List of texts / podcast that caught my attention this year (2023 edition).

1. JAN 2023

1.1. GitHub Copilot preliminary experience report

  • Notes on Experience with Github Pilot, similar to that of mine - it has the potential to surprise you, which is great.

    I was, frankly, stunned. While I do understand that Copilot doesn’t actually understand the code it suggests, Hedgehog is sufficiently esoteric that I didn’t expect Copilot to have enough training data to enable it to make a useful contribution in this niche. I was wrong. I’ve repeatedly seen Copilot make suggestions to my F# and Haskell code. It’s not just for C#, JavaScript, or python code.

1.2. Free YouTube Transcripts

1.3. imaginAIry/ at master · brycedrennan/imaginAIry

1.4. Overconfidence and AI

  • My friend told me “AI is bullshitting a lot” which Seth Godin kindly frames as overconfidence

    Human beings are often more effective when we’re a bit self-effacing. “I think,” “Perhaps,” or “I might be missing something, but…” are fine ways to give our assertions a chance to be considered.

1.5. Fighting Distraction With Unit Tests

1.6. ChatGPT Is Only Going to Get Better, and We Better Get Used to It - Bloomberg

1.7. Key Metrics for Monitoring AWS Fargate

1.8. Amazon ECS container logs for EC2 and Fargate launch types - AWS Prescriptive Guidance

1.9. How to Profile Your Code in Python

1.10. ChatGPT’s killer enterprise use case will be managing knowledge, says EY CTO

1.11. The coming ubiquity - Seth’s Blog

  • On the invisible revolution of making AI everywhere allthetime

    But the real impact of AI isn’t going to be that it regularly and consistently does far better than the best human effort. The impact will be that it is widespread, cheap and always there.

1.12. SQL should be your default choice for data engineering pipelines

  • After a wave of noSQL tools, this is what you get in the beginning of 2023

    SQL should be the first option considered for new data engineering work. It’s robust, fast, future-proof and testable. With a bit of care, it’s clear and readable. A new SQL engine - DuckDB - makes SQL competitive with other high performance dataframe libraries, making SQL a good candidate for data of all sizes.

1.13. dylanjcastillo/shell-genie: Your wishes are my commands

  • Another cool project to get info on AI

    Shell Genie is a command-line tool that lets you interact with the terminal in plain English. You ask the genie what you want to do and it will give you the command you need.

1.14. Natural language is the lazy user interface - Austin Z. Henley

  • A slight critique of chatgpt as an interface as it lacking a big advangates of adaptable GUI.

    People are anticipating that large language models are going to revolutionize the world. And maybe they will. But a chat bot won’t.

1.15. On Email and Horses - Study Hacks - Cal Newport

1.16. The inside story of ChatGPT: How OpenAI founder Sam Altman built the world’s hottest technology with billions from Microsoft

1.17. Oleksiy Danilov interview:

  • n/a

    The West has an old problem: that is fear. The West has always been afraid of the Soviet Union. It believed the USSR was big and powerful and could solve everything quickly through military means. No conclusions were made even after the USSR invaded Afghanistan in 1979. And they couldn’t do anything there against the uneducated, at that moment, the mujahideen. That is when a conclusion should have been made that the USSR is not that powerful.But those conclusions were not made. And the West kept on being afraid.

1.18. Five Days in Class with ChatGPT – The Alperovitch Institute

  • And I say this as somebody who had been a hardened skeptic of the artificial intelligence hype for many years. Note that I didn’t say likely transform. It will transform higher education. Here’s why. The first use-case is that the machine “filters mundane questions,” as one of our students put it quite eloquently. Meaning: you can ask the dumb questions to the AI, instead of in-class. Yes, there are dumb questions—or at least there are questions where the answer is completely obvious to anybody who knows even just a little bit about, say, malware analysis (or has done their assigned readings).


1.19. Get/Want/Have To

  • A poetic approach to a mindset - for a thief of moments for passionate endevours, like reading a book for 5 minutes.

