Tech News
Codex Resets
Developers discuss frequent Codex resets and removal of usage limits, which anchor users to higher baselines and raise concerns about future workflow disruptions.
Transform your sales organization with Amazon Quick: your new agentic AI teammate
In this post, we walk through a few ways that Quick delivers on this promise. We cover the entire sales cycle, from identifying your highest-priority prospect, contacting them, working the deal to close, and keeping.
Kimi K3, and what we can still learn from the pelican benchmark
Chinese AI lab Moonshot AI announced Kimi K3 this morning, describing it as their "most capable model to date, with 2.8 trillion parameters". It's currently available via their website and API, but an open weight rele.
huggingface/transformers Release v5.14.0
Release v5.14.0 New Model additions Inkling (fresh from Thinking Machines): 975B total, 41B active Add Inkling model #47347 by @molbap @Cyrilvallez @eustlb and @zucchini-nlp Inkling is a general-purpose multimodal mod.
OpenAI reduces Codex Model Context Size from 372k to 272k
OpenAI reduced Codex model context size from 372k to 272k tokens, sparking debate on trade-offs between context length and model performance.
GitHub Repos
Panniantong/Agent-Reach
Give your AI agent eyes to see the entire internet.
# Python# agent infrastructure# ai agentzilliztech/claude-context
Code search MCP for Claude Code.
# TypeScript# agent# agentic ragmksglu/context-mode
Context window optimization for AI coding agents.
# TypeScript# antigravity# claudeResearch Papers
DADiff: Diffusion-Driven Cross-Domain Policy Adaptation for Reinforcement Learning
DADiff uses diffusion models to estimate dynamics mismatch between source and target domains for policy adaptation in reinforcement learning, achieving better performance than existing methods.
SciForge: An AI-Native, Multimodal Workbench for Scientific Discovery
SciForge is an open-source AI workbench that helps scientists manage and automate research tasks across papers, code, data, and models, with a focus on auditability and collaboration.
An MLIR-Based Compilation Method for Large Language Models
This paper introduces a compiler method using MLIR to convert large language models into efficient code for specialized AI hardware, addressing challenges in model import and inference scheduling.