Brooke Hartley May lives in Oakland, California, on the East Bay, claiming to get more sunshine than her neighbors in San Francisco. She was a history major in college, which makes her path to technology a bit different. She still enjoys writing and reading in long form to this day. Outside of tech, she is married with a 4 year old son - and a pug. She enjoys life as a parent, startup founder, but was sad that the Oakland A's left Oakland, amongst other teams.
A few years ago, Brooke and her now co-founder observed that people were viewing AI as this end-all-be-all solution. But what quickly happened was that the data needed to make AI effective was not in quite the same state.
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Brian #1: Free-threaded Python no longer “experimental” as of Python 3.14
“PEP 779 ("Criteria for supported status for free-threaded Python") has been accepted, which means free-threaded Python is now a supported build!” - Hugo van Kemenade
As noted in the discussion of PEP 779, “The Steering Council (SC) approves PEP 779, with the effect of removing the “experimental” tag from the free-threaded build of Python 3.14.”
We are in Phase II then.
“We are confident that the project is on the right path, and we appreciate the continued dedication from everyone working to make free-threading ready for broader adoption across the Python community.”
“Keep in mind that any decision to transition to Phase III, with free-threading as the default or sole build of Python is still undecided, and dependent on many factors both within CPython itself and the community. We leave that decision for the future.”
How long will all this take? According to Thomas Wouters, a few years, at least: “In other words: it'll be a few years at least. It can't happen before 3.16 (because we won't have Stable ABI support until 15) and may well take longer.”
typed-ffmpeg offers a modern, Pythonic interface to FFmpeg, providing extensive support for complex filters with detailed typing and documentation.
Inspired by ffmpeg-python, this package enhances functionality by addressing common limitations, such as lack of IDE integration and comprehensive typing, while also introducing new features like JSON serialization of filter graphs and automatic FFmpeg validation.
Features :
Zero Dependencies: Built purely with the Python standard library, ensuring maximum compatibility and security.
User-Friendly: Simplifies the construction of filter graphs with an intuitive Pythonic interface.
Comprehensive FFmpeg Filter Support: Out-of-the-box support for most FFmpeg filters, with IDE auto-completion.
Integrated Documentation: In-line docstrings provide immediate reference for filter usage, reducing the need to consult external documentation.
Robust Typing: Offers static and dynamic type checking, enhancing code reliability and development experience.
Filter Graph Serialization: Enables saving and reloading of filter graphs in JSON format for ease of use and repeatability.
Graph Visualization: Leverages graphviz for visual representation, aiding in understanding and debugging.
Validation and Auto-correction: Assists in identifying and fixing errors within filter graphs.
Input and Output Options Support: Provide a more comprehensive interface for input and output options, including support for additional codecs and formats.
Partial Evaluation: Enhance the flexibility of filter graphs by enabling partial evaluation, allowing for modular construction and reuse.
Media File Analysis: Built-in support for analyzing media files using FFmpeg's ffprobe utility, providing detailed metadata extraction with both dictionary and dataclass interfaces.
“When working with Django applications, it's common to have a mix of fast unit tests and slower end-to-end (E2E) tests that use pytest's live_server fixture and browser automation tools like Playwright or Selenium. ”
Tim is running E2E tests last for
Faster feedback from quick tests
To not tie up resources early in the test suite.
He did this with
custom “e2e” marker
Implementing a
pytest_collection_modifyitems
hook function to look for tests using the
live_server
fixture, and for them
automatically add the e2e marker to those tests
move those tests to the end
The reason for the marker is to be able to
Just run e2e tests with -m e2e
Avoid running them sometimes with -m "not e2e"
Cool small writeup.
The technique works for any system that has some tests that are slower or resource bound based on a particular fixture or set of fixtures.
Dr. David Bray, Former Chief Information Officer of the Federal Communications Commission and CEO at Lead Do Adapt Ventures, and the Honorable Ellen McCarthy, former Assistant Secretary of State for the Bureau of Intelligence and Research join the show for a candid, wide-ranging conversation about the evolving landscape of data, digital trust, and national security. We unpack how the explosion of connected devices, AI-generated content, and synthetic data is reshaping decision-making, security, and public trust at every level of government and society and explore challenges from authenticating digital content to decentralizing emergency response, and the urgent need to empower individuals and local communities in the face of complex, rapidly changing information ecosystems.
Terence Tao is widely considered to be one of the greatest mathematicians in history. He won the Fields Medal and the Breakthrough Prize in Mathematics, and has contributed to a wide range of fields from fluid dynamics with Navier-Stokes equations to mathematical physics & quantum mechanics, prime numbers & analytics number theory, harmonic analysis, compressed sensing, random matrix theory, combinatorics, and progress on many of the hardest problems in the history of mathematics.
