Latest in AI

Researchers at Tilde Research have released Aurora, a new optimizer for training neural networks that addresses a structural flaw in the widely-used Muon optimizer. The flaw quietly kills off a significant fraction of MLP neurons during training and keeps them permanently dead. Aurora comes with a 1.1B parameter pretraining experiment, a new state-of-the-art result on […]

The post Tilde Research Introduces Aurora: A Leverage-Aware Optimizer That Fixes a Hidden Neuron Death Problem in Muon appeared first on MarkTechPost.

In this tutorial, we explore skfolio, a scikit-learn compatible portfolio optimization library that helps us build, compare, and evaluate different investment strategies in a structured Python workflow. We start by loading S&P 500 price data, converting it into returns, and creating a time-based train-test split suitable for financial analysis. From there, we build simple baseline […]

The post A Coding Implementation to Portfolio Optimization with skfolio for Building Testing, Tuning, and Comparing Modern Investment Strategies appeared first on MarkTechPost.

OpenAI on just launched Daybreak, a cybersecurity initiative that combines the company’s frontier AI models with Codex Security, its coding-focused agentic system, and a broad network of security partners. The program is aimed at developers, enterprise security teams, researchers, and government-linked defenders who need to find, validate, and patch software vulnerabilities earlier in the development […]

The post OpenAI Introduces Daybreak: A Cybersecurity Initiative That Puts Codex Security at the Center of Vulnerability Detection and Patch Validation appeared first on MarkTechPost.

Modern large language models are no longer trained only on raw internet text. Increasingly, companies are using powerful “teacher” models to help train smaller or more efficient “student” models. This process, broadly known as LLM distillation or model-to-model training, has become a key technique for building high-performing models at lower computational cost. Meta used its […]

The post Understanding LLM Distillation Techniques  appeared first on MarkTechPost.

In this tutorial, we implement how to use pandas-ta-classic to build a complete technical analysis and trading strategy workflow. We start by installing the required libraries, downloading historical OHLCV stock data with yfinance, cleaning the returned data structure, and inspecting the available indicator categories inside the library. We then calculate popular indicators such as SMA, […]

The post How to Build Technical Analysis and Backtesting Workflow with pandas-ta-classic, Strategy Signals, and Performance Metrics appeared first on MarkTechPost.

Researchers from Meta FAIR and Stanford propose three inference methods for the Byte Latent Transformer that reduce memory-bandwidth cost by over 50% without subword tokenization.

The post Meta and Stanford Researchers Propose Fast Byte Latent Transformer That Reduces Inference Memory Bandwidth by Over 50% Without Tokenization appeared first on MarkTechPost.

Sakana AI and NVIDIA Researchers demonstrate that simple L1 regularization can induce over 99% sparsity in feedforward layers with negligible downstream performance impact, and translate that sparsity into real GPU throughput gains using new sparse data formats and fused CUDA kernels.

The post Sakana AI and NVIDIA Introduce TwELL with CUDA Kernels for 20.5% Inference and 21.9% Training Speedup in LLMs appeared first on MarkTechPost.

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 […]

The post A Coding Implementation to Build Agent-Native Memory Infrastructure with Memori for Persistent Multi-User and Multi-Session LLM Applications appeared first on MarkTechPost.

Vector databases are now core retrieval infrastructure for RAG and agentic AI. This guide compares nine production options on architecture, pricing, and scale.

The post Best Vector Databases in 2026: Pricing, Scale Limits, and Architecture Tradeoffs Across Nine Leading Systems appeared first on MarkTechPost.

Hermes Agent, the open-source self-improving AI agent from Nous Research, has overtaken OpenClaw to claim the #1 position on OpenRouter's global daily token rankings as of May 10, 2026 — generating 224 billion daily tokens versus OpenClaw's 186 billion. The milestone places a Nous Research project ahead of an OpenAI-sponsored platform in real-world daily inference volume, just three months after launch.

The post OpenClaw vs Hermes Agent: Why Nous Research’s Self-Improving Agent Now Leads OpenRouter’s Global Rankings appeared first on MarkTechPost.

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 […]

The post How to Build a Cost-Aware LLM Routing System with NadirClaw Using Local Prompt Classification and Gemini Model Switching appeared first on MarkTechPost.

