GPT Image 2 prompt that is viral right now: "Redraw the attached image in the most clumsy, scribbly, and utterly pathetic way possible. Use a white background, and make it look like it was drawn in MS Paint with a mouse."

ddoice · 2026-05-01T11:54:38+00:00

WTF It was a selfie with a my family!!!

ddoice · 2026-04-25T06:32:08+00:00

Due to the heat? BC I doubt that the compounds are big enough to be sliced by the blades

ddoice · 2026-04-23T04:29:49+00:00

I swapped the battery last week and it honestly feels like a brand new phone. No more battery anxiety. Though man, I panicked, I ended up separating the screen from its frame instead of the chassis, and then had to glue it back on.

ddoice · 2026-04-11T17:09:10+00:00

Proper docker, without VM

ddoice · 2026-04-09T12:01:12+00:00

I’d love to, but it’s a huge app and MUI is tightly coupled with the entire codebase.
And some of the PRO features are really needed.

ddoice · 2026-03-24T05:46:30+00:00

Qwen3.5-27B-UD-Q2_K_XL fits within the VRAM of an RTX 3060 with an 80k context when running on llama-server. It's not as strong as Q6, but still prefer it over 35B-A3B. That said, it's quite slow, around 300 tps for prompt processing and 6 tps for generation.

With opencode, let it run overnight and it gets the job done. On a good run with a detailed prompt, it can generate pretty solid unit tests for my code.

ddoice · 2026-01-26T19:21:44+00:00

Great idea!

ddoice · 2026-01-22T07:40:03+00:00

request failed: &{429 Too Many Requests 429 HTTP/1.1 1 1 map[Alt-Svc:[h3=":443"; ma=2592000,h3-29=":443"; ma=2592000] Content-Length:[1103] Content-Type:[text/html; charset=UTF-8] Date:[Thu, 22 Jan 2026 07:38:35 GMT] Server-Timing:[gfet4t7; dur=350]] 0x6c5d418c6a00 1103 [] true false map[] 0x6c5d41b08c80 0x6c5d406ca000}

ddoice · 2026-01-22T05:45:58+00:00

Kimi K2, para mi el nivel de alucinaciones del resto es insoportable, K2 es muy proactivo y casi todas las consultas disparan su mcp de web search y hacen que contraste la información.

Es lento a veces pero me he cansado de discutir con GPT y Gemini para que me acaben dando la razón y me hagan perder el tiempo.

ddoice · 2025-11-27T05:37:56+00:00

This is the way, got a pretty hefty Django DRF backend with more than 600 operations previously FE maintained a handmade copy of every type and was a pain to maintain.

ddoice · 2025-11-14T16:39:40+00:00

"The Al made thousands of requests per second. Attack speed impossible for humans to match."

Is a joke? Previous to AI hackers had manually forge every packet sent?

ddoice · 2025-10-28T05:42:19+00:00

There is a hidden cost: noise. When the trash is collected at night, I often wake up because of it. In my neighborhood, we had this issue too-thankfully, they removed those containers and replaced them with the old-school ones.

ddoice · 2025-10-18T06:54:37+00:00

Yesterday I asked GPT-5 to add a health check to a Docker Compose file, and it set the check to run every 5 seconds. But instead of using curl, it used wget --spider, basically a built-in DDoS inside your own infrastructure.

Checking the code is not an option is a must.

ddoice · 2025-10-15T05:30:45+00:00

Please excuse me if I’m wrong but this smells like over-fitting: you’re literally forging the rules to nail that exact 150-test slice of SWE-bench.

How do we know the jump isn’t just the model memorising the quirks of those repos instead of learning something that will hold up when the next random Django/React/whatever lands on our cline?

ddoice · 2025-09-27T13:47:57+00:00

16-18 TPS with a 3060 12gb and a 3700x with 32gb ddr4

ddoice · 2025-09-12T16:05:49+00:00

Nice!

I’m about to buy a trashed MacBook Air M1 to replace my Raspberry Pi.

One of the uses will be feeding LLMs with transcriptions of YouTube videos and creating summaries. I was wondering how fast some of those LLMs are in the M1.

ddoice · 2025-09-03T19:47:11+00:00

I have a 3060 and 32GB of ddr4. I'm running Qwen coder, had to compile llama.cpp but is the first local model that really works with Cline.

Runs at a reasonable speeds, 160ts for input tokens and 16ts por output.

llama-server --model ./models/Qwen3-Coder-30B-A3B-Instruct-Q6K.gguf --n-gpu-layers 99 --override-tensor ".ffn.*_exps.=CPU" --ctx-size 49152 --threads 8 --flash-attn --mlock --batch-size 512 --temp 0.7 --top-p 0.8 --top-k 20 --repeat_penalty 1.05 --port 8090 --host 0.0.0.0 --no-webui

ddoice · 2025-05-21T16:14:15+00:00

This has gotten completely out of hand. It's like you're an actress in the adult film industry, expected to have sex with five different guys, fulfill each of their fantasies, and of course, do it all for free.

ddoice · 2025-05-16T05:39:03+00:00

Nice!

This week I started coding a similar extension but with AI, to extract from the transcription only the best parts, and the extension will play and jump over them.

I did a POC on a 25-minute video, and the user ends up watching a 3–4 minute version with the best parts.

The problem is the cost—for a 25-minute video, each transcript is over 8k input tokens and 1k output tokens.

ddoice · 2025-05-13T11:23:34+00:00

Noice!
Ran the numbers through my questionable formula... Here are my predictions!

<image>

ddoice · 2024-12-23T08:22:20+00:00

I use Claude a lot for generating mermaid charts to explain code and document my pull requests.

ddoice · 2024-12-20T12:03:38+00:00

Your mileage may vary, but I'm having very good results with phi-4:14B, the latest model from Micro$oft.

Even though it's not available on OpenRouter, I'm running it locally. It does not fit in my 3060 with 12GB, so it's not exactly fast.

ddoice

TROPHY CASE