ololobus

I got mine at the end of 2021 and then used it till the mid-2023.

I know that it’s not a fair comparison, but I still compare it to macbooks because I’m a mac user for years.

Pros

- Linux support is amazing, basically you just install one of the popular distros and ‘it works’ (c). I used PopOS and was pretty happy. You also get all the Linux tools like eBPF out of the box, which is +1 compared to mac.

- Extensibility is a big deal. You can get 1 TB / 32 GB version for pennies compared to mac, where upgrades from the base are ridiculously expensive.

- Design and look is very neat.

- Keyboard is a classic one and also good.

Cons

- Battery life is really bad; same with cooling. At some point I started having more meetings at work and it gets extremely hot, noisy, and dies very quickly.

- Touchpad is just subpar to mac. Also chassis rigidity is meh. I know they improved the display cover design (switched to CNC), but I have the first revision.

- Display is 2K’ish. I don’t really understand, why they go with this resolution. Even their new display is around 2.5K. IMO, Linux works best either with 1080p/1K or 4K with x2 scaling (I prefer the latter) because fractional scaling is bad. I struggled a lot with external 4K monitor because it was nearly impossible to adjust all sizes so texts were good on both and especially when you disconnect and go portable. I know it’s Linux and you can DIY everything, but for me it was just too much of a headache.

I still fully support this company and wish them all the best, but since getting the MacBook Pro 14 with M2 (company’s, not personal) in the mid-2023 my Framework is waiting for two things: i) 4K display module; and ii) ARM main board. If they release these upgrades I will jump into Framework right away and give it another try.

So I recommend it if Pros are more important than Cons for you.

UPD: formatting and conclusion

I hear it all the time ‘coding interviews are useless’, ‘peer review in scientific journals is broken’ and so on and so on.

I’d say yes and no.

Yes, these are the problems that cannot be solved perfectly.

No, because in such areas any ‘reasonable’ filter is better than nothing. People say that these assignments don’t have anything with reality, but, well, we don’t have months to try to work with each other, we only have 3x1h.

I worked as individual contributor for years, but also had a chance to try a hiring manager role for the past 3 years a lot. We do standard leetcode-style interview (without hardcore) + system design. And I always consider both as a starter and bite to see how the candidate behaves; talks; do they ask questions to clarify something and how. And I always try to help if I see that candidate is stuck. By the end of all interviews you will have some signal, not a comprehensive personality profile. Do we do mistakes? I’m pretty sure, yes. But I think it just works statistically.

I use PiHole, it does break some stuff here and there, and sometimes useful things like Private Relay or iCloud in iOS; or once YouTube history stopped working for me (apparently they use a separate domain to track watched videos and progress!). It also depends on the block lists you upload. It’s pretty easy to unblock, especially web, as you just look on which domain cannot resolve in the browser dev tools and add it to the allow list.

Yet, DNS-based blockers have a limited usefulness at this moment as some major ad-providers started using the same primary domain for serving ads. For example, YouTube, partially Google, Yandex. I guess they cover everything with top level load-balancer and then route internally to specific service ingresses

That's where the separation of storage and compute kicks in, I guess. Startup process of our Postgres instance (compute node) is a bit different from vanilla Postgres. We need to go to the network storage service (pageserver and safekeepers) to get the last known commit LSN, but we don't need to perform any sort of recovery on the compute node side. That way, compute is mostly stateless.

Basically, to start we need to know this LSN and to bootstrap the Postgres processes. This is really that quick. After that compute is ready to accept connections and serve requests, as it's able to get any missing pages from pageserver with GetPage@LSN request.

We do have the whole bunch of problems to solve: queries latency after cold start; startup after the unexpected exit of the heavily loaded Postgres instance could be slower; etc.

> c) Heard the cold start is a second (IIRC), how does that value differ if one runs Neon on bare metal instead of k8s?

Yeah, as Nikita mentioned it's 2 seconds now. We did some tests and measurements and on bare metal, it's sub 500 ms usually, so the remaining part is the k8s (+ our own control plane) orchestration overhead. For example, with plain Docker (which we use in CI in addition to k8s) it's around 1 second already.

K8s provides a convenient abstraction layer, though. So I think that we'll continue using it and optimization will come with pods pool / over-provisioning and it'll be realistic to bring the startup time closer to bare-metal.

-- Cloud engineer @ Neon

We do scale compute part down to zero after 5 mins of inactivity now (no active transactions). This 5 mins threshold is a random pick, it could be 1 min or 30 mins later, or even customizable by the end-user. Storage part is heavily multi-tenant, so it's always running and our main objective is to make resource utilization as effective as possible.

