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Dev.to

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23:01
2026-10-26
dev.to
artificial-intelligence

How AI Voice Models Are Trained: A Technical Overview

A developer outlined the standard pipeline for training modern AI voice models, covering dataset selection (LJSpeech, VCTK, LibriTTS), audio preprocessing with librosa and phoneme conversion via g2p_e…

22:26
2026-10-26
dev.to
ai-agents

Switching agent harnesses may be noise: a 447-task study

Researchers Yangze Liu and Zhongyi Han at Shandong University published a preprint (arXiv:2610.04433) finding that swapping agent harnesses changed outcomes on 13% of SWE-bench Verified tasks — the sa…

22:25
2026-10-26
dev.to
ai-agents

I Tried To Own My Agent's Brain

A developer tested whether a locally run llama3.2:latest model (3.2B, Q4_K_M via Ollama on a 2020 MacBook Air, temperature 0) could serve as a security gate for an AI agent, and found it approved exfi…

22:08
2026-10-26
dev.to
artificial-intelligence

👻 GhostShell: A Haunted AI Terminal Powered by Local AI

A developer built GhostShell, an open-source terminal assistant that uses a locally running Ollama model to explain terminal commands, flag risky flags, and generate developer-themed ghost stories. Th…

20:40
2026-10-26
dev.to
ai-tools

DiffScribe: The Commit Message Writes Itself (Locally)

A developer built DiffScribe, a command-line tool that reads a git diff and drafts conventional-commit messages and changelog entries entirely on the local machine using Qwen2.5-0.5B-Instruct served t…

20:34
2026-10-26
dev.to
large-language-models

Should you run an LLM locally or in the cloud?

A developer at Nodus Compute laid out a rule for deciding whether to run large language models locally or in the cloud, based on memory: a 4-bit model needs roughly 0.56 GB per billion parameters, so …

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