Absolutely. I have a person favorite setup... which is to have these two playing at the * same time * and play around with the combos of sliders / set to automate.
I set the numbers stations to 'narrow' and Arrakis to 'wide' and stereo field, mute the numbers stations that repeats german numbers (those stand out to me too easily)... and it's like some magical productivity hack of my brain.
Learning Neural Networks from Hinton was transformative for me. It must be transformative for the industry, they still use Coursera lecture notes for citing RMSprop. I completed the very first MOOC offerings in Fall 2011, Machine Learning by Andrew Ng, and AI by Norvig and Thrun. It’s the first time ML “clicked” for me although I had took ML course in Master’s before. Sadly no one cares about my “Statement of Accomplishment”s when hiring. I carry them with pride, knowing they effectively taught me timely and relevant knowledge from the best experts in the world.
At one point in his demo, he uploads a file but terminates the upload more or less halfway. Then he begins downloading the file - which only progresses to the point it had been uploaded, and subsequently stalls indefinitely. And, finally, he finishes uploading the file (which gracefully resumes) and the file download (which is still running) seamlessly completes.
I have run ELK, Grafana + Prom, Grafana + Thanos/Coretex, New relic and all of the more traditional products for monitoring/observability. More recently in the last few years, I have been running full observability stacks via either The Grafana LGTM stack or datadog at a reasonable scale and complexities. Ultimately you want one tool that can alert you off a metric, present you some traces, and drill down into logs, all the way down the stack.
I have found Datadog to be, by far hands down the best developer experience from the get go, the way it glues the mostly decent products together is unparalleled in comparison to other products (Grafana cloud/LGTM). I usually say if your at a small to medium scale business just makes sense, IF you understand the product and configure it correctly which is reasonably easy.
The seamless integration between tracing, logging and metrics in the platform, which you can then easily combine with alerts is great. However, its easy to misconfigure it and spend a lot of money on seemingly nothing. If you do not implement tracing and structured logs (at the right volume and level) with trace/span ids etc all the way through services its hard to see the value, and seems expensive. It requires some good knowledge, and configuration of the product to make it pay off.
The rest of the product features are generally good, for example their security suite is a good entry level to cloud security monitoring and SEIM too.
However, when you get to a certain scale, the cost of APM and Infrastructure hosts in Datadog can become become somewhat prohibitive. Also, Datadogs custom metrics pricing is somewhat expensive and its query language cababilities does not quite match the power of promql, and you start to find yourself needed them to debug issues. At that point, the self hosted LGTM stack starts to make sense, however, it involves a lot more education for end users in both integration (a little less now Otel is popular) and querying/building dashboards etc, but also running it yourself. The grafana cloud platform is more attractive though.
Spicy take: read the narrative non-fiction business books. They are written for entertainment and sit in the business section but you can learn things.
barbarians at the gate
when genius failed
bad blood
billion dollar whale
chaos monkey
liars poker
shoe dog
american kingping
broken code
soul of a new machine
and so on. There is nothing wrong with entertainment and since these are usually written by journalists or professional writers, the writing is often better.
I've been involved with the open data movement here in Michigan for a dozen years. A lot of us have been inspired by what happened in Britain in 2010 when a change in government allowed them to reimagine Britain's digital footprint.
Here's a video by their chief architect detailing the changes.
I know there's an O'Reilly video about this guy's boss but I can't find it. Sadly another government change was to end all this development. But in the end near as i can figure though a lot of the bosses left the changes have continued but at a slower rate.
No government website in America begins to compare to the clearness and simplicity that exists in Britain nearly a dozen years later.
> So I became a programmer because I wanted to be a wizard.
You may have already found it, but Fred Brooks's little essay on why programming is fun has always resonated with me [0]:
> The programmer, like the poet, works only slightly removed from pure thought-stuff. He builds his castles in the air, from air, creating by the exertion of the imagination. Few media of creation are so flexible, so easy to polish and rework, so readily capable of realizing grand conceptual structures. [...]
> Yet the program construct, unlike the poet’s words, is real in the sense that it moves and works, producing visible outputs separate from the construct itself. It prints results, draws pictures, produces sounds, moves arms. The magic of myth and legend has come true in our time. One types the correct incantation on a keyboard, and a display screen comes to life, showing things that never were nor could be.
I use a telgram bot (controlled by node-red) that sends the URLs to a script [1] that uses a FIFO to download them one by one via yt-dlp. If the sender ID is from my mum, only the audio track is saved and made available to her via jellyfin. It has been working almost too well for 2 years. She has downloaded almost 1TB of audiobooks (all from youtube).
One safety tip: disable SSH Agent Forwarding before you connect, otherwise the remote server can theoretically reuse your private key to establish new connections to GitHub.com or prod servers (though this host is unlikely malicious).
I find it interesting, that social media and messaging apps are kind of thrown into one pot increasingly.
My mental model has always been like:
- Twitter, Bluesky, Mastodon
- Slack, Discord, Zulip, IRC
- WhatsApp, Telegram, Signal, Matrix
- Zoom, Teams, Jitsi
With mass communication to individual communication from top to bottom (and increasing freedom roughly from left to right).
