GOOGLE FIGHTS BACK! Every Google I/O AI Announcement (Supercut)

Google's I/O event showcased significant advancements in AI, highlighting Gemini, a multimodal AI model capable of reasoning across various inputs like text, images, and videos. Gemini 1.5 Pro has made strides in long context understanding, enabling it to process up to a million tokens. Google Search has integrated Gemini to revolutionize query answering, with plans to expand this experience globally. Google Photos received an upgrade, allowing users to search through photos more intuitively, and the 'Ask Photos' feature will roll out this summer. The company also introduced a lighter model, Gemini 1.5 Flash, designed for tasks requiring low latency and efficiency. Furthermore, Google DeepMind's Project Astra aims to create a universal AI agent for everyday assistance, with a focus on understanding and responding to complex, dynamic environments. Google also announced Trillium, a new generation of TPUs, and the integration of AI into Android for on-device experiences, emphasizing privacy and speed. The event emphasized Google's commitment to AI-first innovation across its products and services.

Takeaways

• 🚀 Google introduced Gemini, a multimodal AI model capable of reasoning across text, images, video, code, and more, signifying a step towards more versatile AI applications.
• 🔍 Gemini 1.5 Pro enhanced long context capabilities, allowing it to process up to 1 million tokens in production, which is more than any other large-scale Foundation model.
• 🔎 Google Search has integrated Gemini to answer billions of queries, enabling new ways of searching, including complex queries and photo-based searches.
• 📈 User satisfaction and search usage have increased with the testing of Google's new search experience, which will be launched fully in the US and expanded to more countries.
• 📱 Google Photos will feature 'Ask Photos', allowing users to search through photos more efficiently by asking questions, and it will understand context to provide more relevant information.
• 📊 Google is expanding the context window to 2 million tokens, moving closer to the goal of infinite context and allowing for more detailed and comprehensive data processing.
• 🎓 Notebook LM will incorporate Gemini 1.5 Pro, enhancing the tool's capabilities to generate discussions and engage in conversations based on provided materials.
• 🤖 Project Astra by Google Deep Mind aims to create a universal AI agent for everyday life that can understand and respond to the complex and dynamic world like humans do.
• 🏎️ Gemini 1.5 Flash is a lightweight model designed for fast and cost-efficient operations at scale, maintaining multimodal reasoning capabilities suitable for tasks requiring low latency.
• 💻 Google Workspace applications like Gmail, Drive, Docs, and Calendar are being enhanced with Gemini's capabilities to automate tasks and improve information flow between apps.
• 📱 Android will integrate on-device AI with Gemini Nano, providing faster and more private experiences, such as real-time fraud protection without compromising user data.

Q & A

What is Gemini, and how does it differ from other AI models?

Gemini is Google's Frontier Model designed to be natively multimodal, capable of reasoning across text, images, video, code, and more. It differs by being built to handle various types of input and output (I/O), and it has a significant breakthrough in long context, being able to run 1 million tokens in production, which is more than any other large-scale Foundation model.

How has Gemini transformed Google search?

Gemini has been integrated into Google search, enabling it to answer billions of queries through a generative experience. Users can now search in new ways, including longer and more complex queries, and even search with photos to get the best results from the web.

What is the new feature in Google Photos that helps users find their license plate number?

Google Photos now has a feature that allows users to ask for their license plate number if they can't recall it. The system recognizes the cars that appear often, determines which one is the user's, and provides the license plate number.

How does Google Photos help users reminisce about their memories?

Google Photos can search through memories more deeply. For example, users can ask when their child learned to swim, and the system can recognize different contexts like swimming laps in a pool or snorkeling in the ocean, and even text and dates on certificates to provide a summary of the child's swimming progress.

What is the significance of expanding the context window to 2 million tokens in Gemini?

Expanding the context window to 2 million tokens allows Gemini to process even more information, such as hundreds of pages of text, hours of audio, a full hour of video, or entire code repositories. This step brings Gemini closer to its ultimate goal of infinite context, enhancing its ability to understand and respond to complex queries.

How does Notebook LM benefit from Gemini 1.5 Pro?

Notebook LM, a research and writing tool, benefits from Gemini 1.5 Pro by being able to generate lively science discussions based on text material. It can also adapt and allow users to join the conversation and steer it in any direction they want.

What is Google DeepMind's Project Astra, and what is its goal?

Project Astra is an initiative by Google DeepMind to build a universal AI agent that can be truly helpful in everyday life. The goal is to create an agent that understands and responds to the complex and dynamic world just like humans do, with capabilities to take in and remember what it sees to understand context and take action.

What is the new development in Google's AI assistance called Gemini 1.5 Flash?

Gemini 1.5 Flash is a lighter weight model designed to be fast and cost-efficient to serve at scale. It features multimodal reasoning capabilities and is optimized for tasks where low latency and efficiency are most important.

What is the sixth generation of TPUs called, and what is its improvement over the previous generation?

