Two popular approaches for customizing large language models (LLMs) for downstream tasks are fine-tuning and in-context learning (ICL). In a recent study, researchers at Google DeepMind and Stanford ...

Researchers at Google have developed a new AI paradigm aimed at solving one of the biggest limitations in today’s large language models: their inability to learn or update their knowledge after ...

What if the next generation of AI systems could not only understand context but also act on it in real time? Imagine a world where large language models (LLMs) seamlessly interact with external tools, ...

The emergence of large language models (LLMs) offers transformative potential for medical research. Current approaches often focus on LLMs as a replacement for researchers or as a supporting tool. In ...

The arrival of AI systems called large language models (LLMs), like OpenAI’s ChatGPT chatbot, has been heralded as the start of a new technological era. And they may indeed have significant impacts on ...

In April 2023, a few weeks after the launch of GPT-4, the Internet went wild for two new software projects with the audacious names BabyAGI and AutoGPT. “Over the past week, developers around the ...

We have all heard about model context protocol (MCP) in the context of artificial intelligence. In this article, we will dive into what MCP is and why it is becoming more important by the day. When ...

AI's struggle with continuous learning reveals a critical gap between artificial and human cognitive processes.

The proliferation of edge AI will require fundamental changes in language models and chip architectures to make inferencing and learning outside of AI data centers a viable option. The initial goal ...