As Google releases its new generative AI model called Gemini, Adarsh takes you through everything we know about it so far.


Ever since ChatGPT made its debut, Google has been in a race to catchup. It’s initial response, Bard, was no match in comparison so they had to pool resources to put together an upgrades generative AI model that could take on ChatGPT.

Image Credit: Maria Diaz/ZDNET

To make this happen and power their AI research, the company combined their AI divisions Google Brain and Deepmind. And that is how Gemini was born.

According to an article published by Google to announce the launch, Gemini can generalize and seamlessly understand, operate across and combine different types of information, including text, images, audio, video and code. The model is being promoted as a significant advancement in natural language processing, with Google calling it “our largest science and engineering project ever.”

Available in 3 Models

Google Gemini is available in 3 models:

1. Gemini Ultra

2. Gemini Pro

3. Gemini Nano

Image Credit: Google DeepMind

Ultra is the largest and most powerful of the three and has been designed for highly complex tasks while Pro is more equipped to handle a wide variety of tasks. Nano is for Android users who want to build Gemini-powered apps. For instance, with Gemini Nano, people can now summarize recordings made using the Recorder app on the Pixel 8 Pro phone (but only in English).

In a recent press conference, Sissie Hsiao, vice president of Google’s AI chatbot, Bard, said Gemini Pro outperformed GPT-3.5 in six out of the eight industry benchmarks. Google’s most advanced model, Gemini Ultra, beat the newer GPT-4 in seven of the eight benchmarks.

Image Credit: Google DeepMind

What the Future holds

Google has been really bigging up the launch and has repeatedly hailed Gemini as the most capable and general-purpose AI it has developed so far. They also plan to expand the advanced version of this large language model (LLM) next year. The LLM is multimodal, which means that it can understand different types of information, including text, audio, images, and video.

The LLM runs on Google-made tensor processing units, or TPUs, specialized hardware designed for training AI models. But in the future, Gemini will be trained on both TPUs and graphics processing units (GPUs), said Amin Vahdat, vice president of Google’s Cloud AI, in a briefing. Nvidia makes the H100 GPU, a popular chip for powering generative AI products.

Bard gets an Update

Bard has got a long impending makeover too. It has now been upgraded with Gemini Pro, which gives the chatbot more advanced reasoning and understanding, among other capabilities.

According to Google, Bard will also be integrated with Gemini Ultra in 2024. In the coming months, the company will add Gemini across its other apps, including search, Google Ads, and the Chrome browser.

Gemini: Google’s newest and most capable AI model.

Inspired by AlphaGo

Gemini owes a debt to AlphaGo, which was developed by Google’s DeepMind and became the first computer program to defeat a professional human Go player. AI history was made back in 2016 when AlphaGo beat Lee Sedol, one of the world’s greatest Go players, at his own game.

The techniques used in AlphaGo has been combined with the technology that powers ChatGPT to create Gemini. In an interview in mid-2023, Demis Hassabis, the boss of DeepMind had explained this: “At a high level, you can think of Gemini as combining some of the strengths of AlphaGo-type systems with the amazing language capabilities of the large models.”

The Last Word

Considering the effort that has gone into Gemini and the way Google has been hyping it up, this is their next big bet and now that it has been officially launched, you can expect several additions and upgrades in the months to come.

Have you tried Gemini yet? What about it has impressed you the most? Let us know in the comments section.

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Adarsh hates personal bios, Chelsea football club and Oxford commas. When he's not writing, he's busy playing FIFA on his PlayStation.

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