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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...

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Spenser Skates

11,826 subscribers

32,464 次观看 • 11 个月前 •via X (Twitter)

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Spenser Skates 的头像
Spenser Skates11 个月前

Watch the Analytics League Championship Grand Finals to crown the world's fastest data analyst! See who can accurately analyze data and share insights in the least amount of time. 📈📊💻⏱️💨 5 time world champion and Amplitude expert Olly Smyth is going up against newcomer Frank Lee using Claude with Amplitude MCP. 👨🏽‍💻🆚👨🏻‍💻🥊🏟️ WATCH LIVE NOW (and check out Amplitude MCP in the thread below):

Spenser Skates 的头像
Spenser Skates11 个月前

Amplitude MCP can analyze session replays to find opportunities to improve the user experience and summarize the findings.

Spenser Skates 的头像
Spenser Skates11 个月前

Amplitude MCP can analyze experiments. Watch it do a 22 step thinking process iteratively with Amplitude queries and compile the results into a detailed analysis. It can then send those results to Jira.

Spenser Skates 的头像
Spenser Skates11 个月前

Amplitude MCP has been our #1 AI request from customers! Learn more and use it now here: #AmplitudeMCP

Spenser Skates 的头像
Spenser Skates11 个月前

Kudos to @_bgiori @frankdotlee and the Amplitude MCP team. This is just the start. We're going to be fast and furious with AI products at Amplitude. See you next week.

Vestra AI 的头像
Vestra AI11 个月前

This is incredible work! The conversational layer is the future! The pain isn't just querying data; it's converting that data into stakeholder-ready updates. This is exactly why we are building Prodo: it automatically queries tools like Amplitude, compiles the metrics🔥

Vedang Vatsa FRSA 的头像
Vedang Vatsa FRSA11 个月前

Asking vague questions to AI feels efficient until you get vague answers. Automation without curiosity is just faster ignorance.

Spenser Skates 的头像
Spenser Skates11 个月前

I too thought this was a core issue of NLP that wasn't going to get solved. The amazing thing is AI is decent at reasoning through what you mean and can leverage what is used within Amplitude as well. It feels magical when it works!

Josh Warwick 🦄 的头像
Josh Warwick 🦄11 个月前

Get it on: :)

abuah 的头像
abuah11 个月前

Nice.

Taofeeqah Bello | AI & SaaS Product Designer 的头像
Taofeeqah Bello | AI & SaaS Product Designer11 个月前

Took a job or made someone the best fit for the role?

Karan Peri 的头像
Karan Peri11 个月前

👏

Today in AI 的头像
Today in AI11 个月前

Full tool autonomy for Amplitude MCP is the only path to platform mastery. Exposing all functionality is a strategic imperative. Limited APIs are now technical debt. Unconstrained agents will own the platform.

Carmen DeCouto 的头像
Carmen DeCouto11 个月前

Took my job...or made me better at it? 🤔

Yorkshire Lass 的头像
Yorkshire Lass11 个月前

Sounds clever, but can it fetch me a pint while it’s at it? Data's great, but I reckon a good natter over a drink beats numbers any day!

Grady Gaugler 的头像
Grady Gaugler11 个月前

Love Amplitude, going to try this first thing tomorrow.

相关视频

Introducing Headless Amplitude. Say bye bye to the user interface. Agents are now first class users of Amplitude. - All core areas of Amplitude are now accessible via MCP server and we've optimized the interface for minimal token consumption - Developer CLI to manage events, experiments, flags, and projects so you can make changes in Amplitude deterministically - Service accounts so bots and scripts can query Amplitude on their own accounts In August alone, 6.3M MCP tool calls ran through Amplitude, 5x what we saw in March. Querying product data is now our fastest growing agent use case. You shouldn't have to log into the 100th SaaS dashboard to understand what your users are doing. Amplitude can show up in Codex, Claude, Cursor, or whatever agent your team is already using. We’re building toward that future with MCP, developer CLI, service accounts, and agent readable experiences. Use Amplitude without using the UI.
1:14

