PodQueue

This is the slightly edited version of our with film director, producer, screenwriter, rapper, and communist Boots Riley. He is the lead vocalist of the musical groups The Coup and Street Sweeper Social Club. He wrote and directed the film Sorry to Bother You and is the creator and director of the television series I’m A Virgo.  We talked to Boots Riley about the recent labor upsurge, including the wave of strikes and increasing militancy among workers in the US. We briefly discuss United Auto Workers’ call for a ceasefire in the war on Gaza and establishment of a Divestment and Just Transition working group.  We also discuss navigating the capitalist film and television industry as a communist and possibilities for organizing among creatives. Boots also answers some questions about making anticapitalist art including some behind the scenes insights from I’m A Virgo. We want to shout-out Boots Riley for joining us for this discussion and definitely recommend I’m A Virgo if people haven’t watched it yet. I also want to say there’s some really special content we released in the month of December on our YouTube channel. Including our conversation with and our with several comrades of his and movement elders including Ashanti Alston, David Gilbert, dequi kioni-sadiki, Matt Meyer, Meg Starr, & Bilal Sunni-Ali so if you haven’t checked that out yet, make sure you do at. This will be our final episode released in 2023. We have a ton of stuff already being edited for release for 2024. This year we released 67 audio episodes, 26 livestreams and our content was listened to or watched over 640,000 times. We’re proud of that, and we’re also proud that our programs are still entirely dependent upon regular folks like yourself who listen and watch the work we put out. Today is your last day of 2023 to support us and that would be much appreciated, but also we hope many of you who have not become patrons of the show yet will do so in 2024. And we want to profusely thank everyone who supported us in 2023 for making the show possible for another year. You can support us at This episode was co-edited and co-produced by Aidan Elias and Jared Ware

Ted Young Talks about 'Human Learning: How We Learn & Why it Matters' at https://SiliconValley-CodeCamp.com in San Jose Hosted by PayPal

Understanding how humans learn helps us inform, teach, and communicate better. Find out how to apply research to create better docs, videos, and presentations.

Session Details:

https://SiliconValley-CodeCamp.com/Session/2018/human-learning-how-we-learn-why-it-matters

Session Materials:

https://www.tedmyoung.com/human-learning-talk-svcc/

Silicon Valley Code Camp site:

https://SiliconValley-CodeCamp.com

Subscribe to the Silicon Valley Code Camp Youtube Channel

https://www.youtube.com/c/SiliconValleyCodeCampVideos

Follow Silicon Valley Code Camp on Twitter: https://twitter.com/sv_code_camp

Join the Silicon Valley Code Camp G+ community: https://plus.google.com/110656351842726857531

Human Learning: How We Learn & Why it Matters at Silicon Valley Code Camp 2018

Follow Ted Young on Twitter: https://twitter.com/jitterted

Speaker Biography for Ted Young

Java Trainer and Coding Coach, specializing in Java, Spring, Object-Oriented Programming, and TDD. Create and deliver customized learning experiences for developers.

Learn what makes the programming language Rust a unique technology, such as the memory safety guarantees that enable more people to write performant systems-level code. Scott talks to Rust core contributor Carol Nichols about what she's so excited about Rust and the future.

Wes McKinney makes the case for a shared infrastructure for data science, discusses the open source community's efforts on Apache Arrow, and offers a vision for seamless computation and data sharing across languages.

Subscribe to O'Reilly on YouTube: http://goo.gl/n3QSYi

Follow O'Reilly on

Twitter: http://twitter.com/oreillymedia

Facebook: http://facebook.com/OReilly

Google: http://plus.google.com/+oreillymedia

Join us for a conversation on the seedy underside to Tech’s past, present, and future.

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If the industry’s most credulous boosters are to be taken at their word, the contemporary tech industry is an economic freight train driven by big-brained disrupters who are charting a path toward a future of mutual prosperity, boundless leisure, and unfettered innovation. But in recent years some of the luster has come off of Tech’s carefully crafted reputation—thanks to stories of self-combusting cars, high-profile fraud convictions, and other headline grabbing fiascos. Just how much bluff and bluster, not to mention skeletons, lay buried beneath Silicon Valley’s idyllic hills? And what does a future without cheap credit and greatly diminished credibility mean for the tech industry?

