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Alibaba’s Qwen AI Releases Compact Dense Qwen3-VL 4B/8B (Instruct & Thinking) With FP8 Checkpoints Asif Razzaq Artificial Intelligence Category – MarkTechPost

​[[{“value”:” Do you actually need a giant VLM when dense Qwen3-VL 4B/8B (Instruct/Thinking) with FP8 runs in low VRAM yet retains 256K→1M context and the full capability surface? Alibaba’s Qwen team has expanded its multimodal lineup with dense Qwen3-VL models at 4B and 8B scales,… Read More »Alibaba’s Qwen AI Releases Compact Dense Qwen3-VL 4B/8B (Instruct & Thinking) With FP8 Checkpoints Asif Razzaq Artificial Intelligence Category – MarkTechPost

Agentic RAG for Software Testing with Hybrid Vector-Graph and Multi-Agent Orchestration Apple Machine Learning Research

​We present an approach to software testing automation using Agentic Retrieval-Augmented Generation (RAG) systems for Quality Engineering (QE) artifact creation. We combine autonomous AI agents with hybrid vector-graph knowledge systems to automate test plan, case, and QE metric generation. Our approach addresses traditional software testing… Read More »Agentic RAG for Software Testing with Hybrid Vector-Graph and Multi-Agent Orchestration Apple Machine Learning Research

Software Defect Prediction using Autoencoder Transformer Model Apple Machine Learning Research

​An AI-ML-powered quality engineering approach uses AI-ML to enhance software quality assessments by predicting defects. Existing ML models struggle with noisy data types, imbalances, pattern recognition, feature extraction, and generalization. To address these challenges, we develop a new model, Adaptive Differential Evolution (ADE) based Quantum… Read More »Software Defect Prediction using Autoencoder Transformer Model Apple Machine Learning Research

Andrej Karpathy Releases ‘nanochat’: A Minimal, End-to-End ChatGPT-Style Pipeline You Can Train in ~4 Hours for ~$100 Asif Razzaq Artificial Intelligence Category – MarkTechPost

​[[{“value”:” Andrej Karpathy has open-sourced nanochat, a compact, dependency-light codebase that implements a full ChatGPT-style stack—from tokenizer training to web UI inference—aimed at reproducible, hackable LLM training on a single multi-GPU node. The repo provides a single-script “speedrun” that executes the full loop: tokenization, base… Read More »Andrej Karpathy Releases ‘nanochat’: A Minimal, End-to-End ChatGPT-Style Pipeline You Can Train in ~4 Hours for ~$100 Asif Razzaq Artificial Intelligence Category – MarkTechPost

Build a device management agent with Amazon Bedrock AgentCore Godwin Sahayaraj Vincent Artificial Intelligence

​[[{“value”:” The proliferation of Internet of Things (IoT) devices has transformed how we interact with our environments, from homes to industrial settings. However, as the number of connected devices grows, so does the complexity of managing them. Traditional device management interfaces often require navigating through… Read More »Build a device management agent with Amazon Bedrock AgentCore Godwin Sahayaraj Vincent Artificial Intelligence

How Amazon Bedrock Custom Model Import streamlined LLM deployment for Salesforce Srikanta Prasad, Utkarsh Arora, Raghav Tanaji, Nitin Surya, Gokulakrishnan Gopalakrishnan, Akhilesh Deepak Gotmare, Artificial Intelligence

​[[{“value”:” This post is cowritten by Salesforce’s AI Platform team members Srikanta Prasad, Utkarsh Arora, Raghav Tanaji, Nitin Surya, Gokulakrishnan Gopalakrishnan, and Akhilesh Deepak Gotmare. Salesforce’s Artificial Intelligence (AI) platform team runs customized large language models (LLMs)—fine-tuned versions of Llama, Qwen, and Mistral—for agentic AI… Read More »How Amazon Bedrock Custom Model Import streamlined LLM deployment for Salesforce Srikanta Prasad, Utkarsh Arora, Raghav Tanaji, Nitin Surya, Gokulakrishnan Gopalakrishnan, Akhilesh Deepak Gotmare, Artificial Intelligence

NVIDIA Researchers Propose Reinforcement Learning Pretraining (RLP): Reinforcement as a Pretraining Objective for Building Reasoning During Pretraining Asif Razzaq Artificial Intelligence Category – MarkTechPost

​[[{“value”:” NVIDIA AI has introduced Reinforcement Learning Pretraining (RLP), a training objective that injects reinforcement learning into the pretraining stage rather than deferring it to post-training. The core idea is simple and testable: treat a short chain-of-thought (CoT) as an action sampled before next-token prediction… Read More »NVIDIA Researchers Propose Reinforcement Learning Pretraining (RLP): Reinforcement as a Pretraining Objective for Building Reasoning During Pretraining Asif Razzaq Artificial Intelligence Category – MarkTechPost

Ivy Framework Agnostic Machine Learning Build, Transpile, and Benchmark Across All Major Backends Asif Razzaq Artificial Intelligence Category – MarkTechPost

​[[{“value”:” In this tutorial, we explore Ivy’s remarkable ability to unify machine learning development across frameworks. We begin by writing a fully framework-agnostic neural network that runs seamlessly on NumPy, PyTorch, TensorFlow, and JAX. We then dive into code transpilation, unified APIs, and advanced features… Read More »Ivy Framework Agnostic Machine Learning Build, Transpile, and Benchmark Across All Major Backends Asif Razzaq Artificial Intelligence Category – MarkTechPost