Hello, very cool app. I have been making apps like this using my tool here:
https://domsy.io
It's pretty cool how quickly and easily I can generate little static apps like this for ad hoc use cases. I have made a weight tracker, expense tracker, prototypes for work, cards for my wife, slides for work, etc.
For anyone looking for a sleep supplement, before you go down the rabbit hole of Theanine, Mg, etc. Try an OTC Azelastine or Fluticasone nasal spray for a month.
Turns out my chronic poor quality, restless sleep was a dust mite allergy that I should have figured out and treated a decade ago. Would wake up with a stuffy nose and very dry mouth but didn't have too many issues during the day. I was allergic to my bed.
Been using antihistamines, and a dehumidifier for several months now and sleeping better than I have in years. Given how extremely common mite allergies are there's got to be a lot of folks with undiagnosed issues here.
The last time I've used a leet code style interview was in 2012, and it resulted in a bad hire (who just happened to have trained on the questions we used). I've hired something like 150 developers so far, and what I ended up with after a few years of trial and error:
1. Use recruiters and network: Wading through the sheer volume of applications was even nasty before COVID, I don't even want to imagine what it's like now. A good recruiter or a recommendation can save a lot of time.
2. Do either no take home test, or one that takes at most two hours. I do discuss the solution candidates came up with, so as long as they can demonstrate they know what they did there, I don't care too much how they did it. If I do this part, it's just to establish some base line competency.
3. Put the candidate at ease - nervous people don't interview well, another problem with non-trivial tasks in technical interviews. I rarely do any live coding, if I do, it's pairing and for management roles, to e.g. probe how they manage disagreement and such. But for developers, they mostly shine when not under pressure, I try to see that side of them.
4. Talk through past and current challenges, technical and otherwise. This is by far the most powerful part of the interview IMHO. Had a bad manager? Cool, what did you do about it? I'm not looking for them having resolved whatever issue we talk about, I'm trying to understand who they are and how they'd fit into the team.
I've been using this process for almost a decade now, and currently don't think I need to change anything about it with respect to LLMs.
I kinda wish it was more merit based, but I haven't found a way to do that well yet. Maybe it's me, or maybe it's just not feasible. The work I tend to be involved in seems way too multi faceted to have a single standard test that will seriously predict how well a candidate will do on the job. My workaround is to rely on intuition for the most part.
Pentax cameras are much better at the ui and do not have any of this shit. They are also bulletproof and nearly indestructible, favoured by war photographers, and tend to have excellent spec sheets (if a bit of a a slow autofocus).
The company went bankrupt and bought by Ricoh, which I sincerely hope will keep the brand alive. Capitalism does really seem to prefer the nickel and dime approach...
A teeny tiny model such as a 1.5B model is really dumb, and not good at interactively generating code in a conversational way, but models in the 3B or less size can do a good job of suggesting tab completions.
There are larger "open" models (in the 32B - 70B range) that you can run locally that should be much, much better than gpt-4o-mini at just about everything, including writing code. For a few examples, llama3.3-70b-instruct and qwen2.5-coder-32b-instruct are pretty good. If you're really pressed for RAM, qwen2.5-coder-7b-instruct or codegemma-7b-it might be okay for some simple things.
> medium specced macbook pro
medium specced doesn't mean much. How much RAM do you have? Each "B" (billion) of parameters is going to require about 1GB of RAM, as a rule of thumb. (500MB for really heavily quantized models, 2GB for un-quantized models... but, 8-bit quants use 1GB, and that's usually fine.)
Otel seems complicated because different observability vendors make implementing observability super easy with their proprietary SDK’s, agents and API’s. This is what Otel wants to solve and I think the people behind it are doing a great job.
Also kudos to grafana for adopting OpenTelemetry as a first class citizen of their ecosystem.
I’ve been pushing the use of Datadog for years but their pricing is out of control for anyone between mid size company and large enterprises. So as years passed and OpenTelemetry API’s and SDK’s stabilized it became our standard for application observability.
To be honest the documentation could be better overall and the onboarding docs differ per programming language, which is not ideal.
My current team is on a NodeJS/Typescript stack and we’ve created a set of packages and an example Grafana stack to get started with OpenTelemetry real quick.
Maybe it’s useful to anyone here: https://github.com/zonneplan/open-telemetry-js
I just donated 133,7€ and will gladly do it again if further legal costs arise. Please consider also making a generous donation and post about it in this thread.
What Newag is doing here is absolutely vile. They want to charge 20.000€ per train to “reactivate” them after they have been serviced at third party workshops. We must not let them win and set a precedent.
I've seen these called "explorables" or "explorable explanations" before and I really like them. I've been collecting notes on them here: https://simonwillison.net/tags/explorables/
Basically stating the fact that people fail to see the value in reinvestment of time and resources for improvement. Being Idle is not a failure but a way to think and be ready if a period of higher intensity comes. And it is healthy to have sometimes more time for a menial task.
People get so crazy about the idea of optimization, but fail to account for severe issues that arise when time is always occupied by something, which seems to happen more and more these days...
Interesting related fact. Some plants like Spathiphyllum are known to remove formaldehyde from the air. This does not eliminate the need of a proper strong ventilation system, but indoor plants helping to protect people from cancer should be in each lab, for good measure.
“Hard times create strong men, strong men create good times, good times create weak men, and weak men create hard times.” (from a postapocalyptic novel by the author G. Michael Hopf)
In my last role as a director of engineering at a startup, I found that a project `flake.nix` file (coupled with simply asking people to use https://determinate.systems/posts/determinate-nix-installer/ to install Nix) led to the fastest "new-hire-to-able-to-contribute" time of anything I've seen.
