Ashad Rehman
In the platform of Google’s Gemini AI, imagine visiting a shoe store and contemplating the purchase of your favorite pair for mountain hiking. However, uncertainty looms about which one would best suit your requirements.
You pull out your Google Pixel 8 Pro smartphone, open Google Search, and enter your search query, “list down the best brands for mountain hiking shoes” and voila! Your phone gives you an accurate list of information. It’s not something as generic as CHAT GPT’s response explaining to you how it has limited data exposure from 2021. But, it shows you the actual list of shoes that you’re looking for, all thanks to a simple Gemini API key.
Over the past couple of years, numerous organizations, including OpenAI, Microsoft, and Google, have been engaged in fierce competition, constantly unveiling new and potent AI generative models. Stepping into the limelight, Google recently launched Gemini on Wednesday, December 6, 2023. This incredibly powerful AI technology has the capability to extract vast datasets, providing accurate and refined information.
According to top software development companies in USA, Gemini’s Ultra performance on the MMMU benchmark has also outperformed the GPT-4V in the following results Art and Design (74.2), Business (62.7), Health and Medicine (71.3), Humanities and Social Science (78.3), and Technology and Engineering (53.00).
In this article, we are going to explore what Gemini AI is, how to set up the Gemini AI environment & its respective advantages. So without further ado, let’s delve into the details & learn everything about it.
What is Gemini – Google’s Largest Capable AI Model Yet?
Gemini is an artificial intelligence model developed by Google AI, which works as a multimodal generative AI.
As a multimodal model, Gemini excels in understanding and processing information from a diverse array of sources, including text, code, audio, video, and images. Its versatility sets it apart from previous AI models launched by Google, which were constrained by their ability to comprehend only a single type of information at a given instance.
The core concept behind Gemini is to usher in a new era of AI models inspired by the nuanced way people understand and communicate through AI-powered tools. The ultimate goal is to create an expert helper or assistant that surpasses the limitations of its predecessors. In the ever-expanding landscape of AI, Google emerges as a frontrunner with Gemini, offering a solution that stands out amidst the competition.
Here are more details on the workings of Google’s largest and most capable AI model as of yet.
During its launch, Google’s CEO Sundar Pichai heralded Gemini as one of the most advanced AI models developed by the company. The aim was to create a revolutionary AI model which makes groundbreaking discoveries in AI.
As Sundar Pichai puts it,
“We’re taking the next step on our journey (as an AI first company) with Gemini, our most capable and general model yet, with state-of-the-art performance across many leading benchmarks,”
He further added,
“Our first version, Gemini 1.0, is optimized for different sizes: Ultra, Pro, and Nano. These are the first models of the Gemini era and the first realization of the vision we had when we formed Google DeepMind earlier this year.”
Gemini Is Not One Model, Its Many AIs Combined
The only way to create such an elegant model was to combine different AI models to create one efficient multimodal AI. It is capable of combining several machine learning models such as audio processing, coding & programming, large language models, computer vision, and 3D models bringing them all to work in complete synergy. The idea was to create a single AI model that empowers all other AI models enabling developers to create new ones.
Understanding Gemini AI
Google’s DeepMind has been dedicated to pursuing artificial intelligence with the overarching goal of creating a model that delivers collective benefits to humanity.
Today, the Gemini AI has achieved groundbreaking advancements in developing a generative AI model known for its high flexibility and ability to handle a diverse range of information. Its versatility allows the multimodal to function across different systems, from powerful data center servers to mobile devices.
The expansive language model Gemini comprises three distinct variations: Gemini Ultra, positioned as one of the largest and most capable categories; Gemini Pro, which scales up to handle a broad spectrum of tasks; and Gemini Nano, designed for specific tasks and optimized for mobile devices.
Notably, Google’s Gemini Ultra outshines the competition, surpassing even the GPT-4 technology across different criteria. It stands as one of the pioneering models to exceed human experts in multitasking, showcasing problem-solving abilities across 57 subject areas. This significant achievement highlights Gemini Ultra’s superior comprehension and problem-solving capabilities.
Here’s a brief Google Gemini Statistics by AI versions comparison performed by merca20.com to give you a more detailed insight into their respective features.
The Software Architecture of the Gemini AI Model
As far as the software architecture of the Gemini model is concerned. All three Gemini models work on the same software architecture. They are decoder-only transformers with significant modifications to train TPUs.
