Stay updated with the latest in AI tooling. Here are the top picks for today, curated and summarized by HappyMonkey AI.

Tooling Roundup


Granite 4.1 LLMs: How They’re Built

Granite 4.1 LLMs: How They’re Built +70 An in-depth technical walkthrough of data engineering, pre-training, supervised fine-tuning, and reinforcement learning behind the Granite 4.1 LLMs.. Authors: Granite Team, IBM TL;DR — Granite 4.1 is a family of dense, decoder‑only LLMs…

Why it matters: Potentially relevant AI tooling update — review for integration potential.


Mixture of Experts (MoEs) in Transformers

Mixture of Experts (MoEs) in Transformers +158 Introduction Over the past few years, scaling dense language models has driven most progress in LLMs.. From early models like the original ULMFiT (~30M parameters) or GPT-2 (1.5B parameters, which at the time was considered “too…

Why it matters: Potentially relevant AI tooling update — review for integration potential.


DeepInfra on Hugging Face Inference Providers 🔥

DeepInfra on Hugging Face Inference Providers 🔥 +7 We’re thrilled to share that DeepInfra is now a supported Inference Provider on the Hugging Face Hub!. DeepInfra joins our growing ecosystem, enhancing the breadth and capabilities of serverless inference directly on the…

Why it matters: Potentially relevant AI tooling update — review for integration potential.