正在加载视频...

视频加载失败

加载此视频时出现问题。这可能是由于临时网络问题，或视频可能不可用。

Gemini 1.5 Pro can analyze, classify and summarize huge quantities of information – including documents with thousands of pages. 📄 When given a 402-page transcript from Apollo 11’s mission to the moon, it was able to reason about conversations and events it finds. ↓

Google DeepMind

1,492,777 subscribers

214,565 次观看 • 2 年前 •via X (Twitter)

Anya Rossi• Live Now

Private livecam show

10 条评论

Tatarin 的头像

Tatarin2 年前

@Google When?

Felipe Cantalice 的头像

Felipe Cantalice2 年前

Gemini should be added to every Livestream class, for students to ask questions and take some notes or expand the knowledge

Omar 的头像

Omar2 年前

Can't wait to use this to "talk" with the vulkan spec when I need to learn something

Skills Gap Trainer 的头像

Skills Gap Trainer2 年前

Facing global challenges, risks, threats & dangers requires ability to understand large quantity of data spread across thousands of books. With #Gemini15Pro, we're now equipped to forecast & design solutions to global risks, for a safer & more predictable future. #GoogleDeepMind

isai 的头像

isai2 年前

but i can't watch a specific part of a YouTube video through gemini 1.5

Muhammad Ahmad 的头像

Muhammad Ahmad2 年前

@Google 🤔🤔🤔

Nikhil Kumar Singh 的头像

Nikhil Kumar Singh2 年前

@Google FOR THE SUCCESS 👽👽👽👽

Saurabh Chalke ᯅ 的头像

Saurabh Chalke ᯅ2 年前

This is cool! Really interested in how this achieves the 10M context window? Time to dust out my coding test again, I think, which is: "here is a tarball of a repository. Write a new module that does X."

Arafath M 的头像

Arafath M2 年前

@Google Gemini gives a wrong answer to the below straightforward question. Does Gemini need more training? A is bigger than B. C is bigger than A. D is smaller than B. Which is the biggest?

بندہ ناچیز 的头像

بندہ ناچیز2 年前

"Be the change that you wish to see in the world." - Mahatma Gandhi

相关视频

Gemini 2.5 can now organize vast amounts of multimodal information, reason about everything it sees, and write code to simulate anything. ↓ #GoogleIO

Gemini 2.5 can now organize vast amounts of multimodal information, reason about everything it sees, and write code to simulate anything. ↓ #GoogleIO

Google DeepMind

137,399 次观看 • 1 年前

Before Artemis II, there was Apollo. From the Apollo 1 fire to the final moon landing in 1972, NASA’s race to the moon was defined by risk, innovation, and history-making firsts. Here’s a timeline of every Apollo mission.

Before Artemis II, there was Apollo. From the Apollo 1 fire to the final moon landing in 1972, NASA’s race to the moon was defined by risk, innovation, and history-making firsts. Here’s a timeline of every Apollo mission.

TIME

34,130 次观看 • 4 个月前

Gemini 1.5 Pro can understand tasks and questions across different modalities because of its long context understanding. When given a 44-minute Buster Keaton film, it's able to find small details in the film and understand plot points. #GeminiAI

Gemini 1.5 Pro can understand tasks and questions across different modalities because of its long context understanding. When given a 44-minute Buster Keaton film, it's able to find small details in the film and understand plot points. #GeminiAI

Google

229,104 次观看 • 2 年前

Today at #GoogleIO, we’re demonstrating how our partnership with Google Cloud is redefining the landscape of Intelligent Content Management. Leveraging the advanced capabilities of Google’s Gemini 2.5 Pro, our new AI Agent with enhanced data extraction transforms complex, unstructured data from various sources—including scanned PDFs, images, and diverse forms—into structured, actionable insights. Check out the demo below to watch Gemini 2.5 Pro and Box AI agents in action. With the Box AI Agent powered by Gemini 2.5 Pro you can: ⭐ Automatically, and instantly, classify and organize documents ⭐ Extract accurate insights and information from documents and images ⭐ Enable workflow automation by leveraging structured and easily retrievable content Our partnership with Google is not just about enhancing current capabilities; it’s about unlocking the full potential of AI, and models like Gemini 2.5 Pro, for intricate enterprise use cases.

