Unlock explosive e commerce growth with AI powered recommendations. Discover how DMT TorchRec and DLRM supercharge personalization conversion rates scalability and inventory management. Steal the step by step playbook to deploy fast and win today.
Ready to turn AI, Machine Learning and Computer Vision into real business results? Steal a step by step blueprint from use case and data strategy to model development, integration, deployment and scaling. Do not ship another model before reading this.
Turn dull product photos into sales machines. Discover how AI-powered background removal streamlines e-commerce workflows, slashes editing costs, scales to thousands of SKUs, and delivers pixel-perfect images that boost trust, CTR, and conversions.
Unlock real-time inventory management with AI. Predict demand with time-series forecasting, cut carrying costs, automate replenishment, and slash stockouts across e-commerce, retail, manufacturing, healthcare & logistics. Ready to transform your supply chain?
Slash defects and costs with AI-powered anomaly detection. Learn how manufacturers automate quality control with real-time monitoring, models like PatchCore & PaDiM, and end-to-end deployment to boost accuracy, speed, and scalability, without slowing the line.
The future is embedded: discover how AI in IoT devices, powered by FPGAs, ASICs & GPUs, uses model compression, BNNs and on-device training for real-time, private, low-power intelligence. Use cases, edge tactics & what’s next.
Meet Florence-2: a unified vision foundation model that uses prompt-based seq2seq to crush computer vision tasks, image captioning, object detection, grounding, segmentation, trained on FLD-5B’s 5.4B annotations. Faster training, fewer params, SOTA results.
SLS Loss + MSHNet: a simpler, faster way to nail Infrared Small Target Detection. Scale/location-aware loss + multi-scale U-Net head hit IoU 67.16%, Pd 93.88% with low FLOPs, lifting other detectors, too. See how they sharpen tiny-target detection.
Your ML model is the new crown jewel, can it survive model extraction? Explore machine learning model security for on-device ML: app, device, communication, and model-based attacks, side-channels, TEEs, encryption, and practical defenses to stop IP theft and privacy leaks.
On-device LLMs are revolutionizing mobile AI: ultra-low latency, private, offline, multimodal. Explore LLaMA, Gemini Nano, OpenELM, MiniCPM, and more, plus quantization, pruning, MoE, and edge-cloud tricks powering smarter Android & iOS apps.