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 In the Compute-Over-Data track at the [2022 IPFS Camp](https://2022.ipfs.camp/), we heard from several projects and lots of people on how the landscape of computing is evolving, and how we believe computing can become refocused and more powerful by embracing content addressing and a “merkle-native” way of doing things. In this post, we’ll do a quick recap of what was covered.
 
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 [Content-addressing](https://proto.school/content-addressing/) and the use of [merkle datastructures](https://en.wikipedia.org/wiki/Merkle_tree) – identifying data by a cryptographic hash – is already a well-known revolution of how data structures can be designed for decentralization, bringing benefits like verifiability, naturally coordination-free data deduplication, and so forth. In examining content-addressed computing, and looking for ways to embrace computing over content-addressed data (sometimes referred to in this community as compute-over-data for short), we look at how we can bring those virtues of verifiability and decentralization to data _processing_ as well as data storage and transport (where content-addressing has already become near-ubitiquous in any modern protocol design), and we look for what new virtues we can discover that are unlocked by giving computations predictable coordination-free identifers.
 
 A wide range of projects exist in this space! In the videos of the event, you’ll find presentations of projects that are ranging in focus from linux containers and how to unify them with content-addressed storage, all the way to new bytecode VMs which have direct integrations to content-addressed storage and content-addressed code execution primitives. You’ll find approaches to scaling and approaches to user adoption which range from developer-centric build tools, all the way to projects with a focus on massively scaled parallelized compute job scheduling. And you’ll find exploration of virtues of developing systems with computation-addressable primitives, ranging from software security and reproducible builds, to public verifiability, to sheer scaling.