Tencent has released AngelSpec, an open-source torch-native framework for training speculative-decoding draft models across six architectures. It introduces DFly, a block-diffusion drafter with hybrid ...
Tencent has released AngelSpec, an open-source torch-native framework for training speculative-decoding draft models across six architectures. It introduces DFly, a block-diffusion drafter with hybrid ...
Perplexity has released pplx, an official command line client for its Search API. The tool returns grounded search results and extracted page text, all as JSON. According to its docs, it targets ...
Agentic RL does not just sample text. It requires the model to act inside a real computer. Every rollout needs an isolated Linux environment with a filesystem, a network stack, and live processes.
In this tutorial, we build an advanced workflow around Anthropic’s financial-services repository and reproduce its skill-driven architecture in pure Python. We begin by installing the required ...
Meet the New Claude Opus 5: Frontier-Class Agentic Coding and Computer Use at Unchanged Opus Pricing
Today, Anthropic released Claude Opus 5. It replaces Claude Opus 4.8 as the Opus-tier flagship. Pricing is unchanged at $5 per million input tokens and $25 per million output tokens. The Anthropic ...
Architecturally, an orchestrator routes every request to one of three specialist sub-agents. Each sub-agent owns its own tools for reading or writing the memory store. First, the IngestAgent handles ...
Datalab has released Marker 2, a full rewrite of its open source document conversion pipeline. Marker converts PDF, image, PPTX, DOCX, XLSX, HTML, and EPUB files into markdown, JSON, HTML, or chunks.
This tutorial starts where most agent demos stop: giving the agent persistent memory, operational context, and a place to write back what happened. An event operator does not just need an agent that ...
Poolside has released Laguna S 2.1, a 118B-parameter open-weight model built for agentic coding. It is a Mixture-of-Experts (MoE) model with 8B activated parameters per token. It supports a context ...
Tokenization is the one part of the language modeling stack that almost nobody profiles. Gigatoken, released by Marcel Rød (a PhD student from Stanford) under an MIT license, argues that this was a ...
Kimi K3 is a sparse Mixture-of-Experts (MoE) model built on two architectural updates. Those are Kimi Delta Attention (KDA) and Attention Residuals (AttnRes). Both change how information flows across ...
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