Learn about DotSlash, a tool that simplifies executable deployment by combining a fast Rust program with a JSON manifest. Discover the differences between DotSlash and other deployment methods like LFS and buck2 run. Hear about where DotSlash is used at Meta and how it improves tool distribution.

Discussing Python 3.12 new features contributed by Meta like custom JITs, type system improvements, and faster comprehensions. Exploring the challenges of upstreaming changes, including Cinder's impact on machine learning. Insights on Python performance enhancements, upcoming features, and managing API changes within tech companies.

In this episode, Pascal interviews Devi, an AI research director at Meta, about the history of AI at Meta and their unique approach to developing and using AI. They discuss topics such as the difference between AI and ML, deep learning and LLMs, Meta's open approach to AI, and exciting future AI developments. They also mention recent product launches, including Meta AI agents and personalized AI assistants.

We’re jumping into our time machine and going back to 2018 for an interview with Will B. about the various twists and turns that led to the creation of Instagram Stories. We will be back with a fresh interview next month. Got feedback? Send it to us on Threads (https://threads.net/@metatechpod), Twitter (https://twitter.com/metatechpod), Instagram (https://instagram.com/metatechpod) and don’t forget to follow our host @passy (https://twitter.com/passy, https://mastodon.social/@passy, and https://threads.net/@passy_). Fancy working with us? Check out https://www.metacareers.com/. Links Rebound: https://github.com/facebookarchive/rebound Origami Studio: https://origami.design/ Timestamps Intro 0:06 Will Bailey 1:14 Early FB iOS app 7:16 Release Trains 11:52 The End of HTML5 13:29 Migration to Native 16:05 Facebook Home 17:02 Design Collaboration 22:03 Instagram 26:33 Slingshot 27:57 Instagram for Android 29:54 Instagram Stories 35:37 Rebound 41:25 Outro 44:41  

Python at Meta is huge. Not only does it famously power Instagram's backend, but it underpins our configuration systems, much of our AI work and many services. Amethyst joins Pascal for this episode of the Meta Tech Podcast to talk about how the Python Foundation Team works to improve the developer experience of everyone working with Python at Meta and Fixit 2, the freshly open-sourced linter framework built on top of libcst. Got feedback? Send it to us on Threads (https://threads.net/@metatechpod), Twitter (https://twitter.com/metatechpod), Instagram (https://instagram.com/metatechpod) and don’t forget to follow our host @passy (https://twitter.com/passy, https://mastodon.social/@passy, and https://threads.net/@passy_). Fancy working with us? Check out https://www.metacareers.com/. Links Fixit 2 announcement post: https://engineering.fb.com/2023/08/07/developer-tools/fixit-2-linter-meta/ Fixit: https://fixit.readthedocs.io µfmt: https://ufmt.omnilib.dev µsort: https://usort.readthedocs.io LibCST: https://libcst.readthedocs.io 5 Things You Didn’t Know About Buck2: https://engineering.fb.com/2023/10/23/developer-tools/5-things-you-didnt-know-about-buck2/ Scheduling Jupyter Notebooks at Meta: https://engineering.fb.com/2023/08/29/security/scheduling-jupyter-notebooks-meta/ Timestamps Intro 0:06 Intro Amethyst 1:57 Production vs Software Engineering 3:41 PE for language teams 5:40 Python at Meta 6:58 Python3 migration 10:15 Projects on the Python Foundation Team 16:30 libcst and codemods 21:55 What Python looks like at Meta 25:53 Meta's involvement in the Python community 30:30 The importance of lints at Meta 35:13 Why another linter? 39:11 Favourite lint 46:26 Outro 48:17 Bloopers 48:54

Learn about the rapid rise of Threads from idea to 100M users in 5 months. Engineers share challenges faced in backend, iOS, and Android development. Insights on building on top of Meta's infrastructure, code sharing, and favorite moments from the journey.

Two software engineers at Meta, Katherine and Dustin, discuss the challenges and benefits of shipping code at Meta. They cover topics such as monorepos, pre-commit code review, and CI infrastructure. They also talk about the life of a diff, writing bots to write code, finding reviewers, and maintaining stability. The episode provides insights into Meta's code development process and the importance of code review and testing.

