1 day 21 hours ago
Asif Razzaq
2 days ago
Asif Razzaq
2 days 1 hour ago
In this tutorial, we walk through an end-to-end, advanced workflow for knowledge graph embeddings using PyKEEN, actively exploring how modern embedding models are trained, evaluated, optimized, and interpreted in practice. We start by understanding the structure of a real knowledge graph dataset, then systematically train and compare multiple embedding models, tune their hyperparameters, and analyze […]
The post A Coding Implementation to Training, Optimizing, Evaluating, and Interpreting Knowledge Graph Embeddings with PyKEEN appeared first on MarkTechPost.
Asif Razzaq
2 days 14 hours ago
Michal Sutter
2 days 14 hours ago
Michal Sutter
2 days 15 hours ago
Asif Razzaq
2 days 23 hours ago
Asif Razzaq
3 days 5 hours ago
Most AI applications still showcase the model as a chat box. That interface is simple, but it hides what agents are actually doing, such as planning steps, calling tools, and updating state. Generative UI is about letting the agent drive real interface elements, for example tables, charts, forms, and progress indicators, so the experience feels […]
The post Beyond the Chatbox: Generative UI, AG-UI, and the Stack Behind Agent-Driven Interfaces appeared first on MarkTechPost.
Asif Razzaq
3 days 15 hours ago
Asif Razzaq
3 days 21 hours ago
Michal Sutter
3 days 21 hours ago
Asif Razzaq
4 days 1 hour ago
Maxime Mommessin
4 days 16 hours ago
Tencent Hunyuan has open sourced HPC-Ops, a production grade operator library for large language model inference architecture devices. HPC-Ops focuses on low level CUDA kernels for core operators such as Attention, Grouped GEMM, and Fused MoE, and exposes them through a compact-C and Python API for integration into existing inference stacks. HPC-Ops runs in large […]
The post Tencent Hunyuan Releases HPC-Ops: A High Performance LLM Inference Operator Library appeared first on MarkTechPost.
Michal Sutter
4 days 23 hours ago
Asif Razzaq
5 days 3 hours ago
Data science agents should inspect datasets, design workflows, run code, and return verifiable answers, not just autocomplete Pandas code. DSGym, introduced by researchers from Stanford University, Together AI, Duke University, and Harvard University, is a framework that evaluates and trains such agents across more than 1,000 data science challenges with expert curated ground truth and […]
The post DSGym Offers a Reusable Container Based Substrate for Building and Benchmarking Data Science Agents appeared first on MarkTechPost.
Michal Sutter
5 days 3 hours ago
Asif Razzaq
5 days 20 hours ago
Asif Razzaq
6 days 7 hours ago
Jean-marc Mommessin
6 days 18 hours ago
Michal Sutter
Checked
3 minutes 53 seconds ago
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