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OpenAI Just Launched GPT-5.3-Codex: A Faster Agentic Coding Model Unifying Frontier Code Performance And Professional Reasoning Into One System
OpenAI has just introduced GPT-5.3-Codex, a new agentic coding model that extends Codex from writing and reviewing code to handling a broad range of work on a computer. The model combines the frontier coding performance of GPT-5.2-Codex with the reasoning and professional knowledge capabilities of GPT-5.2 into a single system, and it runs 25%…

How to Build Production-Grade Data Validation Pipelines Using Pandera, Typed Schemas, and Composable DataFrame Contracts
Schemas, and Composable DataFrame ContractsIn this tutorial, we demonstrate how to build robust, production-grade data validation pipelines using Pandera with typed DataFrame models. We start by simulating realistic, imperfect transactional data and progressively enforce strict schema constraints, column-level rules, and cross-column business logic using declarative checks. We show how lazy validation helps us surface…

Mistral AI Launches Voxtral Transcribe 2: Pairing Batch Diarization And Open Realtime ASR For Multilingual Production Workloads At Scale
Automatic speech recognition (ASR) is becoming a core building block for AI products, from meeting tools to voice agents. Mistral’s new Voxtral Transcribe 2 family targets this space with 2 models that split cleanly into batch and realtime use cases, while keeping cost, latency, and deployment constraints in focus. The release includes: Voxtral Mini…

NVIDIA AI Release VibeTensor: An AI Generated Deep Learning Runtime Built End to End by Coding Agents Programmatically
NVIDIA has released VIBETENSOR, an open-source research system software stack for deep learning. VIBETENSOR is generated by LLM-powered coding agents under high-level human guidance. The system asks a concrete question: can coding agents generate a coherent deep learning runtime that spans Python and JavaScript APIs down to C++ runtime components and CUDA memory management…
Export Your ML Model in ONNX Format
When building machine learning models, training is only half the journey. Source link

How to Build Efficient Agentic Reasoning Systems by Dynamically Pruning Multiple Chain-of-Thought Paths Without Losing Accuracy
In this tutorial, we implement an agentic chain-of-thought pruning framework that generates multiple reasoning paths in parallel and dynamically reduces them using consensus signals and early stopping. We focus on improving reasoning efficiency by reducing unnecessary token usage while preserving answer correctness, demonstrating that self-consistency and lightweight graph-based agreement can serve as effective proxies…
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