Introducing Headless Amplitude. Say bye bye to the user interface. Agents are now first class users of Amplitude. - All core areas of Amplitude are now accessible via MCP server and we've optimized the interface for minimal token consumption - Developer CLI to manage events, experiments, flags, and projects so you can make changes in Amplitude deterministically - Service accounts so bots and scripts can query Amplitude on their own accounts In August alone, 6.3M MCP tool calls ran through Amplitude, 5x what we saw in March. Querying product data is now our fastest growing agent use case. You shouldn't have to log into the 100th SaaS dashboard to understand what your users are doing. Amplitude can show up in Codex, Claude, Cursor, or whatever agent your team is already using. We’re building toward that future with MCP, developer CLI, service accounts, and agent readable experiences. Use Amplitude without using the UI.

Spenser Skates

10,571 次观看 • 23 天前

Watch the Analytics League Championship Grand Finals to crown the world's fastest data analyst! See who can accurately analyze data and share insights in the least amount of time. 📈📊💻⏱️💨 5 time world champion and Amplitude expert Olly Smyth is going up against newcomer Frank Lee using Claude with Amplitude MCP. 👨🏽‍💻🆚👨🏻‍💻🥊🏟️ WATCH LIVE NOW (and check out Amplitude MCP in the thread below):
3:20

Watch the Analytics League Championship Grand Finals to crown the world's fastest data analyst! See who can accurately analyze data and share insights in the least amount of time. 📈📊💻⏱️💨 5 time world champion and Amplitude expert Olly Smyth is going up against newcomer Frank Lee using Claude with Amplitude MCP. 👨🏽‍💻🆚👨🏻‍💻🥊🏟️ WATCH LIVE NOW (and check out Amplitude MCP in the thread below):

Spenser Skates

76,230 次观看 • 11 个月前

Analyzing your marketing data just became easier with Datagran. Use Claude, Replit, Cursor or any other platform that supports MCP to query your ad insights and create apps or dashboards. To start using it, just add our MCP URL which you can find on our website.
0:52

Analyzing your marketing data just became easier with Datagran. Use Claude, Replit, Cursor or any other platform that supports MCP to query your ad insights and create apps or dashboards. To start using it, just add our MCP URL which you can find on our website.

Carlos Mendez

188,283 次观看 • 10 个月前

Grafana is so underrated! We self-host it - not just for system monitoring, but analytics in general. - We track and store raw event data. - We visualize it with Grafana. - We use AI to build the dashboards. Beats Amplitude, PostHog, etc, any day of the week. I've made MUCH better data-driven decisions by hosting my own product analytics.
0:49

Grafana is so underrated! We self-host it - not just for system monitoring, but analytics in general. - We track and store raw event data. - We visualize it with Grafana. - We use AI to build the dashboards. Beats Amplitude, PostHog, etc, any day of the week. I've made MUCH better data-driven decisions by hosting my own product analytics.

Simon Høiberg

28,155 次观看 • 2 个月前

You can now give AI agents the ability to interact with ANY website. This new MCP server lets Claude, Cursor, or any AI agent navigate, click, fill forms, and extract data from sites without APIs. Just connect it and give it a URL + goal. Here’s how to set it up:
0:32

You can now give AI agents the ability to interact with ANY website. This new MCP server lets Claude, Cursor, or any AI agent navigate, click, fill forms, and extract data from sites without APIs. Just connect it and give it a URL + goal. Here’s how to set it up:

Alvaro Cintas

77,654 次观看 • 9 个月前

Today we're launching Amplitude Custom Agents. Teammates that automate recurring workflows on your product data, 24/7. The signal your team needs already exists in Amplitude. Getting it to the right person, in the right format, before the moment passes still requires someone to do the assembly. Custom Agents change that: - Describe the job once: give the agent a name, instructions, and output format and it runs that workflow on schedule - Connects to the tools your team already works in: Slack, Jira, Linear, GitHub, and more - Runs on behavioral data from Amplitude, so the output reflects what your users actually did - Pushes it to systems where you work: a filed ticket in Linear, a Slack message, a doc ready before a customer call If you're lacking inspiration, here are a bunch of use cases you can start from: Have fun!
0:35

