Blog posts/articles from pioneers in AI(industrial)
- Microsoft Reaches Human Parity in Translating News Stories from Chinese to English
- The Machine Learning Reproducibility Crisis
- A Look at Alibaba's AI Strategy
- The Linux Foundation Launches a Deep Learning Foundation
- Using Machine Learning and WiFi-Like-Signals to Detect Alzheimer's Early On
- Identifying Instances of Simpson’s Paradox in Your Data
- Beginners Guide to Monte Carlo Tree Search
- Diving into Deep Convolutional Semantic Segmentation Networks and Deeplab_V3
- Marketing for Data Science: A 7 Step ‘Go-to-Market’ Plan for Your Next Data Product
- Transfer Your Font Style with GANs
- Comparing Deep Learning Frameworks: A Rosetta Stone Approach
- Deepmind: Understanding deep learning through neuron deletion
- What worries me about AI
- Learning Inside of Dreams for RL Agents
- Classification Interpretability with Generative Adversarial Networks
- Deepmind: Learning to Navigate Without Maps
- A Linear Algebra Companion Guide to the Goodfellow-Bengio Deep Learning Book
- Learning Location Embeddings
- France’s AI Strategy
- Highlights from the TensorFlow Developer Summit, 2018
- Predicting Bipolar States with Phone Data and Neural Networks
- China’s Rolled Out Their AI-Based Social Credit System
- The NIH Starts Taking Data Science Seriously - Publishes Strategic Plan and RFI
- Stanford Releases a New Deep Learning Benchmark Focused on Cost & Time
- March Madness is Over - Queue the Statistical Analyses
- Apple Poaches Google’s AI Chief
- The ACM Will Require Submitters to Consider the Negative Impacts of Their Research
- Step By Step Guide to World-Models in Keras
- Fundamentals of Speech & Audio Processing for ML: Filter Banks & Mel Cepstral Coefficients
- How to Quickly Build Your Image Training Set
- Lessons Learned Reproducing a Deep Reinforcement Learning Paper
- Using Decision Trees to Classify White Nationalists
- D3 Data Viz Guide
- Machine Learning on Encrypted Data in TensorFlow
- PyTorch Recommenders 101
- TensorFlow Gets Probabilistic Programming Updates
- NVIDIA And Arm Partnership To Bring Deep Learning Technology To IoT Devices
- Europe Debates Robot Personhood
- Caffe2 Merges With PyTorch
- Accessibility of AI
May
- Neural Nets Can Process and Predict Chaos
- A New Metric to Gauge Bias in Your Word Vectors
- Reward Shaping is Not a Dirty Word in Reinforcement Learning
- MobileNet - v2 Explained
- RNN’s for Non-ML Folk (Artists) Who Use JavaScript
- Removing Background Noises from Your Audio
- EU Countries Team Up to Collaborate on AI to Keep Up with the Rest of the World
- New NLU Benchmark Centered Around Generalization is Released
- Michael Jordan Thinks the AI Revolution Hasn’t Even Started Yet
- Using ML to Predict Bacteria Behavior
- Facebook Enters the AI Chip-Game
- Google’s Use of AI for Security
- OpenAI: AI Safety via Debate; Watching ML-Algs Argue with One Another Might Teach Us About They Behave
- Google Releases an Autonomous Agent, Duplex, that Completes Real Tasks with Human-Interaction
- All About Einsum in TF, PyTorch and Numpy
- HyperTools: Package for Gaining Geometric Insights into High-Dimensional Data
- Stochastic Weight Averaging Tutorial
- Intuitive Approach to Understanding CNN’s
- Some Advice on Hiring Data Scientists
- ML Researchers are Mad at Nature for Paywalling Their New Machine Learning Journal, Boycott
- Carnegie Mellon Launches Undergraduate Degree in Artificial Intelligence
- In-Memory Compute Chips May Be Coming Soon
- Machine Learning for Evil: Keeping Gamblers Hooked
- OpenAI : AI and Compute; OpenAI Tracks Compute Power Used in ML Training Runs - It’s Doubling Faster than Moore’s Law
- Trump Administration Finally Plays Catch Up on the AI-Front
- Statistical power
- The Machine Learning Behind the Cambridge Analytica Scandal
- Playing the Chrome 404 T-Rex Game with Reinforcement Learning, But Really End-to-End
- Statistical Visualization Library Guide with Altair and Jupyter Notebooks
- MLPerf: New Benchmark for Measuring Algorithm Performance Given Certain Hardware
- Moving From Model-Free to Model-Based Deep Reinforcement Learning
- Faster GPU Solutions for a Wide Variety of Algorithms
- Using Apple iWatch + Algorithms to Predict Massive Heart Failures
- Hidden Sound Attacks Can Wake Your Digital Assistant
- Deep Learning-Powered Knitting
- Neural Nets in Artificial Agents Learn to Navigate with Grid-like Representations
June
- Law Enforcement Starts Using Amazon’s Facial Recognition API, ACLU Fires Back
- Uber Open Sources Geo-Data Viz Tool Kepler.gl, and It’s Powerful
- Google: Rules of Machine Learning: Best Practices for ML Engineering
- Another NLP Framework >> NLP-Architect: Explore Deep Learning Based NLP Tools + Techniques
- Tutorial: Build A Semantic-Search System for Code
- Machine Learning Practica: Examples of how Google uses machine learning in its products
- Simple & Comprehensive TensorFlow Tutorials
- How a Kalman filter works, in pictures
- Create beautiful test-driven data visualisations with D3.js
- DARPA is Funding Research Against DeepFakes
- Public Perceptions on AI: A Survey of Americans
- DeepMind Teams Up with Android to Integrate Learned Battery Optimization
- Inside Google, a Debate Rages: Should It Sell Artificial Intelligence to the Military?
