What are the different sizes of Gemini models available?

Gemini comes in various sizes: Pro (largest and most capable), Flash (common in production), Fastlight (smaller, speedy, cost-effective), and Nano (smallest, for on-device use like Pixel phones and Chrome browser).

What is the benefit of Gemini's large context window?

Gemini's large context window (up to 10 million tokens in research) allows it to process vast amounts of information at inference time without extensive fine-tuning or complex databases. This means you can feed it entire documents, codebases, or hours of audio/video for analysis.

How does Gemini handle real-time information or data beyond its training cut-off?

By enabling 'grounding with Google Search' as a tool call within the model, Gemini can access and incorporate real-time information from the web, providing more up-to-date and accurate responses, complete with cited sources.

Can Gemini assist with coding tasks beyond just generation?

Yes, Gemini's 'code execution' feature allows it to write, run, and even fix code if errors are encountered. This iterative debugging capability helps in generating correct and functional code for complex tasks.

What are some advanced applications of Gemini for developers?

Gemini can transcribe audio, assist in creating complex applications like game clones (e.g., Frogger), and powers AI agents like Project Mariner in Chrome. It also shines in image editing, image generation (Imagen), and video generation (Veo).

How does Google support AI startups using Gemini?

Google offers a generous Cloud startup program, providing up to $350,000 in Cloud credits over two years for eligible startups. This includes opportunities for co-marketing and early access to Gemini APIs.

AI Dev 25 | Paige Bailey: A Beginner's Guide to Multimodal AI with Gemini 2 Veo 2 and Imagen 3

DeepLearning.AI

Entertainment5 min read32 min video

Mar 27, 2025|1,457 views|25|2

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Key Moments

TL;DR

Google DeepMind's Paige Bailey introduces Gemini 2.0, Veo 2, and Imagen 3 for multimodal AI development via AI Studio.

Key Insights

Gemini 2.0 is a powerful multimodal AI model capable of understanding and generating text, code, images, and audio.

AI Studio (aistudio.google.com) offers access to Gemini models, API key generation, and experimentation with features like code execution and Google Search grounding.

The Gemini family includes various model sizes (Pro, Flash, Flashlight, Nano) optimized for different use cases, from large-scale to on-device deployment.

Long context windows (up to 10 million tokens in research) reduce the need for fine-tuning and vector databases, allowing direct processing of large datasets.

Features like 'grounding with Google search' and 'code execution' enhance Gemini's ability to access real-time information and self-correct code generation.

Newer capabilities include advanced image editing with Gemini and video generation with Veo 2, with tools like Project Mariner integrating AI into workflows.

INTRODUCTION TO GOOGLE DEEPMIND'S MULTIMODAL AI CAPABILITIES

Paige Bailey from Google DeepMind's newly formed developer relations team introduces the transformative impact of generative AI at Google. She highlights the company's history in building AI models and frameworks, leading up to the latest Gemini models. Gemini 2.0 is presented as a significant advancement, being fundamentally multimodal. It can process various input types like video, images, audio, text, and code, all simultaneously. Crucially, it can also generate multimodal outputs including images and audio, enabling more natural conversational experiences with AI that sound like talking to a friend.

GEMINI 2.0 MODEL FAMILY AND ACCESSIBILITY

The Gemini family offers a range of model sizes to suit diverse needs: Gemini Pro, the largest and most capable; Gemini Flash, commonly used in production and free to try; Gemini Flashlight, a smaller, faster, and cost-effective version; and Gemini Nano, optimized for on-device inference, fitting within Pixel devices and the Chrome browser. All these models are accessible via AI Studio (aistudio.google.com) using a standard Gmail account, making advanced AI capabilities readily available for developers to experiment with and integrate into their projects.

ADVANCED FEATURES AND MULTIMODAL FUNCTIONALITY IN AI STUDIO

AI Studio serves as a central hub for accessing the latest Gemini models and experimenting with their features. Developers can generate API keys, explore multimodal live features, and test capabilities like structured outputs, code execution, and grounding with Google Search. Safety settings can also be adjusted for easier experimentation. The platform provides 'get code' functionality, allowing users to easily translate their UI experiments into usable code snippets for integration into their development environments.

MULTIMODAL UNDERSTANDING: VIDEO ANALYSIS AND DATA PROCESSING

A key demonstration showcases Gemini's video understanding capabilities. By uploading a video of the American Museum of Natural History, the model can generate a table of dinosaurs present, complete with timestamps and interesting facts. This highlights Gemini's ability to process extensive data, such as long videos. The cost-effectiveness of models like Flashlight 8B is emphasized, suggesting that continuous recording and analysis of daily laptop activity could be affordable, making AI integration into everyday workflows increasingly feasible.