    The magic trick begins with realizing that the get to tasks are priceless want to moments if we choose. And, if we’re careful and plan ahead, we can get to the point where the have to agenda is something we can eagerly look forward to.

1.20. Alex Epstein’s Fossil Future - Marginal REVOLUTION

  • Remember Macaes: Most dangerous political movement in the West today is not populism, post fascism, wokeism… It’s a reflexive contrarianism that affirms the opposite of every sensible opinion. Silicon Valley actually played a role in this. Idolatry of disruption but now out of its element.

    My overall view is this: it is a good rebuttal to “the unrealistic ones,” who don’t see the benefits of fossil fuels. But it does not rebut a properly steelmanned case for a transition away from fossil fuels.I view the steelmanned case as this: we cannot simply keep on producing increasing amounts of carbon emissions for centuries on end. We thus need some trajectory where — at a pace we can debate — carbon emissions end up declining. I’ve stressed on MR many times that climate change is not in fact an existential risk, but it could be a civilization-destroying risk if we just keep on boosting carbon emissions without end. I don’t know a serious scientist who takes issue with that claim.

1.21. Yiren Lu on Twitter: I’ve been playing around with GPT for various use cases. Here are some low-hanging ones I haven’t heard people mention

  • Continuing the discovery of usecases and cultivating the general awareness for the arrival the beast.

    At my agency, a great deal of operational work involves simply taking information from email conversations and inputting them in structured ways into a spreadsheet or web app. This is quite tedious to do, and is prone to errors/missing data. But ChatGPT is pretty good at this!

1.22. javascript - Timestamp of when request was submitted from client - Stack Overflow

2. FEB 2023

2.1. Weaponizing hyperfocus: Becoming the first DevRel at Tailscale

  • A case study of the new concept - devrel

    In Spring 2022, I sat down and started to take DevRel seriously at Tailscale. I had heard about the practice in the past, but I had never done it before. I knew that a lot of it was talking about a product to people and finding new and interesting ways to use it, but a lot of that seemed too vague to really have any solid place to start from. It’s like walking into an empty room and having no idea where to start decorating.At some level though, it felt right for me in a way that I have difficulty describing. It’s the same feeling of it being right that I get from working in software in the first place. It felt like the type of rabbit-hole you could spend an entire career in

2.2. Launch HN: Needl (YC S22) – Simple search across all your apps

  • Cool project, I’ve been looking for this for a long time - but simply not enough. I need to search across at least ZD HC and Github Repos.

    To give generated answers to questions, we take the first results on Needl and run them through GPT-3 and use an engineered version of the user’s query to prompt GPT-3 accordingly. It’s similar to what (Hello Cognition) and do with web search.

2.3. Ask HN: Suggestions for working effectively with junior devs?

  • Thinking about owns dreams? Beware what you wish for.

    The devs on my team are smart but mostly naive about getting stuff done in the real world. I’m sure they’ll figure it out over time. But in the meantime, my days are quite frustrating because I’m in teaching mode most of the time instead of building stuff.Unfortunately you will either need to change your attitude or change teams. In your position, the expectation is that you are mostly a working through others and acting as a force multiplier of their work….And in general, there are two ways to go. The first is to accept the fact that many senior engineering and most staff engineering gigs are more about this kind of mentorship approach than actually doing work. And basically accept that the prime “getting shit done” years of your career are done and you will mostly be working in this new way now.The second is to change jobs where you are back in the driver seat. As a senior engineer, these positions DO exist even at FAANG (over on my team, I am the most junior with 12 years of experience). However, the more senior you get, the harder it is to find a role like this, especially in big tech - its the rare exception. Startups and consulting gigs probably better align with wanting to be hands on keyboard, but at the price of a paycut.

2.4. Responsibility - by Kent Beck

  • Kent Beck always presses for Skin in the Game

    CEO: I take full responsibility for these layoffs.Iñigo Montoya: You keep using that phrase. I do not think it means what you think it means.