- Deepfake Videos Are Getting Impossibly Good
- Attacks against machine learning — an overview
- Realtime tSNE Visualizations with TensorFlow.js
- UNDERSTANDING DEEP LEARNING FOR OBJECT DETECTION
- Rademacher Complexity Explained
- Beyond Numpy Arrays in Python Preparing the ecosystem for GPU, distributed, and sparse arrays
- Building a Query Understanding Engine
- Data science vs. statistics: two cultures?
- GM Cruise Prepping Launch Of Driverless Car Pilot In San Francisco: Emails
- Google: AutoAugment
- On The Dark-Side of ML - Training an Agent on Disturbing Material to Create The 1st “Psychopath” AI
- Largest Open Source Self Driving Database Released - 1000 Hours of Footage
- Introducing MLflow: an Open Source Machine Learning Platform
- Deep in the Pentagon, a secret AI program to find hidden nuclear missiles
- UCLA faculty voice: Artificial intelligence can’t reason why
- Machine learning predicts World Cup winner
- Machine Learning: The High Interest Credit Card of Technical Debt
- Why you need to improve your training data, and how to do it
- Add Constrained Optimization to Your Toolbelt - StitchFix Tutorial
- Lessons from My First Two Years of AI Research
- A Visual Introduction to Bias-Variance Trade-off Learning
- Building a Custom Facial Recognition Dataset
- The 50 Best Free Datasets for Machine Learning
- Bringing Machine Learning to Health Systems and Hospital Operations
- IBM Watson’s Successor Can Now Explain Its Answers & Debate You
- TuSimple selects WekaIO to Fuel Artificial Intelligence (AI) for Autonomous Fleet Vehicle Machine Learning.
- Synapse-Like Computing Chips for Deep Learning
- A machine has figured out Rubik’s Cube all by itself
- High Bandwidth Memory: The Great Awakening of AI
- The Google Brain Team — Looking Back on 2017 (Part 1 of 2)
- The Google Brain Team — Looking Back on 2017 (Part 2 of 2)
- Introduction to Various Reinforcement Learning Algorithms. Part I (Q-Learning, SARSA, DQN, DDPG)
- Four deep learning trends from ACL 2017
- Fitting larger networks into memory.
- NIPS 2017: Policy Field Notes
- Introducing the CVPR 2018 Learned Image Compression Challenge
- Wav2Letter: an End-to-End ConvNet-based Speech Recognition System
- Automated Bug Triaging
- Interpreting Deep Neural Networks
- MIT 6.S094: Deep Learning for Self-Driving Cars
- Applied Machine Learning at Facebook: A Datacenter Infrastructure Perspective
- Tacotron 2: Generating Human-like Speech from Text
- Ray RLlib: Scalable Reinforcement Learning
- Generative Adversarial Networks (GANs): Engine and Applications
- Interpretable Machine Learning
- Elon Musk Steps Down From Open Source AI Group
- AAAS AMA: Hi, we’re researchers from Google, Microsoft, and Facebook who study Artificial Intelligence. Ask us anything!
