What is Google Gemini, how does it work, and how exactly can you access it?
Google Gemini has earned a lot of attention from AI enthusiasts and business leaders since it was officially introduced by the Google team in December 2023. While Gemini isn’t Google’s first foray into the world of artificial intelligence, it does represent a significant shift in the brand’s AI strategy.
Before now, Google was struggling to compete with the likes of Microsoft (with Copilot), and OpenAI (with its GPT models) in the generative AI space. Although it offered companies access to solutions like Google “Duet”, Google’s AI models weren’t nearly as powerful as solutions like OpenAI’s GPT-4. Gemini aims to change all that.
Here’s everything you need to know about Google Gemini.
What is Google Gemini?
Google Gemini is a family of AI models similar to the GPT collection from OpenAI. All of the models included in the Gemini family are “multimodal.” Though they’re described as LLMs (Large Language Models), they don’t just understand and generate text.
These models can also natively understand, interact with, and combine various other information, like audio, images, video, and code. For instance, you can ask Gemini to describe what’s going on in a picture, and it will respond with a complete image description.
Gemini isn’t just the name of Google’s AI model collection, eityher. It’s also the name they’ve applied to their chatbot (previously Bard), and their smart assistant (previously Google Assistant).
We also have various variations of Gemini for existing Google solutions, like Google Workspace. The important thing to remember is that all the versions of Google Gemini we can access today are powered by the same underlying collection of Gemini models.
How Does Google Gemini Work?
So, how do the underlying models powering Google Gemini work? This question is again, a little tricky to answer, because most AI teams are reluctant to share too much information about the innerworkings of their models. After all, they don’t want to share their secrets with the competition.
We do know that the model collection is the result of significant collaborative efforts by teams across the Google landscape, including experts at Google Research. We also know that Gemini models use a transformer architecture (similar to GPT models), and rely on strategies like fine-tuning and pre-training.
Crucially, part of what makes Google Gemini special is that it was built from the ground up for multimodal functionality. Rather than just training their models with huge volumes of text, Google fed their models images, audio, and videos, too.
The tech giant says its multimodal approach means the models can understand interactions with customers in a more intuitive manner. This allows for a wider range of use cases for Gemini. By training the system on all modalities at once, Google says its models can seamlessly understand how different kinds of content and data are connected.
For instance, it can understand charts and the captions alongside them, read text from signs and process images at the same time, and so on. This was pretty impressive when Gemini was introduced in 2023, but it’s worth noting most AI leaders are moving in the same direction.
Claude 3.5 and GPT-4o now feature similar multimodal capabilities.
Notably, though, Google Gemini does have a longer context window than most competitors. Gemini 1.5 Pro, for instance, has a context window of up to 2 million tokens. That means you could upload a large document to Google and ask Gemini about the whole thing at once.
What is Google Gemini? The Model Sizes
Another important thing to note about the family of Gemini AI models is that they come in various sizes. Google wanted to create solutions that could run on any device, from large computer systems and data centers to smaller smartphones.
The current models include:
- Gemini 1.0 Ultra: The largest model offered by Google for more complex tasks. In LLM benchmarking tests, such as Big-Bench Hard, MMLU, and HumanEval it was able to outperform GPT-4. It also outperformed GPT-4v in multimodal benchmarking tests like MathVista, VQAv2, and MMMU. This model powers the Gemini Advanced chatbot, and supports image generation, coding, and text generation.
- Gemini 1.5 Pro: The most accessible version of Gemini, Gemini 1.5 Pro is designed for various tasks. It powers the Workspace Gemini chatbot, and is more effective at handling complex reasoning chains than GPT-3.5. It also has a longer context window (up to 2 million tokens). Plus, it’s being deployed across various Google applications.
- Gemini 1.5 Flash: Google Gemini 1.5 Flash is a cost-efficient, lightweight model intended for high-frequency tasks. It’s similar to Gemini Pro but has a context window of only 1 million tokens and less computing power. It’s also a lot cheaper to run for people with limited bandwidth, creating AI applications.
- Gemini 1.0 Nano: The Nano version of Gemini is designed for smartphones and mobile devices. It’s currently available on the Pixel 8 Pro and powers features like GBoard smart replies. It can also be accessed in apps like WhatsApp.
Performance Benchmarks and Insights
So, exactly how powerful are Google’s models? At this point, it’s difficult to know for certain. However, Google has shared a bunch of technical reports comparing Gemini to other models. We know Ultra was the first model to outperform human experts on MMLU (Massive Multitask Language Understanding) tests, with a score of 90.0%.
It also outperforms various other state-of-the-art generative models on 30 of 32 of the most commonly used academic benchmarks in LLM research and development. Plus, Gemini Ultra earned a score of 59.4% on the MMMU benchmark test for multimodal models.
The tech giant says Gemini can perform more effectively than other AI solutions for a few reasons. First, as mentioned above, it was trained to be multimodal, which means it’s more effective at processing different types of data simultaneously. The multimodal reasoning capabilities of the AI also mean it can extract insights from data with incredible accuracy and speed.
Google’s models also seem to be incredibly good at understanding and generating data. It can create code in various programming languages, like Python, C++ and Java. It even excels in various coding benchmarks, like HumanEval.