Thank you for listening ❤ Check out our sponsors: https://lexfridman.com/sponsors/ep472-sc
See below for timestamps, transcript, and to give feedback, submit questions, contact Lex, etc.
OUTLINE:
(00:00) – Introduction
(00:36) – Sponsors, Comments, and Reflections
(09:49) – First hard problem
(15:16) – Navier–Stokes singularity
(35:25) – Game of life
(42:00) – Infinity
(47:07) – Math vs Physics
(53:26) – Nature of reality
(1:16:08) – Theory of everything
(1:22:09) – General relativity
(1:25:37) – Solving difficult problems
(1:29:00) – AI-assisted theorem proving
(1:41:50) – Lean programming language
(1:51:50) – DeepMind’s AlphaProof
(1:56:45) – Human mathematicians vs AI
(2:06:37) – AI winning the Fields Medal
(2:13:47) – Grigori Perelman
(2:26:29) – Twin Prime Conjecture
(2:43:04) – Collatz conjecture
(2:49:50) – P = NP
(2:52:43) – Fields Medal
(3:00:18) – Andrew Wiles and Fermat’s Last Theorem
(3:04:15) – Productivity
(3:06:54) – Advice for young people
(3:15:17) – The greatest mathematician of all time
Ranjan Roy from Margins is back for our weekly discussion of the latest tech news. We cover: 1) Sam Altman's 'Gentle Singularity' essay 2) Is Altman overhyping the technology's current capabilities 3) Why the next few years may see crazy AI development 4) The case for and against humanoid robots 5) OpenAI's o3 pro model and the value of tool use 6) Meta's acquihire-zition of ScaleAI and founder Alexandr Wang 7) The case for the move and the rationale behind Zuck's aggressiveness 8) MetaAI posts 'private' conversations 9) Google traffic to web publishers falls off a cliff -- here's the data. 10) The burning of the Waymos 11) Alex fight robots
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Questions? Feedback? Write to: bigtechnologypodcast@gmail.com
Yaroslav Lazor started writing code when he was 10 years old. It took him a while to understand that making a difference in the world wasn't just about writing code - but he has arrived there these days. He is the father of 4 daughters, 2 of which are artists and a couple who are digging into their entrepreneurial roots with running their own lemonade stand. He lives in Los Angeles, and has learned to be a better person through pushing himself as a founder.
Sergiy Korolov also started coding when he was young, though 4 years later than Yaroslav. He went to a technical university, and as his career in leadership grew, the number of lines of code he contributed to decreased. He is located in Poland, and loves to snowboard in the winter, and bike in the summer. He has 3 kids, and recently started teaching coding to his oldest son.
Yaroslav & Sergiy were building software for clients, the typical Ukrainian software route. Over time, they realized that building their own products was the best way to make an impact - so much so, that they decided to start building their own.
M.G. Siegler is the author of Spyglass. He joins Big Technology to discuss Apple’s subdued WWDC and whether it signals deeper trouble with AI's capabilities. Tune in to hear a breakdown of Apple’s “UI over AI” approach, whether the company can pull off the Apple Intelligence vision at all, and if Liquid Glass is a redesign destined to fail. We also cover the vibes at the conference and the state of Apple today. Hit play for clear-eyed, no-nonsense analysis of the tech world’s biggest stories.
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Enjoying Big Technology Podcast? Please rate us five stars ⭐⭐⭐⭐⭐ in your podcast app of choice.
Want a discount for Big Technology on Substack? Here’s 25% off for the first year: https://www.bigtechnology.com/subscribe?coupon=0843016b
Questions? Feedback? Write to: bigtechnologypodcast@gmail.com
Yaroslav Lazor started writing code when he was 10 years old. It took him a while to understand that making a difference in the world wasn't just about writing code - but he has arrived there these days. He is the father of 4 daughters, 2 of which are artists and a couple who are digging into their entrepreneurial roots with running their own lemonade stand. He lives in Los Angeles, and has learned to be a better person through pushing himself as a founder.
Sergiy Korolov also started coding when he was young, though 4 years later than Yaroslav. He went to a technical university, and as his career in leadership grew, the number of lines of code he contributed to decreased. He is located in Poland, and loves to snowboard in the winter, and bike in the summer. He has 3 kids, and recently started teaching coding to his oldest son.
Yaroslav & Sergiy were building software for clients, the typical Ukrainian software route. Over time, they realized that building their own products was the best way to make an impact - so much so, that they decided to start building their own.