- Algorithmic Impact Assessments: Toward Accountable Automation in Public Agencies
- 'Memtransistor' Forms Foundational Circuit Element to Neuromorphic Computing
- JupyterLab is Ready for Users
- Google AI Education
- Deep Learning, Structure and Innate Priors: A Discussion between Yann LeCun and Christopher Manning
- An in-depth look at Google’s first Tensor Processing Unit (TPU)
- Same Stats, Different Graphs: Generating Datasets with Varied Appearance and Identical Statistics through Simulated Annealing
- Cloud TPU machine learning accelerators now available in beta
- China overtakes US in AI startup funding with a focus on facial recognition and chips
- OpenAI: Preparing for Malicious Uses of AI
- Deep Learning + Survival Analysis: Our Approach to Multi-Task Frameworks
- Self-driving cars offer huge benefits—but have a dark side
- Google Unveils Their Current Progress on Quantum Computing
- Deep Learning to Create New Sounds and Music
- Stanford Employs ML to Understand Conflict in Internet (Reddit) Communities
- A WalkThrough on Real Time Video Segmentation
- Neural Spelling Corrections and the Importance of Accuracy
- Containerization Made Easy for Data Science
- How to build a deep learning model in 15 minutes
- Impacts of System Memory vs Computing Speed for AI Algorithms & Chips
- Google Helps the Military with Interpreting their Drone Imagery for Threats
- Combining the Building Blocks of Interpretability
- Checking in with the Intel® AI Lab
- Guest Post (Part I): Demystifying Deep Reinforcement Learning
- Industry Focus: Serving the Automotive Industry with the Nervana Platform
- Securing the Deep Learning Stack
- End-to-end speech recognition with neon
- Preview Release: Intel® Nervana™ Graph
- 2017: What a Wonderful Year for AI
- Artificial Intelligence at the Edge
- Flexpoint: numerical innovation underlying the Intel® Nervana™ Neural Network Processor
- Taking Telecom to New Heights with Artificial Intelligence
- The Importance of Systems in Machine Learning
- Accelerating Deep Learning Training and Inference with System Level Optimizations
- Biomedical Image Segmentation with U-Net
- The Future of Retail is All About Artificial Intelligence
- The Challenges and Opportunities of Explainable AI
- Neuroscience to Computer Science: An Update from AI Research at Intel
- Kubernetes Volume Controller (KVC): Data Management Tailored for Machine Learning Workloads in Kubernetes
- AI-Enhanced Medical Imaging to Improve Radiology Workflows
- nGraph: A New Open Source Compiler for Deep Learning Systems
- Deep Learning to Study the Brain to Improve...Deep Learning
- TensorFlow* Optimizations for the Intel® Xeon® Scalable Processor
- Teaching Machines to do Image Classification in Health and Life Sciences: Intel® Xeon® Scalable Processors in Lab Coats
- Powering Precision Medicine with Artificial Intelligence
- Announcing the DeepGlobe Satellite Challenge for CVPR 2018
- The next step in Facebook's AI hardware infrastructure
- Announcing Tensor Comprehensions
- Enabling full body AR with Mask R-CNN2Go
- Facebook partners with the University of Washington to create new AR/VR research center
- Facebook showcases latest research at NIPS 2017
- Visual reasoning and dialog: Towards natural language conversations about visual data
- Amazon Web Services to join ONNX AI format, drive MXNET support
- Facebook SOSP papers present real-world solutions to complex system challenges
- Facebook at ICCV 2017
- Inventing the Future
- ONNX AI Format Adds Partners
- A conversation with Dr. Joëlle Pineau, head of new FAIR lab in Montreal
- Using social media data to help measure smoke exposure
- Expanding Facebook AI Research to Montreal
- Facebook and Microsoft introduce new open ecosystem for interchangeable AI frameworks
- Facebook memories: the research behind the products that connect you with your past
- Optimizing 360 photos at scale
- Introducing Social Hash Partitioner, a scalable distributed hypergraph partitioner
- Facebook awards $100,000 to 2017 Internet Defense Prize winners
- Machine learning insights from ICML 2017
- Using AI for new visual storytelling techniques in VR
- Advancing computer vision technologies at CVPR 2017
- Join us live for the ACM’s Celebration of 50 years of the ACM A.M. Turing Award
- Deal or no deal? Training AI bots to negotiate
- Facebook Disaster Maps: Methodology
- Accelerating machine learning for computer vision
- ParlAI: A new software platform for dialog research
- A novel approach to neural machine translation
- Expanded fastText library now fits on smaller-memory devices
- FAIR research being presented at ICLR 2017
- The long game towards understanding dialog
- Introducing Caffe2 to the academic community
- Connectivity: A building block approach
- Caffe2 Open Source Brings Cross Platform Machine Learning Tools to Developers
- Faiss: A library for efficient similarity search
- Facebook AI Academy
- A look at Facebook AI Research Paris
- Accessibility Research: Developing automatic-alt text for Facebook screen reader users
- Prophet: forecasting at scale
- The value of diversity in data science research
