Google has a slew of artificial intelligence announcements it’s making this week at its Cloud Next conference, which kicks off in San Francisco today, and many are focused on the company’s democratization of machine learning tools. Starting today, Google’s AutoML Vision tool will now be available in public beta after an alpha period that started back in January with the launch of its Cloud AutoML initiative, the company announced during its keynote.
Cloud AutoML is basically a way to allow non-experts — those without machine learning expertise or even coding fluency — to train their own self-learning models, all using tools that exist as part of Google’s cloud computing offering. The first of these tools was AutoML Vision, which lets you create a machine learning model for image and object recognition. Google makes these tools legible to those outside the software engineering and AI fields by using a simple graphical interface and universally understood UI touches like drag and drop.
Of course, you won’t be able to develop sophisticated models and software like Google has without the proper expertise, resources, and sizable data sets. But the company is making it easier to start basic training of custom models with these new domains.
Already, Google says publishing giant Hearst is using AutoML Natural Language to help tag and organize content across its many magazines and the numerous domestic and international versions of those publications. Google also gave AutoML Translation to Japanese publisher Nikkei Group, which publishes and translates articles across a number of languages on a daily basis.
“AI is empowerment, and we want to democratize that power for everyone and every business—from retail to agriculture, education to healthcare,” Fei-Fei Li, the chief scientist of Google AI, said in a statement. “AI is no longer a niche in the tech world —it’s the differentiator for businesses in every industry. And we’re committed to delivering the tools that will revolutionize them.”
Duplex is the project unveiled at Google I/O earlier this year that gives people their own conversational AI assistant to make appointments and complete other mundane tasks by pretending to be a human being over the phone. It got Google into hot water when it was discovered this could be done without the consent of the human service worker on the other end. (Google is actively testing Duplex this summer, but only in very limited use cases like asking about holiday hours and reservations.) A Google spokesperson tellsThe Vergethat while Contact Center AI and Duplex are distinct products, they share some underlying components, but with “distinct technology stacks and aims overall.”
With Contact Center AI, Google is shifting into a territory where callers are more familiar with the notion of interacting with a bot and are doing so of their own volition by contacting customer service proactively. Because of that context, it sounds like this technology will more than likely dominant how call centers operate in the future. Call Center AI first puts a caller into contact with an AI agent, which tries to its solve the problem just like a standard automated customer service bot would, but with much more sophisticated natural language understanding and capabilities. If the caller needs or prefers to talk to a human, the AI shifts to a support role and helps a human call center worker solve the problem by presenting information and solutions relevant to the conversation in real time.
Li says the company is working with its existing Contact Center AI partners to “engage with us around the responsible use of Cloud AI.” She’s talking of course about consent and disclosure, particularly around when someone is talking to an AI and how not to imbue that software with unconscious biases, particularly around race and gender. “We want to make sure we’re using technology in ways employees and users will find fair, empowering, and worthy of their trust,” Li writes.
Update 7/24, 2:54PM ET:Clarified that Contact Center AI and Duplex are distinct products but share similarities and some underlying tech.