There’s a lot of focus on using AI to increase productivity and throughput but I haven’t seen many people focusing on techniques for increasing quality while keeping throughput constant.
@itsolelehmann@kimmonismus I don't think he said that. He said "In 12 months, we may be in a world where AI is writing essentially all of the code." and that's basically what's happened at a lot of companies.
@jachiam0 Ok but the problem is that the AI companies are stuck in a Prisoner’s Dilemma-style multi-polar trap where they have to keep racing ahead to keep up with the other AI companies even if doing so is unpopular.
Interesting paper showing how there is an "AI assistant" steering vector: steering towards the AI assistant direction results in more stereotypical AI assistant behavior. Steering away causes the AI to adopt a wide variety of dramatic and entertaining personalities.
The Assistant Axis: Situating and Stabilizing the Default Persona of Language Models: https://t.co/GW4t0ZCQij
Software engineering in the 2020s seems to be going through the kind of industrial revolution the textile industry went through in the 1700s: https://t.co/4cM8vFaGnF
Interesting how AI models see the world in a different way to humans:
"Interestingly, we also found many cases where humans strongly agree on an answer, but the AI models get it wrong. For the third example below, most people agree the starfish is the odd one out. But most vision models focus more on superficial features like background color and texture, and choose the cat instead."
https://t.co/xY65jpoOS6
"Consciousness in Artificial Intelligence:
Insights from the Science of Consciousness" is a great paper on applying different theories of consciousness to understand whether AI models are conscious: https://t.co/TOvw2s64de
The conclusion is that current AI models don't seem to be conscious but that could change in the future.
Good article on the role of people in an advanced AI economy: https://t.co/GNW3q8BVDD
> "Technical education will become more critical than ever—it will be needed to train the human auditors capable of overseeing these powerful systems. We will still need technical specialists, but their primary role will shift from generation (doing the task) to discrimination (auditing the AI's work)."