- Yann LeCun elected to the National Academy of Engineering for advances in AI
- Beringei: A high-performance time series storage engine
- Inferbo: Infer-based buffer overrun analyzer
- Building scalable systems to understand content
- Data Sharing on traffic pattern inside Facebook’s datacenter network
- Facebook researchers at SPSP 2017
- Advancing AI at NIPS 2016
- Artificial intelligence, revealed
- Open population datasets and open challenges
- Facebook demonstrates record-breaking data rate using millimeter-wave technology
- Delivering real-time AI in the palm of your hand
- Building an Efficient Neural Language Model Over a Billion Words
- 360 video stabilization
- Facebook to Accelerate Global AI Research with New GPU Program Recipients
- Learning to Segment
- Robotron: Top-down Network Management at Facebook Scale
- fastText
- Cat People, Dog People
- Imperfect Treatment Assignments
- Harnessing light for wireless communications
- Facebook Researchers Focus on the Most Challenging Machine Learning Questions at ICML 2016
- The Evolution of Advanced Caching in the Facebook CDN
- Three and a half degrees of separation
- Reasoning, Attention, Memory (RAM) NIPS Workshop 2015
- IPv6: It’s time to get on board
- Building communications networks in the stratosphere
- Inferring Algorithmic Patterns with Stack
- Exposure to Diverse Information on Facebook
- Open-sourcing Facebook Infer: Identify bugs before you ship
- FAIR open sources deep-learning modules for Torch
- Introducing Proxygen, Facebook’s C++ HTTP framework
- Introducing data center fabric, the next-generation Facebook data center network
- Facebook’s Top Open Data Problems
- Fast Randomized SVD
- Facebook Advertising Research Around the World
- Using Neural Networks for Modeling and Representing Natural Languages
- Presto: Interacting with petabytes of data at Facebook
- Making Facebook’s software infrastructure more energy efficient with Autoscale
- The strange truth about fiction
- Deep learning tutorial at CVPR 2014
- MobileNetV2: The Next Generation of On-Device Computer Vision Networks
- Investing in France’s AI Ecosystem
- Using Machine Learning to Discover Neural Network Optimizers
- Reformulating Chemistry for More Efficient Quantum Computation
- Using Deep Learning to Facilitate Scientific Image Analysis
- Using Evolutionary AutoML to Discover Neural Network Architectures
- Balanced Partitioning and Hierarchical Clustering at Scale
- Behind the Motion Photos Technology in Pixel 2
- Semantic Image Segmentation with DeepLab in TensorFlow
- Introducing the iNaturalist 2018 Challenge
- Open Sourcing the Hunt for Exoplanets
- The Building Blocks of Interpretability
- A Preview of Bristlecone, Google’s New Quantum Processor
- Making Healthcare Data Work Better with Machine Learning
- Mobile Real-time Video Segmentation
- Google-Landmarks: A New Dataset and Challenge for Landmark Recognition
- A Summary of the Google Zürich Algorithms & Optimization Workshop
- Assessing Cardiovascular Risk Factors with Computer Vision
- Introducing the HDR+ Burst Photography Dataset
- The Instant Motion Tracking Behind Motion Stills AR
- The Google Brain Team — Looking Back on 2017 (Part 2 of 2)
- The Google Brain Team — Looking Back on 2017 (Part 1 of 2)
- Introducing the CVPR 2018 Learned Image Compression Challenge
- Evaluation of Speech for the Google Assistant
- Tacotron 2: Generating Human-like Speech from Text
- Introducing NIMA: Neural Image Assessment
- Improving End-to-End Models For Speech Recognition
- A Summary of the First Conference on Robot Learning
- TFGAN: A Lightweight Library for Generative Adversarial Networks
- Introducing Appsperiments: Exploring the Potentials of Mobile Photography
- Introducing a New Foveation Pipeline for Virtual/Mixed Reality
- DeepVariant: Highly Accurate Genomes With Deep Neural Networks
- Google at NIPS 2017
- Understanding Bias in Peer Review
- Understanding Medical Conversations
- SLING: A Natural Language Frame Semantic Parser
- On-Device Conversational Modeling with TensorFlow Lite
- Seamless Google Street View Panoramas
- Feature Visualization
- AutoML for large scale image classification and object detection
- Tangent: Source-to-Source Debuggable Derivatives
- Latest Innovations in TensorFlow Serving
- Eager Execution: An imperative, define-by-run interface to TensorFlow
- Closing the Simulation-to-Reality Gap for Deep Robotic Learning
- Announcing AVA: A Finely Labeled Video Dataset for Human Action Understanding
- The Google Brain Team’s Approach to Research
- Build your own Machine Learning Visualizations with the new TensorBoard API
- Seminal Ideas from 2007
- Transformer: A Novel Neural Network Architecture for Language Understanding
- Exploring and Visualizing an Open Global Dataset
- Launching the Speech Commands Dataset
- Google at KDD’17: Graph Mining and Beyond
- Announcing the NYC Algorithms and Optimization Site
- Making Visible Watermarks More Effective
- Harness the Power of Machine Learning in Your Browser with Deeplearn.js
- Google at ICML 2017
- Google at ACL 2017
- Expressions in Virtual Reality
- So there I was, firing a megawatt plasma collider at work...
