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In this specific case, it's the other one which is a duplicate of this one, it just so happens the other one got the upvotes and commentary -- it happens, who knows why

I also will never cease to wonder why there isn't the most cursory check for duplicate urls or keywords, but I guess it's the same answer it always is: it's just not important to them, for all values of "them"


This. I've seen a couple open core startups that are less than a year old with thousands of stars on their repositories, so I decided to have a look at some of these profiles who starred the project. Most of them have weird usernames that resemble spam accounts, almost all of them cannot be pointed to some other profile on a different platform (Twitter, LinkedIn, HN etc.).

Another giveaway is the ratio of stars to watchers / forks. I remember one project with thousands of stars but only 10 users "watching" it. They went on to raise a sizable seed round too.


> Another giveaway is the ratio of stars to watchers / forks. I remember one project with thousands of stars but only 10 users "watching" it. They went on to raise a sizable seed round too.

Not necessarily indicative of foul play. I have two projects like this (https://github.com/smacke/ffsubsync and https://github.com/ipyflow/ipyflow) and I attribute it to not having great developer documentation.


Good point. By the way, I checked out both projects above and starred them. Pretty cool!


<3


part of the problem /s


I think they're just playing a larger distribution game to get people locked into Mojo then eventually pay for their Modular engine hosting services, just about the same as most open core, VC backed startups.


I see what you're saying, but it's pretty different from an open core analytics product or something. This is a language/dev environment and the bar is a lot higher because 1) I know it's going to be a big investment to learn the language and ecosystem 2) I'm deeply locked-in technically by writing my stuff in this language 3) the competitors are open source and at this point I'm not worried about python, numpy, typescript etc going away. My feedback is basically that despite this project looking cool, I will not be writing any Mojo until it's open source.


Yup. I've personally used both YAML and TOML for configurations, much more the latter recently and can see pros and cons for both.

> How well suited are their syntactic choices to the community they're targeting?

Also, "best" practices. One could reduce the pain of the other, but by no means is the right solution to a deeper problem at hand. For example, if one has very deep and complex nesting for configs, TOML "may be a lot nicer" compared to YAML, but that doesn't mean using TOML will make all the config parsing problems go away. It just mask away code smell. Maybe time to check if they're overcomplicating configurations in general.


I wear them every day, but take them off if I'm going to high crime cities. The thing is I've been collecting watches for over a decade. My parents are into it, and so is my younger brother. I think it's very rare to share a common interest that won't bore anyone at the dinner table. Now onto the horological aspects - they're like the iPhone / app store back in the day. Keeping track of leap years and all in a 36mm package (think Patek 3940s). Various complications to address various "limitations" of mechanical time telling like the remontoire, co-axial escapements or solid block case constructions for better waterproofness. It's not too different than some of us on HN who fall in love with old Apple IIs, NES or Sega Genesis :)


> On mechanical watches, they are smoother than Quartz since the escapement releases power multiple times / sec. But still ever so slightly jumpy since power is still released in discrete increments.

Yup, and the higher the beat rate, the "smoother" it looks. Grand Seiko Hi-Beats and Zenith El Primeros come to mind. There's a good Hodinkee article describing the tradeoffs of different beat rates [1].

[1] - https://www.hodinkee.com/articles/watchs-frequency-hz-vph-me...


Yep. Hi Beats are real solid.

GS movements really are massively better than others in the 5-10k price range


Malaysian here. Yeah some of the historical sites in Penang or Melaka come to mind. I think the Peranakan [1] culture is one of the most obvious examples in using colors and is widespread to the region, not just in Singapore.

[1] - https://en.wikipedia.org/wiki/Peranakans


VCs aren't always the best capital allocators - a lot has succumbed to the money management + fees disease. They push you to raise more, force you to hire and burn when you really shouldn't / haven't figured out product market fit yet.

> Whatever magical market forces that might change how funding works, they don’t seem to be at play.

I think money is scarcer these days, and founders who are constantly being burned by VCs will think twice about riding the big VC train in the coming years. As a founder myself who work crazy hours getting the business going, it's painful / bad optics to see full time VCs doing weekend Vegas trips, browse art galleries on weekday afternoons and fine dining every couple of days, knowing I've sold a chunk of my / my team's hard earned equity on that bs. Of course there are great VCs, and some businesses needing to be VC backed, but oh boy, are there really bad apples out there.


If someone has given you money to build a business, why is their weekend anything to do with you?


Hey there, OP and author here!

> alluding to with respect to the ONNX being an Azure on ramp

Yeah sorry, should've worded it better in the original article. ONNX is one of the industry's first attempt at standardization of ops across various deep learning frameworks. Here's a way to think about it: Like Google, Microsoft has a cloud business. Unlike Google, it doesn't have a deep learning framework (Tensorflow) and is a significant threat if the cloud players continue to vertically integrate their ML stack. So ONNX makes sense, ie. you, the ML engineer should convert to ONNX so now at least you can run it on multi cloud providers!

Tangential to this, there's also a rise in heterogenous environments, and picking the "best" is non-trivial. A lot of serving / inference hosting companies capitalize on this, and ONNXRuntime is sort of Microsoft (Azure)'s answer: "give me an ONNX or PyTorch (which we will subsequently convert to ONNX), and I'll show you how easy it is to deploy it to Azure". The key nuance here is how much user tooling friction there is to deploying models, and it's in the best interest of these cloud providers to sometimes use their open source initiatives as on-ramps to their larger cash generating products / services.


Same. When I was at my first SWE job after college, I’d get up at 6am and try to beat Chicago traffic to be at my desk at 7am. That’s when I’d pull up HN or my list of technical topics I’d like to learn, then go for it until my teammates arrive. Rather shamelessly, I even had Leetcode open and went through exercises weeks before I left the job. Good reflex training having to force close it right around 8:30am though :)


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