Google AI and DeepMind News and Discussions

[Cyber_Rebel]

Introducing Gemini: our largest and most capable AI model


https://deepmind.google/technologies/ge ... troduction

By Demis Hassabis, CEO and Co-Founder of Google DeepMind, on behalf of the Gemini team

AI has been the focus of my life's work, as for many of my research colleagues. Ever since programming AI for computer games as a teenager, and throughout my years as a neuroscience researcher trying to understand the workings of the brain, I’ve always believed that if we could build smarter machines, we could harness them to benefit humanity in incredible ways.

This promise of a world responsibly empowered by AI continues to drive our work at Google DeepMind. For a long time, we’ve wanted to build a new generation of AI models, inspired by the way people understand and interact with the world. AI that feels less like a smart piece of software and more like something useful and intuitive — an expert helper or assistant.

Today, we’re a step closer to this vision as we introduce Gemini, the most capable and general model we’ve ever built.

Gemini is the result of large-scale collaborative efforts by teams across Google, including our colleagues at Google Research. It was built from the ground up to be multimodal, which means it can generalize and seamlessly understand, operate across and combine different types of information including text, code, audio, image and video.

Gemini is also our most flexible model yet — able to efficiently run on everything from data centers to mobile devices. Its state-of-the-art capabilities will significantly enhance the way developers and enterprise customers build and scale with AI.

We’ve optimized Gemini 1.0, our first version, for three different sizes:

Gemini Ultra — our largest and most capable model for highly complex tasks.
Gemini Pro — our best model for scaling across a wide range of tasks.
Gemini Nano — our most efficient model for on-device tasks.

Source: https://blog.google/technology/ai/googl ... undar-note

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Gemini’s multimodal reasoning capabilities

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VideoPoet: A large language model for zero-shot video generation

Website demo: https://sites.research.google/videopoet/
Blog post: https://blog.research.google/2023/12/vi ... -zero.html

A recent wave of video generation models has burst onto the scene, in many cases showcasing stunning picturesque quality. One of the current bottlenecks in video generation is in the ability to produce coherent large motions. In many cases, even the current leading models either generate small motion or, when producing larger motions, exhibit noticeable artifacts.

To explore the application of language models in video generation, we introduce VideoPoet, a large language model (LLM) that is capable of a wide variety of video generation tasks, including text-to-video, image-to-video, video stylization, video inpainting and outpainting, and video-to-audio. One notable observation is that the leading video generation models are almost exclusively diffusion-based (for one example, see Imagen Video). On the other hand, LLMs are widely recognized as the de facto standard due to their exceptional learning capabilities across various modalities, including language, code, and audio (e.g., AudioPaLM). In contrast to alternative models in this space, our approach seamlessly integrates many video generation capabilities within a single LLM, rather than relying on separately trained components that specialize on each task.

[weatheriscool]

Google Reportedly Replacing Select Sales Staff with AI
AI's foreboded replacement of workers appears to have begun in earnest.
By Adrianna Nine December 26, 2023

Few modern technologies have prompted concerns about the job market like artificial intelligence has. Unfortunately for some Google employees, the consequences of AI’s proliferation across nearly every industry have already started to manifest. The tech giant is reportedly replacing some staff with AI amid a “reorganization” of its ad sales unit.

Sources who spoke with The Information say Google is increasingly leveraging machine learning to generate marketing ideas and copy for advertisers. Tools like these have been available to search engine and YouTube advertisers for years and are “on pace to generate tens of billions of dollars annually in revenue for the company,” according to one anonymous source in particular. Not only are AI ad tools highly lucrative, but because they require very little overhead, their profit margins are larger than those found in other Google units.

But apparently that isn’t enough for Google. While the company’s AI ad generators are relatively hands-off, Google has historically paid about 13,500 human staff to keep an eye on the tools’ outputs and create some ads from scratch. Those staff have been made redundant as Google’s algorithms—like the “new era of AI-powered ads” it announced in May—have gotten better at automating their roles. Now, according to the report, Google plans to “consolidate staff, including through possible layoffs, by reassigning employees at its large customer sales unit who oversee relationships with major advertisers.”

https://www.extremetech.com/internet/go ... ff-with-ai

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[wjfox]

Google DeepMind Scientists in Talks to Leave and Form AI Startup

19 January 2024 at 17:34 GMT

A pair of scientists at Google DeepMind, the Alphabet Inc. artificial intelligence division, have been talking with investors about forming an AI startup in Paris, according to people familiar with the conversations.

The team has held discussions with potential investors about a financing round that may exceed €200 million ($220 million) — a large sum, even for the buzzy field of AI, the people said. Laurent Sifre, who has been working as a scientist at DeepMind, is in talks to form the company, known at the moment as Holistic, with fellow DeepMind scientist Karl Tuyls, said the people, asking not to be identified discussing private information. They said the venture may be focused on building a new AI model.

https://www.bloomberg.com/news/articles ... eddit_wall

[wjfox]

Google releases new Bard Gemini model that is on par with GPT-4 in human evaluation

Jan 27, 2024

Update from January 27, 2024:

Oriol Vinyals, head of deep learning at Google and co-lead of Gemini, points out that evaluating language models is "hard and nuanced," with academic evaluations leaking into the training datasets of AI models.

Vinyals calls human evaluation "far superior," and says it "feels good that Bard Gemini Pro (free tier) climbed quite high on lmsys," suggesting that Gemini Ultra may perform even better.

Original article dated January 26, 2024:

Google's Bard chatbot is powered by a new Gemini model. Early users rate it as similar to GPT-4.

Google's head of AI, Jeff Dean, announced the new Gemini model on X. It is a model from the Gemini Pro family with the suffix "scale".

https://the-decoder.com/google-releases ... valuation/

[wjfox]

Our next-generation model: Gemini 1.5

Feb 15, 2024

Last week, we rolled out our most capable model, Gemini 1.0 Ultra, and took a significant step forward in making Google products more helpful, starting with Gemini Advanced. Today, developers and Cloud customers can begin building with 1.0 Ultra too — with our Gemini API in AI Studio and in Vertex AI.

Our teams continue pushing the frontiers of our latest models with safety at the core. They are making rapid progress. In fact, we’re ready to introduce the next generation: Gemini 1.5. It shows dramatic improvements across a number of dimensions and 1.5 Pro achieves comparable quality to 1.0 Ultra, while using less compute.

This new generation also delivers a breakthrough in long-context understanding. We’ve been able to significantly increase the amount of information our models can process — running up to 1 million tokens consistently, achieving the longest context window of any large-scale foundation model yet.

Longer context windows show us the promise of what is possible. They will enable entirely new capabilities and help developers build much more useful models and applications. We’re excited to offer a limited preview of this experimental feature to developers and enterprise customers. Demis shares more on capabilities, safety and availability below.

https://blog.google/technology/ai/googl ... uary-2024/