Today at #GoogleIO, we’re demonstrating how our partnership with Google Cloud is redefining the landscape of Intelligent Content Management. Leveraging the advanced capabilities of Google’s Gemini 2.5 Pro, our new AI Agent with enhanced data extraction transforms complex, unstructured data from various sources—including scanned PDFs, images, and diverse forms—into structured, actionable insights. Check out the demo below to watch Gemini 2.5 Pro and Box AI agents in action. With the Box AI Agent powered by Gemini 2.5 Pro you can: ⭐ Automatically, and instantly, classify and organize documents ⭐ Extract accurate insights and information from documents and images ⭐ Enable workflow automation by leveraging structured and easily retrievable content Our partnership with Google is not just about enhancing current capabilities; it’s about unlocking the full potential of AI, and models like Gemini 2.5 Pro, for intricate enterprise use cases.

Box

10,565 次观看 • 1 年前

Hours before a court-ordered deadline, the Justice Department releases thousands of pages of records tied to Jeffrey Epstein, including grand jury material, FBI documents and evidence, much of it heavily redacted.

Hours before a court-ordered deadline, the Justice Department releases thousands of pages of records tied to Jeffrey Epstein, including grand jury material, FBI documents and evidence, much of it heavily redacted.

CBS Evening News with Tony Dokoupil

42,886 次观看 • 7 个月前

On this day in 1969, Apollo 11 landed on the Moon. It happened because an entire generation believed there was always another mountain to climb, another record to break, another problem worth solving. This was the era of test pilots who kept pushing faster, higher, and farther. Engineers who built things people said couldn't be built. Americans who looked at the unknown and decided to go anyway. That mindset gave us people like Chuck Yeager, the Mercury and Gemini programs, and, on this day, Neil Armstrong, Buzz Aldrin, and Michael Collins. Apollo 11 wasn't just a mission to the Moon. It was the result of years of risk, trial and error, and thousands of people refusing to settle for "good enough." It's hard not to miss an era when the answer to, "Can it be done?" was simply, "Let's find out." Fifty-seven years later, it's still one of the greatest achievements in American history.

On this day in 1969, Apollo 11 landed on the Moon. It happened because an entire generation believed there was always another mountain to climb, another record to break, another problem worth solving. This was the era of test pilots who kept pushing faster, higher, and farther. Engineers who built things people said couldn't be built. Americans who looked at the unknown and decided to go anyway. That mindset gave us people like Chuck Yeager, the Mercury and Gemini programs, and, on this day, Neil Armstrong, Buzz Aldrin, and Michael Collins. Apollo 11 wasn't just a mission to the Moon. It was the result of years of risk, trial and error, and thousands of people refusing to settle for "good enough." It's hard not to miss an era when the answer to, "Can it be done?" was simply, "Let's find out." Fifty-seven years later, it's still one of the greatest achievements in American history.

Black Rifle Coffee

15,941 次观看 • 16 天前

In December, we launched Gemini 1.0 Pro. Today, we're introducing Gemini 1.5 Pro! 🚀 This next-gen model uses a Mixture-of-Experts (MoE) approach for more efficient training & higher-quality responses. Gemini 1.5 Pro, our mid-sized model, will soon come standard with a 128K-token context window, but starting today, developers + customers can sign up for the limited Private Preview to try out 1.5 Pro with a groundbreaking and experimental 1 million token context window! The 1M tokens feature unlocks huge possibilities for devs - upload hundreds of pages of text, entire code repos, and long videos and let Gemini reason across them. It's still experimental and early and we’d love your feedback - learn more here.

In December, we launched Gemini 1.0 Pro. Today, we're introducing Gemini 1.5 Pro! 🚀 This next-gen model uses a Mixture-of-Experts (MoE) approach for more efficient training & higher-quality responses. Gemini 1.5 Pro, our mid-sized model, will soon come standard with a 128K-token context window, but starting today, developers + customers can sign up for the limited Private Preview to try out 1.5 Pro with a groundbreaking and experimental 1 million token context window! The 1M tokens feature unlocks huge possibilities for devs - upload hundreds of pages of text, entire code repos, and long videos and let Gemini reason across them. It's still experimental and early and we’d love your feedback - learn more here.

Sundar Pichai

852,671 次观看 • 2 年前

Gemini 3.1 Pro comes with SOTA reasoning💡 It can be used in Gemini CLI to reason across multiple sources at once: Google Docs, code, local files. See it analyze user feedback and implement a fix live below 🧑‍💻

Gemini 3.1 Pro comes with SOTA reasoning💡 It can be used in Gemini CLI to reason across multiple sources at once: Google Docs, code, local files. See it analyze user feedback and implement a fix live below 🧑‍💻

Gemini CLI

48,077 次观看 • 5 个月前

As one example of 1.5 Pro’s sophisticated multimodal understanding and reasoning capabilities with long context, when given a 44-minute silent film, the model can analyze various plot points and events, and even makes sense of small details you might have missed.

