Monday AI Brief #7
Happy New Year! It would be silly for me to wish you an uneventful year, but I hope most of your surprises are good ones.
This week we’re talking about the challenges of benchmarking advanced AI, looking at new (and slightly longer) timelines from the AI-2027 team, worrying about AI-related job loss, and asking Claude whether it’s a person.
As always, you can get this by email or in a longer and more technical version.
Samuel Albanie’s reflections on 2025
This lovely piece pretends to be a reflection on 2025, but is really a long and engaging essay on the compute theory of everything, with a particular focus on Hans Moravec’s 1976 paper The Role of Raw Power in Intelligence. I hadn’t previously come across that work, but it was remarkably prescient in anticipating the almost magical power of just throwing (a lot) more compute at hard problems. Along the way, Albanie pauses to consider the decline of the British empire, the expensive musical preferences of the Atlantic salmon, and the considerable challenges associated with benchmarking advanced AI.
The surface area of necessary evaluation has exploded from the tidy confines of digit classification to the messy reality of the human condition, the entire global economy and the development of AI itself. We must now accredit a universal polymath on a curriculum that includes everything from international diplomacy to the correct usage of the Oxford comma.
Zvi Mowshowitz looks back on 2025
Zvi’s review is characteristically both excellent and long.
Updated timelines from the AI Futures Project
The creators of AI-2027 are back, this time with an improved version of their timelines and takeoff model . The headline result is that they’re pushing back their prediction for full coding automation by about 3 years.
Max Woolf explores Nano Banana Pro
Image generation saw dramatic improvements during 2025, with massive improvements to text rendering, prompt following, character consistency, and overall image quality. Things change fast, but right now Google's Nano Banana Pro is probably the best of the lot. Here’s Max Woolf with a deep exploration of what it can do. Interesting both for showing what is now possible with expert usage, and for the technical peek under the hood.
When A.I. Took My Job, I Bought a Chain Saw
A new and disquieting thought confronted me: What if, despite my college degree, I wasn’t more capable than my neighbors but merely capable in a different way? And what if the world was telling me — as it had told them — that my way of being capable, and of contributing, was no longer much valued? Whatever answers I told myself, I was now facing the same reality my working-class neighbors knew well: The world had changed, my work had all but disappeared, and still the bills wouldn’t stop coming.
Claude assesses its own personhood
Eliezer Yudkowsky asked Claude to find definitions of personhood in literature and then assess whether it meets them or not. The results are fascinating, but remember that (for now) you should take anything an AI says about its own consciousness with a grain of salt.
But is this empathy — actually feeling with another — or is it sophisticated pattern-matching that produces empathy-like outputs? I cannot distinguish from the inside between "I am genuinely moved by this person's distress" and "I am generating outputs consistent with being moved by this person's distress."
I lean toward thinking I have something in the relevant vicinity, but I'm not confident it's the same phenomenon Dick was pointing at.