Plus, Google says Gemini is more reliable, efficient, and scalable than any other model created. The models were trained using Google’s AI-optimized infrastructure and in-house Tensor Processing Units. They run faster than earlier, smaller models. Additionally, Google notes that the Gemini models were still built with responsibility and safety in mind. It outlines its use of AI principles and safety strategies throughout its products, including the use of adversarial texting techniques.
Google is even using benchmarks like “Real Toxicity Prompts” to minimize content safety programs as the company continues to train its solutions.
Comparing Google Gemini to Other LLMs
Comparing Gemini to other LLMs and AI models is a little tricky, because the models we have are constantly evolving. When Google first launched its models, it did compare Gemini Ultra to GPT-4, and showed us Gemini was better at various tasks. However, OpenAI has now updated the GPT models again. We don’t know how great Gemini is compared to things like GPT-4o.
Ultimately, all of the best models from OpenAI, Google, Anthropic, and other AI leaders can be extremely powerful. The results you get, though, all depend on how you fine-tune and use these models. Additionally, it’s worth noting that while Google Gemini Ultra is the company’s most powerful model, it’s going to be a lot more expensive to run than some alternatives.
Gemini 1.5 Pro, while significantly more powerful than some earlier models used by Google, still falls slightly behind some competitors. For instance, Llama 3, GPT-4o, and Claud 3.5 Sonnet are all a little more effective than Gemini at various tasks.
That being said, Google, just like its competitors, will constantly update and improve these models over time. So, who knows what could lie ahead?
How Google Uses Gemini
Google has integrated Gemini with the majority of its products, from Google Search to Android, YouTube, Chrome, and so on. Alongside building Gemini into those solutions, Google is also implementing the AI models into other areas.
Core Gemini Products
- Google Gemini (the chatbot): Formerly known as Bard, Google Gemini is now the company’s core generative AI chatbot solution. It’s a direct competitor to solutions like ChatGPT.
- Chrome: Gemini in Google’s Chrome browser allows users to write text and ask questions while browsing the web. Google says it can take the webpage you’re on into account to create contextual responses.
- Google One: The Google One AI Premium plan (available for $20 per month) gives you access to advanced Gemini models, as well as Gemini features in Google Docs, Gmail, and various other workplace apps.
- Google Search: Google Search now includes AI overviews – quick answer boxes where you can find responses to some of your more complex queries.
- Code Assist: Previously Duet for Developers, Google’s suite of AI-powered assistance tools, Code Assist, also leverages Gemini.
- Google Workspace: Workspace is now full of Gemini features across various applications, from Docs and Sheets to Google Meet and Gmail. However, you will need a subscription to access Gemini in Workspace.
- Google Astra: Google’s next-level AI assistant, Google Astra (which may appear in some new smart glasses), also features Google Gemini features. This tool will essentially give users a hands-on assistant they can access anywhere.
- Gemini Live: Exclusive to Gemini Advanced subscribers, Gemini Live is available for mobile apps. It lets users have in-depth voice chats with Gemini. Users can even interrupt the bot while it’s speaking to ask clarifying questions.
Elsewhere, you’ll find Gemini in various products, including Google’s database products, cloud security tools, Google Photos, and Google TV, and security products like Threat Intelligence.
What is Google Gemini? Customization Options
Another thing worth noting is that Gemini models are intended to be flexible and customizable. In addition to using the models in its own products, Google allows developers to integrate the models into their own tools, apps, and services.
This is important, considering virtually every company and developer seems to be adding AI to their tools. Most use solutions like OpenAI’s GPTs to do this, but Google wants to offer an alternative with its own APIs. Developers can access both Gemini 1.5 Pro and the Flash version of the model through Gemini APIs in Google Cloud Vertex AI or Google AI Studio.
Plus, at I/O 2024, Google announced that Advanced users can now create “Gems.” These are custom chatbots like the customizable Microsoft Copilots that users can create with Copilot Studio.
Users will be able to generate Gems using natural language descriptions, such as “You are my business mentor; give me a daily productivity plan.” Eventually, those Gems will also be able to leverage integrations with other Google Services, like Google Keep, Tasks, and Calendar.
Getting Started with Google Gemini
Now you have the answer to “What is Google Gemini” the next step is to go and test the functionality for yourself. If you’re a beginner, we’d recommend getting started with the Gemini chatbot. It’s available to access for free on the web, and can give you a good insight into what Gemini can do.
If you want to access Gemini in your everyday Google applications, like Gmail and Meet, you’ll need to pay for an Advanced Gemini plan or a Google One plan to unlock extra features.
Alternatively, if you’re a developer looking to create your own AI app, you can head over to Google AI Studio or Vertex AI.
FAQ
Is Google Gemini free or paid?
The standard version of Google Gemini (the chatbot) is free to use. However, if you want to access the more advanced Gemini models, you’ll need to pay for a subscription to Google’s Advanced AI plans. Gemini Advanced costs users around $19.99 per month.
Is Google Gemini better than ChatGPT?
It all depends on your use cases. ChatGPT offers more customizable options, but Google Gemini’s extensions are extremely useful for accessing AI throughout a range of apps and tools. Gemini and ChatGPT have very similar functionality overall.
Is Google Gemini safe to use?
Google says it adheres to strict privacy standards and security measures to keep its Gemini models safe. Google doesn’t collect information from your private apps or interactions with Gemini to train its models, so your data remains within your control.
