Arqu

Part of the n0/iroh team, cool to see this here, looking forward to play with it :)

One of the n0/iroh devs here.

Iroh doesn't use DHT as its main discovery mechanism. It uses DNS/pkarr and relays as the primary method. DHT is a separate feature if folks like to do that, we don't have it on by default and don't have it on the public relays.

The whole idea is p2p but trying to be realistic about what network environments actually look like.

I suggest going through https://www.youtube.com/watch?v=RwAt36Xe3UI for an explainer.

We bumped to 1.0 an hour ago https://pypi.org/project/iroh/#history

You don't have to have it public. You can have your app gate against any auth method you like to implement on top. And you can have private relays to segregate your traffic and discovery depending on setup.

Yes I used it in place of NAT for most casual users at home, which is presumably what the user above originally meant.

Yes if you want to. Routers are a necessary abstraction from the IPv4 days and seems it will stick around for a long time, and we need solutions sometimes around those topologies.

A little bit of both. Natively it relies on QUIC and leverages existing IP infrastructure, however it also works with custom transports just as fine so you can interact via bluetooth for example.

Establishing direct connections on the other hand is a much harder problem with the current internet infrastructure.

All the data is e2e encrypted and nothing is stored. The usual self hosting public things rules apply.

By far not a complete list but a starting point https://github.com/n0-computer/awesome-iroh/

Also you can join our discord and there's #showcase https://iroh.computer/discord

Thanks, we agree! We used to have bindings for while but the maintenance burden at that point was too high. Now that 1.0 guarantees everyone some stability and we feel confident in the library, we have enough room to properly support it.

Were interacting with IETF on a number of projects and so far it's been going well :)

Hopefully not that far out, we're actively working on it at n0/iroh https://github.com/n0-computer/quinn/pull/28

Id urge you to try both out again and verify results. The comment is fairly dismissive, yet both do work even behind a cgnat (albeit not under all conditions). If you do find a general solution to the problem, please do share.

I'm super interested in this topic. Recently (and still ongoing) I started on hashing out how to diff large datasets and what that even means.

I would love to get an understanding of how the HN crowd sees diffing datasets should be (lets say >1GB in size).

Are you more interested in a "patch" quality diff of the data which is more machine tailored? Or is a change report/summary/highlights more interesting in that case?

Currently I'm leaning more towards the understanding/human consumption perspective which offers some interesting tradeoffs.

I guess I'm in a good position comming from a Co which scaled from ~30 to currently ~220 before I exited. Nearly 70% is from a growing personal network from a single guy. Another 15% come from direct referals outside that network. The last 15 are a mix of random circumstances and some cold outreach.

Depending how you look at it ie. Building networks or just chatting people up can lead to very different outcomes. The above was mostly focused on the 'getting started' part. Though the 200+ setup is successfully run by a team of 7 or 8.

Things change as you scale and the approach that works on smaller mumbers does not work on largers and vice versa.

Feel free to ping me on email or otherwise if you'd like to chat.

I went the boutique consultancy route just last week and brought on a couple of people into the mix.

I pretty much agree that everybody kind of faces the same question and feelings. To be honest, I might have taken a small leap of faith as I pulled the trigger before securing a client. Though the only reason I felt comfortable with it is that I've been in the space enough to be pretty sure I can land a client in the first month or so (seems like it's happening).

The best advice you can have is 'talk to people'. Most starters think you're BSing them, but nearly everybody fails to leverage their network. You can't go indie fresh from college but after a couple years and some projects it's easy enough.

Talk, talk and talk some more. Don't be shy to send emails and chat people up on LinkedIn. Works wonders once you put yourself out there. Look at your contacts list now and you can surely find at least one that would be able to get you started with some work now or in the very near term.

The reason everyone keeps iterating on the same 'general/bland advice' is that it really is the bread and butter of it. Talk more, can't say it enough. Be honest, be respectful, don't spam, but don't be shy to talk to strangers in your line of work.

