Google Research and Google.ai have been combined, as the firm fights for dominance in AI and machine learning.
Just one day before the opening of Google I/O 2018, Google announced the merging of its research teams under one AI-focused umbrella.
Called Google AI, the new unified team is a combination of Google Research, the company's former research umbrella, and Google.ai, an AI-focused research division announced by Google last year.
"We have increasingly put emphasis on implementing machine learning techniques in nearly everything we do at Google. Our research has been core to the development and integration of these systems into Google products and platforms," Google said. The merger, it added, is to better reflect the AI and machine learning focus its research is centered on.
Google AI will encompass all research being done at Google, so nothing will be lost. As it happens, all of what was happening prior to the team merger was AI focused anyhow.
AI: The future of consumer technology
Google CEO Sundar Pichai has declared more than once that Google is an AI-first company. With Pichai at the helm Google has made huge advancements in AI and machine learning, and its latest move in merging its research teams under an AI umbrella signals a bet on tech's next big move: away from hardware and toward an AI-powered cloud.
It's debatable whether or not total hardware commoditization has occurred, but looking at trends (largely driven by Google) it can be argued that we're definitely moving in that direction.
Products like G Suite, Office 365, and Adobe Document Cloud have rendered the computer one works on irrelevant—simply sign in and you'll find your work waiting for you anywhere.
SEE: IT leader's guide to deep learning (Tech Pro Research)
Chromebooks are another great example of the world of commoditized hardware that Google may believe is the future—They're completely user-agnostic and are designed to be plug-and-play systems that anyone can log into and use immediately.
If hardware becomes irrelevant then user experience has to become the product, and the machine learning models that Google has been perfecting in recent years are designed to that end.
Several decades ago computers entered the business world, and eventually the home as well. They were tools used for particular purposes, relegated to the den or the office, and had no central role in our lives. That era was dominated by Microsoft and was an era in which the capabilities of the software were paramount: The hardware simply existed to help users accomplish tasks.
When computers started becoming integral parts of our lives, design started to matter, and Apple's sleek, easy-to-use, and lifestyle-driven products took over. Hardware became cheaper, better looking, and part of our identities—look at ads for Apple, Samsung, or Google products and it's easy to see that they're selling hardware that complements their buyers.
Technology moves fast, however, and the eclipse of that era is already on the horizon. The cloud is rapidly rendering hardware irrelevant, and Google is perfectly poised to take hold of the baton that Apple is reluctantly near to passing.
If Google's complete investment in AI tells us anything, it's that the products we use—PCs, laptops, smartphones, and wearables alike—will soon be superfluous. They won't need high-powered processors, intense graphics cards, or gigabyte upon gigabyte of RAM to perform complex tasks: It will all be done in the cloud.
The part of computing that people will want in the next era won't be utility or aesthetics. It will be seamless integration into our lives. AI, Google believes, will be the key to delivering that integration. No one else seems to be challenging them yet.
The big takeaways for tech leaders:
- Google has announced the merger of its Google Research and Google.ai teams under a new AI-centered research group called Google AI.
- Google's move indicates its total commitment to AI as the future of computing. It already has a lead, and other companies are going to have to work hard to retain relevance if Google's prediction of the future of tech is accurate. —TechRepublic
- Special report: How to implement AI and machine learning (free PDF) (TechRepublic)
- Google AI can pick out a single speaker in a crowd: Expect to see it in tons of products (ZDNet)
- Machine learning: A cheat sheet (TechRepublic)
- Cloud AutoML: How Google aims to simplify the grunt work behind AI and machine learning models (ZDNet)
- Google uses AI, deep learning to predict cardiovascular risk from retina scans (TechRepublic)