Each transformer comes with a context length of 32,768 tokens capable of accepting multiple forms of input. Since Gemini is multimodal, it can combine different modes such as text, images, and videos.
Images may appear in different resolutions. Videos can appear in the sequence of images. And Audio samples at 16 kHz. All input data is finally converted into a sequence of tokens under the Universal Speech Model.
How to Setup the Gemini AI Environment for Yourself?
To start using the API, obtain the API key from the Google AI for Developers.
Now click on the “Get an API key” button and it will lead you to Google AI Studio. From here, you can generate your own API key.
To access the Gemini Model, you will need a Google Cloud Account and a Google Cloud Project + billing associated with it. Also, you will need to have some familiarity with the Visual Studio Code.
Start by creating a new Gemini application template in Cloud Code:
You can achieve it by visiting the Google Cloud console and logging in. Now choose “Project” and launch “Cloud Shell” and then head on to the Editor.
Launch the VS Code command palette as shown below:
In the command palette, type in:
Cloud Code: New Application
It will bring up Application Templates. Search up Gemini and select the option.
Here you will find two application templates, available (Node.js and Python). Choose the one as per your preference.
Since we are using Python, we will opt-in for the Gemini API Python, and select the folder path within the environment. The chosen path will download the template and associated files.
The provided file list is presented below, and you should observe a comparable set of files:
To have more in-depth information, you can check the README.md file which will provide you with the necessary instructions.
Since we already have the Gemini API key, we have to follow these steps to run Gemini in the Python application.
Launch a Terminal from the Cloud Shell IDE and follow along (assuming you are in the terminal and the folder in which the main.py and requirements.txt files are present.
To set up the environment variable, head on to the main.py and enter your copied API key.
export GOOGLE_API_KEY="Your Gemini API Key"
The next step is to install Python dependencies.
Just ensure that you install the required package google-generativeai which is available in the requirements.txt file.
pip install -r requirements.txt
Once complete, the next step is to run the application.
python main.py
Just add your default prompt such as;
"Please provide a list of the most influential people in the world."
And it will generate the desired result;
How is the Gemini AI Advantageous?
Numerous small and medium-sized businesses (SMBs) along with enterprises leverage Gemini in impactful ways, particularly in improving customer service through chatbots. Gemini is instrumental in providing product recommendations. Its capabilities extend to identifying emerging trends, enabling advertisers to strategically use information for product promotion.
Remarkably, content developers also utilize Gemini for creating campaigns and blog content. Currently, Google Gemini Pro is integrated with Google’s chatbot Bard which helps it with advanced reasoning, planning, understanding, and other capabilities. In the near future, the tool is expected to launch “Bard Advanced” which will use Gemini Ultra as the biggest update to Bard, a more empowering chatbot mimicking CHATGPT.
Gemini plays an important role in trend identification, facilitating product advertising for companies. Beyond that, it serves as a valuable asset for content development, aiding in the creation of marketing campaigns and blog materials. Developers find Gemini to be a versatile tool for code generation. Its capabilities extend to harvesting data from thousands of pages, transforming this information into visual representations, and even capturing screenshots for a comprehensive understanding.
Today the Gemini Ultra, the first model is outperforming many human experts on MMLU (massive multitask language understanding) where it utilizes 57 subjects like math, physics, law, history, medicine, and ethics for amalgamating both, world knowledge as well as problem-solving capabilities. Its diverse application far outweighs the disadvantages of the previous models.
Will Gemini AI Be Better than ChatGPT?
Gemini AI has definitely taken the lion’s share as it has outperformed almost every academic test such as understanding text, images, videos, and even speech.
In several different topics and subjects such as math, physics, and law. The Gemini AI scored a belligerent 90% overall which is higher than the Chat GPT’s 86.4% which was impressive.
Concluding Paragraph
Gemini AI is taking the Internet world by storm.
It is capable of carrying out conversations the same way a human mind would. It is also equipped with the capability to perform extremely complex problems and provide you with suitable solutions. The Gemini AI can understand & process different information such as code, images, music & text.
There’s much more that one can do with Google’s largest & most capable AI model available.
It is also scalable and can also protect user’s private data. You can customize Gemini as per requirements to meet your desired needs. It can translate language, change writing tone & style, and create content that answers complex questions. It is becoming a norm for the custom app development company to use it for coding.
The possibility of Google’s new AI child Gemini is endless, so feel free to access it at Build with Gemini.
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