Loading video...

Video Failed to Load

There was a problem loading this video. This could be due to a temporary network issue or the video might be unavailable.

Why Camp Mamo? Get access to the first hands-on crash course for building on Celestia. You’ll learn how to build with full-stack control across the different stacks and tools among the Celestia ecosystem. Sign up now:

Celestia developers

1,790 subscribers

11,208 views • 1 year ago •via X (Twitter)

Anya Rossi• Live Now

Private livecam show

2 Comments

Hashim Cassandra1 year ago

Celestia $TIA garbage.

Vox Draconis1 year ago

Woke crap all over the show. Do you imbeciles even care about your image? Doesn't seem like it when posting such disgusting things.

Related Videos

Welcome to the Infinite Space Bazaar ☄️ Get ready for the first global online Celestia hackathon, from April 2 to May 17, with $100k+ in prizes. 🏁 Register now:

Welcome to the Infinite Space Bazaar ☄️ Get ready for the first global online Celestia hackathon, from April 2 to May 17, with $100k+ in prizes. 🏁 Register now:

Celestia

506,469 views • 2 years ago

📹 DIA x Celestia: 2024 in Review From ideation to execution, we are excited to spotlight Celestia again as a key infra component of the Lumina stack Celestia powers Lumina with on-chain data storage, offering predictable costs, scalability, and customizability

📹 DIA x Celestia: 2024 in Review From ideation to execution, we are excited to spotlight Celestia again as a key infra component of the Lumina stack Celestia powers Lumina with on-chain data storage, offering predictable costs, scalability, and customizability

DIA Oracles

13,100 views • 1 year ago

🔗 New LangChain Academy Course: Introduction to LangChain (Python) 🔗 Learn how to build with LangChain – our open source framework that makes it easy to start building agents with any model provider. In this course, you’ll create agents that can reason, use tools, and take action, and learn how to debug their behavior with LangSmith. Along the way, you’ll: - Build an agent with the `create_agent` abstraction - Use LangChain’s core building blocks: Models, Messages, Memory, and Tools - Customize your agent with middleware - Debug your agent with LangSmith Observability & Studio By the end of the course, you’ll have assembled a full team of personal assistants. Enroll for free ➡️

🔗 New LangChain Academy Course: Introduction to LangChain (Python) 🔗 Learn how to build with LangChain – our open source framework that makes it easy to start building agents with any model provider. In this course, you’ll create agents that can reason, use tools, and take action, and learn how to debug their behavior with LangSmith. Along the way, you’ll: - Build an agent with the `create_agent` abstraction - Use LangChain’s core building blocks: Models, Messages, Memory, and Tools - Customize your agent with middleware - Debug your agent with LangSmith Observability & Studio By the end of the course, you’ll have assembled a full team of personal assistants. Enroll for free ➡️

LangChain

41,214 views • 9 months ago

❤️ Introducing Raspberry Celestia's first public testnet built On 🟠 Gelato RaaS Celestia helps to reduce the DA cost by up to 99% vs. Ethereum. With Raspberry, you can finally test it out. Gelato/Celestia Raspberry is the first public good Celestia testnet with all the necessary infrastructure for developers to build whatever → Production-ready implementation of Celestia Modular DA → All of the necessary infra to build whatever → No real-world value at risk Raspberry is FREE FOR EVERYONE. Raspberry is a public good initiative by Gelato and 10+ partners to accelerate the modular expansion by lowering the barriers for developers to build and test whatever in a production-ready environment. Like Sepolia to Ethereum, Raspberry is the playground to build whatever on Celestia. → Framework: OP Stack → DA Layer: Celestia → Settlement Layer: Sepolia → Cost per transaction: $ 0.002 → Throughput: ~2000–4000 tps Raspberry is MADE FOR BUILDERS. Raspberry includes all Gelaton Web3 Services and all essential 3rd party tooling & infrastructure. Gelato Web3 Services: → Functions - smart contract automation → Relay - gasless transaction → VRF - verifiable onchain randomness → Bridge UI - bridge testnet Eth 8+ natively integrated tooling & infra: → Goldsky ☀️ - read, edit, and sync fresh chain data → dRPC // AI-powered RPC Infrastructure - access reliable & globally distributed nodes → @blockscoutcom - access essential on-chain data → thirdweb - onboard anyone with flexible sign-in options → - create smart wallets for your users → Safe.eth - use the most secure smart wallet infrastructure → DIA Oracles - source data from on and off-chain platforms → Tenderly - build, test, monitor, and operate smart contracts Start building on 🟠 Raspberry testnet today ↓ Hack on Raspberry at CelestiaOrg's #1st global online Hackathon with $100k+ prize pool ↓ Build whatever