- Teaching Robots to Understand Semantic Concepts
- Google at CVPR 2017
- An Update to Open Images - Now with Bounding-Boxes
- Facets: An Open Source Visualization Tool for Machine Learning Training Data
- Using Deep Learning to Create Professional-Level Photographs
- Building Your Own Neural Machine Translation System in TensorFlow
- The Google Brain Residency Program — One Year Later
- MultiModel: Multi-Task Machine Learning Across Domains
- Accelerating Deep Learning Research with the Tensor2Tensor Library
- Supercharge your Computer Vision models with the TensorFlow Object Detection API
- MobileNets: Open-Source Models for Efficient On-Device Vision
- The Machine Intelligence Behind Gboard
- Introducing the TensorFlow Research Cloud
- Using Machine Learning to Explore Neural Network Architecture
- Efficient Smart Reply, now for Gmail
- Coarse Discourse: A Dataset for Understanding Online Discussions
- Neural Network-Generated Illustrations in Allo
- Updating Google Maps with Deep Learning and Street View
- Experimental Nighttime Photography with Nexus and Pixel
- Research at Google and ICLR 2017
- PhotoScan: Taking Glare-Free Pictures of Pictures
- Teaching Machines to Draw
- Introducing tf-seq2seq: An Open Source Sequence-to-Sequence Framework in TensorFlow
- Predicting Properties of Molecules with Machine Learning
- Federated Learning: Collaborative Machine Learning without Centralized Training Data
- Announcing AudioSet: A Dataset for Audio Event Research
- Adding Sound Effect Information to YouTube Captions
- Distill: Supporting Clarity in Machine Learning
- An Upgrade to SyntaxNet, New Models and a Parsing Competition
- Assisting Pathologists in Detecting Cancer with Deep Learning
- Preprocessing for Machine Learning with tf.Transform
- Headset “Removal” for Virtual and Mixed Reality
- An updated YouTube-8M, a video understanding challenge, and a CVPR workshop. Oh my!
- Announcing TensorFlow 1.0
- On-Device Machine Intelligence
- Announcing TensorFlow Fold: Deep Learning With Dynamic Computation Graphs
- Advancing Research on Video Understanding with the YouTube-BoundingBoxes Dataset
- Using Machine Learning to Predict Parking Difficulty
- Facilitating the discovery of public datasets
- A Large Corpus for Supervised Word-Sense Disambiguation
- Google Brain Residency Program - 7 months in and looking ahead
- Deep Learning for Siri’s Voice: On-device Deep Mixture Density Networks for Hybrid Unit Selection Synthesis
- Hey Siri: An On-device DNN-powered Voice Trigger for Apple’s Personal Assistant
- Learning with Privacy at Scale
- Building Better Bots Using Amazon Lex (Part 1)
- Building Better Bots Using Amazon Lex (Part 2)
- Predicting Customer Churn with Amazon Machine Learning
- Use Amazon Rekognition to Build an End-to-End Serverless Photo Recognition System
- Build Your Own Text-to-Speech Applications with Amazon Polly
- Deploy Deep Learning Models on Amazon ECS
- Running BigDL, Deep Learning for Apache Spark, on AWS
- Amazon and Facebook Collaborate to Optimize Caffe2 for the AWS Cloud
- Fast CNN Tuning with AWS GPU Instances and SigOpt
- Deep Learning on AWS at NVIDIA’s GPU Technology Conference, GTC 2017
- Create Audiobooks with Amazon Polly and AWS Batch
- Powering Language Learning on Duolingo with Amazon Polly
- Integrate Your Amazon Lex Bot with Any Messaging Service
- Tuning Your DBMS Automatically with Machine Learning
- Capturing Voice Input in a Browser and Sending it to Amazon Lex
- Activity Tracking with a Voice-Enabled Bot on AWS
- Using Amazon Rekognition to Identify Persons of Interest for Law Enforcement
- Build a Real-time Object Classification System with Apache MXNet on Raspberry Pi
- Using Amazon Polly to Deliver Health Care for People with Long-Term Conditions
- Find Distinct People in a Video with Amazon Rekognition
- Voice-Enabled Mobile Bot Drives Auto Industry Innovation with Real-Time Trade-in Values for Vehicles
- Building a Reliable Text-to-Speech Service with Amazon Polly
- Train Neural Machine Translation Models with Sockeye
- Create a Serverless Solution for Video Frame Analysis and Alerting
- Exploiting the Unique Features of the Apache MXNet Deep Learning Framework with a Cheat Sheet
- Analyze Emotion in Video Frame Samples Using Amazon Rekognition on AWS
- Estimating the Location of Images Using Apache MXNet and Multimedia Commons Dataset on AWS EC2
- Build Your Own Face Recognition Service Using Amazon Rekognition
- How Amazon Polly Breathed Life into Dan Brown’s Digital Assistant
- Create a Question and Answer Bot with Amazon Lex and Amazon Alexa
- Build an Autonomous Vehicle on AWS and Race It at the re:Invent Robocar Rally
- Capture and Analyze Customer Demographic Data Using Amazon Rekognition & Amazon Athena
- Introducing NNVM Compiler: A New Open End-to-End Compiler for AI Frameworks
- Introducing Gluon — An Easy-to-Use Programming Interface for Flexible Deep Learning
- Build an Autonomous Vehicle Part 2: Driving Your Vehicle
- AWS Collaborates with Emory University to Develop Cloud-Based NLP Research Platform Using Apache MXNet
- Building an Autonomous Vehicle Part 3: Connecting Your Autonomous Vehicle
- Building an Autonomous Vehicle, Part 4: Using Behavioral Cloning with Apache MXNet for Your Self-Driving Car
- Run Deep Learning Frameworks with GPU Instance Types on Amazon EMR
- Amazon Rekognition Announces Real-Time Face Recognition, Support for Recognition of Text in Image, and Improved Face Detection
- Receive Phone Call Alerts for AWS Account Security Events With Amazon Polly
- Extend AWS DeepLens to Send SMS Notifications with AWS Lambda
- How to Deploy Deep Learning Models with AWS Lambda and Tensorflow
- Build a social media dashboard using machine learning and BI services
- Amazon SageMaker BlazingText: Parallelizing Word2Vec on Multiple CPUs or GPUs
- Detect sentiment from customer reviews using Amazon Comprehend
- Deploy a Web UI for Your Chatbot
- Zocdoc builds patient confidence using TensorFlow on AWS
- Train and host Scikit-Learn models in Amazon SageMaker by building a Scikit Docker container
- Create a Word-Pronunciation sequence-to-sequence model using Amazon SageMaker
- Four Big Bets For Better AI Research: A Personal Journey
- Typing in the Virtual Office Environment: Examining the Effects of Keyboard and Hand Representation in VR
- Microsoft Shines at NSDI ’18
- Microsoft and Tsinghua University Work Together on Open Academic Data Research
- Microsoft Pix’s AI gets even smarter, Business Card feature works with LinkedIn to make it easier than ever to manage your contacts
- Touching the Virtual: How Microsoft Research is Making Virtual Reality Tangible
- Microsoft researchers unlock the black box of network embedding
- New institute explores the future of Cortana
- Learn Artificial Intelligence Skills via Residency at Microsoft
- Collecting telemetry data privately
- Deliberation Network: Pushing the frontiers of neural machine translation
- New Meta-learning Techniques for Neural Program Induction
- Will machines one day be as creative as humans?