NVlabs releases cuda-oxide v0.1.0, a custom rustc codegen backend that compiles #[kernel]-annotated Rust functions to PTX through a Rust → Stable MIR → Pliron IR → LLVM IR → PTX pipeline, with single-source host+device compilation from one cargo oxide build command.

The post NVIDIA AI Just Released cuda-oxide: An Experimental Rust-to-CUDA Compiler Backend that Compiles SIMT GPU Kernels Directly to PTX appeared first on MarkTechPost.

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 […]

The post A Coding Implementation to Recover Hidden Malware IOCs with FLARE-FLOSS Beyond Classic Strings Analysis appeared first on MarkTechPost.

NVIDIA researchers have introduced Star Elastic, a post-training method that embeds multiple nested reasoning models — at 30B, 23B, and 12B parameter scales — inside a single checkpoint, eliminating the need for separate training runs or stored model weights per variant. Built on the Nemotron Elastic framework and applied to Nemotron Nano v3, the method trains all three variants in a single 160B-token run, achieving a 360× token reduction compared to pretraining each model from scratch. Beyond training efficiency, Star Elastic introduces elastic budget control — a novel inference scheme that uses a smaller submodel for the thinking phase and the full model for the final answer — delivering up to 16% higher accuracy and 1.9× lower latency compared to standard budget control, while nested FP8 and NVFP4 checkpoints bring the full model family within reach of RTX-class GPUs.

The post NVIDIA AI Releases Star Elastic: One Checkpoint that Contains 30B, 23B, and 12B Reasoning Models with Zero-Shot Slicing appeared first on MarkTechPost.

Vibe coding gets you to a prototype. Spec-driven development gets you to production. As AI coding agents grow more powerful, the engineering community has quietly split into two camps: developers who prompt iteratively and hope for the best, and developers who write structured specifications first and let agents execute against them. The second group is shipping faster, with fewer regressions, and with code that survives review. This guide covers the 9 AI tools driving that shift in 2026 — from AWS Kiro's EARS-structured spec IDE to GitHub Spec Kit's 93K-star open-source workflow, to lean execution frameworks like GSD that have crossed 61K stars in under five months.

The post 9 Best AI Tools for Spec-Driven Development in 2026: Kiro, BMAD, GSD, and More Compare appeared first on MarkTechPost.

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 […]

The post Meet GitHub Spec-Kit: An Open Source Toolkit for Spec-Driven Development with AI Coding Agents appeared first on MarkTechPost.

EU officials have agreed to water down certain aspects of the AI Act, including delaying the implementation of rules covering a number of high-risk applications until December 2027, instead of the originally set deadline of August 2026, according to the latest update of EU lawmakers watering down AI rules. This agreement comes after many companies argued the EU was bogging itself down in unnecessary regulation, leaving the EU behind competitors in the US and Asia. The deal was reached after 9 hours of talks, which is fairly standard for negotiations in Brussels. It still needs to be ratified by EU […]

OpenAI has shipped a Chrome extension for Codex, its AI coding agent, enabling it to complete browser-based tasks directly inside Google Chrome on macOS and Windows — including interacting with signed-in websites, using Chrome DevTools, and running multi-step workflows across browser tabs.

The post OpenAI Adds Chrome Extension to Codex, Letting Its AI Agent Access LinkedIn, Salesforce, Gmail, and Internal Tools via Signed-In Sessions appeared first on MarkTechPost.

In this tutorial, we perform an advanced single-cell RNA-seq analysis workflow using Scanpy on the PBMC-3k benchmark dataset. We start by loading the dataset, inspecting its structure, and applying quality control checks to evaluate gene counts, total counts, mitochondrial content, and ribosomal gene signals. We then filter low-quality cells and genes, detect potential doublets with […]

The post How to Build a Single-Cell RNA-seq Analysis Pipeline with Scanpy for PBMC Clustering, Annotation, and Trajectory Discovery appeared first on MarkTechPost.

When you type a message to Claude, something invisible happens in the middle. The words you send get converted into long lists of numbers called activations that the model uses to process context and generate a response. These activations are, in effect, where the model’s “thinking” lives. The problem is nobody can easily read them. […]

The post Anthropic Introduces Natural Language Autoencoders That Convert Claude’s Internal Activations Directly into Human-Readable Text Explanations appeared first on MarkTechPost.