The sixth generation of TPUs is called Trillium. It delivers a 4.7x improvement in compute performance per chip over the previous generation, making it the most efficient and performant TPU to date.

How does Google's new AI organized search results page enhance the user experience?

Google's new AI organized search results page provides a dynamic whole page experience tailored to the user's query. It uncovers interesting angles for the user to explore, organizes results into helpful clusters, and uses contextual factors to offer personalized suggestions, making it easier for users to find inspiration and information.

What is the potential of on-device AI in the Android operating system?

On-device AI in the Android operating system allows for faster and more private experiences. It can unlock new experiences that work as fast as the user does while keeping sensitive data private. With built-in on-device Foundation models like Gemini Nano, Android can understand the world through text, sights, sounds, and spoken language, enhancing features like search and security.

Outlines

00:00

🚀 Introduction to Gemini: Multimodal AI Model

The first paragraph introduces Gemini, a cutting-edge multimodal AI model designed to process various inputs like text, images, videos, and code. It highlights the model's ability to reason across different formats and convert any input into any output. The speaker discusses the significant breakthrough of Gemini 1.5 Pro in handling long contexts, with its capacity to run 1 million tokens in production, surpassing other large-scale models. The paragraph also covers the integration of Gemini in Google search, which has led to a new way of searching with longer and more complex queries, including photo-based searches. The speaker shares excitement about the increased user satisfaction and plans to roll out a revamped AI experience to more countries. An example is given on how Google Photos can identify a user's car and provide the license plate number, showcasing the model's ability to understand context and generate summaries for user queries.

05:01

🔍 Multimodality and Long Context in Action

The second paragraph delves into the capabilities of multimodality and long context in Gemini. It discusses the expansion of the context window to 2 million tokens, marking a step towards the goal of infinite context. The speaker provides a demo of Notebook LM, an AI tool that can generate an audio discussion based on text material. The demo illustrates how Gemini can create age-appropriate examples without prior knowledge of specific subjects, like basketball, to explain concepts of force and motion. The paragraph emphasizes the potential of mixing and matching inputs and outputs and the ongoing work by Google Deep Mind on Project Astra, an AI assistance system aimed at building a universal AI agent for everyday life that can understand and respond to a complex, dynamic world.

10:04

💡 Launch of Gemini 1.5 Flash and TPU Innovations

The third paragraph announces the launch of Gemini 1.5 Flash, a lightweight model optimized for fast and cost-efficient operations at scale while maintaining multimodal reasoning capabilities. It also mentions the use of Gemini 1.5 Pro and Flash with up to 1 million tokens in Google AI Studio and Vertex AI. The speaker reflects on the journey of building AI and the progress made in the past 15 years. Additionally, the paragraph introduces Trillium, the sixth generation of TPU (Tensor Processing Units), which offers a significant improvement in compute performance. It also discusses Google's offerings of CPUs and GPUs, including the new Axion processors and Nvidia's Blackwell GPUs, to support various workloads.

15:05

🔎 Advanced Search Capabilities with Gemini

The fourth paragraph focuses on the enhanced search capabilities made possible with Gemini. It describes how Google Search can provide AI overviews, multi-step reasoning, and customized pages for users' queries. The speaker also mentions the upcoming feature of asking questions with video in Google Search, demonstrated through a live example of troubleshooting a record player. The paragraph highlights the integration of Gemini into workspace apps, like Gmail and Drive, to automate tasks and streamline information flow between apps. It also teases the upcoming release of these features to Labs users and the potential for automation in various use cases.

20:05

🤖 Personalization and Automation with Gemini App

The fifth paragraph discusses the vision for the Gemini app as a personal AI assistant, providing direct access to Google's latest AI models. It emphasizes the app's multimodal capabilities, allowing users to interact naturally using text, voice, or the phone's camera. The speaker introduces 'gems,' customizable features that let users create personal experts on any topic. The paragraph also demonstrates how Gemini can plan and take actions for users, such as creating a personalized vacation itinerary by analyzing data from the user's Gmail inbox. It also mentions the upcoming data analysis feature in Gemini Advance, which will help users understand their profits by visualizing earnings from spreadsheets.

25:07

📱 On-Device AI and Android Integration

The sixth paragraph outlines the integration of AI into Android phones, aiming to make smartphones truly smart. It discusses the use of on-device AI for fast and private experiences, with a focus on AI-powered search and the upcoming Gemini Nano model. The speaker highlights the protection against fraud provided by Android's ability to detect suspicious activities in real-time. The paragraph also touches on the broader implications of on-device AI for unlocking new experiences and the company's commitment to a responsible approach to AI development. It concludes with a reflection on Google's AI-first approach and the impact of its research and infrastructure on the industry.

Keywords

💡Gemini

Gemini is a multimodal AI model developed by Google, designed to process and reason across various types of data including text, images, video, and code. It plays a central role in the video, showcasing its ability to enhance search functionality, improve user experience, and facilitate natural interactions in applications like Google Photos and Google Workspace. For instance, Gemini enables users to search their photos using complex queries and even photos of objects, like license plates.