2.5. If it helps, this likely is coming. I think we have a tendency to mentally mo

2.6. Google testing ChatGPT-like chatbot ‘Apprentice Bard’ with employees

  • Originally this was ChatGPT Passes Google Coding Interview for Level 3 Engineer with $183K Salary

    underestimate the amount of work needed to make improvements. We’ve been a year away from full self driving cars for the last six years, and it seems like people are getting more cautious in their timing around that instead of getting more optimistic. Robotic manufacturing- driven by AI- was supposedly going to supplant human labor and speed up manufacturing in all segments from product creation to warehousing, but Amazon warehouses are still full of people and not robots.What I’ve seen again and again from people in the field is a gross underestimation of the long tail on these problems. They see the rapid results on the easier end and think it will translate to continued process, but the reality is that every order of magnitude improvement takes the same amount of effort or more.On top of that there is a massive amount of subsidies that go into training these models. Companies are throwing millions of dollars into training individual models. The cost here seems to be going up, not down, as these improvements are made.I also think, to be honest, that machine learning researchers tend to simplify problems more than is reasonable. This conversation started with “highly scalable system from scratch, or an ultra-low latency trading system that beats the competition” and turned into “the parsing of and generation of this kind of code”- which is in many ways a much simpler problem than what op proposed. I’ve seen this in radiology, robotics, and self driving as well.Kind of a tangent, but one of the things I do love about the ML industry is the companies who recognize what I mentioned above and work around it. The companies that are going to do the best, in my extremely bias opinion, are the ones that use AI to augment experts rather than try to replace them. A lot of the coding AI companies are doing this, there are AI driving companies that focus on safety features rather than driver replacement, and a company I used to work for (Rad AI) took that philosophy to Radiology. Keeping experts in the loop means that the long tail isn’t as important and you can stop before perfection, while replacing experts altogether is going to have a much higher bar and cost.

2.7. One dialogue that is missing from the current GPT conversations is about where these technologies will be primarily implemented. There are two places GPTs can be used: Product-level: Implemented within products that companies buy Process-level: Implemented within processes of a company by an analyst – similar to how companies use data analysts today

2.8. Where will the impact of ChatGPT fall? (from my email) - Marginal REVOLUTION

  • An interesting new dimension on ChatGPT Enterprise

    One dialogue that is missing from the current GPT conversations is about where these technologies will be primarily implemented.There are two places GPTs can be used:Product-level: Implemented within products that companies buyProcess-level: Implemented within processes of a company by an analyst – similar to how companies use data analysts todayIf the future has primarily Product-level GPT, then companies like Microsoft clearly win because they have the products (like Teams) where the tech will be embedded and if you want the productivity gains from GPTs you have to go through them.If the future has more Process-level GPT, companies like Zapier and no-code platforms win, because they will be the tools that companies use to implement their custom prompts. (although maybe a “Microsoft Teams Prompt Marketplace” wins as well)

2.9. bash - How to access the metadata of a docker container from a script running inside the container? - Stack Overflow

2.10. ossu/computer-science: Path to a free self-taught education in Computer Science!

2.11. Complete External Attack Surface Management

  • Interesting product for external attack surface detection, testing endpoints with scriptattacks

2.12. The Four Horsemen of the Tech Recession – Stratechery by Ben Thompson

2.13. Anti-pattern - Wikipedia

  • Great metaphor to learn - a warning sign.

    A Big Ball of Mud is a haphazardly structured, sprawling, sloppy, duct-tape-and-baling-wire, spaghetti-code jungle. These systems show unmistakable signs of unregulated growth, and repeated, expedient repair. Information is shared promiscuously among distant elements of the system, often to the point where nearly all the important information becomes global or duplicated.The overall structure of the system may never have been well defined.If it was, it may have eroded beyond recognition. Programmers with a shred of architectural sensibility shun these quagmires. Only those who are unconcerned about architecture, and, perhaps, are comfortable with the inertia of the day-to-day chore of patching the holes in these failing dikes, are content to work on such systems.

