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Kong has been open sourced volcanoa TypeScript SDK for natively building multi-step agent workflows across multiple LLM providers Model Context Protocol (MCP) Use of Tools. The release coincides with wider MCP functionality Kong Artificial...

Do your LLM code benchmarks actually reject solutions of wrong complexity and interactive protocol violations, or do they pass unspecified unit tests? Introducing a team of researchers from UC San Diego, New York University,...

Reinforcement Learning RL post-training is now the primary lever for inference-focused LL.M., but unlike pre-training it is not yet predictive Scaling rules. The team put tens of thousands of GPU hours into the run...

In this tutorial, we build a compact, efficient framework that demonstrates how to convert tool documentation into standardized, callable interfaces, register these tools in a central system, and execute them as part of an...

How to convert complex multilingual documents (dense layouts, small scripts, formulas, diagrams, and handwriting) into faithfully structured Markdown/JSON with state-of-the-art accuracy while keeping inference latency and memory low enough to be suitable for real-world...

A research team from Google Research, Google DeepMind, and Yale University released C2S-Scale 27Ba basic model for single-cell analysis containing 27 billion parameters Gemma-2. This model formalizes single-cell RNA-seq (scRNA-seq) profiles as “Cell Sentence”–...

Agent systems are stochastic, context-sensitive, and policy-bound. Traditional quality assurance (unit tests, static prompts, or scalar “LL.M. as judge” scores) fails to expose multiple rounds of vulnerabilities and provide a weak audit trail. Developer...

In this tutorial, we build an AI-driven cryptographic proxy system that combines the benefits of classic cryptography with adaptive intelligence. We designed the agent to perform hybrid encryption using RSA and AES, generate digital...

Agent systems are stochastic, context-sensitive, and policy-bound. Traditional quality assurance (unit tests, static prompts, or scalar “LL.M. as judge” scores) fails to expose multiple rounds of vulnerabilities and provide a weak audit trail. Developer...