💡Long context

Long context refers to the ability of an AI model to process and understand large amounts of information, such as hundreds of pages of text or hours of audio. In the video, Google discusses the advancement of expanding the context window to 2 million tokens with Gemini 1.5 Pro, allowing for more comprehensive and nuanced understanding and responses. This capability is crucial for handling complex queries and providing detailed, informative answers.

💡Multimodality

Multimodality is the ability of a system to process and understand multiple forms of input, such as text, voice, images, and video. The video emphasizes the significance of multimodality in the next generation of AI, where Google's Gemini model can provide richer, more intuitive experiences. An example given is the integration of text, images, and voice in Google Photos, which allows users to search their memories in a more immersive and contextual way.

💡Google I/O

Google I/O is Google's annual developer conference where the company announces new products, technologies, and AI advancements. The video script is a transcript from a Google I/O event where various AI-related updates and innovations are discussed, highlighting Google's commitment to pushing the boundaries of AI technology.

💡AI Overviews

AI Overviews is a feature that Google is introducing to streamline the process of finding comprehensive information. It automatically compiles an overview that includes various perspectives and links for deeper exploration. This feature is powered by the Gemini model and is designed to reduce the effort required from users to gather information, as demonstrated in the video with examples like finding the best yoga studios.

💡Project Astra

Project Astra is an initiative by Google's DeepMind to develop a universal AI agent that can assist with everyday tasks by understanding and responding to the complex and dynamic world. The project aims to create an AI that is proactive, teachable, and personal, with human-like cognitive capabilities. The video mentions this project in the context of future AI developments at Google.

💡Google Search

Google Search is a web search engine developed by Google, which is central to the video's discussion on how AI is transforming the search experience. With the integration of AI, particularly through the Gemini model, Google Search can now provide more intuitive and comprehensive results, including multi-step reasoning and the ability to understand and respond to complex queries and multimodal inputs.

💡Google Workspace

Google Workspace, previously known as G Suite, is a collection of cloud computing, productivity, and collaboration tools developed by Google. In the video, it is discussed how Gemini can enhance Workspace apps by automating tasks, such as organizing emails and receipts, and generating spreadsheets. This integration of AI aims to make日常工作 (daily work) more efficient and seamless.

💡Gemini Nano

Gemini Nano is an on-device AI model that Google plans to integrate into the Android operating system for a more private and faster AI experience directly on smartphones. The video script mentions the use of Gemini Nano for tasks like fraud detection, where it can analyze and alert users to suspicious activities in real-time, keeping the processing private and secure.

💡AI-First Approach

An AI-First Approach, as mentioned in the video, refers to Google's strategic commitment to prioritize AI in all its products and services. This approach is evident in the numerous AI-driven features and innovations discussed, such as AI Overviews, multimodal AI in Google Photos, and the development of advanced AI models like Gemini. The term encapsulates Google's philosophy of leveraging AI to enhance user experiences and drive technological advancements.

💡Trillium

Trillium is the sixth generation of Google's Tensor Processing Units (TPUs), which are specialized hardware accelerators for machine learning workloads. The video highlights Trillium's significant improvement in compute performance, which is crucial for training state-of-the-art AI models like Gemini. This advancement supports Google's AI-first strategy by providing the necessary infrastructure for AI development.

Highlights

Google introduces Gemini, a multimodal AI model capable of reasoning across text, images, video, code, and more.

Gemini 1.5 Pro allows running 1 million tokens in production, surpassing other large-scale Foundation models.

Google Search has integrated Gemini for a new generative experience, answering billions of queries in new ways.

An increase in search usage and user satisfaction has been observed with the new Google Search experience.

Google Photos now enables searching for specific memories, like finding a car's license plate number or tracking a child's progress in learning to swim.

Google is expanding the context window to 2 million tokens, a step towards the goal of infinite context.

Notebook LM, a research and writing tool, is enhanced with Gemini 1.5 Pro for dynamic science discussions.

Google DeepMind's Project Astra aims to build a universal AI agent for everyday life, with human-level cognitive capabilities.

AI assistance in Project Astra can process information continuously, encoding video frames and speech for efficient recall.

Google Workspace apps like Gmail, Drive, Docs, and Calendar are being enhanced with AI to automate tasks and improve information flow.

The Gemini app is designed to be a personal AI assistant with multimodal capabilities and customizable 'gems' for specific topics.

Gemini Advanced will offer trip planning and data analysis features, simplifying complex tasks.

Google is introducing Gemini 1.5 Flash, a lightweight model optimized for low latency and efficiency at scale.

The sixth generation of TPUs, Trillium, offers a 4.7x improvement in compute performance per chip.

Google Search will feature AI overviews, multi-step reasoning, and the ability to ask questions with video.

Android will be the first mobile OS with a built-in on-device Foundation model, Gemini Nano, for fast and private AI experiences.

Google's AI innovations are being integrated across products like Search, Workspace, and Android to make them smarter and more helpful.