It seems these distinctions get blurred more and more and we will probably end up with different apps differing only in a single dimension from left to right.
I don't trust Time Machine any more. Years ago I wrote some shell scripts that help me mostly automate my complete system setup (with brew and friends). From time to time, I wipe my entire system and restore it with these scripts. Sometimes I have to adjust them, but mostly, they work without changes.
For my data backups, I use restic. Big advantage is, that I can read my backups even when I don't have a macOS system present (e.g. my only macOS system had a hardware issue and my Time Machine Backup was pretty much useless until I got a new one).
I know, this solution is not for everybody, but Time Machine corrupted my backups more than 5 times now and it feels so slow compared to restic, that I don't even think about retrying it after a new macOS release any more - even if my solution is a bit more work to do.
Those who are familiar with US submarine operations would assume this from the start. For an excellent account of the development of US submarine capabilities (including listening and detection), I wholeheartedly recommend the book "Blind Man's Bluff".[0]
How that book hasn't been made into a mini-series is beyond me. The stories and characters are incredible.
[A] ceramics teacher announced on opening day that he was dividing the class into two groups. All those on the left side of the studio, he said, would be graded solely on the quantity of work they produced, all those on the right solely on its quality. His procedure was simple: on the final day of class he would bring in his bathroom scales and weigh the work of the “quantity” group: fifty pound of pots rated an “A”, forty pounds a “B”, and so on. Those being graded on “quality”, however, needed to produce only one pot — albeit a perfect one — to get an “A”. Well, came grading time and a curious fact emerged: the works of highest quality were all produced by the group being graded for quantity. It seems that while the “quantity” group was busily churning out piles of work – and learning from their mistakes — the “quality” group had sat theorizing about perfection, and in the end had little more to show for their efforts than grandiose theories and a pile of dead clay.
"hijacking" the post to ask where I can find a good introduction to machine learning and AI. Not how to use this or this library but the fundamentals and principles behind. Preferably something explaining clearly the principles first then explaining the maths (from the beginning, my maths are quite far now) then showing practical usage/development (in any high level language like python or julia). I do not need to jump straight to the latest algorithms, I prefer starting with building bricks first
This was a recursive `rm -rf node_modules` that turned into a rust learning project and got out of hand :) now supports 14 different languages/project types. https://github.com/tbillington/kondo.
Someone in the comments once explained that the movie, "The Apartment" (1960), has become their New Year's Eve tradition.
It is now mine.
At precisely 9:58 PM I have scheduled "The Apartment" to begin playing on my TV. If you do the same you'll enjoy the synchronization when midnight drops. (And what a great film from 1960.)
I've been on a quest to tame the bookmark monster. I have bookmarks (collectively over 10k probably) all spread around in different devices, different browsers on different computers, and event in text messages I sent to myself, via whatsapp/sms, over a period spanning 6-7 years.
While I'm not close done curating (the dead/expired/out-of-date links)... I needed to collect it all in one central place, and [linkding](https://github.com/sissbruecker/linkding) is fitting the bill quite nicely. I'm using the tags and description field to annonate and sort the mess of bookmarks. It has a simple to use rest API, uses SQLite, and you can import/export bookmarks using the Netscape bookmarks html format. Best of all, it's OSS you can self-host on a RaspberryPi or even for free on say fly.io.
It’s not much for some parts of the world. But I’m well enough from this that I even took the time to build a small calendar app (https://lowtechguys.com/grila) from which all the funds will go to my brother’s college costs so he can stop working 12h/day jobs.
Before this I tried creating paid web services but none took off. I realized I actually don’t use any indie web product after 8 years of professional coding. I’m only using web products from big companies like Google, fly.io, Amazon etc.
Desktop apps on the other hand, most that I use and love are made by single developers.
With the ascent of Apple Silicon, and the ease of SwiftUI, this has the potential of bringing a modest revenue while also being more fulfilling than a corporate job.
In case you’re curious how the code looks for something like that, here’s a small open-source app that I built in a single (long) day, which has proven to be useful enough that people want to pay for it: https://github.com/alin23/Clop
I've been struggling with wrapping my head around asynchronous programming with callbacks, promises and async/await in JS, however I think it's finally clicking after watching these YouTube videos and creating a document where I explain these concepts as if I'm teaching them to someone else:
Edit... I've been rewatching these videos, reading the MDN docs, the Eloquent JavaScript book, javascript.info, blogs about the subject, etc. This further proves you shouldn't limit yourself to a single resource, and instead fill up the laguna with water from different sources if you will.
rqlite[1] author here, happy to answer any questions about it if it helps.
rqlite will give you HA, but won't help with load (rqlite replicates for reliability, not for write performance). But I like to think the it'll give you solid -- and simple to use -- HA. Replicated just replaced their use of Postgres with rqlite for this reason[2].
Pair: https://mynoise.net/NoiseMachines/numberStationsRadioNoiseGe... with: https://mynoise.net/NoiseMachines/magicDuneArrakisGenerator....
I set the numbers stations to 'narrow' and Arrakis to 'wide' and stereo field, mute the numbers stations that repeats german numbers (those stand out to me too easily)... and it's like some magical productivity hack of my brain.