Not sure if this helps anyone, but just wanted to say it's easier than most of you think. You need a marketable skill, a minimal network and to talk. If you're doing honest work, things pick up on it's own.

Known pitfalls - there's more to running a consultancy than just talking and working, admin work takes a lot of time as well. Plan for the extras.

I've had the wonderful opportunity to work on several projects where AI/ML was not just used as a buzzword and marketing gimmick.

The two types of applications I've seen so far generate real value (and thus have monetary value where you can actually earn) are: - Automate existing processes to either reduce the amount of work needed to be done (feature extraction from images or audio, document parsing) or to introduce a higher level of resolution/response time. For example forecasts for the next day every day or live detection of audio/visual events.

- Generating models to extract signals from massive or complex data. Usually once you're done here you can revert to traditional methods based on the newfound insights. Rarely is there "magic" solutions to optimize away your problems. In general it proves more to be a tool in the box to do analytics than it is a solution.

Either of those create new value and you can put a price on it. There's decent opportunity once you understand what are appropriate use cases.

A fairly long time ago (3-4) years I was tasked to do something fairly similar (though running on Android as the end client). HLS was one of the better options but came at the same costs you describe here. However it was fairly easy to reduce the block size to be less to favor response vs resilience. Essentially you trade buffer size and bitrate switching quality for more precise scrolling through the video and faster start times.

I had to hack it quite severely to get fast load with fair resilience for my usecase as the devices are restricted in performance and can have fairly low bandwidth. Since you're looking at a relatively fast connection, simply reducing the chunk size should get you to the target.

As a follow up - I've spent a couple years working on a video product based on WebRTC. This either works for a PoC where you just hack things together or on a large scale where you have time and resources to fight odd bugs and work through a spectrum of logistical hoops in setting it up. So unless you plan to have a large-ish deployment with people taking care of it I would stick to HLS or other simpler protocols.

I would suggest you go for it! A very good collegue of mine. He also finished vet school, went on to get a masters degree in bioinformatics and shaped up his DS/ML skills on his own time. He started in a local data analytics company and then transitioned to a full software development company where together we have brought in and started DS & ML efforts. His colourful experience definitely broadened his view and is now what I would label a senior guy and has the perspective and understanding of the business side of things.

In my eyes, Google pioneered the commercial application of this approach. The advent of BigTable and it's underlying colossus storage engine they literally pushed the advent of HDFS and all the BigData tooling from a decade ago.

Seems like this is a common theme amongst people working on side projects. My 5c is that you do two things to get to release: 1) Cut down to all but the essential, think what really means Minimum, Viable and Product 2) Have a task board - its a good motivation to watch how you burn down through it 3) Keep your eye on the higher goal - the boring or hard parts are a means to an end here

As far as personal experience - took me 6 years to launch with the bulk happening in 6 months where I've decided I WILL LAUNCH FFS. Billing is a PITA and am actually dealing with it at this exact moment. It's crap, always will be, but my motivation is that this is what will aid making money which will keep the project alive, so yeah, means to an end. Lastly, I will launch if it kills me - I'm still kicking but have probably spent way to much time and nerves on some stuff.

I guess take it as a challenge and look at it like this: Only the ones that go through it all get to the end, all others just abandon it and fail. Be the one that sees it through.

I used to be interested a lot in these topics (Mainly Pi and Mersenne Primes) back when cloud was not yet a thing and HPC meant building or renting large clusters. Got me into a lot of fun Beowulf cluster stuff which was super fun. Then also all the coding and tuning and fun algorithms.

An interesting story, though a lot of the details I have forgotten by now, I remember back in that time the race was on to get like 1T or something like that digits and there was a Japanese guy that built some sort of super rig for $10-20k at the time and got to 1T only to be beaten by Yahoo to 5T in like a couple weeks from there. There I saw the future of computing in large IT companies having the infrastructure to host large clusters cheaply which were dominated until then by supercomputers and research institutions. Might have gotten some details wrong as it's been like 10 years since then but the idea still stands.

