TL;DR Parameter efficient fine tuning (PEFT) adapts a pretrained model by training a small set of new or selected weights while the original model stays frozen. The most common method, LoRA, adds two small trainable matrices next to existing weight matrices instead of updating them directly. QLoRA extends this by loading the frozen base model in 4-bit precision, which is
TL;DR Keras and TensorFlow are not competitors. Keras is the high-level API you write models in, and TensorFlow is one of the engines that runs them. Since Keras 3, that engine can also be JAX or PyTorch, chosen per project without rewriting the model. Installing TensorFlow 2.16 or newer gives you Keras 3 by default, so tf.keras and the standalone
TL;DR Generative AI for retail means AI models that write product copy, answer shopper questions, and draft store-associate guidance instead of following fixed templates. The proven returns sit in merchandising content, marketing production, and customer service, not in forecasting. Demand forecasting and pricing still belong to predictive machine learning, not generative models. The 2025-26 shift is agentic commerce, where AI
How Microsoft Fabric Improved Sales & Financial KPIs for a Leading Pharma Manufacturer
Reducing Costs & Boosting Data Performance with Microsoft Fabric
Enhancing Decision-Making and Reducing Costs with Power BI.
Transforming Enterprise Data: Rapid, Automated Migration from Informatica to Taalend
Streamlining Data Operations and Reporting with Microsoft Fabric
Transforming Employee Benefits’ Analytics Through Unified Business Intelligence
AI-Powered Answer Extraction for Enhanced Investor Servicing & Onboarding Efficiency
AI-Driven LPA Summarization for Fund Benchmarking & Regulatory Compliance
Elevating Data Maturity for a Global Packaging Leader
