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HomeAI News & UpdatesGemini 1.5, Google’s Next Gen-AI Model Is Almost Ready

Gemini 1.5, Google’s Next Gen-AI Model Is Almost Ready

Just two months after releasing Gemini, Google is already introducing its successor, a massive language model that the business is hoping would propel it to the forefront of artificial intelligence. Today, Google released Gemini 1.5 to developers and corporate users in preparation for its upcoming full consumer deployment. The company is putting a lot of effort into promoting Gemini as a personal assistant, business tool, and everything in between.

Gemini 1.5 Has Several Enhancements:

Besides being quicker and better, the upcoming Google model also has one impressive new trick up its sleeve. With an 87% improvement over Gemini 1.0 Pro in benchmark testing, Google’s general-purpose model, Gemini 1.5 Pro, appears to be on level with the advanced Gemini Ultra, which the firm only recently announced. Instead of running the entire model every time you submit a query, it executes only a subset of it, thanks to an increasingly popular method called “Mixture of Experts” (MoE). Taking that route should improve the model’s performance for both you and Google.

The whole organization, led by CEO Sundar Pichai, is quite thrilled about one new feature in Gemini 1.5: Thanks to its massive context window, Gemini 1.5 can process significantly bigger searches and display an infinite amount of data all at once. In comparison to OpenAI’s GPT-4 (128,000 tokens) and the existing Gemini Pro (32,000 tokens), that window is an enormous 1 million tokens. Tokens are a complex measure, so Pichai simplifies them.

“It’s about 10 or 11 hours of video, tens of thousands of lines of code.” You may ask the AI bot a question about all of that stuff simultaneously using the context window.

During his explanation, Pichai casually mentions that the full Lord of the Rings trilogy may be accommodated inside that context span. On inquiring, “Hasn’t this already happened?” since it seems too particular. Someone at Google is attempting to decipher the complicated history of Middle-earth, see if AI can interpret Tom Bombadil, and see if Gemini detects any continuity flaws. Pichai chuckles and says, “I’m sure it has happened or will happen — one of the two.”

Career Story of Sundar Pichai

Pichai agrees that companies will benefit greatly from the bigger context window. He explains that this opens up possibilities for situations where users might provide extensive personal details right as they inquire. “Think of it as we have dramatically expanded the query window.” He thinks that firms might use Gemini to sift through mountains of financial details and that filmmakers could submit their full films to see what critics think. It is one of the major achievements that we have accomplished, he says.

Only developers and corporate users with Google Vertex AI or AI Studio accounts will have access to Gemini 1.5. When it’s ready, it will supersede Gemini 1.0, and the regular, public version of Gemini Pro, accessible through and the company’s applications, will be 1.5 Pro featuring a 128,000-token context window. Getting to the million will cost you more. With the recently expanded context window, in particular, Google is evaluating the model’s security and ethical limits.

Google is now racing to create the finest artificial intelligence tool, while companies worldwide are trying to determine their own AI policy and decide between OpenAI, Google, and others when signing developer agreements. This week, OpenAI hinted about “memory” for ChatGPT, suggesting it is getting ready to go into online search. Although there is still more to accomplish on all fronts, Gemini appears to be outstanding thus far, particularly for individuals already involved in Google’s ecosystem.

Google introduces Gemini 1.5 AI model - a huge contextual window capable of processing several hours of video, but not for everyone

In the end, customers will care less about company disputes and all these 1.0s, 1.5s, Pros, and Ultras, according to Pichai. “People will just be consuming the experiences,” he argues. “It’s like using a smartphone without always paying attention to the processor underneath.” But for now, he argues, everyone needs to know the exact model of their phone’s processor. “The underlying technology is evolving so rapidly,” he explains and “People do care.”

Editorial Staff
Editorial Staff
Editorial Staff at AI Surge is a dedicated team of experts led by Paul Robins, boasting a combined experience of over 7 years in Computer Science, AI, emerging technologies, and online publishing. Our commitment is to bring you authoritative insights into the forefront of artificial intelligence.


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