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marktechpost.com /3 weeks ago

Liquid AI Introduces LFM2.5-Embedding-350M and LFM2.5-ColBERT-350M: Dense Bi-Encoder and Late-Interaction Models for Fas...

Liquid AI's LFM2.5 Retrievers combine a dense bi-encoder and ColBERT late-interaction model for multilingual search on edge devices. The post Liquid AI Introduces LFM2.5-Embedding-...

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graphicdesignjunction.com /1 month ago

Small Language Models vs Large LLMs: Performance, Cost, and Latency Compared

AI tools are now part of daily work for designers, writers, developers, students, and business teams. Some people use large AI models like OpenAI ChatGPT, while others use smaller...

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towardsdatascience.com /1 week ago

Setting Up Your Own Large Language Model

Still a long way to go, but the future is promising The post Setting Up Your Own Large Language Model appeared first on Towards Data Science.

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medium.com /1 month ago

How Large Language Models Actually Work

Large Language Models ExplainedContinue reading on Medium »

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marktechpost.com /1 month ago

NVIDIA AI Releases Nemotron-Labs-Diffusion: A Tri-Mode Language Model with 6× Tokens Per Forward Over Qwen3-8B

NVIDIA researchers have released Nemotron-Labs-Diffusion, a language model family that unifies three decoding modes in one architecture. The model supports autoregressive (AR) deco...

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dzone.com /2 weeks ago

A Low-Latency Routing Pattern for Multiple Small Language Models

A multi-SLM platform creates value only when specialization does not introduce a new latency tier. Small language models are inexpensive enough to dedicate to focused work such as ...

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techmeme.com /13 hours ago

Thinking Machines Lab debuts Inkling, an open-weight MoE model with 975B total and 41B active parameters, trained to be...

Thinking Machines Lab: Thinking Machines Lab debuts Inkling, an open-weight MoE model with 975B total and 41B active parameters, trained to be broad rather than optimized for one a...

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venturebeat.com /1 month ago

Context compression finally works in production: new research cuts LLM input 16x without the accuracy hit

Context windows are becoming a computational bottleneck. The longer an agent runs, the more tokens accumulate from retrieved documents, reasoning traces and conversation history, a...

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marktechpost.com /1 week ago

Interfaze Ships diffusion-gemma-asr-small, an Open-Source Diffusion ASR Model Transcribing Six Languages via DiffusionGe...

Interfaze open-sourced diffusion-gemma-asr-small, a multilingual ASR model that transcribes via diffusion, not autoregression. It adds audio to Google's frozen DiffusionGemma using...

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habr.com /5 days ago

Энтузиаст запустил GLM-5.2 на ноутбуке с 25 ГБ RAM: без дистилляции, но на скорости от 0,05 токена в секунду

Разработчик-одиночка под ником JustVugg представил Colibri — движок, который запускает открытую модель GLM-5.2 с 744 миллиардами параметров на обычном компьютере с 25 ГБ оперативно...

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computerra.ru /1 month ago

Cloud.ru предоставил доступ к GLM-5.1, Kimi K2.6 и DeepSeek V4

Источник: Компьютерра - Журнал о науке и технологиях Провайдер облачных и AI-технологий Cloud.ru объявил о пополнении каталога в сервисе Evolution Foundation Models. Всем зарегист...

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kdnuggets.com /1 week ago

5 Ways Small Language Models Are Powering Next-Gen Agents

This article looks at five concrete ways SLMs are showing up inside next-generation agents right now, from the research backing them to the tools and numbers worth knowing if you'r...

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kdnuggets.com /1 week ago

5 Ways Small Language Models Are Powering Next-Gen Agents

This article looks at five concrete ways SLMs are showing up inside next-generation agents right now, from the research backing them to the tools and numbers worth knowing if you'r...

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adexchanger.com /3 weeks ago

Large Language Models Are Overkill For Some Marketing Tasks. Enter The Small Language Model

It’s no secret that large language models (LLMs) have gotten exorbitantly expensive. Companies are starting to limit their employees’ AI usage to save money; OpenAI has even discus...

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scottcmcmahan.medium.com /1 month ago

Why Domain-Specific LLMs Matter for Data Science

Large language models have become a powerful tool for organizations looking to unlock value from their data. While general-purpose models…Continue reading on Medium »

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pandaily.com /4 weeks ago

Chinese AI Models Find a Way Forward Through Multi-Model Routing and Cost-Effective Architectures

Chinese domestic large language models are finding their path to commercial relevance through multi-model dynamic routing (Fusion) and hybrid agent architectures that prioritize co...

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medium.com /1 month ago

The Long-Tail Speech Problem: How Modern ASR Fails on Rare Words, Accents, and Jargon, and Why…

If you measure ASR on LibriSpeech-clean, the field is essentially solved.Continue reading on Medium »

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simplilearn.com /5 days ago

SLM vs LLM: Key Differences and Use Cases | Simplilearn

TL;DR: LLMs and SLMs are two types of language models used in artificial intelligence systems. LLMs are built to handle large-scale tasks with higher reasoning ability, while SLMs...

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towardsdatascience.com /4 days ago

Long Context Isn’t Free — I Built a Safe Prompt-Pruning Layer That Makes LLM Systems Work

LLMs don’t fail because they forget—they fail because they remember too much. As conversations grow, prompts accumulate redundant and low-value tokens, driving up cost and latency...

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marktechpost.com /1 week ago

Meituan Releases LongCat-2.0: A 1.6T-Parameter Open MoE Model with Native 1M Context and LongCat Sparse Attention

Meituan has released LongCat-2.0, a 1.6 trillion-parameter Mixture-of-Experts model that activates about 48 billion parameters per token. It pairs a native 1-million-token context,...

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kdnuggets.com /1 month ago

Tweaking Local Language Model Settings with Ollama

In this article, we will go deep under the hood of Ollama's configuration engine, exploring how to fine-tune local language model parameters.

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kdnuggets.com /1 month ago

5 Cool Things I Did with Local Language Models

I have been running local models as part of my daily workflow for some time, and what surprised me most is how often local turned out to be the better choice, not a compromise.

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kdnuggets.com /1 month ago

5 Cool Things I Did with Local Language Models

I have been running local models as part of my daily workflow for some time, and what surprised me most is how often local turned out to be the better choice, not a compromise.

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theregister.com /1 month ago

Google's new open-weights model brings image-generation tricks to AI text generation

Language model builds on diffusion tech to boost output performance by up to 4x, claims Chocolate Factory

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