Computer vision

Google’s speech recognition technology now has a 4.9% word error rate

Google CEO Sundar Pichai today announced that the company’s speech recognition technology now has achieved a 4.9 percent word error rate. Put another way, Google transcribes every 20th word incorrectly. That’s a big improvement from the 23 percent the company saw in 2013 and the 8 percent it shared two years ago at I/O 2015.

The tidbit was revealed at Google’s I/O 2017 developer conference, where a big emphasis is artificial intelligence. Deep learning, a type of AI, is used to achieve accurate image recognition and speech recognition. The method involves ingesting lots of data to train systems called neural networks, and then feeding new data to those systems in an attempt to make predictions.

“We’ve been using voice as an input across many of our products,” Pichai said onstage. “That’s…

Facebook to launch ParlAI, a testing ground for AI and bots

Facebook Artificial Intelligence Research (FAIR) today announced plans to launch a testing environment in which AI researchers and bot makers can share and iterate upon each other’s work.

While the initial focus is on open-sourcing the dialogue necessary to train machines to carry on conversations, other research on ParlAI will focus on computer vision and fields of AI beyond the natural language understanding required for this task. The combination of smarts from multiple bots and bot-to-bot communication will also be part of research carried out on ParlAI.

Researchers or users of ParlAI must have Python knowledge to test and train AI models with the open source platform. The purpose of ParlAI, said director of Facebook AI Research Yann LeCun, is to “push the state of the art further.”

“Essentially, this is a problem that goes beyond any one heavily regarded dialogue agent that has sufficient background knowledge. A part of that goes really beyond strictly getting machines to understand language or being able to understand speech. It’s more how do machines really become intelligent, and this is not something that any single entity — whether it’s Facebook or any other — can solve by itself, and so that’s why we’re trying to sort of play a leadership role in the research community and trying to direct them all to the right problem.”

The ability to hold a conversation has been key…

Nvidia and SAP use AI to spot brand appearances in the real world

Nvidia and SAP have teamed up to use artificial intelligence and computer vision to figure out how many times a brand appears in the real world.

Somewhere, somebody whose job it is to count how many times a logo appears on a race car in front of a TV camera or a crowd in the real world is saying thanks. Normally, it takes humans a lot of work to estimate how many advertising impressions are made in the real world. Nvidia showed a demo of the capability at its GPU Technology Conference in San Jose, Calif.

But SAP…