Does the UK’s liver transplant matching algorithm systematically exclude younger patients?
Seemingly minor technical decisions can have life-or-death effects
Newsletters 259 stories
FAQ about the book and our writing process
What's in the book and how we wrote it
Can AI automate computational reproducibility?
A new benchmark to measure the impact of AI on improving science
Start reading the AI Snake Oil book online
The book was published September 2024
What's Missing From LLM Chatbots: A Sense of Purpose
LLM-based chatbots’ capabilities have been advancing every month. These improvements are mostly measured by benchmarks like MMLU, HumanEval, and MATH (e.g. sonnet 3.5, gpt-4o). However, as…
AI companies are pivoting from creating gods to building products. Good.
Turning models into products runs into five challenges
We Need Positive Visions for AI Grounded in Wellbeing
IntroductionImagine yourself a decade ago, jumping directly into the present shock of conversing naturally with an encyclopedic AI that crafts images, writes code, and debates philosophy.…
AI existential risk probabilities are too unreliable to inform policy
How speculation gets laundered through pseudo-quantification
New paper: AI agents that matter
Rethinking AI agent benchmarking and evaluation
Financial Market Applications of LLMs
The AI revolution drove frenzied investment in both private and public companies and captured the public’s imagination in 2023. Transformational consumer products like ChatGPT are powered…
A Brief Overview of Gender Bias in AI
A brief overview and discussion on gender bias in AI
Mamba Explained
Is Attention all you need? Mamba, a novel AI model based on State Space Models (SSMs), emerges as a formidable alternative to the widely used Transformer…
Car-GPT: Could LLMs finally make self-driving cars happen?
Exploring the utility of large language models in autonomous driving: Can they be trusted for self-driving cars, and what are the key challenges?
Do text embeddings perfectly encode text?
'Vec2text' can serve as a solution for accurately reverting embeddings back into text, thus highlighting the urgent need for revisiting security protocols around embedded data.
Why Doesn’t My Model Work?
Have you ever trained a model you thought was good, but then it failed miserably when applied to real world data? If so, you’re in good…
Deep learning for single-cell sequencing: a microscope to see the diversity of cells
On the the pivotal role that Deep Learning has played as a key enabler for advancing single-cell sequencing technologies.
Salmon in the Loop
On fish counting – a complex sociotechnical problem in a field that is going through the process of digital transformation.
Neural algorithmic reasoning
In this article, we will talk about classical computation: the kind of computation typically found in an undergraduate Computer Science course on Algorithms and Data Structures…
The Artificiality of Alignment
This essay first appeared in Reboot. Credulous, breathless coverage of “AI existential risk” (abbreviated “x-risk”) has reached the mainstream. Who could have foreseen that the smallcaps…