It still has a significant latency on the first connection attempt after suspend (1-2 seconds), but we are working on that and it seems to be realistic to put the startup time under 1 sec.

Pricing model is still work-in-progress, so cannot say much about it. Yet, my personal intention is to make it cost-effective for both end-user and us. I'd prefer to don't build a service with claims like 'here is your free-tier serverless Postgres with zero-latency on connect', which actually means that under the hood there is an always-running compute burning the investors money. Hope it's realistic to achieve :)

-- Cloud engineer @ Neon

I would rephrase it to 'Do not build websites that work 100% fine and fast only in Google Chrome'. Unfortunately, this is the case and most of users just choose the most convenient tool, while trading their privacy.

The main thing about building all these private cloud setups, that bothered me most of time is security. It is not a big deal to take from GitHub and run all these bricks of your infrastructure, but how to maintain? Everything should be updated regularly, otherwise you risk to get your data dumped and leaked by some automatic crawler or home-grown hacker, once new vulnerability is discovered in any part of your tech stack.

The only easy solution I see is to hide everything in the private network and make accessible only under VPN. However, it is not that useful, when you need to get some file or read/reply email from some new device not owned by you.

I dare to promote one StackOverflow question [1] about pandas I have tried to investigate and answer [2] half a year ago. And I was rather horrified by its internal complexity after digging into pandas source :)

OP was wondering, why pandas facing a strange overhead after each 100th iteration in some very specific case. There was a proposal about Python's GC, but it was not clear at all.

Finally, I have dived into pandas and found that it has a hard-coded constant == 100 (!) of a number of internal data storage blocks. After reaching this value it runs some consolidation routines [3], and they consume a lot of memory even leading to crash with memory error.

What was much more wondering, is that after changing this constant to some large value (1000000, actually it disables consolidation at all) reduces memory consumption dramatically! This consolidation seems to reduce storage and memory consumption, so I still do not know why the opposite happens and why it works well in all other cases.

[1] https://stackoverflow.com/questions/56690909/python-is-facin... [2] https://stackoverflow.com/a/56705419/978424 [3] https://github.com/pandas-dev/pandas/blob/761bceb77d44aa63b7...

16 GB of RAM and I use Safari mostly and Firefox from time to time with less than 20 tabs usually (less than 10 in average, I guess).

I check Data written in the Activity monitor — Disk.

"As for writes, at 1 gb a day - far more than my current rate of data use - it would take the same 114 years to reach 40 tb."

Maybe it works for author's very specific system or use-case, but on my personal MBP laptop with very occasional usage pattern--some days I do not use it at all during the week--I end up with 10 GB per day of writes on average. That way it will be 11.4 years already, not so many. And I do not do something very disk-expensive on it like torrents downloading or database testing, only some general development task, watching online videos, web surfing, docs, etc.

Hm, maybe I'm missing something, but for me it seems unfair to compare initially open source LightTable and closed Cursive, doesn't it? Even more, according to the website Cursive is built on top of IntelliJ---well known and polished/tested by dozens of developers commercial IDE.

So I cannot get a point in this comparison: different business models, different licenses, etc.

If we abstract away and understand that we are not representative here, then we realize that people actually love ads in general. Just take a look on some Instagram star profile with thousands of active followers, it is full of integrated ads and sponsored content. Then check some general/tech news, non-professional one, sponsored content sometimes is more than half of the whole website.

So actually people hate those old-fashioned ad banners and pop-ups, but currently the advertising industry is more about integrating hidden ads everywhere and personalizing it as much as possible. That speaking, if you are not deeply into privacy and anonymity or just turn off you ads/track blocking stuff, then you will see how personal ads could be. They are not entirely correct, but more and more often I found them horrifyingly personal and targeted.

I don't think that this principle is directly applicable here. DNA-based inheritance is still 50/50% split and I guess DNA is most important anyway. Although, the epigenetic one (let's assume its overall contribution is <5-10%) may be split according to something similar to Pareto.

AFAIK Brandur uses Monodraw [1]. It's so cool, I even purchased a license for myself, although the author of the app stopped its active development [2].

[1] https://monodraw.helftone.com/

[2] https://blog.helftone.com/monodraw-maintenance-mode/

On my Ubuntu 18.04 LTS and FF 67.0.1 it have launched fine after a second try, while the first one just froze

Both will be cool, but anyway, to use Braava for mopping you should manually install and fill mopping module. You cannot leave it for a week of fully autonomous work. I have a Roborock S50 and it has a similar mopping cartridge, so actually it can do both, but mopping is semi-manual

I don't think so. My guess is that the industry of consumer electronics is moving toward the right direction. I have two pieces of IoT in my household:

1) Robot vacuum cleaner, and I am absolutely felt in love with it. My floor now is always clean during weekdays, when I am busy working, no more visible dust, crumbs, etc. I just have to clean filter and container once a week, otherwise it is fully autonomous. The only thing I want to add is a self-cleaning and automatic floor mopping, but I've seen such a project on Kickstarter, so it is close.