- New Microsoft Research Podcast invites you to log on, tune in and geek out
- Microsoft Research and Microsoft Azure improve the efficiency and capacity of cloud-scale optical networks
- Microsoft extends AirSim to include autonomous car research
- Microsoft Azure and Microsoft Research take giant step towards eliminating network downtime
- Scientists use machine learning to predict DNA binding rates from sequence
- Changing the world with data science
- Counting every person on Earth to eradicate poverty and empower women
- Microsoft researchers achieve new conversational speech recognition milestone
- Microsoft unveils Project Brainwave for real-time AI
- Program that repairs programs: how to achieve 78.3 percent precision in automated program repair
- Researchers build nanoscale computational circuit boards with DNA
- Transfer learning for machine reading comprehension
- AI with creative eyes amplifies the artistic sense of everyone
- Second version of HoloLens HPU will incorporate AI coprocessor for implementing DNNs
- Transportation Data Science at Microsoft
- Path Guide: A New Approach to Indoor Navigation
- What problems will we solve with a quantum computer?
- Relevance of Unsupervised Metrics in Task-Oriented Dialogue for Evaluating Natural Language Generation
- Microsoft and intelligent markets at ACM EC’17
- Hybrid Reward Architecture (HRA) Achieving super-human performance on Ms. Pac-Man
- A Joint Model for Question Answering and Question Generation
- NSF Big Data Innovation Hubs collaboration — looking back after one year
- Holograms: The future of near-eye display?
- Toward AI that operates in the real world
- Where cryptography and quantum computing intersect
- Advancing machine comprehension with question generation
- Deep Learning for Program Synthesis
- The next challenges for reinforcement learning
- Teaching AI to make decisions and communicate
- From cancer to crop genomics — using Research as a Service at the intersection of computers and biology
- A new understanding of the world through grassroots Data Science education at UC Berkeley
- Democratizing AI to improve citizen health
- From improving a golf swing to reducing energy in datacenters
- AI is getting smarter; Microsoft researchers want to ensure it’s also getting more accurate
- Microsoft Research and the industrial research cycle
- Decomposing tasks like humans: Scaling reinforcement learning by separation of concerns
- Memory & machines: A study in goal-oriented dialogue systems
- Creating curious machines: Building information-seeking agents
- VINE: An Open Source Interactive Data Visualization Tool for Neuroevolution
- Introducing the Uber AI Residency
- COTA: Improving Uber Customer Care with NLP & Machine Learning
- Year in Review: 2017 Highlights from the Uber Engineering Blog
- Welcoming the Era of Deep Neuroevolution
- Gleaning Insights from Uber’s Partner Activity Matrix with Genomic Biclustering and Machine Learning
- Welcoming Peter Dayan to Uber AI Labs
- Engineering More Reliable Transportation with Machine Learning and AI at Uber
- Uber AI Labs Open Sources Pyro, a Deep Probabilistic Programming Language
- Engineering Extreme Event Forecasting at Uber with Recurrent Neural Networks
- Presenting the Engineering Behind Uber at Our Technology Day
- Rewriting Uber Engineering’s Android Rider App with Deep Scope Hierarchies
- Powering UberEATS with React Native and Uber Engineering
- Engineering Stability in Migrations: Moving to Immutable Collections in Uber’s Android Apps
- Redesigning Uber Engineering’s Mobile Content Delivery Ecosystem
- The Journey To Android Monorepo: The History Of Uber Engineering’s Android Codebase Organization
- Engineering Signature Rendering on iOS with UberSignature
- Demystifying RxJava Backpressure on Android at Uber Engineering
- How Uber Engineering Verifies Data at Runtime with the Annotations You Already Use
- Driver Profiles: How Uber Engineering Celebrates Drivers
- Building More Reliable Apps with Uber Engineering’s Startup Reason Reporter
- IBM GPU-Accelerated Semantic Similarity Search at Scale Shows ~30000x Speed Up
- IBM Sets Tera-scale Machine Learning Benchmark Record with POWER9 and NVIDIA GPUs; Available Soon in PowerAI
- Deep Learning Advances from IBM Research
- Capturing the value of place and time with geospatial-temporal insights
- Changing the Way the World Works: IBM Research’s “5 in 5”
- Charity Models Supply Chain Performance with IBM
- Demystifying Social Entrepreneurship: A Data-Driven Approach
- Deep Learning Training Times Get Significant Reduction
- Mitigating Bias in AI Models
- Tapping Machine Learning to Foster Greater Use of Biomimicry for Innovation
- Automating Code Generation for Deep Learning Models from Research Papers
- End-to-End Open-Domain QA via Multi-Passage Reading Comprehension