2.14. Guido van Rossum: Python and the Future of Programming

2.15. MotherDuck: Big Data is Dead

  • DuckDB is positioning itself for doing analysis on what would previously have been considered “big data” but on your laptop. So, for data scientists who know SQL but prefer R or Python - there are limitations there as both R and Python work in memory (there are workarounds, but they are complicated).

    DuckDB allows you to analyse larger datasets (10-100gb lets say) on your machine with very fast SQL queries - whereas before you would have had to load into your warehouse manually to be able to perform those types of analyses or transformations, adding more boring work for data scientists.DuckDB have also added some really nice improvements to their SQL syntax, making SQL nicer to work with for data scientists who are used to the flexibility R and Python allow them.

2.16. From Bing to Sydney – Stratechery by Ben Thompson

  • Unsure how much this matter, and it may be a fad, but having mainstream debates about sentient AI AND unidentified flying objects within a week is borderline weird.

    Look, this is going to sound crazy. But know this: I would not be talking about Bing Chat for the fourth day in a row if I didn’t really, really, think it was worth it. This sounds hyperbolic, but I feel like I had the most surprising and mind-blowing computer experience of my life today.

2.17. Good times create weak men @

  • The biggest a-ha moment of the talk was that if you are working on Y and Y is based on X, that does not imply automatically that you would know X also. Even if the people who build X are still around, knowledge does not spread automatically and, without actual necessity, it will go away with the people who originally possessed it.

2.18. An example of how to use command-line tools to transcribe a viral video of Cardi B

  • simply a great job here

    nspired by the following exchange on Twitter, in which someone captures and posts a valuable video onto Twitter, but doesn’t have the resources to easily transcribe it for the hearing-impaired, I thought it’d be fun to try out Amazon’s AWS Transcribe service to help with this problem, and to see if I could do it all from the bash command-line like a Unix dork.

2.19. KJF-2023. Day 1. Tyler Cowen. Interview - YouTube

2.20. The Ryan Holiday Reading Recommendation Email -

  • Wonderful Kids Section in abstract principles it contains

    My wife and I re-read This Is Your Time by Ruby Bridges to both boys, which showcases the incredible bravery of the first black child to integrate an all-white elementary school in New Orleans in 1960. This is not the distant path…Ruby Bridges is the same age as my in-laws. We felt it was best to follow that up with another favorite, Each Kindness, and its lesson of how small acts of kindness (like Ruby’s teacher Mrs. Henry) can change the world. My oldest and I just finished the beautiful illustrated version of Harry Potter and the Sorcerer’s Stone (a popular seller last month!). We promised him a lego set from each book, so he was excited to go straight into the next one in the series, Harry Potter and the Chamber of Secrets.

2.21. More alternatives to Google Analytics []

  • Learning about Countly as I’ve had one of their solution architects at home for lunch

    ountly’s basic plugins provide typical analytics metrics such as simple statistics and referrers for web and mobile devices, but also some more advanced features like scheduling email-based reports and recording JavaScript and mobile app crashes. However, its enterprise edition brings in a wide range of plugins (made either by Countly or by third-party developers) that provide advanced features such as HTTP performance monitoring, funnels with goals and completion rates, A/B testing, and so on. Overall, Countly’s community edition is a reasonably rich offering for companies with mobile apps or that are selling products online, and it provides the option to upgrade to the enterprise version later if more is needed.

2.22. command line - How to use Ffmpeg to convert wma to mp3 recursively, importing from txt file? - Ask Ubuntu

2.23. petewarden/spchcat: Speech recognition tool to convert audio to text transcripts, for Linux and Raspberry Pi.

2.24. Transcribe Audio - Python Tutorial

2.25. Transcribing mp3 to text (python) –>

2.26. My excellent Conversation with Will MacAskill - Marginal REVOLUTION

2.27. Text is All You Need - by Venkatesh Rao - Ribbonfarm Studio

  • Almost hegelian definition of personhood as the crucial moment seems to be the moment of Acknowledgement as person ?

