Art Of Philosophy

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[Art Of Philosophy @Deep_philo]

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Psychology Thread

[Art Of Philosophy @Deep_philo]

@Manu_Sisti How

[Manu Sisti @Manu_Sisti]

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[Art Of Philosophy @Deep_philo]

@Manu_Sisti 🙏

[Chris @ChrisGPT]

Been hearing some pretty interesting things about a small AI research team experimenting with post-training Qwen 3.8 27B.

Apparently their post-hoc GQA → MLA conversion, which reportedly reduces KV-cache memory requirements by up to 8.4x without additional training

[Manu Sisti @Manu_Sisti]

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[Art Of Philosophy @Deep_philo]

@TommiPedruzzi KDP

[Tommi Pedruzzi @TommiPedruzzi]

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[Stijn Noorman @stijnnoorman]

https://t.co/zUgujWlxAC

[Art Of Philosophy @Deep_philo]

@Manu_Sisti Thanks

[Manu Sisti @Manu_Sisti]

If I had $300 and wanted to turn it into $10k, I wouldn't invest it in:

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[Rohan Paul @rohanpaul_ai]

Some of the most interesting agent results this year are coming out of post-trains of small open models.

A new RL post-train Qwen3.8-27B model trained with an open-source environments cuts the hallucination rate on AA-Omniscience from 30.4% to 15.1%.

the compressed copy of the mla version fits on my single 24 GB RTX 4090 and holds about 3.5x more context than base Qwen.

It beats GPT 6 Luna-medium on DeepSWE, placing in between Luna 6 medium and high.
scores higher on Terminal-Bench 2.1 while writing a median 23.8K output tokens per solved task, where base Qwen writes 54.9K.

Tried an unreleased version of this model, and really felt the comparative intelligent density, that it writes a lot less.

tops Muse Glimmer 30B and OpenAI’s GPT-6 Luna (high) on Terminal-Bench, τ³-bench, ClawEval and BFCL v4 (Berkeley Function Calling Leaderboard), though Luna still wins DeepSWE at 53.1%.

They also released an MLA version, which is the same model with its 16 full-attention layers converted to multi-head latent attention, which shrinks the memory each token takes from 64 KiB to 18 KiB so far more or longer sessions fit on one GPU.

[Art Of Philosophy @Deep_philo]

@Manu_Sisti Send

[Manu Sisti @Manu_Sisti]

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[Brian Roemmele @BrianRoemmele]

A small team just took a 27B open model and cut its hallucinations in half.

Built on Qwen, trained only on open-source environments, and it beats GPT-6 Luna on Terminal-Bench.

It also writes half the words to get the job done.

Their second version runs 7 long agent sessions at once on a single gaming card.

Free. Apache 2.0. Yours to run.

This is how local AI wins. I have been saying it for years, but I am a nerd.

[Art Of Philosophy @Deep_philo]

@TommiPedruzzi Thanks

[Tommi Pedruzzi @TommiPedruzzi]

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[Art Of Philosophy @Deep_philo]

@TommiPedruzzi PDF

[Tommi Pedruzzi @TommiPedruzzi]

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[Art Of Philosophy @Deep_philo]

@TommiPedruzzi Nice read

[Tommi Pedruzzi @TommiPedruzzi]

A busy dad asked me how he could make money online without quitting his job.

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