ac29

I took an embedded C/C++ class online 5-10 years ago and hated it. I dont want to be doing bit shifting math to put some device's registers in the correct state for me to write text to a screen

Yeah I did a project with ESP32 and micropython recently and getting the proof of concept up was very very quick. The agent I was using also had no problem writing drivers for peripherals that didnt already have micropython drivers (I seem to recall it ported C or Arduino reference code)

I’d really rather we didn’t kill animals tbh, but when it comes to growing our food we have little choice right now

Several hundred million Indians would disagree

Its just a single benchmark, but Luna 5.6 xhigh scores within the margin of error the same as Opus 4.8 max on DeepSWE for 8x cheaper. Luna max is quite a bit higher than Opus and still 4x cheaper

OpenCode Go is a great deal but I recently dumped my subscription because I found myself rarely reaching for it over my Anthropic sub (I can get 40 hours of work a week out of the $20 sub and almost never hit weekly limits). Subscribed to OpenAI as my secondary and I've been really impressed with that too so far.

I expect if they add Kimi 3 to Go the limits are going to be really low since 2.7 is already one of the most limited models and 3 is much larger.

You do understand that the "frontier" people are usually talking about is the cost-intelligence frontier right?

By definition there is no model that is both cheaper and as intelligent or better than another on the frontier.

You will see people claim Claude uses 2x to 4x the tokens of GPT.

My guess is something to this effect was in the prompt and the LLM made a point of correcting it

Try an 8 bit quant of Qwen 35B, but temper your expectations. Those Qwen 3.6 models are impressive for the size, but you need an order of magnitude more parameters to actually be useful for more than trivial work in my opinion.

Phased array radars are export controlled in the US. It doesnt mean its illegal to build or own, but it might be illegal to sell in some cases

llama.cpp supports a wide variety of 4-bit and smaller quants and mmap's models by default, so you dont need to be able to hold the weights in memory (the OS will handle bringing them in from storage as needed)

Its cool to see this implemented in a tiny amount of code without dependencies, but does it actually bring more performance?

So... maybe we can still use third party harnesses with Claude Code subscriptions... for now?

The way I read this is: yes, if the third party harness uses Anthropic's Agent SDK. Most of them do not, AFAIK, and are still against ToS (though maybe its not enforced for now)

I have a SwitchBot Meter Pro CO2 that is just temp/humidity/C02. Works well and was inexpensive ($50 or so).

I've got a NDIR CO2 sensor about 6 weeks into a supposed 1 year battery life, still reporting 100% battery. Power use is very low since it only fires up the CO2 sensor every 30 mins.

Giving users ability to use apt with root privileges is pretty much game over security wise. Full root is a malicious package away

Anthropic just provides a subscription - which Enterprise usually doesn't want you to use because everything you're submitting through that will be trained on / becomes part of their model.

My Pro account very clearly has a toggle for "Help improve our AI models: Allow the use of your chats and coding sessions to train and improve Anthropic AI models."

The inference providers are running batch sizes much larger than 10

I'm certainly willing to believe the M1 was the most energy efficient, but your data center didnt have anything faster than a laptop?

I did my first ESP32 project recently and was amazed you can get a system that starts up Micropython, then a Wifi AP, DNS, and Web Server in a second or two total and uses less than 512kB RAM. And thats with a high level programming language.

IBM no longer owns any fabs

Per IBM: "IBM Research at Albany [...] includes more than 100,000 square feet of semiconductor fabrication space"

I guess that is technically a R&D fab not a production one, but they definitely have in house fabrication capability

Most real financial transactions need to start and end in fiat though, and that's where the costs are

A change in regulations is not a meritless argument, it's useful information

You could subscribe to Anthropic/OpenAI for the rest of your life for the cost it would take to host GLM5.2 locally - you need 1.5TB of VRAM just for the weights

I'd rather use Sonnet than Qwen

I get this, though the pace of Chinese releases is relentless. Qwen3.7 Plus/Max (closed variants) feel notably better than Qwen3.6, and Minimax M3 is a big jump from 2.7 in capability as well. Both of these families had their previous major release less than 90 days ago.

Anthropic must have Sonnet 5 either waiting or cooking though, they said smaller and larger models than Opus were coming and we already briefly had the larger model.

If you use uv, python apps use a shared cache which helps a lot.

All current Qwen 3.7 models are closed though they have said more releases are coming

Been using zmx for a few months and love it: https://github.com/neurosnap/zmx/

Very similar, based on libghostty

I'm curious what the downside for this speed is here

"DiffusionGemma's speedup is designed for local and low-concurrency inference. In high-QPS cloud serving, autoregressive models can be deployed to saturate compute efficiently, so DiffusionGemma's parallel decoding offers diminishing returns and can result in higher serving costs"

Most of that cost was presumably the 100,000 GPUs it contains, they didn't even build the building

According the the X post, each 150kW satellite is a bit over 2 tons, so a full year of launches would get you 75MW. Thats not much when AI datacenters are GW-class.

in the process standardized not just electric charging but the plug we're all using today

Wat? Are you talking about NACS? If so, a minority of non-Tesla EVs currently on the road use it in the US, and AFAIK zero outside of North America.

And even in the US, the vast majority of EV charging stations are AC and use J1772, a SAE standard that predates Tesla's existence.