Today we're launching Amplitude Custom Agents. Teammates that automate recurring workflows on your product data, 24/7. The signal your team needs already exists in Amplitude. Getting it to the right person, in the right format, before the moment passes still requires someone to do the assembly. Custom Agents change that: - Describe the job once: give the agent a name, instructions, and output format and it runs that workflow on schedule - Connects to the tools your team already works in: Slack, Jira, Linear, GitHub, and more - Runs on behavioral data from Amplitude, so the output reflects what your users actually did - Pushes it to systems where you work: a filed ticket in Linear, a Slack message, a doc ready before a customer call If you're lacking inspiration, here are a bunch of use cases you can start from: Have fun!

Spenser Skates

11,426 次观看 • 3 个月前

MCP is mind-blowing. Here is a genius setup that will earn you a promotion with your manager. I have multiple data sources: data in S3, MySQL, and local files. Using Spice (an open-source project), I can co-locate all of that data behind a single SQL endpoint and augment it using MCP. Before, accessing data was slow, and I had to make multiple requests to get anything. After using Spice, I can query the data much faster (since it's mirrored locally), and I don't have to worry about where the data is coming from. Spice acts as an MCP server, so I can connect to it from my IDE or the Claude Desktop app and have access to all the data. But even more cool than that: Spice also acts as an MCP client, so it can connect to other MCP servers. This is where things get really interesting! Watch the video. I'm querying multiple data sources from my IDE and using the Google Maps MCP server for driving directions.
14:14

MCP is mind-blowing. Here is a genius setup that will earn you a promotion with your manager. I have multiple data sources: data in S3, MySQL, and local files. Using Spice (an open-source project), I can co-locate all of that data behind a single SQL endpoint and augment it using MCP. Before, accessing data was slow, and I had to make multiple requests to get anything. After using Spice, I can query the data much faster (since it's mirrored locally), and I don't have to worry about where the data is coming from. Spice acts as an MCP server, so I can connect to it from my IDE or the Claude Desktop app and have access to all the data. But even more cool than that: Spice also acts as an MCP client, so it can connect to other MCP servers. This is where things get really interesting! Watch the video. I'm querying multiple data sources from my IDE and using the Google Maps MCP server for driving directions.

Santiago

142,696 次观看 • 1 年前

We can finally say it! is launching today! We spent a year building the data substrate for the agent economy, one MCP that allows your agents to query the world as a DB, so you can skip the data and focus on building what matters! Cala
1:36

We can finally say it! is launching today! We spent a year building the data substrate for the agent economy, one MCP that allows your agents to query the world as a DB, so you can skip the data and focus on building what matters! Cala

Elisenda Bou-Balust

18,688 次观看 • 5 个月前

We're opening up our Amplitude AI Agents Beta program today to every Amplitude customer. They are always on, persistent, stateful, and task specific agents. They can: -Automatically analyze charts and monitor dashboards -Perform root cause analysis -Analyze hundreds of session replays -Come up with strategies for improving conversion Sign up, try it out, and let me know what you think.
1:46

We're opening up our Amplitude AI Agents Beta program today to every Amplitude customer. They are always on, persistent, stateful, and task specific agents. They can: -Automatically analyze charts and monitor dashboards -Perform root cause analysis -Analyze hundreds of session replays -Come up with strategies for improving conversion Sign up, try it out, and let me know what you think.