I rarely just straight out drop money for some large group or cause but rather prefer to do something closer to me. Usually if there is an opportunity to directly support the cause I do it. It manifests mainly in 2 ways. 1) I participate in the event and pay a fee 2) I know the local population and people in need and donate both cash and in items/food directly

Neither is for any gain but seeing it first hand is such a great experience that you're inclined to do more. I usually advise people to take care of issues locally first. I also support the cause of supporting remote regions and less covered issues when I travel to such places. Don't want to just give money and "be done" with it - there's more to the cause and a nice conversation can also go a long way.

This is a known trick of many registrars, but GoDaddy has to be the leader. Happened to me on two occasions as well. Recently it's supposed to be a bit cracked down on as they have strict quotas on how many domains they can reserve without outright buying.

As for my case, it was a couple years ago where they would also host a small site redirecting to the auction. It states that it is owned by some XYZ entity, but if you peel enough layers of the onion scheme you can get to their name.

You can read more about the practice and measures here: https://en.wikipedia.org/wiki/Domain_tasting https://en.wikipedia.org/wiki/Domain_name_front_running

Their UIs and tooling are inconsistent and clunky. They kind of shove some of their tooling on to you as well.

Obviously, my experience is rather shallow here and wouldn't dare go into too deep discussions on that. And the shoving part can easily be avoided with some extra elbow grease.

Touching on big G trying to catch up - I've recently had some issues with GCP and while the addition of more accessible support (you can now reach some support person relatively easy) it helps little unless it's a request that they can handle with a single button press. While it now FEELS less frustrating as you have somebody to talk to, it doesn't help that I have an issue that is being ping-ponged around different reps for >10 days by now.

Regarding MS taking 2nd place - recently came in contact with their cloud. It's not up to par to the rest from a tech perspective, however, they are killing it on their sales channels and in sectors such as banks and retail due to their ubiquity in those.

Edit: Wording, horrible is not the best description of the MS cloud, just not as good for me.

I'm not arguing the case here that the whole scene is set up fair and square. Probably the complete opposite. However, expecting 1M views of random music play to be worth more than some $5k is a long stretch. On their own, sure 1M views would account for much more if it was a very focused platform, however, it caters to a huge palette of artists. The dispersion of risk/quality and focus targets makes it not really the prime money machines.

If you want to make money in this industry - keep to the old-fashioned methods. Concerts and live performances are what rake in the big money - CDs, Views or whatever useless metric people try to convert to $$ numbers only works in obscene numbers. All else is just trying to get there - and that is usually the dirty and hard part of the music industry.

I somehow keep being fascinated by people think they're ripped off. I mean sure, Spotify is making a decent buck out of it, but it's not like the artists are doing it for free.

There's much more to the whole process. Firs to earn something per play there need to be ads that finance it. Then imagine the technical hurdle and cost to host such a platform (ie Spotify cut) and then you actually being worth a damn as an artist.

1M views might seem like a lot, but actually its quite a limited resource for serving ads. The other thing here is that most artists wouldn't have a single view if it wasn't for one or the other distributor. Basically, the barrier is so low to entry and the risk is dispersed across a million other artists so you all get a very diluted value per view. But at least you get value per view. Otherwise, it would have been an all or nothing business, like it used to be. It's the same effect the app stores had for software devs.

In essence, you get low fees because those funds pay for the distribution and risk that is dispersed. The general pay scale is a hockey stick with the last couple % making the majority of the money.

Since you even got the opportunity to get in front of an audience, use it wisely as you need to pump those numbers up. It's a numbers game and your numbers are too low. You need double-digit millions to make a good living off of it. And that's just what it takes. It's not easy, not everyone will make it above the fold, for whatever reason life, luck, marketing...