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 Why doesn’t Streams use AI?

Why doesn’t Streams use AI? by DeepMind


 Introduction To Neural Networks

 

This tutorial was originally posted here on Ben’s blog, GormAnalysis. Artificial Neural Networks are all the rage. One has to wonder if the catchy name played a role in the model’s own marketing and adoption. I’ve seen business managers giddy to mention that their products use “Artif…


 October Kaggle Dataset Publishing Awards Winners’ Interview

This interview features the stories and backgrounds of the October winners of our $10,000 Datasets Publishing Award–Zeeshan-ul-hassan Usmani, Etienne Le Quéré, and Felipe Antunes. If you’re inspired to contribute a dataset and compete for next month’s prize, check out this page fo…


 Specifying AI safety problems in simple environments

Specifying AI safety problems in simple environments by DeepMind


 Bringing still photos to life and 3D photography to your phone

Facebook researchers are transforming photography into entirely new consumer experiences—infusing still portraits with emotion and movement, and bringing 3D photography […] Bringing still photos to life and 3D photography to your phone by Kelly Berschauer


 Population based training of neural networks

Population based training of neural networks by DeepMind


 Applying machine learning to mammography screening for breast cancer

Applying machine learning to mammography screening for breast cancer by DeepMind


 Understanding Medical Conversations

   

Posted by Katherine Chou, Product Manager and Chung-Cheng Chiu, Software Engineer, Google Brain Team Good documentation helps create good clinical care by communicating a doctor’s thinking, their concerns, and their plans to the rest of the team. Unfortunately, physicians routinely spend more…


 High-fidelity speech synthesis with WaveNet

High-fidelity speech synthesis with WaveNet by DeepMind


 Amazon Web Services to join ONNX AI format, drive MXNET support

The Open Neural Network Exchange (ONNX) is a community project originally launched in September 2017 to increase interoperability between deep […] Amazon Web Services to join ONNX AI format, drive MXNET support by Kelly Berschauer


 Introducing Data Science for Good Events on Kaggle

Today, we’re excited to announce Kaggle’s Data Science for Good program! We’re launching the Data Science for Good program to enable the Kaggle community to come together and make significant contributions to tough social good problems with datasets that don’t necessarily fit the tight cons…


 Product Launch: Increased Dataset Resources

Today we’re pleased to announce a 20x increase to the size limit of datasets you can share on Kaggle Datasets for free! At Kaggle, we’ve seen time and again how open, high quality datasets are the catalysts for scientific progress–and we’re striving to make it easier for anyone in the world…


 President Reif: We must build a future in which technology works for everyone

Boston Globe op-ed by MIT president calls for a “whole-society effort” to address profound challenges posed by automation. President Reif: We must build a future in which technology works for everyone by MIT News Office


 Sharing our insights from designing with clinicians

Sharing our insights from designing with clinicians by DeepMind


 Summit discusses impact of machines on jobs, productivity, and the global economy

Two-day “AI and the Future of Work” summit at MIT focused on the artificial intelligence revolution and the workplace. Summit discusses impact of machines on jobs, productivity, and the global economy by Rachel Gordon | CSAIL


 Feature Visualization

 

Posted by Christopher Olah, Research Scientist, Google Brain Team and Alex Mordvintsev, Research Scientist, Google Research Have you ever wondered what goes on inside neural networks? Feature visualization is a powerful tool for digging into neural networks and seeing how they work. Our new articl…


 Latest Innovations in TensorFlow Serving

  

Posted by Chris Olston, Research Scientist, and Noah Fiedel, Software Engineer, TensorFlow Serving Since initially open-sourcing TensorFlow Serving in February 2016, we’ve made some major enhancements. Let’s take a look back at where we started, review our progress, and share where we are head…


 Artificial intelligence aids materials fabrication

System could pore through millions of research papers to extract “recipes” for producing materials. Artificial intelligence aids materials fabrication by Larry Hardesty | MIT News Office


 Bringing Streams to Yeovil District Hospital NHS Foundation Trust

Bringing Streams to Yeovil District Hospital NHS Foundation Trust by DeepMind


 Visual reasoning and dialog: Towards natural language conversations about visual data

The broad objective of visual dialog research is to teach machines to have natural language conversations with humans about visual […] Visual reasoning and dialog: Towards natural language conversations about visual data by Kelly Berschauer


 Faster big-data analysis

System for performing “tensor algebra” offers 100-fold speedups over previous software packages. Faster big-data analysis by Larry Hardesty | MIT News Office


 Introducing Kaggle’s State of Data Science & Machine Learning Report, 2017

In 2017 we conducted our first ever extra-large, industry-wide survey to captured the state of data science and machine learning. As the data science field booms, so has our community. In 2017 we hit a new milestone of reaching over 1M registered data scientists from almost every country in the wor…


 Facebook SOSP papers present real-world solutions to complex system challenges

SVE: Distributed Video Processing at Facebook Scale Video is a growing part of the experience of the billions of people […] Facebook SOSP papers present real-world solutions to complex system challenges by Kelly Berschauer


 Can artificial intelligence learn to scare us?

With Shelley, the world’s first artificial intelligence-human horror story collaboration, MIT researchers aim for goosebumps. Can artificial intelligence learn to scare us? by MIT Media Lab


 Learning a Hierarchy

We’ve developed a hierarchical reinforcement learning algorithm that learns high-level actions useful for solving a range of tasks, allowing fast solving of tasks requiring thousands of timesteps. Our algorithm, when applied to a set of navigation problems, discovers a set of high-level actio…