LLMs

AI presents challenges for data privacy in Large Language Models (LLMs) like ChatGPT emphasizing the need for robust security measures.

LLM Guard is a toolkit designed to fortify the security of Large Language Models, and it's freely available for usage with various LLMs.

As websites start to block Common Crawl, and as the project leans in to its role in training LLMs, will it become harder to use data from the web for other purposes?

Prompt Engineering, also known as In-Context Prompting, refers to methods for how to communicate with LLM to steer its behavior for desired outcomes without updating the model weights. It is an empirical science and the effect of prompt engineering methods can vary a lot among models, thus requiring heavy experimentation and heuristics. This post only focuses on prompt engineering for autoregressive language models, so nothing with Cloze tests, image generation or multimodality models.

A paper has shown that a compression algorithm – gzip – outperforms some large language models (LLMs) in some tasks. This has the NLP community …

LLMs can deliver just-in-time knowledge tailored to real programming tasks, making it a great way to learn about coding idioms and libraries.

A primer on what large language models are, why they are used, the different types, and what the future may hold for LLM applications.

In the LLM app stack, a playground is where developers can test out (and deploy) prompts. We discussed this new concept with Humanloop's CEO.

Web3 failed to remake the developer ecosystem, but the emerging LLM stack is forcing the cloud native era to adapt. We examine its progress.

To train a large language model, you must overcome three big challenges: data, hardware and legal. It helps to be a large organization, too.

LLMs hold the key to generative AI, but some are more suited than others to specific tasks. Here's a guide to the five most powerful and how to use them.

A successful first use of GPT-4 Code Interpreter raises the hope that LLMs can help democratize scripting.

🤖 What are LLMs? How can you use them? And why should you care?

In the 20th episode of my Mastodon series I pivoted to a new topic: LLM-assisted coding. After three posts in the new series, it got picked up by The New Stack. Here’s the full list so far, I…

LLMs can be more useful and less prone to hallucination when they’re able to read relevant documents, webpages, and prior conversations before responding to a new user question.

We take a look at LlamaIndex, which allows you to combine your own custom data with an LLM — without using fine-tuning or overly long prompts.

LMQL is a query language for large language models (LLMs). It facilitates LLM interaction by combining the benefits of natural language prompting with the expressiveness of Python.

The new era of tech seems to be built on superstitious behaviour

Containers, large language models (LLMs), and GPUs provide a foundation for developers to build services for what Nvidia CEO Jensen Huang describes as an "AI Factory."

At QCon New York earlier this month, two OpenAI engineers demonstrated ChatGPT's newest feature, Functions, in one session. Another talk, however, pointed to the inherent limitations of LLMs.