AI models were perplexed by a baby giraffe without spots. They’re perplexed by me, too.

Learn more about the current moment for language technology and how the UW’s computational linguistics program prepares students to work in the field in this Q

Dataherald is a natural language-to-SQL engine built for enterprise-level question answering over structured data. It allows you to set up an API from your database that can answer questions in plain English.

Get up and running with large language models, locally.

In this post, we’ll talk about why fine-tuning is probably not necessary for your app, and why applying two of the most common techniques to the base GPT models — few-shot prompting and retrieval-augmented generation (RAG) — are sufficient for most use cases.

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browser based LLM, no install!

ChatGPT and other AI applications such as Midjourney have pushed “Artificial Intelligence” high on the hype cycle. In this article, I want to focus specifically on the energy cost of training and using applications like ChatGPT, what their widespread adoption could mean for global CO₂ emissions, and what we could do to limit these emissions.

Key points

• Training of large AI models is not the problem
• Large-scale use of large AI models would be unsustainable
• Renewables are not making AI more sustainable

The enormous energy requirement of these brute force statistical models is due to the following attributes:

• Requires millions or billions of training examples
• Requires many training cycles
• Requires retraining when presented with new information
• Requires many weights and lots of multiplication

ChatGPT and other AI applications such as Midjourney have pushed “Artificial Intelligence” high on the hype cycle. In this article, I want to focus specifically on the energy cost of training and using applications like ChatGPT, what their widespread adoption could mean for global CO₂ emissions, and what we could do to limit these emissions.

Key points

• Training of large AI models is not the problem
• Large-scale use of large AI models would be unsustainable
• Renewables are not making AI more sustainable

The author shares how he leveraged Chat-GPT to solve some of the CTF hacking challenges at BSides 2023.

No matter what, though, I argue that “information retrieval” is—despite how LLMs are marketed—is one of the least interesting and reliable things you can do with them. It’s mostly interesting, as described above, a “common wisdom” sampler to examine the common narratives that show up repeatedly in the corpus.

One of the relatively little-discussed phenomena in the social critique of AI is the fact that it is not only a centralizing technology, but also one that increases the distance between people and the power of the owners of the coordinating infrastructure. Of course, there is no direct determinism of the infrastructure, but it matters in which way the playing field is tilted.

This is aguide for how to build the LLM from Facebook in an M2 Macbook Pro

OpenAssistant is a chat-based assistant that understands tasks, can interact with third-party systems, and retrieve information dynamically to do so.

OpenAssistant is a chat-based assistant that understands tasks, can interact with third-party systems, and retrieve information dynamically to do so.

We’re on a journey to advance and democratize artificial intelligence through open source and open science.