Google Gemini is now one of the most popular AI chatbots and one of the highest-performing chatbots in certain categories.
If you’re curious about Gemini, how it works, and how to use it effectively, you’ve come to the right place. Let’s jump in and go over everything you need to know about Google’s AI platform and how it’s changing all its apps and services.
What is Gemini?
Gemini (originally called Bard) is Google’s entry into the AI industry. Google has long been leveraging AI with DeepMind and Google Research. Now, the company offers Gemini as its “largest and most capable” model.
Gemini gives users direct access to Google’s AI in the form of a chatbot. The Gemini chatbot produces text of all kinds, completing tasks like:
Text generation
Summarization
Translation
Code analysis and code generation
In addition, Gemini can produce images, and you can use it to create videos from inside the Google Vids app.
Like other chatbots, Gemini is a large language model (LLM) trained on large collections of text data. It can communicate with users in human conversations, responding to the finest details of user prompts. That means you can communicate with it by:
Asking questions and receiving answers
Giving it a specific task to complete
Asking it to analyze textual data and find patterns
Gemini was first introduced by Google CEO Sundar Pichai in December of 2023.
Multimodal
All of the initial models and those that came after were natively multimodal. That means that Gemini AI models can simultaneously work with and analyze more forms of content than just text.
Gemini’s training included a wide range of images, audio files, videos, and codebases. Of course, it was also trained on massive quantities of text in many different languages. In terms of coding languages, Gemini models also thoroughly understand Python, C++, Java, and Go.
This multimodal training is one of the most significant aspects of Gemini’s development. Thorough multimodal training sets Gemini apart from other major AI models, including Google’s other AI model. Most of them were initially trained exclusively on text data.
Google Search
The integration of Gemini with Google also extends to the search function for which Google first became famous.
If, for example, you are looking for dinner in a local area, Google may suggest options based on data from your Gmail or Google Maps. Gemini would generate a list of options based on what it understands your preferences to be.
The same process can be applied to more complex searches. For example, Gemini can generate travel plans, including flight tickets, tours, and hotels.
Gemini’s Other Uses
Image credit: Google Workspace
As the grand result of Google’s hard work on AI, they naturally have many plans for Gemini. We’ve gone over the basics of what Gemini is and how it works, including some of its most prominent and unique features. But there are also other applications enabled by Gemini’s AI models:
Gemini Live: Live detailed voice chats
Imagen 3: High-resolution AI image generation
Vids Extension: The AI feature in Google Vids
How Does Gemini Work?
Gemini is a large language model (LLM) that was developed to process human language. It uses neural network techniques to process the information you give it. When you type something in the Gemini chat bar, it uses transformer model-based neural networks to respond with outputs that answer the given query.
Gemini’s ability to perform these AI chatbot tasks has changed over time. Like other AI chatbots, it offers a few models with different speeds, complexities, and levels of factual accuracy. Let’s start at the beginning.
Gemini 1.0
In 2023, Google introduced the first version of its chatbot with three different sizes:
Gemini Nano is the streamlined option. It is an efficient AI model meant for fast performance on smaller devices. It can complete many simple tasks very efficiently.
Gemini Pro was built for medium complexity. It was created with scaling in mind and can perform a wide range of tasks.
Gemini Ultra is the largest, most capable model. It was created for highly complex tasks that require more memory and better processing.
Early on, Gemini Ultra produced extremely promising results against Open AI’s GPT-4 in several benchmarks. Most significantly, it performed better than GPT-4 on the multi-disciplinary MMLU benchmark. According to Google, it was the first model to outperform human experts in their respective disciplines.
Image credit: Google Blog; Sundar Pichai & Demis Hassabis
Gemini 1.5 Flash
Gemini 1.5 Flash is an even sleeker model built for cost-efficiency and speed. The idea was to offer quality that could almost match the larger Gemini models but at a much smaller cost. While it’s not a great option for the most complex tasks at scale, it’s a good compromise for many casual or business use cases.
At the release of Gemini 1.5 Flash, DeepMind could boost first-token latency at less than a second. But this did not sacrifice much quality. According to DeepMind, a Flash model has a one-million token context window. That adds up to the equivalent of 700,000 words or 11 hours of audio.
