Full Stack Web Devel... • 9h
Small language models (SLMs) are compact NLP models optimized for edge devices (smartphones, IoT, embedded systems). With fewer parameters they enable faster, low‑latency on‑device inference, improving privacy by avoiding cloud transfers, reducing energy use and cloud costs, and enabling real‑time responses. Use cases include healthcare (summarizing records, assisting diagnoses), automotive voice systems, personalized retail recommendations, and adaptive education tools. Ongoing research promises better context and reasoning; challenges include limited training data and bias, so ethical tuning and domain adaptation are crucial. Organizations should adopt SLMs for efficient, private edge AI.
Founder | Agentic AI... • 3d
Small Language Models are set to transform AI agents-but only if implemented the right way. By 2027, Gartner predicts task-specific SLMs will be used three times more than general-purpose LLMs. NVIDIA agrees, calling them “the future of AI agents.”
See MoreFull Stack Web Devel... • 1m
Agentic AI—systems that act autonomously, are context-aware and learn in real time—paired with small language models (SLMs) enables efficient, specialized automation. SLMs are lightweight, fast, fine-tunable for niche domains and accessible to smalle
See MoreFull Stack Web Devel... • 4m
Edge computing moves compute and storage closer to users—CDN PoPs, gateways or devices—reducing latency, bandwidth and improving resiliency. Gartner predicts ~75% of enterprise data will be created/processed outside traditional datacenters by 2025. T
See MoreHey I am on Medial • 1y
Edge AI and Edge Computing: Transforming Technology Edge AI and Edge Computing are revolutionizing how data is processed by enabling local computation on devices, minimizing reliance on centralized cloud servers. Edge computing processes data closer
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