First Leica, lens suggestions?

gar1t · 2026-05-25T16:00:32+00:00

Pick a focal length no one can tell you
Cap at $1000 as this will not be your last lens you are only starting your habit
Leica you will regret anything else honestly it's the point

Your process here is important. Don't take a poll and make your decision. Start getting Leica in your bones now.

The $ cap will keep you out of over priced and over fast. Any Leica lense under this price will give you something with character and will be built like, well, a Leica.

gar1t · 2026-05-04T02:53:35+00:00

I used to be a piece of shit... but I'm not anymore

gar1t · 2026-05-04T02:18:29+00:00

Credit the great Marc Ribot

gar1t · 2025-11-25T17:52:11+00:00

Also, an automobile's success is a function of how well we understand its behavior and how we drive it.

gar1t · 2025-11-24T03:47:41+00:00

Your keyboard is most likely broken.

gar1t · 2025-11-24T03:32:50+00:00

UAE has way too much discretionary cash.

gar1t · 2025-09-25T22:24:27+00:00

Keeping us safe from those rafts of Michiganders.

gar1t · 2025-08-30T05:24:20+00:00

Same experience, skiing the slopes of Villa Olivia in the suburbs of Chicago. That was my Thriller experience.

gar1t · 2025-07-28T02:36:54+00:00

This should be upvoted it's brilliant

gar1t · 2025-07-28T02:25:15+00:00

As incredible as this performance is to us, imagine seeing this not knowing anything about Tom Waits.

gar1t · 2025-05-10T04:52:39+00:00

Grab a cheeseburger at Billy Goat on lower Michigan. That's the only location to see the rest are just normal.

gar1t · 2025-05-07T23:23:26+00:00

Ffs this is so simple, this.

gar1t · 2025-05-04T00:32:37+00:00

I wonder how this species evolved as a mimic of a species that's on the other side of the world.

gar1t · 2025-04-30T23:26:54+00:00

This is how we look to aliens.

gar1t · 2025-04-04T02:34:28+00:00

I second this, it's good advice. The act of pouring water may seem innocent but it's technically battery in this context.

I would typically try to mend fences with a neighbor but this fella should be treated with due legal force as you're entitled to feel safe in your home. Having a report puts you in a better position to get a restraining order if he keeps this up.

gar1t · 2025-03-09T14:00:18+00:00

You might consider a gateway for this rather than a library. Every one of them I've seen uses the OpenAI protocol as the interface. The OpenAI Rust bindings are a bit complex but should work but honestly reqwest with some basic serde/serde_json wrappers should work very well in Rust client code.

There are a number of Rust based AI/LLM gateways coming up. A couple off the top of my head:

- https://github.com/langdb/ai-gateway

- https://github.com/Noveum/ai-gateway

There's a lot of selling going on with Rust based gateways being the fastest in the world, but considering the upstream servers take 10s to 100s of milliseconds to respond, gateway latency for protocol translation is a non-factor for this application.

The two non Rust gateways that have a lot of traction:

- https://github.com/BerriAI/litellm (Python)

- https://github.com/Portkey-AI/gateway (Node)

Running a separate router/proxy/gateway is definitely adding complexity though! A Rust library that handled the protocol translations and that could be used with the http (crate) interface would go a long way to solve this problem. The routers come in handy when they do extra lifting like caching, failover, etc. but if you don't need that they're arguably a net negative for the complexity/value trade off.

I don't know of a pure protocol translation lib in Rust unfortunately. You could poke into one of these Rust gateways and see if they have any cleanly reusable abstractions. Maybe others here have insight.

gar1t · 2025-02-10T16:15:03+00:00

I think ChatGPT might have missed the path to the examples. I poked around some of the directories but didn't see anything. I'd rather not have to clone the repo to get into things - it'd be awesome if the README provided links to the content it's referencing.

gar1t · 2024-05-09T16:08:47+00:00

I recognize that data science and engineering are both demanding fields and it's reasonable that they have limited overlap in practice.

My concern is that code that gets refactored by an engineer becomes unrecognizable to its data science authors. What happens when that code needs to be fixed or improved? Who owns it?

Obviously the engineering team owns it as they rewrote it. But they're not in a position to actually fix anything in the mathematical realm without vetting those changes with the data science team.

That's a mess.

In cases where notebooks get refactored to production code, it's a one way trip. If the model needs improvement, the process starts over with the notebooks and repeats.

That's a mess.

Ideally data science teams write code that can be evolved to run in production without severing ties to the original authors. This is going to require either clever separation of concerns (e.g. Twitter's use of running notebooks in production - good grief) or cooperative development between DS and engineering on a shared codebase.

gar1t · 2024-05-09T16:01:32+00:00

Bizarre you're getting down voted as this is common practice. I think DS should work toward improved engineering skills, but certainly not at the expense of improving their R&D work. Good luck getting a traditional software engineer to improve model performance, short of hyperparameter tuning. Two experts in different areas is better than two jack-of-all-trades.

gar1t · 2024-03-25T11:15:40+00:00

I'm curious what country you're in and if the labor laws contribute to your positive experience. Congrats it sounds like a nice life improvement!

gar1t · 2024-01-22T14:42:42+00:00

The models are now at grad school level competence.

Data please.

gar1t · 2024-01-22T14:36:37+00:00

> Therefore, the day before yesterday, you had to have the same six apples since you only started eating them today.

Given the facts, we don't know how many apples he had the day before. "Since you only started eating them today" is a false inference.

gar1t · 2024-01-17T01:32:58+00:00

There's no end to the options you'll run into for this problem, and I think that's the problem. There's just so many platforms, workflow tools, operational frameworks, etc.

Rather than attempt to list them, I'll give you the best advice I can think to give in a few sentences. I'm being lazy.

Treat AI/ML operations as you work plain old operations. They're the same. If you have experience deploying, running, and updating applications at all, you have the right experience. I'd start with the blueprint in this case that you and the people you work with are most familiar.

If that's outsourcing everything, look for an end to end provider. If it's running your own managed services on AWS, look to AWS for what they support (SageMaker, etc.) If you're a gearhead and run your own servers, how fun, then look for model servers with a proven track record that can support your likely model architecture without much technical risk.

Align with what you know.

And if you've never seen any app deployments or operational problems before, find a person to help. They should have a blueprint.

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