As one example of 1.5 Pro’s sophisticated multimodal understanding and reasoning capabilities with long context, when given a 44-minute silent film, the model can analyze various plot points and events, and even makes sense of small details you might have missed.

Sundar Pichai

348,318 次观看 • 2 年前

Everything from the Apollo landing sites is still on the Moon... exactly where it was left. Congratulations to NASA and the Artemis II crew on a spectacular mission!

Everything from the Apollo landing sites is still on the Moon... exactly where it was left. Congratulations to NASA and the Artemis II crew on a spectacular mission!

Encyclopaedia Britannica

35,565 次观看 • 3 个月前

JUST IN: Google releases Gemini 1.5, a powerful MoE model. It's a huge breakthrough. The model has the longest context window ever seen: 1 million tokens. It can process 1 hour of video, 11 hours of audio, 30,000 lines of code, or 700,000 words in a single prompt. When tested on text, code, image, audio and video evaluations, 1.5 Pro outperforms 1.0 Pro on 87% of the benchmarks used for developing LLMs. You can can sign up in AI Studio to try it out.

JUST IN: Google releases Gemini 1.5, a powerful MoE model. It's a huge breakthrough. The model has the longest context window ever seen: 1 million tokens. It can process 1 hour of video, 11 hours of audio, 30,000 lines of code, or 700,000 words in a single prompt. When tested on text, code, image, audio and video evaluations, 1.5 Pro outperforms 1.0 Pro on 87% of the benchmarks used for developing LLMs. You can can sign up in AI Studio to try it out.

Lior Alexander

83,432 次观看 • 2 年前

On This Day 1969 - Apollo 11 Landing on the Moon HD from LM Window Footage of the first moon landing in July 1969 from lunar orbit all the way down to the surface, as seen from the Apollo 11 Lunar Module piloted by Neil Armstrong and Buzz Aldrin. The footage was filmed on the 16mm DAC Camera from Buzz Aldrin's Lunar Module window and has been upscaled, interpolated from 12 FPS to 50 FPS, and synced to mission audio by Moonpans. The video captures the drama of the first moon landing including the 1202 alarms and low fuel warnings Original footage from the Apollo Flight Journal Audio from the Apollo Lunar Surface Journal

On This Day 1969 - Apollo 11 Landing on the Moon HD from LM Window Footage of the first moon landing in July 1969 from lunar orbit all the way down to the surface, as seen from the Apollo 11 Lunar Module piloted by Neil Armstrong and Buzz Aldrin. The footage was filmed on the 16mm DAC Camera from Buzz Aldrin's Lunar Module window and has been upscaled, interpolated from 12 FPS to 50 FPS, and synced to mission audio by Moonpans. The video captures the drama of the first moon landing including the 1202 alarms and low fuel warnings Original footage from the Apollo Flight Journal Audio from the Apollo Lunar Surface Journal

Mike Constantine

32,708 次观看 • 16 天前

Welcome to the Gemini app, Audio Overviews 🎧 We've seen incredible excitement around Audio Overviews in NotebookLM, which helps people make sense of complex information. Today, we're making Audio Overviews available in the Gemini app, too. Transform your documents, slides, and even Deep Research reports into engaging, podcast-style conversations between two AI hosts to summarize information while you’re on the go. Give it a try in the app today:

Welcome to the Gemini app, Audio Overviews 🎧 We've seen incredible excitement around Audio Overviews in NotebookLM, which helps people make sense of complex information. Today, we're making Audio Overviews available in the Gemini app, too. Transform your documents, slides, and even Deep Research reports into engaging, podcast-style conversations between two AI hosts to summarize information while you’re on the go. Give it a try in the app today:

Google Gemini

307,082 次观看 • 1 年前

With Gemini 3, you can take an image of anything, like a board game, a floor plan, or a doodle, and make it an interactive experience. This is because of Gemini 3’s deep multimodal understanding. The model is able to analyze the content of the image, distill the most compelling parts, and then translate the image’s details into a functional, interactive experience.

With Gemini 3, you can take an image of anything, like a board game, a floor plan, or a doodle, and make it an interactive experience. This is because of Gemini 3’s deep multimodal understanding. The model is able to analyze the content of the image, distill the most compelling parts, and then translate the image’s details into a functional, interactive experience.

Google AI

98,281 次观看 • 8 个月前

Pope Paul VI's message to Apollo 11 upon landing on the Moon: "Honor, greetings and blessings to you, conquerors of the Moon, pale lamp of our nights and our dreams! Bring to it, with your living presence, the voice of the Spirit, a hymn to God, our Creator and our Father."