- IBM Research AI at the AAAI Conference on Artificial Intelligence
- How AI can help enterprise workers automatically triage conversations
- Prediction of psychotic onset with AI: words portend the future
- ROMEO Seeks to Improve Wind Farms with Machine Learning and IoT at the Edge
- Distributing Control of Deep Learning Training Delivers 10x Performance Improvement
- Pruning AI networks without performance loss
- New AI algorithm recommends right products at the right time
- Making interaction with AI systems more natural with textual grounding
- TJBot goes digital, and more playground adventures
- Reducing discrimination in AI with new methodology
- Publishing in The Lancet’s EBioMedicine: New research in AI pushes frontiers in epileptic seizure prediction
- How dictionaries act as strong foundations for training AI systems
- IBM scientists demonstrate 10x faster large-scale machine learning using GPUs
- Using Neural Networks to Predict Outcomes of Organic Chemistry
- Helping AI master video understanding
- IBM Research showcases AI advances @ NIPS 2017
- Automated knowledge base construction solution wins at ISWC 2017
- Interactive supervision with TensorBoard
- QISKit for quantum computation
- How inventing became a passion: Developing autonomous vehicles to help support healthy aging and people with disabilities
- Building a winning team using AI
- Learning to navigate in cities without a map
- Learning to write programs that generate images
- Understanding deep learning through neuron deletion
- Stop, look and listen to the people you want to help
- Learning by playing
- Researching patient deterioration with the US Department of Veterans Affairs
- IMPALA: Scalable Distributed DeepRL in DMLab-30
- Learning explanatory rules from noisy data
- Open-sourcing Psychlab
- Game-theory insights into asymmetric multi-agent games
- 2017: DeepMind's year in review
- Collaborating with patients for better outcomes
- DeepMind papers at NIPS 2017
- Why doesn't Streams use AI?
- Specifying AI safety problems in simple environments
- Population based training of neural networks
- Applying machine learning to mammography screening for breast cancer
- High-fidelity speech synthesis with WaveNet
- Sharing our insights from designing with clinicians
- AlphaGo Zero: Learning from scratch
- WaveNet launches in the Google Assistant
- Why we launched DeepMind Ethics & Society
- The hippocampus as a 'predictive map
- DeepMind and Blizzard open StarCraft II as an AI research environment
- DeepMind papers at ICML 2017 (part one)
- DeepMind papers at ICML 2017 (part two)
- DeepMind papers at ICML 2017 (part three)
- AI and Neuroscience: A virtuous circle
- Going beyond average for reinforcement learning
- Agents that imagine and plan
- Imagine this: Creating new visual concepts by recombining familiar ones
- Producing flexible behaviours in simulated environments
- DeepMind expands to Canada with new research office in Edmonton, Alberta
- Independent Reviewers release first annual report on DeepMind Health
- The Information Commissioner, the Royal Free, and what we’ve learned
- Interpreting Deep Neural Networks using Cognitive Psychology
- Enhancing patient safety at Taunton and Somerset NHS Foundation Trust
- Learning through human feedback
- A neural approach to relational reasoning
- AlphaGo's next move
- Exploring the mysteries of Go with AlphaGo and China's top players
- Innovations of AlphaGo
- Open sourcing Sonnet - a new library for constructing neural networks
- Distill: Communicating the science of machine learning
- Enabling Continual Learning in Neural Networks
- Trust, confidence and Verifiable Data Audit
- A milestone for DeepMind Health and Streams
- Understanding Agent Cooperation
- Our collaborations with academia to advance the field of AI
- DeepMind’s work in 2016: a round-up
- Bringing the best of mobile technology to Imperial College Healthcare NHS Trust
- DeepMind Papers @ NIPS (Part 3)
- DeepMind Papers @ NIPS (Part 2)
- Open-sourcing DeepMind Lab
- DeepMind Papers @ NIPS (Part 1)
- Working with the NHS to build lifesaving technology
- Reinforcement learning with unsupervised auxiliary tasks
- DeepMind and Blizzard to release StarCraft II as an AI research environment
- Differentiable neural computers
- Announcing the Partnership on AI to Benefit People & Society
- Putting patients at the heart of DeepMind Health
- WaveNet: A Generative Model for Raw Audio
- Applying machine learning to radiotherapy planning for head & neck cancer
- Decoupled Neural Interfaces Using Synthetic Gradients
- DeepMind AI Reduces Google Data Centre Cooling Bill by 40%
- Announcing DeepMind Health research partnership with Moorfields Eye Hospital
- Deep Reinforcement Learning
- We are very excited to announce the launch of DeepMind Health
- Introducing OpenAI
- Team++
- Welcome, Pieter and Shivon!
