Since large language models (LLMs) and generative AI (GenAI) are increasingly being embedded into enterprise software, barriers to entry – in terms of how a developer can get started – have almost ...
A team of researchers has found a way to steer the output of large language models by manipulating specific concepts inside these models. The new method could lead to more reliable, more efficient, ...
This desktop app for hosting and running LLMs locally is rough in a few spots, but still useful right out of the box.
Contrast that with how LLMs are currently the dominant form of AI people think of when they hear the term and how they actually function. In reality, LLMs are statistical prediction machines that have ...
Large language models are AI systems trained on huge datasets to understand inputs provided in natural, human language and output a variety of responses—everything from written content to unique ...
As large language models (LLMs) continue to improve at coding, the benchmarks used to evaluate their performance are steadily becoming less useful. That's because though many LLMs have similar high ...
The use of large language models (LLMs) as an alternative to search engines and recommendation algorithms is increasing, but early research suggests there is still a high degree of inconsistency and ...
Tech Xplore on MSN
Personalization features can make LLMs more agreeable, potentially creating a virtual echo chamber
Many of the latest large language models (LLMs) are designed to remember details from past conversations or store user profiles, enabling these models to personalize responses. But researchers from ...
Tech Xplore on MSN
Platforms that rank the latest LLMs can be unreliable
A firm that wants to use a large language model (LLM) to summarize sales reports or triage customer inquiries can choose between hundreds of unique LLMs with dozens of model variations, each with ...
Large language models (LLMs) sometimes learn the wrong lessons, according to an MIT study. Rather than answering a query based on domain knowledge, an LLM could respond by leveraging grammatical ...
Some results have been hidden because they may be inaccessible to you
Show inaccessible results