Compared with Gemini Ultra, however, Gemini 1.5 Flash (models 1.5 Flash and 1.5 Flash-8B) performs at a much lower level on the major benchmarks. According to the data released by DeepMind in September 2024, 1.5 Flash scored 67.3% on the MMLU-Pro benchmark.
Gemini 1.5 Advanced
Right now, free users who go to gemini.google.com have two choices:
Gemini 1.5 Flash (free)
Gemini 1.5 Advanced
You can upgrade to Gemini Advanced for a monthly subscription (the rate varies by country), although you can also gain access to Gemini Advanced through Google One with the AI Premium plan. The advanced version comes with a larger context window and can perform more complex tasks. When you look at the actual outcomes, the main things you’ll notice are:
Better logical reasoning
More advanced coding
Better understanding of nuances in language
More creative responses
However, one of the more unique aspects of this paid subscription is the integration with regular Google services.
Gemini Advanced isn’t just working as its own standalone application. The recent AI models are slowly seeping into a lot of Google applications. Gemini can be used inside the most popular Google services, including Gmail and Google Docs. For example, you can now use Gemini in Gmail on your smartphone. You just need to search for it on the tab at the top right of the screen.
Is Gemini Safe?
Gemini is generally safe to use so long as you:
Follow the terms of service that you have to agree with before using Gemini
Follow your local laws
Make sure you review the details and remember the basic implications of creating and submitting any AI-generated content as your own.
You Are Responsible for Your Content
Remember that if you misuse Gemini, whether intentionally or not, you are responsible for the consequences.
Gemini has many built-in safeguards against harmful and inflammatory material. It also tends to lean towards factual accuracy. However, Gemini’s own disclaimers indemnify them from responsibility for the content that the tool generates under your instructions. You are responsible for your use of any content generated with Gemini. The terms of service state that Google doesn’t claim ownership over original content.
Also, all Gemini AI terms pages contain the same disclaimer that their service may generate content that is inaccurate or offensive. They disallow any such content that goes against their company views, meaning you must use your own discretion when using AI-generated content.
The guidelines are similar to all the other noteworthy AI chatbots. It’s always up to you to scrutinize anything an AI model produces for you before using it. This is especially important for academic or for-profit purposes.
Privacy
Privacy is a more controversial topic with AI chatbots. With Gemini, Google does use your data to offer enhanced service within your Google account. Specifically, Google collects data from:
Your conversations
How your conversations relate to product usage
Your location
Feedback you provide
How all of this is used is laid out under Google’s Privacy Policies.
In some cases, Google employees may read user conversations for research purposes. However, Google claims that your conversations are disconnected from Gemini apps before the reviewers access them.
In its privacy policy, Google makes it clear that you should not include any information in your conversations that you wouldn’t want reviewers to see.
When it comes to third parties, Google’s policy is that they will not share your data. The only major exception is if you use Gemini apps to interact with any third-party services. In those cases, the third parties can use your data according to their own privacy policies, and it’s out of Google’s hands.
At the moment, Google states that they do not take Gemini user data for advertising purposes. However, they do use that data for training purposes, meaning your data may be used for changes to their models.
Crucially, you can also opt out of having your data used at some point in the future by deleting it.
If you’re worried about malicious actors getting ahold of your data, it’s worth noting that Gemini’s security is very strong. That should be the case because Gemini also offers security services of its own, including:
Threat intelligence (insights and summaries)
Code insights
Automation of repetitive cybersecurity tasks
AI interactions with security events
Investigation assistance
Basically, Gemini AI offers a “cybersecurity assistant” that speeds up threat detection and analysis while catching things that would otherwise be missed. These capabilities come from:
Training on security databases
Multi-step reasoning
Is Gemini Factually Accurate?
One of the most controversial topics for any AI chatbot is factual accuracy. Depending on who you ask, you will get a different answer. That’s because whether or not Gemini will give you factual information depends on:
Your prompting
The amount of information available that Gemini was trained on
The level of controversy surrounding that particular topic
At the anecdotal level, Gemini can be very accurate or very inaccurate. The data that does exist paints a more nuanced picture. Gemini outperforms other AI chatbots in some topics, while lagging behind in others.
