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large language models

Large Language Models (also known as LLMs) are a class of generative model that makes use of deep neural network technology to facilitate natural language processing. As a starting point, check out Mark Riedel's A Very Gentle Introduction to Large Language Models without the Hype, on Medium.

Mindreading Models: Do LLMs Have Theory of Mind?

July 22, 2024

Did you know we're all mind readers? Humans develop what’s called “theory of mind” (ToM) around the age of four, enabling us to hold views and beliefs about our own mental states and the mental states of others. It’s one of those things that, well, makes us human. However, a recent paper by Strachan et al. explores this capability in the context of AI -- a finding which has some interesting implications. The authors compared the performance of a series of LLMs (GPT-3, GPT-4, and LLaMA2) against around 1,900 humans across a battery of tests designed to explore ToM. They determined that, in every task bar one (designed to test faux pas), LLMs can perform at or above human level. My own cursory testing suggests that GPT-4o may even be able to demonstrate ToM across the board. While we can’t conclude that these models actually have ToM (in a cognitive sense) they certainly seem to behave as if they do. So what does this mean in practice? These LLMs open the door to exciting potential applications across areas such as mental health and decision support making. Ultimately, this paper’s conclusions give us a moment to stop and think about the state of our technology: to be impressed by what we’ve accomplished, and acknowledge the risks that should be considered as we move forward.

Who’s Responsible for AI Safety?

May 22, 2024

The past few weeks have brought the issue of AI Safety to the fore in two contrasting ways: first, OpenAI launched GPT-4o, a promising new model that will be free for public use. Around the same time, Ilya Sutskever (OpenAI's renowned co-founder and chief scientist) left the company amidst reports that OpenAI had dissolved its long-term AI Safety team. Although the company reiterated its commitment to safe development, questions linger. Second, the UK's Department of Science, Innovation and Technology released its interim International Scientific Report on the Safety of Advanced AI. The report focuses on general-purpose AI and explores various risks as well as some technical risk mitigation techniques. It also leaves plenty unanswered. With so much uncertainty, it's imperative we seek to resolve the most practically-relevant question as soon as possible: who's responsible for AI Safety?

Sunday Sweep: Week in Review (March 3, 2024)

March 3, 2024

This week, Brazil adopted new A.I. regulation tackling election disinformation. It requires disclosing A.I. generated content as such, restricts chatbot use, and prohibits deepfakes. In an important election year across the globe, this'll be a space to watch closely. Another lawyer (this time in B.C., Canada) fell victim to LLM hallucinations and received a costs penalty for her blunder. Meanwhile, a Caribbean court is turning to A.I. for automatic transcript generation. Finally, Elon's suing OpenAI, ostensibly because they're taking money from Microsoft and that isn't what OpenAI was meant to be. While it's hard not to be skeptical about his intentions, the case certainly opens up interesting questions around AGI.