Gemini 1.5's Context Length is a Game Changer

Welcome Renaissance Creator,

Every day it comes time for another AI company to change the game, and today those are our friends at Google.

While we have mentioned Gemini in previous editions of this newsletter, today is different because we have actual experiments we can display from people using the product.

The biggest deal here seems to clearly be the larger context length Google allows as input (you can upload larger file sizes for the model to use in its responses).

This simple improvement has let to a world of experimentation and could be a game changer for certain industries.

Let’s dive in.

The One Big Thing

As simple as it sounds, it turns out that increasing the context window of an AI model (increasing the amount of information it can take in and process) does wonders for its overall capabilities and usefulness.

Gemini impressively boasts a context window length of 1 million tokens in production, a massive increase from the 32,000 limit in Gemini 1.0. According to Google, “This means 1.5 Pro can process vast amounts of information in one go — including 1 hour of video, 11 hours of audio, codebases with over 30,000 lines of code or over 700,000 words.”

To this point, Gemini is already doing things that other AI’s have failed to do for many months and years now:

The implications of such a model with a context length of 10 million tokens (their research limit) are profound. This could very reasonably revolutionize the entire research industry.

An astute Redditor pointed out that “Whether Gemini 1.5 can do that isn't even that relevant; what is relevant is that in a not so distant future we will have AI capable of reading every book and research paper ever written, remember everything with perfect recollection and combine the information in new creative ways.”

Now imagine a world where we have Gemini 1.5 and more advanced models running on Groq, providing instant outputs via mixed or virtual reality. This is not a future pipe dream but something we will likely see in the next few months.

I do not think it is outlandish to say that the Gemini 1.5 update is as big of a release as we have had in many months.

While the beta is still closed to researchers and similar power users, there are already prompting guides that will work well for this model. Becoming a Gemini expert and understanding what data, what prompts, and what settings apply for which use cases could lead to a very lucrative career down the line.

Imagine a world where you can start feeding Gemini large datasets and documents from seemingly unrelated fields, and putting the model to work at finding deep connections that would be generally beyond the human capacity to discover.

We are headed toward a whole new world. Some would say a Renaissance.

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