Unfortunately, after a few hires (hand-picked by me), this is what happened:
1) People didn't want to learn Nix, neither did they want to ask me how to make something work with Nix, neither did they tell me they didn't want to learn Nix. In essence, I told them to set the project up with it, which they'd do (and which would be successful, at least initially), but forgot that I also had to sell them on it. In one case, a developer spent all weekend (of HIS time) uninstalling Nix and making things work using the "usual crap" (as I would call it), all because of an issue I could have fixed in probably 5 minutes if he had just reached out to me (which he did not, to my chagrin). The first time I heard them comment their true feelings on it was when I pushed back regarding this because I would have gladly helped... I've mentioned this on various Slacks to get feedback and people have basically said "you either insist on it and say it's the only supported developer-environment-defining framework, or you will lose control over it" /shrug
2) Developers really like to have control over their own machines (but I failed to assume they'd also want this control over the project dependencies, since, after all, I was the one who decided to control mine with the flake.nix in the first place!)
3) At a startup, execution is everything and time is possibly too short (especially if you have kids) to learn new things that aren't simple, even if better... that unfortunately may include Nix.
4) Nix would also be perfect for deployments... except that there is no (to my knowledge) general-purpose, broadly-accepted way to deploy via Nix, except to convert it to a Docker image and deploy that, which (almost) defeats most of the purpose of Nix.
I still believe in Nix but actually trying to use it to "perfectly control" a team's project dependencies (which I will insist it does do, pretty much, better than anything else) has been a mixed bag. And I will still insist that for every 5 minutes spent wrestling with Nix trying to get it to do what you need it to do, you are saving at least an order of magnitude more time spent debugging non-deterministic dependency issues that (as it turns out) were only "accidentally" working in the first place.
Paul's animation wasn't playing at an even rate for me, for some reason, so I created two video versions (8Hz and 12Hz) with the 16 second on/off period, starting with an off period, running for 254 seconds, as per the paper. These versions end with an an additional off period, as a 'cool down' from the flicker.
Framerate of 24Hz differs from the 120Hz as presented in the paper, but here there is no 40Hz flicker attempt so it shouldn't be an issue.
Compression may affect the edges of the lines, but downloads are enabled.
For anyone who hasn't tried local models because they think it's too complicated or their computer can't handle it, download a single llamafile and try it out in just moments.
They even have whisperfiles now, which is the same thing but for whisper.cpp, aka real-time voice transcription.
You can also take this a step further and use this exact setup for a local-only co-pilot style code autocomplete and chat using Twinny. I use this every day. It's free, private, and offline.
A principal mechanism of action of metformin is AMPK-dependenent inhibition of mTORC1 in the liver. [1] mTORC1 inhibition also occurs when fasted and when taking Rapamycin. Rapamycin has been floated many times as a life extension drug. [2]
mTOR is one of the major nutrient sensing pathways in the body, particularly sensitive to amino acids (especially methionine and leucine) but also to energy levels in general via AMPK. Inhibition of mTOR slows down cell division and induces autophagic flux -- further mTOR dysregulation is implicated in about 70% of cancers. It is an incredibly highly conserved pathway in everything from yeast to humans, and [m]TOR inhibition has been shown to dramatically extend life in basically everything that moves. I believe there's a life extension trial in humans under way around Rapamycin but I could be mistaken.
It acts as a very targeted partial starvation mimetic.
[edit] > that it's healthy to not be overweight?
This is separately also true. But what's neat about metformin is that generally diabetics on metformin are less likely to develop cancer than non-diabetics. [3] So it stands to reason that non-diabetics taking metformin would have even lower incidence of cancer no?
[edit] I find this stuff very cool, and I personally expect mTOR to be the next golden child after everyone gets on GLP-1s.
These patterns were identified using a type of Deep Learning model, the paper then goes on studying the association between different factors (such as chronic diseases) and brain atrophy.
So in conclusion, this study have demonstrated how brain atrophy manifests itself in MRI brain scans and how we can "classify" them into one of five categories (or "patterns", if you like). The gain here is in diagnosis, imagine if a doctor could easily determine that a specific person exhibits " Type 2" atrophy? Much time, money and human suffering could be saved providing the patient with tailored treatment at the get-go.
Magnesium L-Threonate - has the most potent therapeutical effect because it can effortlessly cross blood-brain barrier. The drawback is that some people are sensitive to this form of magnesium, those people can have nausea, vomit, migraines, etc. IMHO, I would advise against everyday use because this form is more a medication than a supplement. It is used for serious conditions like dementia, neurological impairment, nutrimental deficiencies.
Magnesium Taurate - a combination of magnesium and taurine. A good form for people with metabolic conditions: T1DM, T2DM, hyperlipidemia, vitamin and mineral deficiencies.
Magnesium Glycinate (aka Magnesium Bisglycinate) - a bit less potent form of magnesium, but has good bioavailability, fewer side-effects. This form is also a source of glycine which is an important amino acid beneficial for metabolism, has a mild calming and stabilizing effect on nervous system. Helps to cope with anxiety, panic attacks, insomnia.
Magnesium Citrate - a cheaper but ok magnesium form for everyday use.
Magnesium Oxide - the cheapest and the least efficient form of magnesium. Unfortunately, this is the most widespread form in many countries due to its low price. Try to avoid this form if you have a choice.
Bonus point: if you have a specific condition, you can combine several forms of magnesium to reach multiple therapeutic goals. For example, some popular combinations are presented below:
a. Magnesium Taurate + Magnesium Glycinate
b. Magnesium L-Threonate + Magnesium Taurate
c. Magnesium L-Threonate + Magnesium Taurate + Magnesium Glycinate
There's also Python bindings for the fork for anyone who uses Python: https://github.com/lexiforest/curl_cffi