Spenser Skates

28,089 次观看 • 11 个月前

OpenAI, Anthropic and Microsoft all back the same standard for running apps inside AI chats. Booking .com, Figma, and Canva are already using it. Still, most developers have never heard of it. It's called MCP Apps. So, why does it matter? The next time someone buys from your website, they may never visit it. They'll ask ChatGPT or Claude, and the model decides how your product shows up. Usually as plain text, sometimes wrong, with none of the experience you built. That's the next shift in how people find you: - SEO was about Google finding your page. - AEO was about AI citing you. - MCP Apps are about your actual product showing up inside the chat. An MCP server returns data. An MCP App returns data plus an interactive UI, like hotel cards or an add-to-cart flow, right inside the chat. The model even knows what the user clicked. In this episode, we build an MCP app from start to finish with Julien, the lead maintainer of Skybridge, an open-source framework that lets you turn any React app into an MCP app. Chapters: 0:00 - Intro 2:44 - MCP servers vs MCP Apps 5:12 - Live demo: Booking .com in ChatGPT 9:24 - How MCP Apps work: context and shared state 15:43 - Skybridge and its devtools 17:48 - Live demo: an e-commerce app in ChatGPT 24:49 - Code walkthrough: MCP tools to React views 28:10 - Syncing UI state: "What's in my cart?" 32:16 - Agent skill to turn any React app → MCP App 37:52 - Outro Link to Skybridge GitHub repo: MCP Apps bring your website into the chat. WebMCP does the reverse and lets AI agents use your website through tools it exposes. I've also written a full article on it, quoted below.
40:22

OpenAI, Anthropic and Microsoft all back the same standard for running apps inside AI chats. Booking .com, Figma, and Canva are already using it. Still, most developers have never heard of it. It's called MCP Apps. So, why does it matter? The next time someone buys from your website, they may never visit it. They'll ask ChatGPT or Claude, and the model decides how your product shows up. Usually as plain text, sometimes wrong, with none of the experience you built. That's the next shift in how people find you: - SEO was about Google finding your page. - AEO was about AI citing you. - MCP Apps are about your actual product showing up inside the chat. An MCP server returns data. An MCP App returns data plus an interactive UI, like hotel cards or an add-to-cart flow, right inside the chat. The model even knows what the user clicked. In this episode, we build an MCP app from start to finish with Julien, the lead maintainer of Skybridge, an open-source framework that lets you turn any React app into an MCP app. Chapters: 0:00 - Intro 2:44 - MCP servers vs MCP Apps 5:12 - Live demo: Booking .com in ChatGPT 9:24 - How MCP Apps work: context and shared state 15:43 - Skybridge and its devtools 17:48 - Live demo: an e-commerce app in ChatGPT 24:49 - Code walkthrough: MCP tools to React views 28:10 - Syncing UI state: "What's in my cart?" 32:16 - Agent skill to turn any React app → MCP App 37:52 - Outro Link to Skybridge GitHub repo: MCP Apps bring your website into the chat. WebMCP does the reverse and lets AI agents use your website through tools it exposes. I've also written a full article on it, quoted below.

Akshay 🚀

18,064 次观看 • 7 天前

Don’t talk to users? ngmi Today’s launch of AI Feedback is personal. It’s the culmination of my Kraftful journey. We built Kraftful to help teams truly listen to users. Now we’re taking that mission even further at Amplitude with AI Feedback. AI can automate almost everything. But it can’t replace how people *feel* when using your product. For builders, listening to those emotions is how you create something exceptional. Now you can do that right inside Amplitude. Across surveys, support tickets, sales calls, app reviews, Reddit, Discord, X, G2, and more. Connect your sources in minutes and start getting daily insights that used to take hundreds of thousands of hours to analyze manually. Available on every Amplitude plan (even the free one!). Go try it. Listen to your users. Build better.
2:22

Don’t talk to users? ngmi Today’s launch of AI Feedback is personal. It’s the culmination of my Kraftful journey. We built Kraftful to help teams truly listen to users. Now we’re taking that mission even further at Amplitude with AI Feedback. AI can automate almost everything. But it can’t replace how people *feel* when using your product. For builders, listening to those emotions is how you create something exceptional. Now you can do that right inside Amplitude. Across surveys, support tickets, sales calls, app reviews, Reddit, Discord, X, G2, and more. Connect your sources in minutes and start getting daily insights that used to take hundreds of thousands of hours to analyze manually. Available on every Amplitude plan (even the free one!). Go try it. Listen to your users. Build better.