For this event, Malcolm Harris, author of Palo Alto: A History of California, Capitalism, and the World will be conversation with Timnit Gebru, found and executive director of the Distributed Artificial Intelligence Research Institute (DAIR).

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Timnit Gebru is the founder and executive director of the Distributed Artificial Intelligence Research Institute (DAIR). Prior to that she was fired by Google in December 2020 for raising issues of discrimination in the workplace, where she was serving as co-lead of the Ethical AI research team. She received her PhD from Stanford University, and did a postdoc at Microsoft Research, New York City in the FATE (Fairness Accountability Transparency and Ethics in AI) group, where she studied algorithmic bias and the ethical implications underlying projects aiming to gain insights from data. Timnit also co-founded Black in AI, a nonprofit that works to increase the presence, inclusion, visibility and health of Black people in the field of AI, and is on the board of AddisCoder, a nonprofit dedicated to teaching algorithms and computer programming to Ethiopian highschool students, free of charge.

Malcolm Harris is a freelance writer and the author of Palo Alto: A History of California, Capitalism, and the World, Kids These Days: The Making of Millennials, and Shit is Fucked Up and Bullshit: History Since the End of History. He was born in Santa Cruz, CA and graduated from the University of Maryland.

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This event is sponsored by Haymarket Books. While all of our events are freely available, we ask that those who are able make a solidarity donation in support of our important publishing and programming work.

Introduction Welcome to this deep dive into the world of Large Language Models (LLMs) and vector databases for the Crazy Wisdom Podcast. Our guest today is Eden Marco (), a Customer Engineer at Google Cloud and a best-selling Udemy instructor with a passion for General Artificial Intelligence (GenAI). In this episode, we unpack the complexities and intricacies of LLMs, explore the role of vector databases, and discuss the future of autonomous agents and machine learning. Key Discussion Points Vector Databases & Similarity Search: Vectors play a critical role in similarity searches, a common use case in vector databases. These databases are pivotal in developing LLMs and help in getting the right context to prompts. They are also used to truncate long pieces of text into paragraphs for vector outputs. Understanding LLMs and Context: How does an LLM answer questions about things it hasn't been trained on? The answer lies in in-context learning. We delve into the main problems LLMs face in understanding context and the role of vector stores in this process. LLMs and Long Term Memory: We discuss the concept of coreference resolution in LLMs, the issue of growing queries due to token limitations, and techniques to handle these challenges. Eden explains the human-like behavior of LLMs and how autonomous agents interact with other agents using memory as context. Prompt Engineering & Autnomous Agents: What is sophisticated prompt engineering? It's the art of getting the LLM to do what you want. We explore autonomous agents with Langchain, the process of augmenting prompts, and the growing importance of prompt engineering. Human Simulation & Machine Learning: Despite advancements, a real human simulation remains distant. We touch upon the statistical nature of machines and humans and discuss whether machine learning could be considered a parasite in the digital ecosystem. Twitter API & Coding: We discuss the implications and challenges of using Twitter's API for scraping tweets, and how coding can be used to overcome limitations and navigate permissions. Chroma - A Vector Database: An introduction to Chroma, a vector database that facilitates in-context learning and filtering. Eden sheds light on the competitive vector database market, the benefits of using managed servers, and the potential of combining vector databases with relational ones for enhanced utility. Long Term Memory and Scaling Databases: We discuss the potential of using vector databases for long term memories, the importance of cataloging memories, and the ease of scaling databases with cloud services. People to Follow: Hari Sanchez, co-founder, and creator of the Langchain framework, is a must-follow for anyone interested in long-term memory and LLMs. The Gap in Machine Learning: We wrap up the discussion with insights into how the gap between machine learning programmers, data scientists, and PhDs has been bridged, and the potential future of open-source models in the face of state-of-the-art LLMs. Websites & Resources Mentioned : A resource that describes how LLMs think. : A comprehensive course by Eden Marco on GenAI. by Hari Sanchez: A groundbreaking framework for autonomous agents. : Stay updated with Eden's latest insights and work.  

