CallMissed Blog
Insights on AI communication, voice agents, WhatsApp automation, and the future of customer engagement.
5 min readSmall Language Models for Edge Devices in 2026
Running LLMs on edge devices is one of the most important trends in AI for 2026. Small models under 10 billion parameters are now capable enough for many tasks while fitting consumer hardware constraints. Why Edge Inference Matters 1. Latency: On-device responses in tens of milliseconds versus 100-5…
On-Device AI in 2026: Apple Intelligence, Phi, and the Local LLM Renaissance
For most of LLMs' history, "local model" meant either "demo-quality" or "you own a GPU." In 2026 that has shifted. Small models tuned for consumer hardware are crossing the threshold of usefulness — not parity with frontier models, but good enough that real apps are shipping with on-device inference…
AI Data Privacy in 2026: GDPR, DPDP, and Real Risks
AI data privacy in 2026 is no longer an abstract concern. Two regulatory regimes — the EU's GDPR (paired with the AI Act) and India's Digital Personal Data Protection (DPDP) Act — now define the floor for any company using LLMs at scale. Plus the practical risks: training-data leakage, prompt-inject…