Google rebrands its AI services as Gemini, launches new app and subscription service.


Alphabet CEO Sundar Pichai speaks about Google DeepMind at a Google I/O event in Mountain View, Calif., Wednesday, May 10, 2023. Google on Thursday, Feb. 7, 2024, introduced a free artificial intelligence app that will implant the technology on smartphones to enable people to quickly connect to a digital brain that can write for them, interpret what they’re reading and seeing in addition to helping manage their lives.

Google on Thursday introduced a free artificial intelligence app that will enable people to rely on technology instead of their own brains to write, interpret what they’re reading and deal with a variety of other task in their lives.

With the advent of the Gemini app, named after an AI project unveiled late last year, Google will cast aside the Bard chatbot that it introduced a year ago in an effort to catch up with ChatGPT, the chatbot unleashed by the Microsoft-backed startup OpenAI in late 2022. Google is immediately releasing a standalone Gemini app for smartphones running on its Android software.

In a few weeks, Google will put Gemini’s features into its existing search app for iPhones, where Apple would prefer people rely on its Siri voice assistant for handling various tasks.

Although the Google voice assistant that has been available for years will stick around, company executives say they expect Gemini to become the main way users apply the technology to help them think, plan and create. It marks Google’s next foray down a new and potentially perilous avenue while remaining focused on its founding goal “to organize the world’s information and make it universally accessible and useful.”

“We think this is one of the most profound ways we are going to advance our mission,” Sissie Hsiao, a Google general manager overseeing Gemini, told reporters ahead of Thursday’s announcement.

The Gemini app initially will be released in the U.S. in English before expanding to the Asia-Pacific region next week, with versions in Japanese and Korean.

Besides the free version of Gemini, Google will be selling an advanced service accessible through the new app for $20 a month. The Mountain View, California, company says it is such a sophisticated form of AI that will it be able to tutor students, provide computer programming tips to engineers, dream up ideas for projects, and then create the content for the suggestions a user likes best.

The Gemini Advanced option, which will be powered by an AI technology dubbed “Ultra 1.0,” will seek to build upon the nearly 100 million worldwide subscribers that Google says it has attracted so far—most of whom pay $2 to $10 per month for additional storage to back up photos, documents and other digital material. The Gemini Advanced subscription will include 2 terabytes of storage that Google currently sells for $10 per month, meaning the company believes the AI technology is worth an additional $10 per month.

Google is offering a free two-month trial of Gemini Advanced to encourage people to try it out.

The rollout of the Gemini apps underscores the building moment to bring more AI to smartphones—devices that accompany people everywhere—as part of a trend Google began last fall when it released its latest Pixel smartphones and Samsung embraced last month with its latest Galaxy smartphones.

It also is likely to escalate the high-stakes AI showdown pitting Google against Microsoft, two of the world’s most powerful companies jockeying to get the upper hand with a technology that could reshape work, entertainment and perhaps humanity itself. The battle already has contributed to a $2 trillion increase in the combined market value of Microsoft and Google’s corporate parent, Alphabet Inc., since the end of 2022.

Google’s DeepMind plans bitcoin-style health record tracking for hospitals


Tech company’s health subsidiary planning digital ledger based on blockchain to let hospitals, the NHS and eventually patients track personal data

 Patients at the A and E department of London’s Royal Free Hospital, which has partnered with Deepmind Health.
Patients at the A&E department of London’s Royal Free Hospital, which has partnered with DeepMind Health. 

Dubbed “Verifiable Data Audit”, the plan is to create a special digital ledger that automatically records every interaction with patient data in a cryptographically verifiable manner. This means any changes to, or access of, the data would be visible.

DeepMind has been working in partnership with London’s Royal Free Hospital to develop kidney monitoring software called Streams and has faced criticism from patient groups for what they claim are overly broad data sharing agreements. Critics fear that the data sharing has the potential to give DeepMind, and thus Google, too much power over the NHS.

Suleyman says that development on the data audit proposal began long before the launch of Streams, when Laurie, the co-creator of the widely-used Apache server software, was hired by DeepMind. “This project has been brewing since before we started DeepMind Health,” he told the Guardian, “but it does add another layer of transparency.

“Our mission is absolutely central, and a core part of that is figuring out how we can do a better job of building trust. Transparency and better control of data is what will build trust in the long term.” Suleyman pointed to a number of efforts DeepMind has already undertaken in an attempt to build that trust, from its founding membership of the industry group Partnership on AI to its creation of a board of independent reviewers for DeepMind Health, but argued the technical methods being proposed by the firm provide the “other half” of the equation.

Nicola Perrin, the head of the Wellcome Trust’s “Understanding Patient Data” taskforce, welcomed the verifiable data audit concept. “There are a lot of calls for a robust audit trail to be able to track exactly what happens to personal data, and particularly to be able to check how data is used once it leaves a hospital or NHS Digital. DeepMind are suggesting using technology to help deliver that audit trail, in a way that should be much more secure than anything we have seen before.”

Perrin said the approach could help address DeepMind’s challenge of winning over the public. “One of the main criticisms about DeepMind’s collaboration with the Royal Free was the difficulty of distinguishing between uses of data for care and for research. This type of approach could help address that challenge, and suggests they are trying to respond to the concerns.

“Technological solutions won’t be the only answer, but I think will form an important part of developing trustworthy systems that give people more confidence about how data is used.”

The systems at work are loosely related to the cryptocurrency bitcoin, and the blockchain technology that underpins it. DeepMind says: “Like blockchain, the ledger will be append-only, so once a record of data use is added, it can’t later be erased. And like blockchain, the ledger will make it possible for third parties to verify that nobody has tampered with any of the entries.”

Laurie downplays the similarities. “I can’t stop people from calling it blockchain related,” he said, but he described blockchains in general as “incredibly wasteful” in the way they go about ensuring data integrity: the technology involves blockchain participants burning astronomical amounts of energy – by some estimates as much as the nation of Cyprus – in an effort to ensure that a decentralised ledger can’t be monopolised by any one group.

DeepMind argues that health data, unlike a cryptocurrency, doesn’t need to be decentralised – Laurie says at most it needs to be “federated” between a small group of healthcare providers and data processors – so the wasteful elements of blockchain technology need not be imported over. Instead, the data audit system uses a mathematical function called a Merkle tree, which allows the entire history of the data to be represented by a relatively small record, yet one which instantly shows any attempt to rewrite history.

Although not technologically complete yet, DeepMind already has high hopes for the proposal, which it would like to see form the basis of a new model for data storage and logging in the NHS overall, and potentially even outside healthcare altogether. Right now, says Suleyman, “It’s really difficult for people to know where data has moved, when, and under which authorised policy. Introducing a light of transparency under this process I think will be very useful to data controllers, so they can verify where their processes have used or moved or accessed data.

“That’s going to add technical proof to the governance transparency that’s already in place. The point is to turn that regulation into a technical proof.”

In the long-run, Suleyman says, the audit system could be expanded so that patients can have direct oversight over how and where their data has been used. But such a system would come a long time in the future, once concerns over how to secure access have been solved.