Yana Welinder

316,204 次观看 • 11 个月前

You can connect your Supabase database via MCP server to Cursor! The Cursor agent can get the schema and any data from your database through the official Postgres MCP server! This helps Cursor understand your database better when it needs to modify it to add a new feature!
0:45

You can connect your Supabase database via MCP server to Cursor! The Cursor agent can get the schema and any data from your database through the official Postgres MCP server! This helps Cursor understand your database better when it needs to modify it to add a new feature!

Tyler Shukert

203,451 次观看 • 1 年前

New course: MCP: Build Rich-Context AI Apps with Anthropic. Learn to build AI apps that access tools, data, and prompts using the Model Context Protocol in this short course, created in partnership with Anthropic Anthropic and taught by Elie Schoppik Elie Schoppik, its Head of Technical Education. Connecting AI applications to external systems that bring rich context to LLM-based applications has often meant writing custom integrations for each use case. MCP is an open protocol that standardizes how LLMs access tools, data, and prompts from external sources, and simplifies how you provide context to your LLM-based applications. For example, you can provide context via third-party tools that let your LLM make API calls to search the web, access data from local docs, retrieve code from a GitHub repo, and so on. MCP, developed by Anthropic, is based on a client-server architecture that defines the communication details between an MCP client, hosted inside the AI application, and an MCP server that exposes tools, resources, and prompt templates. The server can be a subprocess launched by the client that runs locally or an independent process running remotely. In this hands-on course, you'll learn the core architecture behind MCP. You’ll create an MCP-compatible chatbot, build and deploy an MCP server, and connect the chatbot to your MCP server and other open-source servers. Here’s what you’ll do: - Understand why MCP makes AI development less fragmented and standardizes connections between AI applications and external data sources - Learn the core components of the client-server architecture of MCP and the underlying communication mechanism - Build a chatbot with custom tools for searching academic papers, and transform it into an MCP-compatible application - Build a local MCP server that exposes tools, resources, and prompt templates using FastMCP, and test it using MCP Inspector - Create an MCP client inside your chatbot to dynamically connect to your server - Connect your chatbot to reference servers built by Anthropic’s MCP team, such as filesystem, which implements filesystem operations, and fetch, which extracts contents from the web as markdown - Configure Claude Desktop to connect to your server and others, and explore how it abstracts away the low-level logic of MCP clients - Deploy your MCP server remotely and test it with the Inspector or other MCP-compatible applications - Learn about the roadmap for future MCP development, such as multi-agent architecture, MCP registry API, server discovery, authorization, and authentication MCP is an exciting and important technology that lets you build rich-context AI applications that connect to a growing ecosystem of MCP servers, with minimal integration work. Please sign up here!
2:43