Of all the Gemini models, only Gemini Ultra consistently stands ahead in terms of accuracy. Gemini Ultra leads the MMLU benchmark for general knowledge in 57 different subjects.
While Gemini performs well in terms of knowledge, it doesn’t score as highly in all categories. For math word problem solving (MATH benchmark), it comes in 39th place at 53.2% accuracy. For code generation (HumanEval benchmark), it performs quite well at 21st place with 74.4% accuracy.
Overall, Gemini Ultra consistently provides a high degree of accuracy with textual information. It’s a great tool that, like other AI chatbots, can and does make mistakes. So, as you should with any AI chatbot, you should fact-check any significant information it gives you.
Early Controversies
Gemini does not have a perfect record of keeping its content accurate, relevant, and inoffensive. In February 2024, the Senior Vice President Prabhakar Raghavan released an apology regarding the Gemini Image Generator.
Admitting to errors that produced “inaccurate” or “offensive” results, Raghavan paused some aspects of the service while promising to improve the accuracy resulting from image prompts.
Gemini has not been immune to biases that could result from training data and the controls built into its services. Issues like the image generator controversy stem from internal mistakes. However, when it comes to the question of massive quantities of training data pulled from so many sources, there are other potential problems.
The Issues with Public Data AI Training
Training AI models with public data can lead to many questionable outcomes. In some cases, AI models are trained on data pulled from sources without the owner’s consent. This isn’t always the case, as AI training is conducted with a mix of public domain, free-use content, and copyright-protected content.
Most of the time, the legality and ethics involved are not clear. If you prompt a chatbot, including Gemini, to create content that you want to use academically or for profit, you may even be accidentally misusing intellectual property. It’s a simple issue of training material not being adequately compartmentalized. If you’re not careful, you can end up plagiarizing someone’s work.
For their part, AI chatbots all contain disclaimers and indemnification policies meant in part to protect users. But these policies mainly serve to protect them. You cannot blame the chatbot if you misuse it and get in trouble with your school, employer, or local law enforcement. The issues the parent companies face commonly stem from being accused of intellectual property theft in the course of AI model training.
Remember, chatbots like Gemini are a very young but impactful phenomenon. That’s why even Gemini’s chatbot page includes caution against accepting information as factual without checking with reputable sources of information.
How to Detect Gemini-Produced Content
Gemini-produced content is increasingly easy to detect. There are a few giveaways that the naked human eye can learn how to detect. Excessively colorful language, fluff, and repetition in long-form content are clear giveaways. However, for many people, it can, in fact, be difficult to differentiate between AI and human writing.
AI content generators are the other option for detecting AI-produced content. Even with directions to “write like a normal human,” AI chatbots still retain detectable signs of AI authorship.
If you want to know if the writing you’re looking at was generated with AI, just:
Copy the text
Paste the text in an AI detector like AI Detector
Click “Detect Text” or “Upload File”
Wait for the detector to analyze the text
Review the results and see how much of the text was likely generated with AI
How to Use Gemini
Anyone with a Google account can start using Gemini. All you need to do is go to the Gemini AI website or install one of the mobile apps. Once you’ve successfully logged in, you can provide it with any kind of instructions, so long as it doesn’t violate their terms and automatically get blocked.
The real question is how you can use Gemini properly. While it can provide a high degree of accuracy and has strong safeguards, there’s always a possibility that the result of your input will be incorrect or inflammatory. It’s up to you to scrutinize those results and decide what to do about it.
Using Gemini as a writing assistant is a practical way to use it that minimizes risk. You can use it as an assistant as you browse Google thanks to the extension. With a paid subscription, you can benefit from its features as you use your regular Google services like Gmail.
A Last Word on Gemini
Gemini is a comprehensive AI chatbot, but also an accessory to all the Google services people use daily. This makes it a good tool to learn how to work with if you want some AI enhancement in your work or personal life.
Even as a standalone service, the Gemini AI chatbot performs extremely well with the Gemini Ultra model. It can compete with all the big trailblazers in the AI industry when it comes to the scope of its knowledge and its speed. When used thoughtfully and responsibly, Gemini can be a great tool.
If you’re ever curious whether content was written with Gemini or other AI chatbots, try AI Detector to find out.