❤️ Introducing Raspberry Celestia's first public testnet built On 🟠 Gelato RaaS Celestia helps to reduce the DA cost by up to 99% vs. Ethereum. With Raspberry, you can finally test it out. Gelato/Celestia Raspberry is the first public good Celestia testnet with all the necessary infrastructure for developers to build whatever → Production-ready implementation of Celestia Modular DA → All of the necessary infra to build whatever → No real-world value at risk Raspberry is FREE FOR EVERYONE. Raspberry is a public good initiative by Gelato and 10+ partners to accelerate the modular expansion by lowering the barriers for developers to build and test whatever in a production-ready environment. Like Sepolia to Ethereum, Raspberry is the playground to build whatever on Celestia. → Framework: OP Stack → DA Layer: Celestia → Settlement Layer: Sepolia → Cost per transaction: $ 0.002 → Throughput: ~2000–4000 tps Raspberry is MADE FOR BUILDERS. Raspberry includes all Gelaton Web3 Services and all essential 3rd party tooling & infrastructure. Gelato Web3 Services: → Functions - smart contract automation → Relay - gasless transaction → VRF - verifiable onchain randomness → Bridge UI - bridge testnet Eth 8+ natively integrated tooling & infra: → Goldsky ☀️ - read, edit, and sync fresh chain data → dRPC // AI-powered RPC Infrastructure - access reliable & globally distributed nodes → @blockscoutcom - access essential on-chain data → thirdweb - onboard anyone with flexible sign-in options → - create smart wallets for your users → Safe.eth - use the most secure smart wallet infrastructure → DIA Oracles - source data from on and off-chain platforms → Tenderly - build, test, monitor, and operate smart contracts Start building on 🟠 Raspberry testnet today ↓ Hack on Raspberry at CelestiaOrg's #1st global online Hackathon with $100k+ prize pool ↓ Build whatever

Gelato

50,570 views • 2 years ago

The only trading bot you need to make it this cycle WoodsBot Watch the full video on YouTube showcasing some of our tools and how to gain full access to them. Sign up now:

The only trading bot you need to make it this cycle WoodsBot Watch the full video on YouTube showcasing some of our tools and how to gain full access to them. Sign up now:

woods.ai

13,989 views • 1 year ago

Bullet will be upgrading to @Celestia underneath 🦣 CLOBs on blobs belong with the pioneers of Modular Blockchains. With Celestia, Bullet traders can count on seamless scalability. Why is this partnership bull(et)ish? 👇

Bullet will be upgrading to @Celestia underneath 🦣 CLOBs on blobs belong with the pioneers of Modular Blockchains. With Celestia, Bullet traders can count on seamless scalability. Why is this partnership bull(et)ish? 👇

Bullet

162,658 views • 1 year ago

Workflows are now rolling out across all plans. Learn how to start building the tools that work for you with today's episode of Runway Academy.

Workflows are now rolling out across all plans. Learn how to start building the tools that work for you with today's episode of Runway Academy.

Runway

32,403 views • 11 months ago

Here it is! Learn how to build real-time games with...Laravel! Watch the first episode right here, then head over to Laracasts for the full course.

Here it is! Learn how to build real-time games with...Laravel! Watch the first episode right here, then head over to Laracasts for the full course.

Laracasts

28,901 views • 2 years ago

Curious to know #Celestia's roadmap and how #MantaPacific will play a vital role in it? 🤩 Listen to our co-founder, 🤓Kenny, and Mustafa Al-Bassam, co-founder of Celestia. The future is modular on #MantaNetwork with Celestia underneath 🧱

Curious to know #Celestia's roadmap and how #MantaPacific will play a vital role in it? 🤩 Listen to our co-founder, 🤓Kenny, and Mustafa Al-Bassam, co-founder of Celestia. The future is modular on #MantaNetwork with Celestia underneath 🧱

Manta Network (🔱,🔱)