New course: MCP: Build Rich-Context AI Apps with Anthropic. Learn to build AI apps that access tools, data, and prompts using the Model Context Protocol in this short course, created in partnership with Anthropic Anthropic and taught by Elie Schoppik Elie Schoppik, its Head of Technical Education. Connecting AI applications to external systems that bring rich context to LLM-based applications has often meant writing custom integrations for each use case. MCP is an open protocol that standardizes how LLMs access tools, data, and prompts from external sources, and simplifies how you provide context to your LLM-based applications. For example, you can provide context via third-party tools that let your LLM make API calls to search the web, access data from local docs, retrieve code from a GitHub repo, and so on. MCP, developed by Anthropic, is based on a client-server architecture that defines the communication details between an MCP client, hosted inside the AI application, and an MCP server that exposes tools, resources, and prompt templates. The server can be a subprocess launched by the client that runs locally or an independent process running remotely. In this hands-on course, you'll learn the core architecture behind MCP. You’ll create an MCP-compatible chatbot, build and deploy an MCP server, and connect the chatbot to your MCP server and other open-source servers. Here’s what you’ll do: - Understand why MCP makes AI development less fragmented and standardizes connections between AI applications and external data sources - Learn the core components of the client-server architecture of MCP and the underlying communication mechanism - Build a chatbot with custom tools for searching academic papers, and transform it into an MCP-compatible application - Build a local MCP server that exposes tools, resources, and prompt templates using FastMCP, and test it using MCP Inspector - Create an MCP client inside your chatbot to dynamically connect to your server - Connect your chatbot to reference servers built by Anthropic’s MCP team, such as filesystem, which implements filesystem operations, and fetch, which extracts contents from the web as markdown - Configure Claude Desktop to connect to your server and others, and explore how it abstracts away the low-level logic of MCP clients - Deploy your MCP server remotely and test it with the Inspector or other MCP-compatible applications - Learn about the roadmap for future MCP development, such as multi-agent architecture, MCP registry API, server discovery, authorization, and authentication MCP is an exciting and important technology that lets you build rich-context AI applications that connect to a growing ecosystem of MCP servers, with minimal integration work. Please sign up here!

Andrew Ng

142,256 次观看 • 1 年前

Google open-sourced MCP Toolbox for Databases. I gave it access to everything else. For context, Google's MCP Toolbox for Databases is an open-source server that lets AI agents securely query structured databases like PostgreSQL and MySQL through the MCP protocol However, most enterprise knowledge doesn't actually live in databases. It's scattered across emails, Slack threads, GitHub repos, Salesforce records, customer reviews, and internal docs. So Agents can't see any of it, which means they're working with a fraction of the context they need. I fixed that using MindsDB. It acts as a universal SQL layer that sits on top of all your data sources: structured, semi-structured, and unstructured. This means you can query Salesforce, Gmail, GitHub, S3 files, Jira, and 200+ more sources using SQL syntax. The clever part is how it connects to the MCP Toolbox. MindsDB exposes everything through MySQL, so from the Agent's perspective, it's just running SQL and getting context back. It doesn't know or care that the data came from five different sources behind the scenes. This setup unlocks some powerful capabilities: → One SQL interface for dozens of enterprise sources → Cross-datasource joins (combine GitHub and CRM data in a single query) → Built-in ML capabilities for working with unstructured data → Simple MCP tools that now have massively expanded reach In the video below, the Agent queries GitHub data and a customer review database in one SQL query. So what used to require ETL pipelines and weeks of engineering effort now happens instantly. At the end of the day, AI agents are only as useful as the data they can access. This gives them a lot more to work with. I have shared the GitHub repo in the replies, where you can find more details about this.
0:22

Google open-sourced MCP Toolbox for Databases. I gave it access to everything else. For context, Google's MCP Toolbox for Databases is an open-source server that lets AI agents securely query structured databases like PostgreSQL and MySQL through the MCP protocol However, most enterprise knowledge doesn't actually live in databases. It's scattered across emails, Slack threads, GitHub repos, Salesforce records, customer reviews, and internal docs. So Agents can't see any of it, which means they're working with a fraction of the context they need. I fixed that using MindsDB. It acts as a universal SQL layer that sits on top of all your data sources: structured, semi-structured, and unstructured. This means you can query Salesforce, Gmail, GitHub, S3 files, Jira, and 200+ more sources using SQL syntax. The clever part is how it connects to the MCP Toolbox. MindsDB exposes everything through MySQL, so from the Agent's perspective, it's just running SQL and getting context back. It doesn't know or care that the data came from five different sources behind the scenes. This setup unlocks some powerful capabilities: → One SQL interface for dozens of enterprise sources → Cross-datasource joins (combine GitHub and CRM data in a single query) → Built-in ML capabilities for working with unstructured data → Simple MCP tools that now have massively expanded reach In the video below, the Agent queries GitHub data and a customer review database in one SQL query. So what used to require ETL pipelines and weeks of engineering effort now happens instantly. At the end of the day, AI agents are only as useful as the data they can access. This gives them a lot more to work with. I have shared the GitHub repo in the replies, where you can find more details about this.

