Large language models and small language models will play different roles in ensuring that we deliver valuable generative AI applications at cost-effective levels. Generative AI applications revolve ...

Small, regular, medium or large - sir/madam? When it comes to coffee, pitchers of beer, cheeseburgers and items of clothing, going large usually means you’re getting more value for money, a better ...

The future of generative AI could rely on smaller language models for every application an enterprise uses, models that would be both more nimble and customizable — and more secure. As organizations ...

In the AI wars, where tech giants have been racing to build ever-larger language models, a surprising new trend is emerging: small is the new big. As progress in large language models (LLMs) shows ...

Small Language Models (SLM) are trained on focused datasets, making them very efficient at tasks like analyzing customer feedback, generating product descriptions, or handling specialized industry ...

Running massive AI models locally on smartphones or laptops may be possible after a new compression algorithm trims down their size — meaning your data never leaves your device. The catch is that it ...

While Large Language Models (LLMs) like GPT-3 and GPT-4 have quickly become synonymous with AI, LLM mass deployments in both training and inference applications have, to date, been predominately cloud ...

John Licato is the founder and owner of an AI startup called Actualization AI, LLC. He receives funding from various federal agencies, including the National Science Foundation, Army Research Office, ...