Retrieval-augmented generation breaks at scale because organizations treat it like an LLM feature rather than a platform ...

A consistent media flood of sensational hallucinations from the big AI chatbots. Widespread fear of job loss, especially due to lack of proper communication from leadership - and relentless overhyping ...

Much of the interest surrounding artificial intelligence (AI) is caught up with the battle of competing AI models on benchmark tests or new so-called multi-modal capabilities. But users of Gen AI's ...

Performance. Top-level APIs allow LLMs to achieve higher response speed and accuracy. They can be used for training purposes, as they empower LLMs to provide better replies in real-world situations.

Retrieval-augmented generation, or RAG, integrates external data sources to reduce hallucinations and improve the response accuracy of large language models. Retrieval-augmented generation (RAG) is a ...

Retrieval-Augmented Generation (RAG) is rapidly emerging as a robust framework for organizations seeking to harness the full power of generative AI with their business data. As enterprises seek to ...

General purpose AI tools like ChatGPT often require extensive training and fine-tuning to create reliably high-quality output for specialist and domain-specific tasks. And public models’ scopes are ...

Prof. Aleks Farseev is an entrepreneur, keynote speaker and CEO of SOMIN, a communications and marketing strategy analysis AI platform. Large language models, widely known as LLMs, have transformed ...

To operate, organisations in the financial services sector require hundreds of thousands of documents of rich, contextualised data. And to organise, analyse and then use that data, they are ...

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