Filecoin / FVM Space Warp Hackathon

Honghao Qiu of Protocol Labs provides an introduction to Filecoin at the start of the Space Warp Summit.

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Zak Ayesh of Protocol Labs talks about Programming on the FEVM.

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Corey James of Protocol Labs talks about Impact Evaluators at the FVM Space Warp Summit.

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Molly Mackinlay of Protocol Labs provides an introduction to FEVM and a countdown to Space Warp.

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JV and Matt Hamilton of Protocol Labs imagine different ideas for start-ups and give examples of what is being built, and what could be built.

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Sarah Thiam and Matt Hamilton of Protocol Labs moderate a talk with Karen Sheng, Nandit Mehra, Ilya Orlov, Ning Ren and Lamont Veal about the progress of early builders on FVM.

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Raúl Kripalani of Protocol Labs explains onboarding Ethereum developers to the Filecoin EVM.

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Sarah Thiam of Protocol Labs joins Yondon Fu and Akshit Gupta in discussing video use cases on FVM.

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Join Alison Haire from Filecoin for a workshop titled "AI Art NFTs on FEVM with Bacalhau Stable Diffusion".

Hack the future of Filecoin! The launch of the Filecoin Virtual Machine is almost here. Come celebrate this momentous occasion and launch your first FVM application alongside hundreds of developers worldwide. Complete with talks and workshops from ecosystem leaders like Filecoin founder Juan Benet, get ready to explore the frontier of web3 and win over $150,000+ in prizes.


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In this video we walk through how to make your very own open source Text to Image script (stable diffusion on a GPU) and how to run it on Bacalhau - the decentralised computation platform.

This example aims to show how easy and efficient it is to analyse large datasets with Bacalhau - you do not need any prior knowledge of data science or machine learning to build along with us here!

This is example is built in python using the Tensorflow machine learning library and based on stable diffusion for text to image processing and aims to inspire you to build your own models to run on Bacalhau! Feel free to 'show us what you got' by connecting with us in Slack!

Full example documentation can be found here:
👉 https://docs.bacalhau.org/examples/model-inference/stable-diffusion-gpu/


00:00 Intro: Building a Text to Image Model with Stable Diffusion
01:05 The Text to Image Model in Action!
04:45 Why Build with Bacalhau?
10:45 Bacalhau & the Filecoin Virtual machine (FVM / FEVM)
11:00 Bacalhau Architecture & Job lifecycle
14:10 Machine Learning & Stable Diffusion Primer
16:25 Let's code! Setup
17:25 Building & Testing the Text to Image Scripts on Google Collab
21:50 A Great Dane in Paris
23:00 Dockerising the build
23:30 Running our open source DALL-E model on Bacalhau
26:10 Pizza with no topping
27:10 Get in touch & stay updated!

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About Bacalhau:

Currently Filecoin is known for being a decentralised storage and retrieval network, providing over 17 EiB of distributed data storage capacity to the world through thousands of Storage providers globally.

We can think of this distributed storage layer of Filecoin as the Layer 0, while the ability to perform on-chain computation - or computation over state with FVM brings Layer 1 capabilities to the Filecoin stack.
Bacalhau then brings the additional capability for off-chain verifiable compute loads on large data to the Filecoin Network.. Making for some powerful tools enabling new and innovative applications to arise.

Bacalhau is a platform for faster, cost efficient, and more secure distributed computation, by running jobs next to where the data is generated and stored. Bacalhau enables users to run arbitrary Docker containers and WebAssembly (WASM) images as tasks, meaning little (or no) rewriting of the workflows that already work.

Why Bacalhau?
⚡ Process jobs fast: Jobs in Bacalhau are processed where the data was created and all jobs are parallel by default.
💰 Low cost: You get to save on ingress/egress fees you encounter whenever you move data around since jobs are processed where the data is created, as well as reusing idle computation (where available)
🔒 Secure: Data is not collected in a central location before processing, meaning all scrubbing and security can be applied at the point of collection, and a far more granular, code-based permission model.

What will you build with Bacalhau??

Links:
🌐 See more examples on the docs: https://docs.bacalhau.org
🦄​ Follow our twitter @BachalauProject
👨‍👩‍👦‍👦 Join the chat: #bacalhau on the Filecoin Slack Channel (visit filecoin.io to join)