ac29

> How many programmers really exist out there? Surely it can’t support the weight of investment that exists in AI already. It’s just such a small pool of the human race

I dont consider myself a programmer but use LLMs almost exclusively for coding.

The number of people able to create useful software today is much much larger than it used to be and arguably a minority of these people are/were "programmers"

> Sign in with ChatGPT: how is this not major news? They're launching with partnerships with a bunch of harnesses so you can use your subscription outside of Codex.

Maybe the sign on process is new but OpenAI has explicitly allowed subscriptions to be used in 3rd party apps at least as long as I've been a subscriber (a few months)

I dont think the post you are replying to was saying gambling on lotteries is rational. They are just saying the best possible outcome of buying a lottery ticket is much, much higher than buying an index fund (and the average, median, and worst outcomes are much worse)

I use a tiling wm, but the split view is more compact because it doesnt have two (vertical) tab bars. Useful on a cramped laptop, less so on a large screen

I've eaten wine grapes and while they taste... winey? I also quite like them

Not $518B in the next year, they plan "to spend $518 billion on cloud, computing and infrastructure obligations in coming years" (number of years unspecified)

Haiku 5.5 is DOA without a massive price cut. Luna is literally 10x cheaper at current pricing

> I think almost nobody from that era would have believed you if you told them that more than 50 years later not a single human would have traveled beyond low Earth orbit

Four people went around the moon earlier this year (leaving earth's orbit for the first time since '72)

>They invested $900 million[1] in 2015, and it is worth $94.1 billion today. Why sell?

Didnt you answer your own question? Most would consider a 100x ROI more than sufficient for taking profits

> Note that this is a concept, I've never seen an actual production model look anything like the concept.

Yeah the new Nissan Leaf looked horrible as a concept car, very "2003 idea of the future". The actual production version is just a boring SUV

Which ones? I was prepared to complain about this as well but it supports every band under 3GHz on my carrier

Relevant article about Andon Market: https://www.sfgate.com/local/article/san-francisco-market-ai...

> I always wanted to try atopile - that might be a good match for AI/PCB work.

Unfortunately all public open source work halted 6 months ago and they pivoted to a browser based IDE product to monetize: https://atopile.io/blog/atopile-v16

I sent in a larger, slightly more complex board to JLCPCB over the weekend and it was $175 for 5 boards with components and assembly. Shipping, tariffs (ouch), and sales taxes added another ~$100 or so.

gpt-oss-120b only has 5B active parameters, so its not surprising Qwen3.8 27B outperforms it (Qwen3.8 is also ~13 months newer, which is forever in LLMs)

I did that with Codex+Sol alone, and made something even more complex in less time with Codex+Astra over the weekend.

Its maybe more hands on than you want it to be, but you mostly just need to supervise the work. But yes, the CAD outputs go directly to the JLCPCB ordering form, or whereever you fab

US prices dont include taxes, EU prices do

GPT-6 is multimodal, LLMs alone have no vision capability

the methyl groups make it organic chemistry (and dangerous), elemental mercury is fairly safe

> AMD Strix Halo is about to release 192GB system which is a big upgrade to their current 128GB ai pc

Big upgrade to memory capacity but memory speed is only going up by a few percent, so its still going to be slow with more than a few B active params (I have one)

Micropython runs on tons of stuff and while it isnt capital-P Python, its close enough for doing a wide variety of embedded work without learning a new language/libraries/etc.

Because process affects performance per watt more than architecture so its a useful data point.

Even knowing nothing about performance, knowing that it is N6 means it probably isnt particularly power efficient (as compared to leading edge x86/ARM).

> FCC allows suppliers to self-declare conformance with EMI/EMC rules

Yes, though they can also ask for your lab results or to inspect your testing facility and hit you with massive fines if it turns out you falsified your compliance documents. As you mentioned this is very rare though - even enforcement actions against non-certified intentional radiators are uncommon.

I have Kagi and ChatGPT subs and would agree ChatGPT is the better offering. But you can use Luna with Kagi Assistant on the cheap plan which works pretty well too

There haven't been any free resets in the past week, there were 4 in the first half of the month

Cost per task:

  Model                        Score    Cost / Task    Output Tokens / Task
  -------------------------------------------------------------------------
  Muse Spark 1.2 (xhigh)        56.8          $0.40                  30,430
  Gemini 3.7 Flash (high)       56.0          $0.40                  36,847
  GPT-5.6 Terra (max)           56.6          $0.51                  20,838
  GPT-5.6 Sol (high)            57.3          $0.52                   7,545
  GLM-5.2 (max)                 53.0          $0.56                  32,200
  GLM-5.3 (max)                 59.5          $0.68                  41,107
  GPT-5.5 (xhigh)               56.3          $0.69                  16,893
  Grok 4.6 (high)               60.9          $0.84                  21,735
  Kimi K3 (max)                 59.7          $0.84                  25,474
  GPT-5.6 Sol (xhigh)           59.0          $0.87                  11,098
  Qwen3.8 2.4T A95B             57.7          $0.95                  32,472
  Claude Opus 5 (medium)        58.6          $0.98                  12,459
  Qwen3.8 Max                   58.1          $1.13                  38,287
  GPT-5.6 Sol (max)             60.9          $1.23                  16,879
  Claude Opus 5 (high)          61.5          $1.52                  21,353
  Claude Opus 4.8 (max)         57.3          $1.65                  33,557

Benchmark score:

  Model                        Score    Cost / Task    Output Tokens / Task
  -------------------------------------------------------------------------
  Claude Opus 5 (high)          61.5          $1.52                  21,353
  GPT-5.6 Sol (max)             60.9          $1.23                  16,879
  Grok 4.6 (high)               60.9          $0.84                  21,735
  Kimi K3 (max)                 59.7          $0.84                  25,474
  GLM-5.3 (max)                 59.5          $0.68                  41,107
  GPT-5.6 Sol (xhigh)           59.0          $0.87                  11,098
  Claude Opus 5 (medium)        58.6          $0.98                  12,459
  Qwen3.8 Max                   58.1          $1.13                  38,287
  Qwen3.8 2.4T A95B             57.7          $0.95                  32,472
  Claude Opus 4.8 (max)         57.3          $1.65                  33,557
  GPT-5.6 Sol (high)            57.3          $0.52                   7,545
  Muse Spark 1.2 (xhigh)        56.8          $0.40                  30,430
  GPT-5.6 Terra (max)           56.6          $0.51                  20,838
  GPT-5.5 (xhigh)               56.3          $0.69                  16,893
  Gemini 3.7 Flash (high)       56.0          $0.40                  36,847
  GLM-5.2 (max)                 53.0          $0.56                  32,200

> Using Google products in general is an effing nightmare as soon as you have to give them money

Spending money via Google Pay on Android is extremely easy, Google does know how to accept customer's money (in the consumer space)

Last time I used the AI studio free tier it was limited to one or two requests, effectively useless. I think people are complaining its too hard to set up a paid API key (no reason you should make paying customers spend more than a few clicks and a minute of their time to pay you)

Muse Spark 1.2 benchmarks just shy of Opus/Sol and is significantly less expensive than Sonnet (which admittedly is overpriced). Haven't personally used it though

China has as least much engineering talent as the US, the claims that Chinese models must just be distilled US models feels like xenophobia.

There are more plausible explanations for why the models are similar - all the labs are buying the same datasets from third parties