Researchers at MIT have created a framework—TextFooler—that brought down the prediction accuracy of certain NLP models from 90% down to under 20% by simply using synonyms in place of certain words.

NLP and LLM teams often grow their training corpuses to improve model performance but they still do not always obtain predictable results in the real world. Generally speaking, this variability is due ...

Natural language processing (NLP) is the ability of a computer program to understand human language as it's spoken and written -- referred to as natural language. It's a component of AI. Computers ...

As a business owner, how good are you at communicating? Do you find it easy to land new clients, get your brand message across and work efficiently, or does it all feel like you’re wading through ...

SEO has come a long way from the days of keyword stuffing. Modern search engines like Google now rely on advanced natural language processing (NLP) to understand searches and match them to relevant ...

Developers and data scientists use generative AI and large language models (LLMs) to query volumes of documents and unstructured data. Open source LLMs, including Dolly 2.0, EleutherAI Pythia, Meta AI ...

A team of researchers at the MIT Computer Science & Artificial Intelligence Lab (CSAIL) recently released a framework called TextFooler which successfully tricked state-of-the-art NLP models (such as ...

Stephane is a tech enthusiast and AI advocate with a deep-seated passion for leveraging technology to solve real-world problems. With a background in Chemistry and hands-on experience in AI,... We ...