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Key points There is no flagship race yet, and competition is fierce around the world, locally developed LLMs (such as GPT-4, Claude 3.5, Llama 3.1) have not yet appeared from Australia. Australian research and...

Research Published Hermes 4an open model (based on the Llama 3.1 checkpoint) open model (14B, 70B and 405B parameter sizes) achieves cutting-edge level performance through purely training technology. Hermes 4 introduction Mixed reasoning –...

In this advanced qutip Tutorial, we explore the rich dynamics of quantum systems using Python and Qutip frameworks. First, we will prepare the basic single quantities and two points (including bell pairs) and then...

What is an agent rag? Agent rags combine the advantages of traditional rags – Large Language Models (LLMS) search and ground output in external environments as well as proxy decision making and tool use....

Large Language Models (LLMs) have reshaped AI reasoning and have parallel thinking and self-contradictory approaches are often considered key advances. However, these technologies face a basic trade-off: sampling multiple inference paths improves accuracy, but...

Welcome to a new era of AI interoperability, where Model Context Protocol (MCP) prepares to provide agents and AI assistants with what HTTP does for the Web. If you are building, scaling, or analyzing...

Google’s new regression language model (RLM) approach allows large language models (LLMS) to predict industrial system performance directly from raw text data without relying on complex functional engineering or rigid tabular formats. Challenges of...