ENHANCING AI WITH EXTERNAL KNOWLEDGE AND CODE EXECUTION

Gemini models can be augmented with real-time information through 'grounding with Google search,' enabling them to provide up-to-date responses on topics like new model releases (e.g., Gemma 3). This feature is integrated by adding a simple tool call. Furthermore, 'code execution' allows Gemini to write, run, and recursively fix code. This agent-like capability is demonstrated by asking Gemini to create a cluster plot for the Iris dataset, where it self-corrects errors and generates the final visualization, simplifying complex coding tasks without requiring users to manage their own infrastructure.

GENERATING AND EDITING IMAGES AND VIDEOS

The presentation delves into Gemini's image generation and editing capabilities, integrated with models like Imagen 3. Users can upload an image and request specific edits, such as changing a car's color or transforming it into a convertible. Advanced editing, like placing a mouse on a beach, showcases Gemini's segmentation and manipulation prowess. Additionally, Veo 2 allows for video generation, either from natural language descriptions or a seed image, producing hyper-realistic short clips that can be incorporated into projects, expanding creative possibilities.

INTEGRATION AND PRODUCTIVITY TOOLS WITH GEMINI

Gemini is being embedded into various developer tools and platforms, including Cursor, GitHub Copilot, and Contine.dev, with an extension called R code also supporting Gemini models. AI Studio acts as an initial testing ground before exporting code. Project Mariner is an agent framework that integrates Gemini into Google Chrome, enabling tasks like product searching and browsing websites to find information, such as a specific puppy, with user feedback integrated throughout the process.

EXPERIMENTAL MODELS AND FUTURE DEVELOPMENTS

The 'flash thinking experimental' model offers insights into Gemini's background thought processes for complex tasks, such as creating a Frogger clone, revealing its planning and decision-making stages. The upcoming Google DeepMind co-scientist is highlighted as a tool designed to accelerate scientific research. This framework uses a fleet of Gemini agents to execute research tasks, from ideation and experiment framing to data analysis and result compilation, potentially shaving years off research timelines in fields like biosciences and physical sciences.

RESOURCE AND DEVELOPMENT SUPPORT FOR STARTUPS AND DEVELOPERS

Google offers a generous Cloud startup program providing significant cloud credits for AI startups, along with co-marketing opportunities and early access to Gemini APIs. For developers, AI Studio is the primary resource for hands-on experimentation. The presentation encourages developers to utilize these tools and provide feedback, with Paige Bailey sharing her direct contact information. Resources like a Gemini hackathon guide are also available to support developers in their upcoming projects and competitions.

Mentioned in This Episode

●Products

●Software & Apps

●Companies

●Organizations

●Concepts

●People Referenced

Leveraging Gemini for AI Development

Practical takeaways from this episode

Do This

Utilize AI Studio (aistudio.google.com) to experiment with latest Gemini models.

Enable 'grounding with Google search' for up-to-date information.

Use 'code execution' feature for models to write, run, and fix code.

Consider smaller models like Flash and Flashlight for cost-effectiveness and speed.

Explore Gemini Nano for on-device and browser-based inference.

Leverage multimodal capabilities for understanding and generating images, audio, and video.

Use Project Mariner for AI agents within Chrome to browse and interact with websites.

Explore Imagen 3 for image generation and Veo for video generation.

Integrate Gemini into your workflow via IDEs and extensions like Cursor, GitHub Copilot, and Continue.dev.

Use Gemini to review pull requests and assist with code reviews.

Access Gemini APIs via AI Studio for programmatic use.

Avoid This

Do not assume models have up-to-date information without enabling grounding features.

Do not overlook the cost-effectiveness of smaller Gemini models for production use.

Do not limit yourself to text-based interactions; explore Gemini's multimodal outputs.

Do not build complex agent frameworks from scratch; leverage Google's existing tools and integrations.

Common Questions

Gemini is Google's latest multimodal AI model. It can understand and generate various types of content including text, code, images, audio, and video. It's notable for its ability to process multiple inputs simultaneously and output diverse content formats.

Mentioned in this video

conceptcode execution

A feature within Gemini that allows the model to write, run, and fix code to solve tasks, demonstrated with the Iris dataset.

softwareR code

An extension that allows the use of Gemini models.

softwareContinue.dev

A platform where Gemini models are integrated.

mediaSimCity 2000

A video game compared to the visual style of tiles presented in a Gemini audio transcription example.

softwareVeo

A model that can animate images described in natural language or starting from a seed image, generating short video clips.

legislationGoogle Cloud startup program

A program offering significant cloud credits and co-marketing opportunities for AI startups.

organizationAmerican Museum of Natural History

A museum featured in a video used for a Gemini multimodal demonstration.

softwareProject Mariner

A framework for AI agents that allows running experiments within Google Chrome, leveraging Gemini.

softwareFlash Thinking Experimental

A Gemini model variant capable of handling complex tasks and showing its background thinking process, used for creating a Frogger clone.

softwareImagen 3

Mentioned in the video title and refers to Google's image generation capabilities.

softwareGCS

Google Cloud Storage, a location where enterprise data can be stored for grounding in Vertex AI.

softwareGoogle Code Assist

A platform that has integrated Gemini for code review, functioning as a GitHub action.

toolMCP

productSilicon Valley

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