Fine-tuning large language models (LLMs) might sound like a task reserved for tech wizards with endless resources, but the reality is far more approachable—and surprisingly exciting. If you’ve ever ...

Imagine unlocking the full potential of a massive language model, tailoring it to your unique needs without breaking the bank or requiring a supercomputer. Sounds impossible? It’s not. Thanks to ...

Thinking Machines Lab Inc., the artificial intelligence startup led by former OpenAI executive Mira Murati, today introduced its first commercial offering. Tinker is a cloud-based service that ...

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 OpenAI trained a single language model on 175 billion learned numerical weights, each one adjusted during training to predict the next word in a sequence. That model, GPT-3, ...

Database giant Oracle Corp. unveiled its long-awaited Oracle Cloud Infrastructure Generative AI service today, launching it with various innovations that will enable big companies to leverage the ...

The hype and awe around generative AI have waned to some extent. “Generalist” large language models (LLMs) like GPT-4, Gemini (formerly Bard), and Llama whip up smart-sounding sentences, but their ...

A popular strategy for engaging with generative AI chatbots is to start with a well-crafted prompt. In fact, prompt engineering is an emerging skill for those pursuing career advancement in this age ...

AI thrives on data but feeding it the right data is harder than it seems. As enterprises scale their AI initiatives, they face the challenge of managing diverse data pipelines, ensuring proximity to ...

A new academic study challenges a core assumption in developing large language models (LLMs), warning that more pre-training data may not always lead to better models. Researchers from some of the ...