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AI & Machine Learning

Empowering teams to unlock the value of AI

September 1, 2020
Andrew Moore

Vice President & General Manager: Cloud AI & Industry Solutions

As we kick off Cloud AI week at Google Cloud Next: OnAir, you will hear from customers at all stages of the AI journey who are using our tools and solutions to fundamentally change how their businesses are run.

From Etsy, which exemplifies the new era of scaling a business, to deluged government agencies like the Illinois Department of Employment Security to HSBC, one of the largest banks in the world—organizations in every industry are using our Cloud AI services to solve problems and innovate. 

Here are some of the new capabilities in our Cloud AI portfolio driving customer success.

Tools for everyone on your team

We have made it easier for your entire team—from developers, to data scientists and ML engineers—to apply AI to your business.

Even for the ML experts, the long-term success of ML projects hinges on making the jump from science project and analysis to repeatable, scalable operations. Often, analyst teams will hack together an activation process that can be extremely manual and error-prone with too many parameters, decoupled workflow dependencies, and security vulnerabilities. In fact, an entire discipline called MLOps has emerged to solve this issue by operationalizing machine learning workflows.

To improve the MLOps experience, we’re pre-announcing: Prediction backend GA, Managed Pipelines, Metadata, Experiments, and Model Evaluation. These features—part of AI Platform—provide automation and monitoring at all steps of ML system construction, including integration, testing, releasing, deployment and infrastructure management. Read more about MLOps in Key requirements for an MLOps foundation.

One company that has been pulling all of this together using AI to build a more curated shopping experience for their customers is Etsy. Their marketplace includes more than 65 million seller-generated listings. They're using AI to build sophisticated workflows to help buyers find exactly what they’re searching for, and to deliver enriched recommendations that better reflect their buyers’ unique styles and tastes.

“The sky’s the limit when it comes to our ability to innovate and improve our marketplace, as we leverage the strength and efficiencies we’ve gained through our partnership with Google Cloud,” said Mike Fisher, CTO, Etsy. 

More improvements for MLOps practitioners include: Vizier, now in beta, which auto tunes the hyperparameters of your model to get the best output and AI Platform Notebooks service is now GA.

We are working hard to bring ML tools and frameworks to citizen data scientists and the talent you have today, to accelerate your time to see results. Cloud AI Building Blocks provide access to commonly used models (for vision, translation, speech etc) via APIs. And by the end of September, AI Platform will include AutoML as an integrated function in the workflow. This combines the best of no-code and code-based options to build custom ML models faster and with high quality.

We’re also focused on building industry-specific solutions for application developers that are easy to integrate into existing workflows through partners and are supported with SLAs. The latest of these includes Dialogflow CX, our virtual agent, and Document AI Procure-to-Pay, now in beta (more on both below). 

For many customers, an all-in approach to using cloud services is not an option, which is why we’re extending our AI capabilities to run on-prem. Last week we announced Speech-to-Text On-Prem, the first of our hybrid AI offerings, now generally available. 

Improved experience for your customers

Our expertise and leadership in AI is one of the reasons many organizations choose Google Cloud. We are steadily transfering advancements from Google AI research into cloud solutions that help you create better experiences for your customers. 

An area that best demonstrates this path from Google AI research to cloud solution to customer success is the work we are doing to advance contact centers. Contact Center AI (CCAI) helps speed-up customer requests using virtual agents, helps assist live agents, and offers insights on all your contact center data to improve your customer interactions. 

Telecommunications leader, Verizon, chose CCAI to create intuitive, consistent customer experiences across all its channels. 

“A platform that can handle our scale was critical—in all these areas we saw Google Cloud CCAI excel,” said Shankar Arumugavelu, SVP & CIO at Verizon. 

We’re continuing to invest in CCAI, and today we’re launching more intuitive conversations with Dialogflow CX. This new version of Dialogflow, which is quickly becoming the industry standard for virtual agents, is ideal for companies with large contact centers. It’s designed to support complex (multi-turn) conversations and is truly omnichannel - you build it once and deploy it everywhere - both in your contact center and digital channels. 

"Dialogflow CX brings conversation state management to a whole new level,” said Lukasz Rewerenda, Principal Solutions Architect, Randstad (Netherlands). 

Further improvements to CCAI include: Agent Assist for Chat, a new module for Agent Assist that provides agents with continuous support over “chat” in addition to voice calls, by identifying intent and providing real-time, step-by-step assistance. Read more about the latest updates to CCAI in: Conversational AI drives better customer experiences.

Providing the most value with Deployed AI

Deployed AI is about bridging the expertise gap, which is why we’re investing in a technology stack that takes the risk out of an AI strategy—sparing you the complexity of implementation. We are focused on building functional solutions like Contact Center AI as well as industry-specific solutions like Lending DocAI, now in alpha.

Lending DocAI is a new, specialized solution powered by Document AI for the mortgage industry, that processes borrowers’ income and asset documents to speed-up loan applications—a notoriously slow and complex process. It automates many of the routine document reviews so mortgage borrowers can focus on the more important decisions. Mortgage service provider, Mr Cooper, is a Document AI customer: 

“Google Cloud’s Document AI and our custom solutions help us make better decisions across our massive library of mortgage and real estate documents. We've trained over 130 critical mortgage document labels and are seeing good results on our journey so far,” said Madhavi Vellore, VP Product Management, Mr. Cooper.

Similarly, Procure-to-Pay DocAI, now in beta, helps companies automate one of their highest volume, and highest value business processes -- the procurement cycle. We provide a group of AI-powered parsers - starting with Invoices and Receipts - that take documents in a variety of formats and return cleanly structured data. We’re working closely with customers and partners such as Workday - to address their procure-to-pay cycle.

One of the advantages of Google Cloud’s industry-specific solutions is you get great business results from AI without having to hire an army of AI experts to get there.

Another example of industry-specific capabilities you can integrate into your workflows is the Media Translation API, which provides real-time speech translation from streaming audio data. Chinese smartphone manufacturer OnePlus is using the API in its video chat app across countries, time zones and even languages:

“With Google Cloud’s Media Translation API, we are now able to provide real-time streaming translation for video chat with a simple API integration and ensure our customers feel effortlessly connected with minimal latency,” said Gary Chen, Head of Software Product at OnePlus.

In July, we announced the public beta of Recommendations AI, and we have a deep roadmap of these industry-specific solutions coming soon, including Retail forecasting, Anti-money laundering, Know your customer, Healthcare NLP, Media asset management, Industrial adaptive controls, and Visual inspection.

And there’s more to come

Whether you have a team of ML engineers and data scientists looking for tools and frameworks to operationalize and scale their work, or you want to integrate an AI-powered industry or functional solution to solve a particular business problem, or, you want to apply AI to better serve your customers, we have the breadth and depth in AI and machine learning to fit your needs.

For more info, join us at Google Cloud Next OnAir for Cloud AI week, when Principal Software Engineer Ting Lu and VP of Product Management Rajen Sheth take to the stage to talk about generating value with Cloud AI. All the content is available today!

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