Pope Paul VI's message to Apollo 11 upon landing on the Moon: "Honor, greetings and blessings to you, conquerors of the Moon, pale lamp of our nights and our dreams! Bring to it, with your living presence, the voice of the Spirit, a hymn to God, our Creator and our Father."

Catholic Arena

70,675 次观看 • 3 个月前

Pope Paul VI's message to Apollo 11 upon landing on the Moon on July 20th 1969: "Honor, greetings and blessings to you, conquerors of the Moon, pale lamp of our nights and our dreams! Bring to it, with your living presence, the voice of the Spirit, a hymn to God, our Creator and our Father."

Pope Paul VI's message to Apollo 11 upon landing on the Moon on July 20th 1969: "Honor, greetings and blessings to you, conquerors of the Moon, pale lamp of our nights and our dreams! Bring to it, with your living presence, the voice of the Spirit, a hymn to God, our Creator and our Father."

Catholic Arena

19,380 次观看 • 16 天前

We partnered with ICC to show how Gemini 3 Pro can analyze video content. By uploading a segment of the Cricket World Cup, Gemini can seamlessly process visual and audio data to identify key players, explain techniques, and highlight crucial turning points. 🏏

We partnered with ICC to show how Gemini 3 Pro can analyze video content. By uploading a segment of the Cricket World Cup, Gemini can seamlessly process visual and audio data to identify key players, explain techniques, and highlight crucial turning points. 🏏

Google Gemini

4,322,477 次观看 • 6 个月前

Apollo 16 'Grand Prix' Rover Test on the Moon HD 60FPS Stabilised See comments for full video During the Apollo 16 mission in April 1972 the crew were tasked with putting the Lunar Roving Vehicle through a series of tests to asses its capabilities. Commander John Young drove the electrically powered rover through a series of maneuvers—including S-turns, hairpin turns, hard stops, and acceleration to "high" speeds of roughly 6–11 mph (10–18 km/h)—while Charles Duke (lunar module pilot) filmed it with a 16 mm camera from a safe distance. This video has been upscaled in quality, interpolated to 60FPS, Stabilised and synced with mission audio by Moonpans Original Source Footage: Apollo Flight Journal

Apollo 16 'Grand Prix' Rover Test on the Moon HD 60FPS Stabilised See comments for full video During the Apollo 16 mission in April 1972 the crew were tasked with putting the Lunar Roving Vehicle through a series of tests to asses its capabilities. Commander John Young drove the electrically powered rover through a series of maneuvers—including S-turns, hairpin turns, hard stops, and acceleration to "high" speeds of roughly 6–11 mph (10–18 km/h)—while Charles Duke (lunar module pilot) filmed it with a 16 mm camera from a safe distance. This video has been upscaled in quality, interpolated to 60FPS, Stabilised and synced with mission audio by Moonpans Original Source Footage: Apollo Flight Journal

Mike Constantine

124,567 次观看 • 4 个月前

Today we're launching Amplitude MCP MCP was made for data analytics. Ask a vague question and have an AI model iteratively query Amplitude to find you insights. Amplitude MCP exposes all of Amplitude's functionality so an agent can interact with it directly. It allows you to use Amplitude without having to know anything about Amplitude's user interface or your data taxonomy. It uses the intelligence of off the shelf AI agents, including Claude, Gemini, and Cursor, to query Amplitude data you already have to find answers. It leverages all of your existing Amplitude data and how it's used to navigate through large complex behavioral datasets. You can have conversations about your product data directly inside any AI model with MCP. It can create Amplitude dashboards and notebooks with what it finds and even make recommendations. This is the best MCP use case I've ever seen. Watching an AI agent think, reason, query Amplitude, and then repeat that process iteratively is magical. See it in action:

Today we're launching Amplitude MCP MCP was made for data analytics. Ask a vague question and have an AI model iteratively query Amplitude to find you insights. Amplitude MCP exposes all of Amplitude's functionality so an agent can interact with it directly. It allows you to use Amplitude without having to know anything about Amplitude's user interface or your data taxonomy. It uses the intelligence of off the shelf AI agents, including Claude, Gemini, and Cursor, to query Amplitude data you already have to find answers. It leverages all of your existing Amplitude data and how it's used to navigate through large complex behavioral datasets. You can have conversations about your product data directly inside any AI model with MCP. It can create Amplitude dashboards and notebooks with what it finds and even make recommendations. This is the best MCP use case I've ever seen. Watching an AI agent think, reason, query Amplitude, and then repeat that process iteratively is magical. See it in action:

Spenser Skates

32,332 次观看 • 9 个月前