BeefySwain

New policy: no more non-competes

> The Commission also finds that instead of using noncompetes to lock in workers, employers that wish to retain employees can compete on the merits for the worker’s labor services by improving wages and working conditions.

I absolutely love this.

> The linters teach what to do, but not why

Ruff specifically actually has a web page for every single check with a section on the rationale behind it.

I regularly use this when I see an error that I don't understand the purpose of, and am often convinced, though sometimes I recognize that the thing it's trying to protect me from doesn't apply in my particular case and so I disable it. Regardless. I feel it has had the effect of making me a better developer.

The feature I am most excited for is definitely the splitting of "economy time" from "calendar time".

Detailed here: https://www.openttd.org/news/2024/03/23/timekeeping

Can someone ELI5 what this may make possible that wasn't possible before? Does this mean I can buy a handful of 4090s and use it in lieu of an h100? Just adding the memory together?

I believe this is what they are referring to: https://www.crowdsupply.com/solokeys/somu

How does this work exactly? What calls that function and when?

I am used to postmortems posted to here being a rare chance for us to take a peek behind the curtain and get a glimpse into things like architecture, monitoring systems, disaster recovery processes, "blameless culture", etc for large software service companies.

In contrast, I feel like like the greatest insight that could be gleaned from this post is that OpenAI uses GPU's.

I see this said a lot and while I understand the spirit of it, do any of these apps actually call it a bid when it works that way? I don't believe they do

If you would like to contribute to a Python Text Editor / IDE, I would suggest https://github.com/Akuli/porcupine

It has a great (but very small) community and the maintainer is phenomenal as well.

You should go to a Midwest Dollar General and buy a days worth of food for a family of 5 and report back on if you think the theory still doesn't apply.

Can you expand on what you mean by this? Specifically: "you can't move the responsibility of operations away from the application teams without seriously compromising incentives that effect quality, throughput and reliability"

Can you expand on what you mean by slow? For me everything loaded extremely fast.

Is this something that is available to purchase?

In a similar vein: https://github.com/PyHAT-stack/awesome-python-htmx

> some affordable and reasonably low powered x86 thing

https://www.digital-loggers.com/api.html

Outside of the headline, there is some major stuff hiding in here: - new gpt-3.5-turbo-instruct model expected "in the coming weeks" - fine tuning of 3.5 and 4 expected this year

I am especially interested in gpt-3.5-turbo-instruct, as I think that the hype surrounding ChatGPT and "conversational LLMs" has sucked a lot of air out of what is possible with general instruct models. Being able to fine tune it will be phenomenal as well.

If I'm understanding this correctly you need to use Cargo to install part of this. That makes it a lot harder to start using as someone in the Python ecosystem (who is not also in the Rust ecosystem)

Sidestepping all of the ethical questions of embarking on this "research", I'm surprised the number was that low.

Linux[0] itself has about 1.2 million commits, so apparently Linux is within an order of magnitude of bringing GitHub to it's knees?

[0] https://github.com/torvalds/linux

Some discussion yesterday: https://news.ycombinator.com/item?id=36452101

I would love to see a more fleshed out rebuttal of it. Is it a scale issue?

Great list, I went ahead and added it to the bottom of my "Awesome" Python HTMX page: https://github.com/PyHAT-stack/awesome-python-htmx/tree/main

> The UNIHIKER's pins are compatible with micro:bit

They really bury the lede here, awesome that there is already an ecosystem that exists for the edge connector.

And are wanting to have all your Google accounts banned for life.

Can you give an example of a prompt and the output for each that you find Bard to be better for?

Come on everyone, we all know that "most of the work that goes into software engineering isn't writing code", that "it's impossible to create a working system in one shot", etc etc etc, and therefore this tool will not give a realistic idea of what it would cost to build a system with nothing but GPT-4.

No one here (including the author) is under the impression that you can just ask ChatGPT to "write a Unix-like kernel" and get Linux spit out the other side.

That said, I am really curious what it would cost, as a theoretical lower bound, to pay OpenAI to write the Linux Kernel. 10 grand? 100 grand? I have no clue, but I'm glad someone wrote a tool to make it easier to find out!

Okay fair enough then! I'd be interested to see what the rationale was, and if my knee-jerk reaction was unwarranted :)

Using Mustache instead of Jinja for a Python package is a choice

> Yes, a website is different than a webapp and has different requirements.

The piece missing here is that most people do not stop to think which they are building before they reach for a JS heavy SPA framework and start spinning up microservices in whatever AWS calls their Kube implimentation.

I keep seeing people talk about this, can someone create a minimum example of what this exploit would look like?