Maintaining OpenStreetMap.org

Andy Allan

I volunteer as a maintainer for the "openstreetmap-website" project - the open-source code that powers the website, the API and the core database for OpenStreetMap. But what exactly does being a maintainer involve?

In this talk I'll be showing you behind the scenes. What do I work on in a typical week? How do I choose what to do? What makes a topic worth working on? How do I deal with the endless backlog of open issues and pull requests?

I'll also be delving into some recent changes that we've made, along with giving you some inspiration to get you involved in the translation, design, and development work.

In the mythology of open source, programming languages are created by people who seemingly have no direct economic function. They are just really good at compilers (somehow) and have a house to live in (somehow) and have a lifetime to devote to creating a useful programming language (somehow!)

We will examine specific organizations that create programming languages. Where do the salaries for compiler engineers come from? How does Go end up with 5 engineers and Dart end up with 30? Who signs off on these expenses and why? Does this put any boundaries on language design or development practices? And how do the economics work for people outside of the major tech corporations?

My goal is to give the talk I needed to hear 10 years ago when I was just starting on Elm. By clearly delineating the many variations of corporate funding and independent funding, I hope users will come away with a better foundation for evaluating and comparing programming languages.

Evan Czaplicki

Creator of Elm

@evancz

Evan is the creator and developer of the Elm programming language. He lives in Denmark, working alongside his wife at elm.studio to keep Elm independent and interesting.

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Recorded Sept 22, 2023 at Strange Loop 2023 in St. Louis, MO.

https://thestrangeloop.com

Clay Shirky, “Living with AI Discombobulation” hosted by HLS and Ostrom Workshop

Small technological changes can make life better or worse. Anti-lock brakes are good, robocalls bad. Big changes – automobiles, the internet, smartphones, now AI – make life weirder. With large-scale change, it becomes impossible to say if things have gotten better or worse, because the technology upends old benchmarks.

Generative AI can easily generate office memos or spam. However, it can also clone voices, evolve behaviors, confidently explain non-existent memes, and create pictures of the Pope rocking a white puffer good enough to fool people.

Away from the ‘3 day workweek/AI will kill us all’ predictions, the most surprising near-term uses of AI will not be good or bad so much as discombobulating. What can we expect in a world where unexpected new skills have become widely available?

What is AI? A dominant view describes it as the quest "to solve intelligence"—a solution supposedly to be found in the secret logic of the mind, such as in its complex neural networks. Matteo Pasquinelli argues, to the contrary, that the inner code of AI is shaped not by the imitation of biological intelligence, but the intelligence of labour and social relations. Here he is interviewed by Richard Hames, audio producer at Novara Media.

Matteo Pasquinelli's new book, The Eye of the Master: A Social History of Artificial Intelligence, is out now: https://www.versobooks.com/en-gb/products/735-the-eye-of-the-master?utm_source=youtube&utm_medium=social&utm_campaign=verso_video&utm_content=the_eye_of_the_master

Matteo Pasquinelli is associate professor in Philosophy of Science at the Department of Philosophy and Cultural Heritage at Ca’ Foscari University in Venice. His writing has appeared in AI and Society, e-flux, Multitudes, Radical Philosophy, and the South Atlantic Quarterly, amongst other journals.

0:00 Intro

0:39 What is an algorithm

6:03 Algorithms are social not natural

8:56 Large language models (ChatGPT)

13:09 AI and the social division of labour

16:26 Babbage and machines

18:00 IQ tests and psychometrics

19:39 AI and automation

26:39 All labour is logic

29:30 Measuring intelligence is reductive

35:07 What is the political response? Provincialising AI

37:59 AI as a snapshot

43:32 AI vs actual humanity

45:41 Connectionism and AI utopianism

49:58 Research, regulation and risk