    The Copernican MomentSo what’s being stripped away here? And how?The what is easy. It’s personhood.By personhood I mean what it takes in an entity to get another person treat it unironically as a human, and feel treated as a human in turn. In shorthand, personhood is the capacity to see and be seen.This is obviously a circular definition, but that’s not a problem so long as we have at least one reference entity that we all agree has personhood. Almost any random human, like me or you (I’m not entirely sure about a few, but most people qualify), will do. So long as we have one “real person” in the universe, and agree to elevate any entity they treat unironically as a person as also a person, in principle, we can tag all the persons in the universe.In Martin Buber’s terminology (ht Dorian Taylor for suggesting this way of looking at it), X is a person if another person relates to it in an I-you way rather than an I-it way.

2.28. The Sociological Canon, Relations between Theories and Methods, and a Latent Political Structure: Findings from a Survey of Sociology Students in Germany and Consequences for Teaching - Christian Schneickert, Alexander Lenger, Leonie C. Steckermeier, Tobias Rieder, 2019

2.29. The Sociological Canon, Relations between Theories and Methods, and a Latent Political Structure: Findings from a Survey of Sociology Students in Germany and Consequences for Teaching - Christian Schneickert, Alexander Lenger, Leonie C. Steckermeier, Tobias Rieder, 2019

2.30. The Sociological Canon, Relations between Theories and Methods, and a Latent Political Structure

2.31. Presentations — Benedict Evans

2.32. snowplow-incubator/snowplow-event-generator

2.33. OpenAI /ChatGPT— How to Use it With Python

2.34. Is it possible to monitor the number of pod-replicas in a Kubernetes cluster over time with StackDriver? - Stack Overflow

2.35. Is it possible to monitor the number of pod-replicas in a Kubernetes cluster over time with StackDriver? - Stack Overflow

2.36. Racket (programming language) - Wikipedia

2.37. Krickelkrackel

  • I have a formalist approach to interpretation, i.e. that the knowledge of forms used by an artist (or a deliberate lack of thereof) lets you communicate better with the work or art, same as understanding the language improves the communication with another human being

2.38. Why we are teaching this class · Missing Semester

  • Looks really useful. Sometimes things that catch your eye take time, and often they are not forgotten (OSSU!). But I’m bookmarking all the same. Memory is a trickster.

    During a traditional Computer Science education, chances are you will take plenty of classes that teach you advanced topics within CS, everything from Operating Systems to Programming Languages to Machine Learning. But at many institutions there is one essential topic that is rarely covered and is instead left for students to pick up on their own: computing ecosystem literacy.

2.39. An open-source LLM based research assistant

2.41. What Is Nix

  • The most basic, fundamental idea behind Nix is this:Everything on your computer implicitly depends on a whole bunch of other things on your computer.All software exists in a graph of dependencies.Most of the time, this graph is implicit.Nix makes this graph explicit

2.42. The typical course on programming teaches a

2.43. How to Design Programs > Preface

  • n/a

    The typical course on programming teaches a “tinker until it works” approach. When it works, students exclaim “It works!” and move on. Sadly, this phrase is also the shortest lie in computing, and it has cost many people many hours of their lives. In contrast, this book focuses on habits of good programming, addressing both professional and vocational programmers.By “good programming,” we mean an approach to the creation of software that relies on systematic thought, planning, and understanding from the very beginning, at every stage, and for every step. To emphasize the point, we speak of systematic program design and systematically designed programs. Critically, the latter articulates the rationale of the desired functionality. Good programming also satisfies an aesthetic sense of accomplishment; the elegance of a good program is comparable to time-tested poems or the black-and-white photographs of a bygone era. In short, programming differs from good programming like crayon sketches in a diner from oil paintings in a museum.