- Concrete AI Safety Problems
- OpenAI Gym Beta
- Team Update
- Generative Models
- OpenAI Technical Goals
- Special Projects
- Team Update
- Machine Learning Unconference
- Faulty Reward Functions in the Wild
- Infrastructure for Deep Learning
- Report from the Self-Organizing Conference
- OpenAI and Microsoft
- Universe
- Team Update
- Attacking Machine Learning with Adversarial Examples
- Learning to Communicate
- Roboschool
- Distill
- Evolution Strategies as a Scalable Alternative to Reinforcement Learning
- Spam Detection in the Physical World
- Unsupervised Sentiment Neuron
- Robots that Learn
- OpenAI Baselines: DQN
- Learning to Cooperate, Compete, and Communicate
- Learning from Human Preferences
- Faster Physics in Python
- Robust Adversarial Examples
- Better Exploration with Parameter Noise
- Proximal Policy Optimization
- Gathering Human Feedback
- Dota 2
- More on Dota 2
- OpenAI Baselines: ACKTR & A2C
- Learning to Model Other Minds
- Meta-Learning for Wrestling
- Nonlinear Computation in Deep Linear Networks
- Competitive Self-Play
- Generalizing from Simulation
- Learning a Hierarchy
- Block-Sparse GPU Kernels
- Preparing for Malicious Uses of AI
- Scaling Kubernetes to 2,500 Nodes
- Requests for Research 2.0
- Discovering Types for Entity Disambiguation
- Interpretable Machine Learning through Teaching
- OpenAI Supporters
- OpenAI Hackathon
- Ingredients for Robotics Research
- OpenAI Scholars
- Reptile: A Scalable Meta-Learning Algorithm
- Report from the OpenAI Hackathon
- Retro Contest
- OpenAI Charter
- Neural Voice Cloning with a Few Samples
- Baidu Research Showcased at Top Artificial Intelligence Conferences
- Baidu Research Announces the Hiring of Three World-Renowned AI Scientists
- PaddlePaddle Fluid: Elastic Deep Learning on Kubernetes
- Deep Learning Scaling is Predictable, Empirically
- Deep Speech 3: Even more end-to-end speech recognition
- Deep Voice 3: 2000-Speaker Neural Text-to-Speech
- Mixed Precision Training
- A Spatial-Temporal Modeling Framework for Large-scale Video Understanding
- Baidu Research Announces Next Generation Open Source Deep Learning Benchmark Tool
- Learning to Speak via Interaction
- Deep Voice 2: Multi-Speaker Neural Text-to-Speech
- Deep Speaker: an End-to-End System for Large-Scale Speaker Recognition
- An AI agent with human-like language acquisition in a virtual environment
- Introducing SwiftScribe: A Breakthrough in AI-Powered Transcription Software
- PaddlePaddle’s New API Simplifies Deep Learning Programs
- Gram CTC: Speech Recognition with Word Piece Targets
- Deep Voice: Real-Time Neural Text-to-Speech for Production
- Bringing HPC Techniques to Deep Learning
- PaddlePaddle and Kubernetes Join Forces, Helping Developers Efficiently Train Deep Learning Models
- Baidu’s Melody: AI-Powered Conversational Bot for Doctors and Patients
- Baidu Research Announces New Open Source Deep Learning Benchmark
- Baidu’s Duer Personal Assistant Has New Talent: Sports Commentary
- Baidu’s Silicon Valley AI Lab is Hiring!
- Porting HTM Models to the Heidelberg Neuromorphic Computing Platform
- Encoding Data for HTM Systems
- Evaluating Real-time Anomaly Detection Algorithms - the Numenta Anomaly Benchmark
- Properties of Sparse Distributed Representations and their Application to Hierarchical Temporal Memory
- How do neurons operate on sparse distributed representations? A mathematical theory of sparsity, neurons and active dendrites
- Continuous Online Sequence Learning with an Unsupervised Neural Network Model
- Unsupervised Real-Time Anomaly Detection for Streaming Data
- The HTM Spatial Pooler—A Neocortical Algorithm for Online Sparse Distributed Coding
- Why Neurons Have Thousands of Synapses, A Theory of Sequence Memory in Neocortex
- A Theory of How Columns in the Neocortex Enable Learning the Structure of the World
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