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LightSeek Foundation Releases TokenSpeed, an Open-Source LLM Inference Engine Targeting TensorRT-LLM-Level Performance for Agentic Workloads

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Inference efficiency has quietly become one of the most consequential bottlenecks in AI deployment. As agentic coding systems such as Claude Code, Codex, and Cursor scale from developer tools to infrastructure powering software development at large, the underlying inference engines serving those requests are under increasing strain. The LightSeek Foundation researchers have released TokenSpeed, an […]

LightSeek Foundation Releases TokenSpeed, an Open-Source LLM Inference Engine Targeting TensorRT-LLM-Level Performance for Agentic Workloads Read More »

Meta AI Releases NeuralBench: A Unified Open-Source Framework to Benchmark NeuroAI Models Across 36 EEG Tasks and 94 Datasets

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Evaluating AI models trained on brain signals has long been a messy, inconsistent topic. Different research groups use different preprocessing pipelines, train models on different datasets, and report results on a narrow set of tasks — making it nearly impossible to know which model actually works best, or for what. A new framework from Meta

Meta AI Releases NeuralBench: A Unified Open-Source Framework to Benchmark NeuroAI Models Across 36 EEG Tasks and 94 Datasets Read More »

Zyphra Releases ZAYA1-8B: A Reasoning MoE Trained on AMD Hardware That Punches Far Above Its Weight Class

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Zyphra AI has released ZAYA1-8B, a small Mixture of Experts (MoE) language model with 760 million active parameters and 8.4 billion total parameters. Trained end-to-end on AMD hardware, the model outperforms open-weight models many times its size on math and coding benchmarks, and is now available under an Apache 2.0 license on Hugging Face and

Zyphra Releases ZAYA1-8B: A Reasoning MoE Trained on AMD Hardware That Punches Far Above Its Weight Class Read More »

CopilotKit Introduces Enterprise Intelligence Platform That Gives Agentic Applications Persistent Memory Across Sessions and Devices

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Most agentic applications today have a memory problem. Every time a user opens a new session, the agent starts from zero. There is no recollection of what was discussed, what workflows were in progress, or what decisions were already made. The session ends, and everything disappears. For dev teams shipping production agentic applications, the only

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How to Build a Fully Interactive Multi-Page NiceGUI Application with Real-Time Dashboard, CRUD Operations, File Upload, and Async Chat

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In this tutorial, we build a fully interactive, multi-page web application using NiceGUI. We start by setting up the environment and designing a reusable layout that includes navigation, theming, and dark mode support. As we move forward, we implement a live dashboard with real-time metrics and charts, demonstrating reactive bindings and timed updates. We then

How to Build a Fully Interactive Multi-Page NiceGUI Application with Real-Time Dashboard, CRUD Operations, File Upload, and Async Chat Read More »

Closing the ‘Expressivity Gap’: How Mistral’s Voxtral TTS is Redefining Multilingual Voice Cloning with a Hybrid Autoregressive and Flow-Matching Architecture

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Voice AI has a dirty secret. Most text-to-speech systems sound fine — until they don’t. They can read a sentence. What they cannot do is mean it. The rhythm is off. The emotion is flat. The speaker sounds like themselves for two seconds, then drifts into generic synthetic territory. That gap between intelligible audio and

Closing the ‘Expressivity Gap’: How Mistral’s Voxtral TTS is Redefining Multilingual Voice Cloning with a Hybrid Autoregressive and Flow-Matching Architecture Read More »

Build a Modular Skill-Based Agent System for LLMs with Dynamic Tool Routing in Python

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In this tutorial, we build a complete skill-based agent system for large language models and explore how modular capabilities can be structured like an operating system for AI agents. We define reusable skills, attach metadata and schemas to them, register them in a central registry, and enable dynamic orchestration through tool calling and multi-step reasoning.

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A Coding Guide to Survey Bias Correction Using Facebook Research Balance with IPW CBPS Ranking and Post Stratification Methods

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In this tutorial, we walk through a complete, end-to-end workflow for correcting bias in survey data using the balance library. We simulate a realistic population, deliberately introduce sampling bias, and then apply multiple re-weighting techniques to recover unbiased estimates. We focus on four widely used methods: Inverse Probability Weighting (IPW), Covariate Balancing Propensity Scores (CBPS),

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Zyphra Introduces Tensor and Sequence Parallelism (TSP): A Hardware-Aware Training and Inference Strategy That Delivers 2.6x Throughput Over Matched TP+SP Baselines

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Training and serving large transformer models at scale is fundamentally a memory management problem. Every GPU in a cluster has a fixed amount of VRAM, and as model sizes and context lengths grow, engineers constantly have to make trade-offs about how to distribute work across hardware. A new technique from Zyphra, called Tensor and Sequence

Zyphra Introduces Tensor and Sequence Parallelism (TSP): A Hardware-Aware Training and Inference Strategy That Delivers 2.6x Throughput Over Matched TP+SP Baselines Read More »

How to Build an End-to-End Production Grade Machine Learning Pipeline with ZenML, Including Custom Materializers, Metadata Tracking, and Hyperparameter Optimization

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In this tutorial, we walk through an end-to-end implementation of an advanced machine learning pipeline using ZenML. We begin by setting up the environment and initializing a ZenML project, then define a custom materializer that enables seamless serialization and metadata extraction for a domain-specific dataset object. As we progress, we build a modular pipeline that

How to Build an End-to-End Production Grade Machine Learning Pipeline with ZenML, Including Custom Materializers, Metadata Tracking, and Hyperparameter Optimization Read More »