Real-time AI: Microsoft announces preview of Project Brainwave
Every day, thousands of gadgets and widgets whish down assembly lines run by the manufacturing solutions provider Jabil, on their way into the hands of customers.
Along the way, an automated optical inspection system scans them for any signs of defects, with a bias toward ensuring that all potential anomalies are detected. It then sends those parts off to be checked manually.
The speed of operations leaves manual inspectors with just seconds to decide if the product is really defective, or not.
That’s where Microsoft’s Project Brainwave could come in. Project Brainwave is a hardware architecture designed to accelerate real-time AI calculations. The Project Brainwave architecture is deployed on a type of computer chip from Intel called a field programmable gate array, or FPGA, to make real-time AI calculations at competitive cost and with the industry’s lowest latency, or lag time. This is based on internal performance measurements and comparisons to other organization’s publicly posted information.
Microsoft’s mission: AI for every developer
Vulcan Steel makes about 3,000 deliveries of steel a day to businesses throughout New Zealand and Australia – which means that each day, its employees need to use their training to figure out how to safely get large, heavy and unwieldly pieces of steel off of its trucks and into the hands of a very diverse group of customers.
“It’s an awkward product to transport, and it’s difficult to design out all of the risks,” said James Wells, who acts as the company’s chief information officer. “So essentially what that means for us is one of the key requirements or skills for us to keep people safe is around education.”
For years, Vulcan Steel did what most companies do – they educated their employees about safety before sending them into the field, and then they did additional training as needed if someone reported an accident or near miss.
Now, they’re using artificial intelligence to try to more proactively prevent accidents and near misses before they happen. The company recently started using Microsoft Cognitive Service’s Custom Vision tools to evaluate camera footage from the company’s trucks for actions that could be risky or lead to an accident.
AI news from Microsoft’s Build developers conference
At Microsoft’s Build developers conference in Seattle this week, the company is unveiling a series of new and updated tools that will help developers incorporate artificial intelligence into their processes and applications, regardless of their background and training in the fast-emerging field of AI.
AI technology helps students who are deaf learn
As stragglers settle into their seats for general biology class, real-time captions of the professor’s banter about general and special senses – “Which receptor picks up pain? All of them.” – scroll across the bottom of a PowerPoint presentation displayed on wall-to-wall screens behind her. An interpreter stands a few feet away and interprets the professor’s spoken words into American Sign Language, the primary language used by the deaf in the US.
Except for the real-time captions on the screens in front of the room, this is a typical class at the Rochester Institute of Technology in upstate New York. About 1,500 students who are deaf and hard of hearing are an integral part of campus life at the sprawling university, which has 15,000 undergraduates. Nearly 700 of the students who are deaf and hard of hearing take courses with students who are hearing, including several dozen in Sandra Connelly’s general biology class of 250 students.
Like a phone call: XiaoIce, Microsoft’s social chatbot in China, makes breakthrough in natural conversation
When people interact with most personal digital assistants or chatbots today, the experience is a lot like speaking into a walkie-talkie or texting: First one party says or writes something, and then the other party digests that information and responds.
It’s effective, but Li Zhou, engineer lead for XiaoIce, Microsoft’s wildly popular artificial intelligence-powered social chatbot in China, notes that it has one big drawback.
“People don’t actually talk that way,” Zhou said
Aiming to fill skill gaps in AI, Microsoft makes training courses available to the public
As a software engineer at Microsoft, Elena Voyloshnikova’s job is to make informed recommendations about how to improve the performance of software engineering tools.
But too often, she spends her days manually analyzing the data she needs to make those decisions. Lately, her team has been discussing the potential of building machine learning models to automate that task – creating more time to focus on the decision-making.
Microsoft reaches a historic milestone, using AI to match human performance in translating news from Chinese to English
A team of Microsoft researchers said Wednesday that they believe they have created the first machine translation system that can translate sentences of news articles from Chinese to English with the same quality and accuracy as a person.
Researchers in the company’s Asia and U.S. labs said that their system achieved human parity on a commonly used test set of news stories, called newstest2017, which was developed by a group of industry and academic partners and released at a research conference called WMT17 last fall. To ensure the results were both accurate and on par with what people would have done, the team hired external bilingual human evaluators, who compared Microsoft’s results to two independently produced human reference translations.
In order for scientists to make breakthroughs that could help lead to cures for pediatric cancers, researchers around the world need to be able to easily share and collaborate on genomic data. That’s why, in 2010, computational biologist Jinghui Zhang and her team at St. Jude Children’s Research Hospital in Memphis started uploading anonymized genomes of their patients’ healthy and cancerous cells to public data repositories.
“We realized that it was very hard for people to download the data and use the data for their research because of the sheer size and volume of the data,” said Zhang. “So, St. Jude started to seriously explore other ways to facilitate data sharing with the global research community.”