09/05 — Google Updates Its Street View Cameras with AI and Machine Learning
Google just upgraded its street view camera for the first time in eight years, which will be used to capture images with higher resolution, sharper detail, and more vivid color. The company’s machine learning and AI capability can extract vendor information based on Street View’s HD pictures and mark them on Google map.
09/06 — Walmart Wants Build GPU Cloud for Machine Learning to Fend Amazon
Walmart is working with NVIDIA on a cloud platform using GPUs for data storage. The size is about 1/10 the size of Amazon’s GPU cloud. Amazon has been competing with Walmart in the retail business, the latter now refuses to continue using the Amazon Web Service.
09/06 — IBM Partners with MIT to Develop AI Research Lab Spending USD 240 Million
IBM announced spending of USD 240 million to establish the MIT-IBM Watson AI Lab. The lab will have 100 researchers and aims at conducting long-term machine learning research on applications in healthcare, cyber security and so forth.
09/07- Facebook and Microsoft Works Together to Introduce Open Neural Network Exchange ONNX
Facebook and Microsoft introduced Open Neural Network Exchange (ONNX), a new format that enables developers to share deep learning models between PyTorch and Caffe2. Until now, different machine learning frameworks, such as Tensorflow, PyTorch and Caffe2, have different a process of building deep learning models. ONNX can remove barriers and help developers convert models built in PyTorch into Caffe2 models and vice versa.
09/12- IKEA Launched IKEA Place App Using iPhone’s ARKit
IKEA launched its official AR-based App IKEA Place, whereby users can find a catalog of 2,000 items and place any furniture into a real-life space through AR technology. They can also save the pictures and reserve items on a local IKEA site. To date, the app is around for only seven weeks. IKEA works in partnership with Metaio, an augmented reality startup acquired by Apple in 2015.
09/13 — Apple’s Neural Engine Chip Adds AI to iPhone
Apple’s latest iPhones come with the “Neural Engine” mobile chip designed to accelerate artificial neural networks for image and speech processing. Many of the new features such as FaceID, animated emoji, and augmented reality rely on machine learning algorithms. The chip allows machine learning to be done faster on mobile devices without replying on internet and cloud connections.
09/14 — Samsung Launches 300M USD Autonomous Driving Fund, Puts USD 90M into TTTech
Samsung announces a USD 300 million fund called Automotive Innovation Fund to invest in the autonomous vehicle market. The first investment from this fund is USD 90 million in TTTech, an Austrian company focused on providing safety software for connected cars.
09/14 — Washington Post’s Robot Reporter Published 850 Articles in 2016
Heliograf, The Washington Post’s own AI journalist has now been producing automated news for over a year. It was first deployed during the Rio Olympics generating 300 stories. It also produced 500 stories last year’s US election, bringing in a total of 500,000 click. The bot performed much better than humans in some areas, for example it reported far more accurately on financial news at a much lower cost.
09/15 — Facebook Expands AI Research Lab to Montreal Canada
Yann LeCun, Chief AI Scientist at Facebook, announced that the company will be opening an AI research lab in Montreal as part of the Facebook AI Research (FAIR) division. The lab will employ Canadian researchers and engineers, focusing on reinforcement learning and dialogue system research.Professor Joelle Pineau from McGill University will head the lab and build the team while retaining her academic position.
09/16 — British TV Executives Say Voice Search and AI are the Next in Media
British TV executives from Channel 4, IBM, Liberty Global, and Ericsson see voice and AI as their next big business drivers. Voice enabled assistants like Alexa is adopted by consumer worldwide and will likely change the way users interact with the news and affiliated media content. AI and machine learning are also being watched by the executives for it’s potential to extract data from videos and target ads effectively.