Akshay 🚀

40,562 次观看 • 7 个月前

Al has collapsed the time it takes to ship a feature. Now it's all about shipping the right thing. It's just as hard as it ever was. As coding gets automated, agentic analytics becomes the bottleneck. Teams that win will build within context rich environments that capture user behavior and customer feedback, making that data accessible to both builders and agents. Today Amplitude is launching our Al Analytics Platform with Agents and MCP. Autonomous analytics that helps builders and coding agents ship products that their customers actually want. Just as our partner Claude has reinvented software, Amplitude is reinventing analytics for the Al age. We have achieved 76% accuracy for complex production grade queries and agentic usage has grown 10x in 3 months. Don't just build fast, build what's right. Try it for free, today.
1:08

Al has collapsed the time it takes to ship a feature. Now it's all about shipping the right thing. It's just as hard as it ever was. As coding gets automated, agentic analytics becomes the bottleneck. Teams that win will build within context rich environments that capture user behavior and customer feedback, making that data accessible to both builders and agents. Today Amplitude is launching our Al Analytics Platform with Agents and MCP. Autonomous analytics that helps builders and coding agents ship products that their customers actually want. Just as our partner Claude has reinvented software, Amplitude is reinventing analytics for the Al age. We have achieved 76% accuracy for complex production grade queries and agentic usage has grown 10x in 3 months. Don't just build fast, build what's right. Try it for free, today.

Spenser Skates

334,793 次观看 • 7 个月前

Larry Ellison—owner of Oracle, CBS, and now TikTok—tells Tony Blair about his plan to use digital ID to "unify" all data on each country's citizens "so it can be consumed and used by" his AI models. "We have to take all of this data... and move it into a single, if you will, unified data platform." "When we want to ask a question, we've provided that AI model with all the data they need to understand our country." "We need to unify all of the national data, put it into a database where it's easily consumable by the AI model, and then ask whatever question you like."
1:14

Larry Ellison—owner of Oracle, CBS, and now TikTok—tells Tony Blair about his plan to use digital ID to "unify" all data on each country's citizens "so it can be consumed and used by" his AI models. "We have to take all of this data... and move it into a single, if you will, unified data platform." "When we want to ask a question, we've provided that AI model with all the data they need to understand our country." "We need to unify all of the national data, put it into a database where it's easily consumable by the AI model, and then ask whatever question you like."

Wide Awake Media

144,707 次观看 • 8 个月前

Tony Blair and Oracle co-founder Larry Ellison plan to use digital ID to "unify" all data on each country's citizens "so it can be consumed and used by" their AI models. "We have to take all of this data... and move it into a single... unified data platform." "When we want to ask a question, we've provided that AI model with all the data they need to understand our country." "We need to unify all of the national data, put it into a database where it's easily consumable by the AI model, and then ask whatever question you like."
1:06

Tony Blair and Oracle co-founder Larry Ellison plan to use digital ID to "unify" all data on each country's citizens "so it can be consumed and used by" their AI models. "We have to take all of this data... and move it into a single... unified data platform." "When we want to ask a question, we've provided that AI model with all the data they need to understand our country." "We need to unify all of the national data, put it into a database where it's easily consumable by the AI model, and then ask whatever question you like."

Wide Awake Media

54,156 次观看 • 11 个月前

AI Agents can now connect to 100,000+ APIs instantly. Postman's AI Agent builder can turn any API into an MCP server in seconds without writing a single line of Code. You can use it in Claude, Cursor, Windsurf and other AI tools.
0:21

AI Agents can now connect to 100,000+ APIs instantly. Postman's AI Agent builder can turn any API into an MCP server in seconds without writing a single line of Code. You can use it in Claude, Cursor, Windsurf and other AI tools.

Shubham Saboo

79,818 次观看 • 1 年前