Quotient - Wikipedia

  • Learning Math Terminology with Dr Racket - in Python I’ll just call this floored quotient or floor divide. Also

    In arithmetic, a quotient (from Latin: quotiens ‘how many times’, pronounced /ˈkwoʊʃənt/) is a quantity produced by the division of two numbers.[1] The quotient has widespread use throughout mathematics, and is commonly referred to as the integer part of a division (in the case of Euclidean division),[2] or as a fraction or a ratio (in the case of proper division). For example, when dividing 20 (the dividend) by 3 (the divisor), the quotient is “6 with a remainder of 2” in the Euclidean division sense, and 623

50 conversations in Bangalore and Chennai

  • Always interesting !

    I went to Chennai and Bengaluru, India. My sole purpose was to meet new friends. I’m an “Overseas Citizen of India” and my son is half-Indian (Tamil). I will always have ties to India. I wanted to deepen those ties and make new connections.So I scheduled fifty one-hour conversations with fifty interesting people over seven days. Back-to-back meetings from 9am to 10pm every day. It was one of the most intense and fascinating (and heart-warming and educational) things I’ve ever done in my life. I recorded almost every conversation into a little voice recorder, then had it transcribed. When I got home to New Zealand I spent 30 hours reading through the transcriptions to help me remember what we talked about, then made a tiny summary, below….And WhatApp is practically the sole mode of communication.

MAR 2013

A Devastating Moment of Clarity in Ukraine - Tablet Magazine

The Future of the Modern Data Stack in 2023

Thinking about Tracking Design, Part 1: What is tracking anyways?

Louis CK- Back to the Garden

  • His first standup I did not pay for (sorrry Louis), the provocations are great, I can’t help, however, but to think if some deeper mechanism responsible also for his art is not too affected by his enemies. Jordan Peterson’s appearance on Lex Friedman’s show left a weird taste in my mouth and I am attributing his pro-russian stance as being in a wrong battle against woke for way too long.

: We haven’t ramped up industrial production at all. At peak, the Ukrainians were firing—expending—upward of ninety thousand artillery shells a month. U.S. monthly production of artillery shells is fifteen thousand. With all our allies thrown in, everybody in the mix who supports Ukraine, you get another fifteen thousand, at the highest estimates. So you can do thirty thousand in the production of artillery shells while expending ninety thousand a month. We haven’t ramped up. We’re just drawing down the stocks. And you know what? We’re running out.

How the War in Ukraine Ends

  • At peak, the Ukrainians were firing—expending—upward of ninety thousand artillery shells a month. U.S. monthly production of artillery shells is fifteen thousand. With all our allies thrown in, everybody in the mix who supports Ukraine, you get another fifteen thousand, at the highest estimates. So you can do thirty thousand in the production of artillery shells while expending ninety thousand a month. We haven’t ramped up. We’re just drawing down the stocks. And you know what? We’re running out.

The Great Feminization of the American University

  • I worked for NYU, so this interesting mostly on a personal level. Else, I have a more of a “hardcode history” view where the feminization is probably the part of civilization that would and will erode in terms of acute crisis, collapse and war. I may be mistaken, of course.

    Sometimes a single incident efficiently summarizes a larger trend. So it is with New York University’s selection of its new president, Linda Mills, a licensed clinical social worker and an NYU social work professor. She researches trauma and bias, as well as race and gender in the legal academy. She is a documentary filmmaker and teaches advocacy filmmaking. She serves as an NYU vice chancellor and as a senior vice provost for Global Programs and University Life. In all these roles, Mills is the very embodiment of the contemporary academy. The most significant part of her identity, however, and the one that ties the rest of her curriculum vitae together, is that she is female, and thus overdetermined as NYU’s next president.

Who are the people I most admire? - Marginal REVOLUTION

  • I have the similar look like Tyler, where the people of my admiration not just sacrificied but were able to 1)risk 2)display courage 3)value love and in my case 4)love books. So Vaclav Havel (inprisoned by communists) and Vaclav Cerny (imprisoned by nazis) are on the top of the list, being a great artist and a great scholar, respectivelly.

