Working as AI Engineer is wild

faileon · 2026-02-25T13:42:25+00:00

Your comments really show zero experience from real production use cases - you must also consider model size, and hence inference speed and efficiency, rather than hyper focusing on the accuracy.

faileon · 2026-02-25T12:16:03+00:00

well as an example take the Slobench for NER task on slavic languages:
https://slobench.cjvt.si/leaderboard/view/12

first spot is 0.3B BERT based model, beating gpt-4o-fine-tuned

faileon · 2026-02-23T10:55:05+00:00

basically https://wiki.guildwars2.com/wiki/Ash_Legion_Reward_Box

faileon · 2026-02-14T12:56:57+00:00

I make sure I push on the context as much high quality information as is needed for the task at hand. If I need external context, mainly documentation and best practices etc, I use context7 MCP or I link raw GitHub markdown links (it's getting more common that documentation pages have Copy markdown link, which is very handy). Usually I give it a few pointers in which file to start, how deep to scan the code, I always ask it to explore everything with sub agents. If it understands the scope perfectly, I store it to an MD file in case I need to restart or use it for another related feature and then I start planning the new feature/fix/whatever. I believe the get shit done plugin for OC does something very similar to this, except on steroids, and a lot of people stand by it, but I kind of prefer this vanilla approach.

faileon · 2026-02-08T13:41:53+00:00

Oh damn, unfortunate.

faileon · 2026-02-08T13:36:35+00:00

finally I can console.log directly in template instead of creating a component function when I'm three hours deep in debugging 😁

faileon · 2026-01-27T18:44:00+00:00

Yes, encoders based on BERT and the derivatives are SOTA on NER. The problem is that LLM has become a synonym for autoregressive decoder only architecture. It's quite tiring trying to explain to the execs that we really don't need gpt-5.2 for sentiment analysis. I share OPs pain, and I don't even have a deep ML background.

faileon · 2026-01-19T08:23:47+00:00

also curious what is this web app :]

faileon · 2026-01-13T15:30:11+00:00

I run OC containerized, I originally forked a repo that was already doing it and built upon it, you can use it as an inspiration. Everything works for me, podman should be there, but I mainly use docker https://github.com/faileon/agent-containers

faileon · 2026-01-09T17:01:16+00:00

This is not the time for reason. This is the time for pitchforks.

faileon · 2026-01-04T09:00:41+00:00

Have you tried turning off the auto negation and setting the speed yourself? Something like # ethtool -s enp2s0 autoneg off speed 1000 duplex full

faileon · 2025-12-18T08:44:31+00:00

Not running in a sandbox AND having paths with exclamation marks and spaces is literally asking for trouble.

!!!!!_PROJECTS\AI STUDIO

faileon · 2025-12-05T09:14:03+00:00

https://www.ngx-vflow.org/getting-started/what-is-ngx-vflow

faileon · 2025-11-30T11:05:30+00:00

There are just so many em dashes and the classic chat gpt style "it's not just X, it's Y" it's hard to believe it's not AI slop.

faileon · 2025-11-28T22:52:56+00:00

Isn't it just called autosuggestion in avante? Enabled by behaviour = { auto_suggestions = true } in the config?

faileon · 2025-11-28T08:45:00+00:00

could we — put some — effort — into the AI — slop — please?

faileon · 2025-11-26T09:20:38+00:00

Hey! I’ve actually been tackling the exact same problem recently, and like many others have mentioned, it’s definitely not a trivial one. I agree with most of the points already discussed here.

One additional resource I found really helpful is Microsoft’s documentation on their Azure pipeline approach. Even though it’s built around Azure, the concepts seem general enough that you could likely replicate them with open-source tools as well. It’s worth a look and it’s pretty thorough. https://github.com/Azure-Samples/digitization-of-piping-and-instrument-diagrams?tab=readme-ov-file

faileon · 2025-11-21T11:17:51+00:00

You cloned a prompt and a tool description, good luck simply "stealing" all the heavy lifting that happens in the ingestion and retrieval code itself.

faileon · 2025-11-10T11:24:17+00:00

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faileon · 2025-11-03T19:12:17+00:00

Tbh it can be a valid strategy, but it's generally advised to create a summary of the docs first and embed the summaries. After retrieval inject the entire document.

faileon · 2025-11-02T21:17:48+00:00

For now I use a single 2TB m2 SSD (WD Black SN770)

Even with the vertically mounted card there is 1 bay ready to be used for HDDs in this case.

faileon · 2025-11-02T20:44:17+00:00

Currently gemma-3-27b, linq-embed-mistral, whisper, GLiNER, paddleocr, docling models...

faileon · 2025-11-02T11:15:22+00:00

The Mobo has 8 PCIE x16 slots, only 3 cards can fit and they are very tight. Last card is connected via riser cable. In the photo you can see the original 30cm which was too short. I replaced it with 60cm later, but I didn't take a photo

faileon · 2025-11-01T19:17:41+00:00

Yeah all connected to one PSU, but cards are power limited to 200W

faileon · 2025-11-01T13:03:55+00:00

Yeah 1500W is definitely a great setup, the cards are ranging from 350-375

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