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Scaling large language models (LLMs) is expensive. Every token processed during inference and every gradient computed during training flows through feedforward layers that account for over two-thirds of model parameters and more than 80% of total FLOPs in larger models. A team researchers from Sakana AI and NVIDIA have worked on a new research that […]
In this tutorial, we implement how Memori serves as an agent-native memory infrastructure layer for building more persistent, context-aware LLM applications. We start by setting up Memori in a Google Colab environment and connecting it to both synchronous and asynchronous OpenAI clients, so that every model call can automatically pass through the memory layer. We
Vector databases have graduated from experimental tooling to mission-critical infrastructure. In 2026, vector databases serve as the core retrieval layer for RAG pipelines, semantic search systems, and agentic AI workflows — and choosing the wrong one has real cost and performance consequences. This guide breaks down the top vector databases available today, covering architecture, performance,
The open-source AI agent space has a new leader. As of May 10, 2026, Hermes Agent — built by Nous Research — has overtaken OpenClaw to hold the #1 position on OpenRouter’s global daily app and agent rankings. Hermes is currently generating 224 billion daily tokens on OpenRouter versus OpenClaw’s 186 billion, making it the
In this tutorial, we explore NadirClaw as an intelligent routing layer that classifies prompts into simple and complex tiers before sending them to the most suitable model. We start by installing the required packages, setting up an optional Gemini API key, and testing the local classifier through the NadirClaw CLI without making any live LLM
NVIDIA AI researchers recently released cuda-oxide, an experimental compiler that allows developers to write CUDA SIMT (Single Instruction, Multiple Threads) GPU kernels in standard Rust code. The project compiles Rust directly to PTX (Parallel Thread Execution) — the assembly-like intermediate representation that CUDA uses to target NVIDIA GPUs — without requiring domain-specific languages, foreign function
In this tutorial, we explore how FLARE-FLOSS helps us recover hidden and obfuscated strings from a Windows PE file. We begin by setting up FLOSS and the MinGW-w64 cross-compiler. We synthesize a small malware-like executable that hides strings using multiple techniques, including static strings, stack-built strings, tight strings, and XOR-decoded strings. After that, we compare
Training a family of large language models (LLMs) has always come with a painful multiplier: every model variant in the family—whether 8B, 30B, or 70B—typically requires its own full training run, its own storage, and its own deployment stack. For a dev team running inference at scale, this means multiplying compute costs by the number
As AI coding agents grow more capable, a structural problem has emerged: speed without clarity. Developers generate working code in minutes, only to discover days later that it doesn’t match what the system actually needed. Spec-driven development (SDD) addresses this directly — by treating a structured specification as the source of truth and code as
9 Best AI Tools for Spec-Driven Development in 2026: Kiro, BMAD, GSD, and More Compare Read More »
If you have spent time using AI coding agents — GitHub Copilot, Claude Code, Gemini CLI — you have probably run into this situation: you describe what you want, the agent generates a block of code that looks correct, compiles, and then subtly misses the actual intent. This “vibe-coding” approach can work for quick prototypes