    Overall I was surprised how few of you approached the question the way I have, rather as a group you picked too many nerdy white guys. Now I don’t like to play “the PC card,” and if a process generates a lot of nerdy white guys, I don’t then assume that process is necessarily biased or requiring correction. Still, the fact that my list creates so much room for women (and non-whites) suggests it reflects the universality of human experience more than what most of you came up with.

Manhole cover - Wikipedia

PEP 435 – Adding an Enum type to the Python standard library

  • Python has an ENUM type which was not known to me until studying

    The properties of an enumeration are useful for defining an immutable, related set of constant values that may or may not have a semantic meaning. Classic examples are days of the week (Sunday through Saturday) and school assessment grades (‘A’ through ‘D’, and ‘F’). Other examples include error status values and states within a defined process.It is possible to simply define a sequence of values of some other basic type, such as int or str, to represent discrete arbitrary values. However, an enumeration ensures that such values are distinct from any others including, importantly, values within other enumerations, and that operations without meaning (“Wednesday times two”) are not defined for these values. It also provides a convenient printable representation of enum values without requiring tedious repetition while defining them (i.e. no GREEN = ‘green’).

enum — Support for enumerations — Python 3.11.2 documentation

Python list of lists from enum - Stack Overflow

We’re Missing a Key Driver of Teen Anxiety - The Atlantic

  • It must be possible to grow-up both smart and wise in a better way than exemplified here. But from Central European perspective, it’s still “probably the phones”

    Last week, columbia university became the latest school to announce that it would no longer require SAT or ACT scores for undergraduate admissions. The school’s decision was “rooted in the belief that students are dynamic, multi-faceted individuals who cannot be defined by any single factor,” the college said in a defense of its policy change.The SAT has faced heavy scrutiny for privileging rich families, which can pay for test-prep classes for their kids. Some believe that dropping the test is an ethical move toward equality in selective college admissions. Others argue that Columbia is replacing one metric skewed toward rich students with a bundle of metrics that are even more stratified by socioeconomic status, such as high GPAs, internships in Nicaragua, and expensive traveling soccer teams.

High Quality Server Hosting at a Value for Everyone

  • Getting to known another server hosting provider.

    While everyone brags about their prices, we actually deliver on this promise. For example whenever choosing hardware we not only look at the raw performance, but also on the purchase price in relation to performance and power consumption. Read more about how we keep our prices low. In Contabo we believe that every customer deservers a Premium Support Experience no matter they spend thousands or just €5.99 a month. That’s why we’ve set rigorous quality standards for our support team making sure that your experience is as good as possible. The great reviews we get only makes us work harder.

How-To Find the Process ID Holding Open Ports

Is there a way to have a default value inside a dictionary in Python? - Stack Overflow

Simple techniques for complex projects

  • Seth needs to repeat and repeat and repeat the good old insights, as we all are defaulting to crappy practices. Refreshments required.

    Invest in slack buffers for any critical dependent components.Heroism is more fun but less reliable than good planning.Invest in slack buffers for any critical dependent components….and more

The False Promise of ChatGPT

  • It would be interesting to have a longitudinal study on the arrival of AI, done in real-time, to have researcher’s reflextion as well

    ChatGPT is a bullshit artist with no real understanding of what it’s writing about, but so are an awful lot of white-collar workers. It reliably emulates the shibboleths that indicate membership of the professional middle class. It isn’t particularly creative or interesting, but it wasn’t trained to do that - it was trained to produce maximally safe, inoffensive output. If people don’t see ChatGPT as being massively disruptive, then I think they have failed to recognise the sheer proportion of working hours that are spent writing quite mundane letters and reports. Anyone who spends most of their working day in Outlook and Word should be extremely nervous about the medium-term implications of LLM

Snowclone - Wikipedia

The Strongest Evidence Yet That an Animal Started the Pandemic - The Atlantic

Mass converting .doc to .docx - Microsoft Community Hub

Awakening from the Meaning Crisis - YouTube

Awakening from the Meaning Crisis

Mocking, Monkey Patching, and Faking Functionality — Python 401 2.1 documentation

  • Learning the differences between mocking, monkeypatching, fixtures and alike.