In April, WhatsApp announced the launch of a new cryptographic security feature to automatically verify a secured connection based on key transparency. Key transparency helps strengthen the guarantee that end-to-end encryption provides to private, personal messaging applications in a transparent manner available to all. Rolling out a feature like this to WhatsApp's user base is not a small feat and requires some clever engineering to scale to the billions of users relying on WhatsApp to stay in touch with friends, family and business. Pascal is joined by Sean and Kevin to discuss what Key Transparency means in practice and the various challenges they encountered as they scaled it up to billions of users. Got feedback? Send it to us on Threads (https://threads.net/@metatechpod), Twitter (https://twitter.com/metatechpod), Instagram (https://instagram.com/metatechpod) and don’t forget to follow our host @passy (https://twitter.com/passy, https://mastodon.social/@passy, and https://threads.net/@passy_). Fancy working with us? Check out https://www.metacareers.com/. Links Infer: https://fbinfer.com/ Infer on GitHub: https://github.com/facebook/infer MTP Episode 18 about Infer: https://pca.st/5U9V Deploying key transparency at WhatsApp - Engineering at Meta: https://engineering.fb.com/2023/04/13/security/whatsapp-key-transparency/ GitHub - facebook/akd: An implementation of an auditable key directory: https://github.com/facebook/akd/  Parakeet: Practical Key Transparency for End-to-End Encrypted Messaging: https://www.ndss-symposium.org/ndss-paper/parakeet-practical-key-transparency-for-end-to-end-encrypted-messaging/  SEEMless: Secure End-to-End Encrypted Messaging with less trust: https://eprint.iacr.org/2018/607 Coniks: Bringing Key Transparency to End Users: https://www.usenix.org/conference/usenixsecurity15/technical-sessions/presentation/melara  IETF Working Group on Key Transparency: https://datatracker.ietf.org/wg/keytrans/about   Timestamps Intro 0:06 News Update: Infer turns 10 1:34 Interview Intro 4:27 Intro Kevin 4:45 Intro Sean 6:07 WhatsApp's mission 6:47 PETs 7:58 E2E basics 8:59 Key transparency 10:32 Crypto community response 18:20 End-user changes 19:57 Technical challenges and zero-knowledge proofs 23:18 AKD 28:27 Internal deployment 32:02 Outro 42:16 Bloopers 43:05

Red Team X is a security team at Meta that is responsible for finding and exploiting vulnerabilities in third-party products that could impact Meta's own security. The team acts as a hybrid between a traditional red team, which focuses on probing their own organisation's systems and products for vulnerabilities, and an elite bug-hunting group. The team was founded by Vlad I. in 2020 when the pandemic and the sudden shift to Work From Home challenged various previously-held assumptions about security. In his discussion with Pascal, Vlad explains the roles of different security teams within Meta, how they go about prioritising the highest-impact targets to exploit and how they work with vendors to ensure not just Meta but the entire world benefits from the fixes produced. Got feedback? Send it to us on Twitter (https://twitter.com/metatechpod), Instagram (https://instagram.com/metatechpod) and don’t forget to follow our host @passy (https://twitter.com/passy and https://mastodon.social/@passy). Fancy working with us? Check out https://www.metacareers.com/.   Links: The Diff episode about Velox: https://thediffpodcast.com/docs/episode-17 Risky Business Podcast: https://risky.biz/ RTX Blog: https://rtx.meta.security RTX Disclosures: https://rtx.meta.security/bugs RTX in WIRED: https://www.wired.com/story/facebook-red-team-x-vulnerabilities/   Timestamps: Intro 0:06 Vlad Intro 1:55 Red Teaming 2:43 Staying up-to-date 6:34 Different team colours 10:02 Defence-in-depth 12:44 Red Team X 15:57 Hardware v Software 19:43 Focus areas 21:29 Prioritising requests 22:44 Notable RTX Disclosures 26:05 Vulnerability disclosure policy 28:52 Getting into offensive security 38:48 Outro 40:51  

PyTorch is now one of the most popular machine learning frameworks out there but that was not a foregone conclusion when it was released in 2016. Our host Pascal is joined by Suraj, a developer advocate here at Meta, to dissect the history of PyTorch and look at the factors that contributed to its success. That includes understanding your target audience, maintaining backwards compatibility, fostering a helpful community and so much more.  You don't need to be an expert in PyTorch to enjoy the discussion as Suraj explains all the basics. Got feedback? Send it to us on Twitter (https://twitter.com/metatechpod), Instagram (https://instagram.com/metatechpod) and don’t forget to follow our host @passy (https://twitter.com/passy and https://mastodon.social/@passy). Fancy working with us? Check out https://www.metacareers.com/.   Links: Meta Open Source Blog: Creating Safe Spaces for Underrepresented Individuals in Open Source Communities - https://developers.facebook.com/blog/post/2023/05/31/creating-safe-spaces/  PyTorch Developer Podcast - https://pytorch-dev-podcast.simplecast.com/ PyTorch - https://pytorch.org/  PyTorch on GitHub - https://github.com/pytorch/pytorch Announcing the PyTorch Foundation: A new era for the cutting-edge AI framework - https://ai.facebook.com/blog/pytorch-foundation/   Timestamps: Intro 0:05 Suraj Intro 1:52 What is PyTorch? 4:39 History of PyTorch 5:33 Choosing a Target Audience 7:27 Python and Performance 11:20 Design Decisions 19:04 OSS Governance and Community 21:11 PyTorch 2.0 25:47 How to get started 28:32 Outro 30:14 Bloopers 32:16