 Yeah, so I'm I'm a lot different than a lot of people here and then I've spent the last Decade working pretty close to the metal building libraries to process tabular data sets So I started the Python pandas project in 2008 and I've been working in the Python ecosystem You know basically since then So one of the problems that I've been spending a lot of my time on is technology to enable better code reuse and easier System interoperability and data sharing so one of the primary artifacts is a project. We've been building called Apache arrow, which is broadly speaking an open standard for data frames where there was none before that So I don't have time to go through all this, but there's good reason to create open standards We have a lot of them for you know stuff like JSON and XML and HTML and so forth But in the space of data processing we have some standards for data storage But relatively little in in memory data processing and so you know particularly with the way that hardware is changing Data is moving from disk to memory And so when two systems can't work on the same data set without serializing you have this This friction whenever you want to use two tools to perform Some some science so my goal is to make the ecosystem data science less fragmented but also to enable collaboration to happen between the database world and the data but in the data science world We're in the past there really hasn't been a basis for any collaboration to happen between those these two worlds of Engineering so at a high level The goal is to create portable data frames where we have we say data frame, but if you look at Python pandas are Various table data structures and Java. There's Julia data frames, you know, there's data frames and go Internally the architecture and design of those those objects is completely different. So the goal is to define a cross a language independent standard for arranging the data and memory, so Essentially, we're trying to Deconstruct the analytic database and create reusable libraries that could be used in many different domains. So you constructed food Anyway, so We're building implementations and lots of languages So I don't know if you're involved in building data processing systems But the way that you can help me and people like me that are doing low level systems work Is if you encounter people building computational systems for for data science And they are not using open standards to make them aware that there are people that are working on open standards and see if there's a way for them to At least make their use cases and their needs aware to us so that we can take them into account and our design and implementation implementation process So collaborating with some fine folks here at Berkeley, you know, lots of different folks involved at this point But we're always looking to bring more people into the into the community Thanks