    Sometimes while testing you need some fake data. is a part of the library that allows you to intercept what a function would normally do, substituting its full execution with a return value of your own specification. Note that monkey patching a function call does not count as actually testing that function call! You ARE NOT actually using the function that you’ve monkey patched; you are rejecting its default behavior and subsituting it with new behavior.

A Year after the Invasion, the Russian Economy Is Self-Immolating

  • This is working in slower time then headlines, but it seems to be working. Ezra Klein has a great podcast on this, too.

    Russia’s permanent loss of 1,000+ global multinational businesses coupled with escalating economic sanctionsPlummeting energy revenues thanks to the G7 oil price cap and Putin’s punctured natural gas gambitTalent and capital flightRussia will only become increasingly irrelevant as supply chains continue to adaptThe Russian economy is being propped up by the KremlinMore can be done…..

Colonialism: A Moral Reckoning - Marginal REVOLUTION

  • The good old “If you want attention, start a fight” seems to suit here, I am afraid. Tyler’s takes on books are just amazing.

    That is the new book by Nigel Biggar, and it has already created a storm of controversy because of his claims that the British empire is, in my words, “underrated.”Let me first say that I am in no way upset at this thesis being put explicitly on the table. And the book has many valuable discussions, covering issues such as how hard (at some point) the British worked to ban slavery, what were their motives for empire, what kinds of pressures for assimilation were asserted, and much more.My disappointment is how little space is devoted to the topic of sustainable economic growth. In which parts of the empire did British rule boost sustainable economic growth, relative to a counterfactual of peaceful interaction but no conquest? Singapore and Hong Kong seem obviously much richer and better off due to earlier British rule. Malaysia likely as well, though the magnitude of the gain there is smaller. But Sierra Leone not? The country is miserably poor and has had numerous years of civil war, with a legacy of slavery as well. Who could object to trying another run of history there, removing the British imperial role? It is hard to see that it could get very much worse. But then where does one put Kenya?

Dmytro Kuleba: Russian victory will ruin everything the West stands for - New Statesman

  • Really impressed by the age/responsibility ratio here.

    Only 41, he is Ukraine’s youngest foreign minister and a career diplomat, as well as the son of a career diplomat. But when I spoke to him by video link on 9 March he was blunt and direct with his answers, though he never strayed too far from his role. When I asked him if the war would end with a military victory or diplomacy, his first instinct was to reply, “Russian defeat”, but he quickly reverted back to diplomat in chief.

Ezra Klein: This Changes Everything

Pynecone: The easiest way to build web apps.

  • I’ve been automating workflows using CLI tools and it’s working great for me. However terminal is scary for non-programmers; this could be a way to migrate python scripts to web apps rather quickly.

The Impact of AI on Productivity - Marginal REVOLUTION

  • Quantitative Expression of the Programmer’s Acceleration via GitHub Copilot. I just wonder that since it SO facilitates programming by co-incidence, I wonder if also AI will do all of the maintenance work where it is essential to reason on the level of model in order to implement the change efficiently (as opposed to jumping straight into the code)

    Conditioning on completing the task, the average completion time from the treated group is 71.17 minutes and 160.89 minutes for the control group. This represents a 55.8% reduction in completion time. The p-value for the t-test is 0.0017, and a 95% confidence interval for the improvement is between [21%, 89%]. There are four outliers with time to completion above 300 min. All outliers are in the control group, however our results remain robust if these outliers are dropped. This result suggests that Copilot increases average productivity significantly in our experiment population. We also find that the treated group’s success rate is 7 percentage points higher than the control group, but the estimate is not statistically significant, with a 95% confidence interval of [-0.11, 0.25].