Gemini organizes the world’s information and makes it universally accessible and useful. Human beings in our society, have five senses, and the world we build, and the media we consume are in those different modalities.
So, google announced the launch of the Gemini era, a first step towards a truly universal AI model.The Gemini approach to multi modality are all the kinds of things you want an artificial intelligence system to be able to do, and the capabilities that Gemini possesses, haven’t existed in computers before.
Traditionally, multi modal models are created by stitching together text-only, vision-only,
and audio-only models in a sub optimal way at a secondary stage. Gemini is multi modal from the ground up,so it can seamlessly have a conversation across modalities and give you the best possible response.
Gemini is the largest and most capable model, it means that Gemini can understand the world around us
in the way that we do and absorb any type of input and output, so not just text like most models, but also code, audio, image, and video.
The amazing thing about Gemini is that it’s so good at so many things. it’s as good as the best expert humans in those areas like understanding the environment, logics, thinking and interpretations.
Gemini is Excellent in Competitive Programming that requires not only coding but Maths and logical reasoning, Alpha Code 2 powered by Gemini is reasonably best in performing competitive programming and is twice sharp in results than Alpha Code 1 and have 85% competition participants.
Gemini generate bespoke user experiences that go beyond chat interfaces.Gemini uses a series of reasoning steps going from broad decisions to increasingly high resolution of reasoning, finally, getting to code and data. it can turn images into codes, like a tree image into an html or java code. It can guess the name of movie. understand environment give suggestions like what type of light a plant needs to grow. also it finds similarities and differences. sense body movement, even one can play rock, paper, scissor with it.
Gemini can search a large corpus of literature for relevant papers and extract key information
from these papers, as well as update figures. Of course, these capabilities can help more than just biologists or even scientists. They extend naturally to any domain that is reliant on large datasets, such as law or finance.
So, that’s what Gemini can make possible, and we are excited to see what anyone will create with Gemini.
Types Of Models:
A family of models are created that can run on everything from mobile devices to data centers, each of which is best in class. Gemini will be available in three sizes. Gemini Ultra, most capable and largest model for highly complex tasks; Gemini Pro, best-performing model for a broad range of tasks; and Gemini Nano, most efficient model for on-device tasks.
As these systems become more capable, all of those capabilities also raise new questions.
We have to think about what it means to have an image, be a part of, for example, the input. Because an image might be innocuous on its own, or text might be innocuous on its own, but the combination could be offensive or hurtful. Safety and responsibility has to be built in from the beginning. And at Google DeepMind, that’s what they have done with Gemini. They develop proactive policies and adapt those to the unique considerations of multimodal capabilities;
Google end up with a world that has more knowledge and that people have more access to information that otherwise would not be available to them.That’s what excites them, the chance to make AI helpful
for everyone, everywhere in the world.