2) Cheap WiFi RGB light-bulb. I have connected it to Homebridge and it is nice to say 'Hey Siri, turn off the floor lamp' or 'Hey Siri, set the floor lamp to 10%', but it is not one of essentials.

There are a lot of questions of course: there should be an option to work completely without proprietary servers and continuous internet connection; 'smart' kettles, hairdriers and so on are useless stuff; security; universal and open protocols; etc.

Hmm, how is it actually regulated? So, e.g. if I am going to my friends and carrying a bottle of wine altogether with pocket knife bundled with a corkscrew to be sure I will be able to open it, then I am in a grey zone or even illegal?

This is applicable to almost every research area, where the publication of peer-reviewed (PR) papers is de-facto a standard. I have a background in physics and a few papers published in Q1 journals, so I heard these complaints about "peer-review pressure" many times. But the truth is somewhere in between: 1. yes, sometimes you get a stubborn reviewer and it is extremely difficult to get through, I've experienced this several times; 2. but PR still deliver a required filter against a flood of low-quality papers.

In essence, I found the note above as too emotional, since currently we have nothing better than PR of papers, review of code, etc., in order to guarantee the minimal level of quality.

Off topic, but my life will never be the same again, there are 18 types of crystalline water ice and one amorphous! [1]

[1] https://en.wikipedia.org/wiki/Ice#Phases

I absolutely agree, interference with instance variable/method alias '@' looks awkward. For me it seems a little bit against Ruby-way.

This may differ from one student to another or from lab to lab, but the general thesis is definitely true. I decided to quit academia in favor of IT industry exactly due to this high stress problem, even having a number of relative good papers published. I just could not bear it more.

PhD student/postdoc life is extremely unstable: 1) you are very limited in finances; 2) you have to perform a number of different research trials and most of them will have no success; 3) you are always limited in time; 4) there is a continuous flow of grant applications, reports, papers preparation, sometimes teacher assistance works. And in the middle of this you have to find your own unique path in science, your niche.

In summary, you have to be ready to live in a continuous disaster during relatively long period of life. If it fits you, then you can achieve success after ~10 years of hard work. Anyway, it was interesting experience for me :)

JFYI 50% is an adoption achieved in only 23 days after iOS 12 release [1]

"Apple’s latest mobile OS hitting 50 percent adoption across eligible devices in 23 days (via VentureBeat).

For comparison, iOS 11, released on September 19th, 2017, didn’t hit 52 percent adoption until November 6th of that year, taking 48 days, or over twice as long as it took iOS 12 to hit its own 50 percent mark."

So now it is probably higher, though I didn't find any fresh stats.

[1] https://www.theverge.com/2018/10/11/17965302/ios-12-install-...

There is also some feedback in the Reddit thread [1] and it is mixed, though someone claims, that got full refund.

[1] https://www.reddit.com/r/promethease/comments/9866da/dante_l...

This is a quite questionable statement. There was a post here at HN a few days ago [1] and the article [2] says:

"Meanwhile, global warming lurches ahead. Greenhouse gas emissions continue to grow. So do solar and wind power. But do you know how much of the world’s primary energy comes from fossil fuels today? It’s 81 percent—the same as in 2006."

I didn't check the numbers by myself, but it sounds reasonable: while renewable sources grow, the consumption grows as well. So maybe we need nuclear power too in addition to solar/wind/etc? I don't see too much alternatives around.

[1] https://news.ycombinator.com/item?id=18411991

[2] https://blogs.scientificamerican.com/observations/why-we-nee...

Despite the fact that quantum entanglement is frequently referred to the new ways of communication, at the current state of Standard model/Quantum physics quantum entanglement does not mean interaction or information transfer. Furthermore, instantaneous information transfer is restricted and its speed is limited to the speed of light.

Quantum entanglement is rather about correlation and statistics, which is, hopefully, will be quite useful for some applications, but not for communication channel. Otherwise, it will ruin the current foundation of quantum mechanics.

I strongly recommend reading the book of Nicolas Gisin 'Quantum Chance' [1], which is quite good for the general audience to understand, what quantum entanglement actually means in the real life, i.e. in the physical experiment.

[1] https://www.springer.com/gp/about-springer/media/press-relea...