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Ai Artificial Intelligence Archive

Archives for December 2023

Google launches Gemini, the AI model it hopes will take down GPT-4

Google has been an ‘AI-first company’ for nearly a decade. Now, a year into the AI era brought on by ChatGPT, it’s finally making a big move.

David Pierce
How AI is fooling the photography worldHow AI is fooling the photography world
Play
Richard Lawler
Richard Lawler
OpenAI execs dubbed ChatGPT a “Low key research preview.”

The phrase became an internal joke after ChatGPT’s popularity exploded right out of the gate, according to the NYT’s recap of its launch a year ago and the reaction among Big Tech companies.

Google and Meta scrambled AI teams to launch competing products — even if that meant removing some guardrails — like Bard and LLaMa. And Microsoft’s rush to beat Google had Satya Nadella saying, “We have a big order coming to you, a really big order coming to you,” to Nvidia’s Jensen Huang as he ordered $2 billion in chips.

Alex Heath
Alex Heath
The GPU haves and have-nots.

This chart from Omdia Research estimating Nvidia’s largest customers this year has been making the rounds in my social media feeds.

As I wrote in an earlier issue of Command Line, these H100s are essentially the tech industry’s new gold, since they are the preferred workhorse for powering generative AI. The gap in shipment volume between Meta, Microsoft and everyone else is quite something, and tracks with what I’ve heard from sources in recent months.

A chart showing H100 GPU shipments this year.
Omdia Research
Elizabeth Lopatto
Elizabeth Lopatto
Well, I’m back from my little sabbatical!
Wes Davis
Wes Davis
How many phone charges does an AI-generated image take?

The answer, according to a pre-print study, is about one. Researchers at AI company Hugging Face and Carnegie Mellon University found that general-purpose AI models like GPT-4 are “orders of magnitude” more power-hungry than purpose-made models powering products like Google Translate.

The study, though not yet peer-reviewed, puts into context the environmental cost of generative AI, particularly of inefficient models (one image from the least efficient image-creating model can use as much CO2 as an average gas car driving about 4 miles, for instance).

A chart showing the cost of different generative AI tasks — image generation sits at the high end, generating significantly more CO2 than text classification models.
A comparison of the power consumption required for different generative AI tasks.
Image: Hugging Face / Carnegie Mellon University
A better way to YouTubeA better way to YouTube
David Pierce