Google expects more advanced AI models to arrive on phones in 2025

Google is bullish on the prospect of its more advanced artificial intelligence models coming to smartphones in the next year.  

The internet giant expects that its currently available Gemini large language model (LLM), which competes with Microsoft-backed OpenAI’s most powerful GPT-4 AI model, will begin to get embedded into devices starting next year.  

Google already offers Gemini Nano, which is the company’s most efficient model for “on-device” AI, across its Pixel devices and on all other capable Android devices. 

Brian Rakowski, vice president of product management for Google’s Pixel unit, said that he expects the company’s most advanced large language models, which are currently only accessible via remote data centers via an internet connection, to begin arriving on smartphones directly next year. 

“There are smaller versions of our Gemini model on the cloud,” Rakowski told CNBC. “There’s been quite a few breakthroughs to compress these models to get them to run on device.” 

“Some have already been proven and some are being explored for some applications. It’d be great having all models on device. It still has wondrous applications.” 

“Gemini Nano is performing at a level that our online models were at less than one year ago,” Rakowski added. “You can do a lot with these distilled small versions of the models on device.” 

“If you just follow that trajectory, some of that stuff we thought we would have had to go to the cloud for next year will be on device, which is pretty exciting, which is instantaneous without requiring a connection or subscription.” 

Large language models, or LLMs, are AI models capable of understanding and generating language in a humanlike way. Gemini Ultra is Google’s top LLM, clocking in at a whopping 1.56 trillion parameters. For comparison, OpenAI’s GPT-4 consists of 1.76 trillion parameters. 

Smartphone makers have been dreaming of a “supercycle” in their industry, driven by artificial intelligence, after a bruising few years that saw device sales slow aggressively. In 2023, smartphone sales fell to 1.16 billion units, the lowest point for unit shipments in a decade.  

Analysts say a supercycle is unlikely to occur within the next few years as there’s not enough going on in the market in terms of novel features and innovation that will convince people holding their aging smartphones to upgrade. 

“Unfortunately, we don’t expect that boom,” Francisco Jeronimo, vice president of data and analytics at research firm IDC, told CNBC. 

“The last supercycle we saw was between 2010 and 2015, where in five years the market grew five times from around 300 million smartphones per year to 1.5 billion.” 

Nonetheless, more and more smartphone makers are making big investments in AI in the hope that it will drive some more excitement around mobile technology. 

The likes of Humane, Rabbit, and China’s Meizu are betting on a future for smartphones that doesn’t even look like a traditional smartphone. These are devices that would be smaller and more compact, and that we could interact with via voice activation, like an Amazon Echo speaker but on the go. 

Google has been making huge bets on AI in an effort to gain an edge over its rivals like OpenAI, the Microsoft-backed company behind ChatGPT.

Google recently announced a major rebrand of Bard, its ChatGPT alternative, including a fresh app and subscription options. Bard was renamed Gemini, the same name as the suite of AI models that power the chatbot.

Android users can download a dedicated Android app for Gemini, while iPhone users can use Gemini in the Google app on iOS.

Alphabet CEO Sundar Pichai highlighted the firm’s commitment to AI during the company’s Jan. 30 earnings call. Pichai said he eventually wants to offer an AI agent that can complete more and more tasks on a user’s behalf, including within Google Search, although he said there is “a lot of execution ahead.”

Likewise, chief executives at tech giants from Microsoft to Amazon have underlined their commitment to building AI agents as productivity tools.