Google is launching what it considers its largest and most capable artificial intelligence model Wednesday as pressure mounts on the company to answer how it’ll monetize AI.
The large language model Gemini will include a suite of three different sizes: Gemini Ultra, its largest, most capable category; Gemini Pro, which scales across a wide range of tasks; and Gemini Nano, which it will use for specific tasks and mobile devices.
With Gemini providing a helping hand, Google promises Bard will become more intuitive and better at tasks that involve planning. On the Pixel 8 Pro, Gemini will be able to quickly summarize recordings made on the device and provide automatic replies on messaging services, starting with WhatsApp, according to Google.
Gemini's biggest advances won't come until early next year when its Ultra model will be used to launch “Bard Advanced," a juiced-up version of the chatbot that initially will only be offered to a test audience.
The AI, at first, will only work in English throughout the world, although Google executives assured reporters during a briefing that the technology will have no problem eventually diversifying into other languages.
Google's Gemini launch comes as the AI race between tech giants heats up, with a few incumbents leading the charge.
"The only people who are actually deploying gen AI are startups and the hyperscalers," specifically Microsoft, Google, and Amazon (AMZN), Jefferies analysts wrote.3
Just yesterday, Meta (META) and IBM (IBM) launched the AI Alliance, a coalition to accelerate open innovation in AI of more than 50 organizations working in the AI space that notably lacked some early AI leaders like OpenAI, Google, and Amazon, in what could be a move to counter their influence.
Alexei Efros, a professor at UC Berkeley who specializes in the visual capabilities of AI, says Google’s general approach with Gemini appears promising. “Anything that is using other modalities is certainly a step in the right direction,” he says.
Efros suspects Gemini will still, like GPT-4, show marked limitations in its ability to understand the complexities of the real world. But he and other researchers are unlikely to get to know everything they’d like to about Google’s creation. “That's the problem with all these proprietary models,” Efros says. “We don't really know what's inside.”
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