coffeecoders

7 ms·

61.
by coffeecoders 11mo ago
A lot of these "Uber for X" conversations miss a deeper point. The software only works as a force multiplier when the underlying labor is modular and fungible. Ridesharing works because every trip is basically the same API call i.
62.
by coffeecoders 11mo ago
Yeah, it’s a never-ending curve. I built an 8-bit computer on breadboards once, then went down the rabbit hole of flight training for a PPL. Every time I think I’m "done," the finish line moves a few miles further. Guess we nerds
63.
by coffeecoders 1y ago
Your site gives me ssl error.
64.
by coffeecoders 1y ago
This line is often used to downplay how much economic stress shapes mental health.
65.
by coffeecoders 1y ago
Sure, for most of human history, survival was a daily concern. It's just unnatural that in a time of record productivity and abundance, many still feel the same survival anxiety. My point isn’t that we’re worse off than pre-industrial
66.
by coffeecoders 1y ago
The idea of slowing down and finding joy in small routines assumes you've already escaped the constant anxiety of bills. It’s hard to be at peace when your baseline reality is a few paychecks away from chaos. There’s a quiet cruelty in
67.
by coffeecoders 1y ago
Wanted to see if it's worth upgrading from the M1 Pro, but I don't see the M5 Pro in the compare dropdown. https://www.apple.com/macbook-pro/compare/
68.
by coffeecoders 1y ago
Love the grind! One suggestion would be to add a demo link with some test data so we can see it in action. I am also slowly "offlining" my life. Currently, it is a mix of synology, hard drives and all. I have always thought about
69.
by coffeecoders 1y ago
The troubling part is we are in the AI bubble whether we opted in or not. The downstream effects are everywhere - real estate (data centers), energy (power consumption), education (automated tools), employment (tech layoffs), and equity mar
70.
by coffeecoders 1y ago
@dang Title needs to be changed to something like "Bezos says AI is in industrial bubble yet promises huge benefits"
71.
by coffeecoders 1y ago
Every bubble looks obvious in hindsight. The dot-com crash left behind Amazon and Google. The crypto crash left behind Coinbase and a few real revenue generating companies. If this is the AI bubble, then the survivors are going to look very
72.
by coffeecoders 1y ago
My washer has this 'Eco' mode, that is supposed to optimize time, water, and energy usage based on load weight and how dirty my clothes are. It finishes anywhere between 30 to 50ish minutes. Same settings an d all.
73.
by coffeecoders 1y ago
Such a good UI.
74.
by coffeecoders 1y ago
Uber and Airbnb solved real pain points: global availability, predictable, nice interfaces, cashless payments, reviews etc. These are the things small, local systems struggled to provide consistently. Also, my point isn't that the cur
75.
by coffeecoders 1y ago
Nothing extraordinary like yall. I've been down a prime numbers rabbit hole. Trying to see the largest prime I can generate in a browser.
76.
by coffeecoders 1y ago
Convenience, consistency, and global. They solved real pain points, even if the cost and ethics are now questionable. It’s like a software library that’s buggy and bloated but everyone depends on it because rewriting it from scratch is hard
77.
by coffeecoders 1y ago
Yeah, the valuations are crazy, but think about it this way: the app economy and gig economy seemed absurdly speculative at first too. And now they’re worth trillions. Early stage hype overshoots, sure, but sometimes it’s just pricing in th
78.
by coffeecoders 1y ago
Totally get the frustration. Uber and Airbnb definitely have their flaws. But the sheer scale of users (200M last I checked) shows that a product can be both polarizing and essential at the same time. Kind of like how we’re seeing with LLMs
79.
by coffeecoders 1y ago
Hackernews used to dunk on Airbnb, Coinbase and Uber. Now they're part of our daily lives. Feels like we’re watching the same arc play out with LLMs. I wonder if we’re seeing the same pattern repeat here with ChatGPT becoming big. Outr
80.
by coffeecoders 1y ago
Ollama started out as the clean "just run a model locally" story, but now it’s branching into paid web search, which muddies the open-source appeal. Windows ML goes the other direction: deep OS integration, but at the cost of tyin
81.
by coffeecoders 1y ago
On a slightly related note- I've been thinking about building a home-local "mini-Google" that indexes maybe 1,000 websites. In practice, I rarely need more than a handful of sites for my searches, so it seems like overkill to
82.
by coffeecoders 1y ago
I find it interesting how a lot of this advice overlaps with the same tricks we use in software engineering to tackle big problems. Breaking things into smaller chunks or even gamifying with streaks is basically the human version of agile s
83.
by coffeecoders 1y ago
Yes, the key difference is GNOME has strong downstream partners that treat it as the default (e.g. Fedora Workstation, Ubuntu). This way GNOME gets a lot of testing, polish, and feedback without having to maintain its own dist.
84.
by coffeecoders 1y ago
Without being too negative, I'd like to point out that Neon, ElementaryOS etc tried the same thing. A project thinks we need our own distro but ends up pulling resources away from improving the desktop environment itself. GNOME doesn’t
85.
by coffeecoders 1y ago
It is less about conversion and more about extending ANE support for transformer-style models or giving developers more control. The issue is in targeting specific hardware blocks. When you convert with coremltools, Core ML takes over and d
86.
by coffeecoders 1y ago
I agree that it's kind of magical that you can download a ~10GB file and suddenly your laptop is running something that can summarize text, answer questions and even reason a bit. The trick is balancing model size vs RAM: 12B–20B is ab
87.
by coffeecoders 1y ago
I feel the same way. Back in the day, I spent a lot of time on namepros and xda developer forums, and a few of the friendships I made there have lasted for years. I still talk to some of those folks weekly, and even meet a couple in person
88.
by coffeecoders 1y ago
I think that’s the real distinction: the Pi isn’t interesting as a "cheap desktop", it’s interesting because of GPIO + the huge ecosystem of HATs, sensors, and weird little projects. If you just want a small, cheap computer, x86 b
89.
by coffeecoders 1y ago
This is my recurring gripe with these "mini computers": Power cable? Not included. SSD adapter? Not included. Needs a mini HDMI to HDMI cable. Needs a cooling case (absolutely required for Pi 5). It feels a bit like Tesla’s "
90.
by coffeecoders 1y ago
There isn't anything really. The WSL backend is the pain point, which doesn't go away with Docker or Podman or anything else.

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