61,225 views • 2 years ago

Introducing the context course: a free course on doing ML with agent context. You will learn how to train models, optimize inferences, and build datasets, all by defining harness context with`SKILLS.md`, Plugins, MCP, Subagents, and Hooks. The course includes: - Weekly live AMA on YouTube - Weekly practical projects for ML with context - Instructions in Pi, Codex, Claude, and Opencode - Tutorials and guides on fundamentals - Interactive Quizzes Learn to give AI agents the right knowledge, tools, and structure to actually get work done. Skills, MCP servers, plugins, multi-agent workflows, and building an agent from scratch. Join here:

Introducing the context course: a free course on doing ML with agent context. You will learn how to train models, optimize inferences, and build datasets, all by defining harness context with`SKILLS.md`, Plugins, MCP, Subagents, and Hooks. The course includes: - Weekly live AMA on YouTube - Weekly practical projects for ML with context - Instructions in Pi, Codex, Claude, and Opencode - Tutorials and guides on fundamentals - Interactive Quizzes Learn to give AI agents the right knowledge, tools, and structure to actually get work done. Skills, MCP servers, plugins, multi-agent workflows, and building an agent from scratch. Join here:

Ben Burtenshaw

16,905 views • 4 months ago

"Introducing Multimodal Llama 3.2": As promised two weeks ago, here's the short course on Meta's latest open model! This short course is created with Meta and taught by Amit Sangani, Director of AI Partner Engineering at Meta. Meta’s Llama family of models is leading the way in open models, allowing anyone to download, customize, fine-tune, or build new applications on top of them. Learn about the vision capabilities of the Llama 3.2, and use it for image classification, prompting, tokenization, tool-calling. You'll also learn about the open-source Llama stack, which gives building blocks for many different stages of the LLM application life cycle. In detail, you’ll: - Learn what are the features of Meta's four newest models, and when to use which Llama model. - Learn best practices for multimodal prompting, with applications to advanced image reasoning, illustrated by many examples: Understanding errors on a car dashboard, adding up the total of photographed restaurant receipts, grading written math homework. - Use different roles—system, user, assistant, ipython—in the Llama 3.1 and 3.2 models and the prompt format that identifies those roles. - Understand how Llama uses the tiktoken tokenizer, and how it has expanded to a 128k vocabulary size that improves encoding efficiency and multilingual support. - Learn how to prompt Llama to call built-in and custom tools (functions) with examples for web search and solving math equations. - Learn about Llama Stack, a standardized interface for common toolchain components like fine-tuning or synthetic data generation, useful for building agentic applications. By the end of this course, you’ll be equipped to build out new applications with the new Llama 3.2. Thank you to Ahmad Al-Dahle, Amit Sangani, and the whole AI at Meta team AI at Meta for all the hard work on Llama 3.2 — we’re excited to make these open models even more accessible to more developers with this new course! Please sign up here!

"Introducing Multimodal Llama 3.2": As promised two weeks ago, here's the short course on Meta's latest open model! This short course is created with Meta and taught by Amit Sangani, Director of AI Partner Engineering at Meta. Meta’s Llama family of models is leading the way in open models, allowing anyone to download, customize, fine-tune, or build new applications on top of them. Learn about the vision capabilities of the Llama 3.2, and use it for image classification, prompting, tokenization, tool-calling. You'll also learn about the open-source Llama stack, which gives building blocks for many different stages of the LLM application life cycle. In detail, you’ll: - Learn what are the features of Meta's four newest models, and when to use which Llama model. - Learn best practices for multimodal prompting, with applications to advanced image reasoning, illustrated by many examples: Understanding errors on a car dashboard, adding up the total of photographed restaurant receipts, grading written math homework. - Use different roles—system, user, assistant, ipython—in the Llama 3.1 and 3.2 models and the prompt format that identifies those roles. - Understand how Llama uses the tiktoken tokenizer, and how it has expanded to a 128k vocabulary size that improves encoding efficiency and multilingual support. - Learn how to prompt Llama to call built-in and custom tools (functions) with examples for web search and solving math equations. - Learn about Llama Stack, a standardized interface for common toolchain components like fine-tuning or synthetic data generation, useful for building agentic applications. By the end of this course, you’ll be equipped to build out new applications with the new Llama 3.2. Thank you to Ahmad Al-Dahle, Amit Sangani, and the whole AI at Meta team AI at Meta for all the hard work on Llama 3.2 — we’re excited to make these open models even more accessible to more developers with this new course! Please sign up here!

Andrew Ng

131,846 views • 1 year ago