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You may have noticed that OpenAI, creators of ChaptGPT technology, is going through some turmoil with massive resignations and re-assignations, notably with its CEO Sam Altman leaving for a potential job with Microsoft then returning with an all-new board. It’s wild over there. You may have also noticed that Google has been making great strides in business-and-consumer-facing AI over the past year, with the massive LLM (large language model) PaLM 2 update, releasing Google Bard, and generally solidifying its AI services into cohesive platforms.
Put all that together, and it’s really no surprise Google has taken this opportunity to launch a brand generative (a.k.a., it makes stuff) AI, this one called Google Gemini. It’s new, it’s fun, it’s kinda weird: Here’s what you should know about Google Gemini’s AI.
What is Google Gemini?
Google Gemini is a new suite of generative AI services Google is launching, specifically for businesses interested in expanding their AI services. It’s a family of multimodal AI models (we’ll get more into that below) created by the Google DeepMind project.
Google Gemini is currently very new. Google added an English-tuned version of Gemini Pro to Google Bard in December 2023. Despite the name, Google describes Gemini Pro as the “lite” version of the AI model, although it looks more like the standard version to us. The family also includes Gemini Ultra, the premium AI that Google wants to be the flagship of the suite.
Gemini Nano rounds out the trio. Nano is the mobile-friendly version of the large language model that is launching on the Google Pixel 8 Pro with its December Feature Drop. It allows for on-device processing and will eventually make its way to other Android phones.
Is Google Gemini a chatbot? Can it create content?
Gemini can certainly create content, but Gemini is far more ambitious than a chatbot, and that requires some explanation.
Gemini is technically an LLM or large language model, which means it’s a machine learning framework that’s taught by dumping a bunch of human stuff (online content, generally) in it and helping it make rules to understand that content. Do that enough, and LLMs can process language data enough to put together their own sentences and mimic certain styles as we see ChatGPT and Bard doing — like expert puzzle solvers creating mathematical ways to “solve” human speech. The more they learn, the better they can get at it.
To read the rest of the article: Google Gemini: Everything you need to know about Google’s next-gen multimodal AI
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