidt puts it, “New developments in machine intelligence will make us far, far smarter as a result, for everyone on the planet.” read more…..
Has the computer developed its own internal language to represent the concepts it uses to translate between other languages? Based on how various sentences are related to one another in the memory space of the neural network, Google’s language and AI boffins think that it has. Read more………..
As a distributed ledger that ensures both transparency and security, the blockchain is showing promise to fix the current problems of the supply chain. A simple application of the blockchain paradigm to the supply chain would be to register the transfer of goods on the ledger as transactions that would identify the parties involved, as well as the price, date, location, quality and state of the product and any other information that would be relevant to managing the supply chain…….
SAP chief executive Bill McDermott is preparing the German software giant for the next big trend in the world of technology: artificial intelligence……
Regardless of your feelings about the outcome of the election, it’s pretty clear the present voting system is so antiquated it struggles to provide a meaningful mechanism for translating the will of the people into action……
Apr 03 - EACL 2017
Date: April 3-7 2017
Location: Valencia Conference Center (SP)
The European Chapter of the Association for Computational Linguistics invites you to participate in the 15th EACL Conference. EACL 2017 will take place in April 3-7, 2017 at the Valencia Conference Center from the Mediterranean city of Valencia, Spain. The main chairs of the conference are the following:
April 24 - Linguamatics Spring Text Mining Conference 2017
The conference provides new, experienced and potential users of Linguamatics I2E software an excellent opportunity to explore the latest trends in natural language processing-based text mining.
Delegates will discover how I2E is delivering valuable intelligence from text in a range of applications, as well as have an opportunity to network with the Linguamatics community.
Our evening social events will be held at beautiful and historic Cambridge venues. This year we will be dining at Queens College on Tuesday, April 25.
Who should attend: New and experienced users of Linguamatics I2E and other text mining software, alongside any professionals interested in the mining and analysis of textual information.
July 15-20 13th International Conference on Machine Learning and Data Mining - MLDM
Venue: Ramada Plaza Hotel, Newark, New Jersey 07114
The aim of the conference is to bring together researchers from all over the world who deal with machine learning and data mining in order to discuss the recent status of the research and to direct further developments. Basic research papers as well as application papers are welcome.
All kinds of applications are welcome but special preference will be given to multimedia related applications, biomedical applications, and webmining. Read more….