Enterprise deployment of Generative AI depends on the seamless optimisation of hardware and software, driving higher performance at lower cost.

Enter large language model (LLM) evaluation. The purpose of LLM evaluation is to analyze and refine GenAI outputs to improve their accuracy and reliability while avoiding bias. The evaluation process ...

Want smarter insights in your inbox? Sign up for our weekly newsletters to get only what matters to enterprise AI, data, and security leaders. Subscribe Now Large language models (LLMs) are prone to ...

Large language models by themselves are less than meets the eye; the moniker “stochastic parrots” isn’t wrong. Connect LLMs to specific data for retrieval-augmented generation (RAG) and you get a more ...

LiteLLM allows developers to integrate a diverse range of LLM models as if they were calling OpenAI’s API, with support for fallbacks, budgets, rate limits, and real-time monitoring of API calls. The ...

In the world of Large Language Models, the prompt has long been king. From meticulously designed instructions to carefully constructed examples, crafting the perfect prompt was a delicate art, ...

An analysis of LLM referral traffic shows low volume, rapid growth, shifting citations, and an 18% conversion rate.

India’s AI ecosystem has been on a steady growth in the last few years. Both public initiatives and private startups are working in this stream. From the early days of experimentation and scattered ...