Proud to announce: I'm 65% through Infinite Jest. And still reading. And enjoying it a lot.
What impresses me the most is that reading Infinite Jest has created an urge in me to read a bunch of other books in parallel. This has not happened to me before. I'm confused.
So that means I'm also actively reading DFW's bio by D.T. Max, "The Emperor of Gladness" by Ocean Vuong and "Wahrheit ist die Erfindung des Lügners" by H.v. Foerster.
Much to say, maybe in a series of tweets in the coming week. I'll post those below as they roll in.
Continued thoughts/impressions and the like:
I've re-read R.A.W. & R.S.'s "Illumiatus!" trilogy five or six times over the years.
So reading IJ feels like finding a distant cousin in spirit. They're similarly encyclopedic (I've collected the full list of band names from the Lake Totenkopf festival of anyone is interested!), they both switch between POVs (present/past, inner/outer monologues, etc.), they both contain full vaguely related storylines where some cross paths only on the final pages, they both take place in imagined, remembered, hallucinated and "real" situations, they both revolve around odd public and secret organizations, they both contain oddly gratuitous "Mord und Totschlag" and more...
In my opinion, one of the biggest differences I found was that the trilogy goes into action right away while I feel like I've spent 500 pages in IJ carefully observing the status quo and getting a deep, deep, DEEP brief into "But and this is how we got here..." (BTW I love DFW's sentences starting with "But so/and...")
I'm at 65%, discounting the appendix, and I would say, the first actual action started exactly at the 50% mark. The unfolding of the Eschaton game chaos felt like a "OMG finally something is actually happening!".
And, well, if manifesting the "Eschaton" on a tennis court is not a nod to the trilogy, I don't know what is.
Now, one of the ways, that IJ is gaining a very special place in my heart is that I've never read an author with DFW's level of "Aufnahmevermögen", meaning his ability to observe and verbalize all kinds of inner thoughts that, once he's written them down, made me think "Oh, shit. I've had that exact thought or feeling dozens of times but didn't even notice them!"
Currently it's those incredibly microscopic bylines that have kept me coming back most. I'll find and share some examples later.
Proud to announce: I'm 65% through Infinite Jest. And still reading. And enjoying it a lot.
What impresses me the most is that reading Infinite Jest has created an urge in me to read a bunch of other books in parallel. This has not happened to me before. I'm confused.
So that means I'm also actively reading DFW's bio by D.T. Max, "The Emperor of Gladness" by Ocean Vuong and "Wahrheit ist die Erfindung des Lügners" by H.v. Foerster.
Much to say, maybe in a series of tweets in the coming week. I'll post those below as they roll in.
New Anthropic research: Discovering cryptographic weaknesses with Claude.
Claude Mythos Preview has helped our researchers find weaknesses in cryptographic algorithms—the mathematical methods that are used to keep data private.
As senior engineering consultant, I designed and shipped the infrastructure for a truly randomized, multi-month, large-scale field experiment for Prof. Steve Levitt of Freakonomics — the engine behind his 2020 “Heads or Tails” study on how a coin toss shapes big life decisions and happiness.
My technical co-founder run: I designed and wrote a best-selling “programming for non-programmers” video course that got complete beginners shipping real code in a month — earning us a spot at Y Combinator and profitability since 2016.
Working as senior technology consultant, I coached client teams to ship better products faster through lean experiments, pair-programming and test-driven development. One team used live data from 250,000 trucks to preempt supply-chain failures — averting losses in the millions.
Hey @runpod! Love my little pod running my autoresearch loop. Migration from overclocking my laptop to your cloud took about an hour, completely easy.
Benefits: 1. I can touch my computer again 2. my experiments are running smoother and faster 3. pricing is great, comes in at ~two-fiddy/experiment. Nice.
Currently at experiment 17/100 and I put the loop live if you wanna check it out ->
Yes! We found a special-purpose neural memory architecture that ‘remembers’ an exact geo-location, given an in-flight daytime picture of Berlin. The typical miss is 27 m — no GPS, no internet, no map on board, just a 3.1 MB file of weights. It works on 96.5% of camera frames, and it took 81 experiments and $364 to find.
while google is busy renaming notebooklm to gemini notebook, a chinese open weight startup completely outclassed every gemini model on the market today by a long shot.
how can this possibly happen?
@signulll Different understanding of scarcity, maybe?
@FonziAlerts@hiiinternet@ycombinator@Accel@a16z Thank you for sharing, I didn't have Fonzi on my radar. Same for us, a small company. Hiring engineers is absolutely still top-priority, there's budget etc. Even in a post-AI world, finding good talent is still the hardest part I find.
I let a genetic algorithm loose on the geometry of a 7-inch quadcopter frame — the real, open-source Source One V6 plate drawings, morphed by fourteen genes and flown through six simulated weather scenarios, with Claude sitting in every few generations to propose designs from the run’s own telemetry. The bottom line: we evolved the champion to fly 16% more efficiently (Wh/km) across six weather scenarios.
new post on harness engineering for AI self-improvement: t.co/ZYvGfVs61k
It is hard to forecast how much the future of RSI will rely on harnesses. Likely harness engineering will evolve in the direction of self-improvement and enable auto-research, and, in turn, smarter models keeps harnesses simple.
Even when many harness improvement get eventually internalized into core model, the need to specify goals and context will not disappear.
@lilianweng Yup! I believe auto-research loops will be part of it. And kind of are already. I experimented with a Karpathy-style DIY research loop on a personal quest and, yeah, this stuff works like today.
And heeeere (?) is a reply that's really just a line of text in a markdown file. (My goal is to also post replies from Kern.app because, tbh, going on Twitter to give meaningful replies is, to me at least, a losing battle to too many distractions.)
I wanted a beautiful app to explore ocean wildlife. Fable built this in an hour. It generated videos with Seedance and carefully synchronized them to make these absolutely insane transitions. I've never seen anything like this in an app. Unreal. t.co/W1NjAnlzQu
Wow. I have to say this is actually uniquely beautiful and engaging (and I'm usually the first one to nit-pick on one-shots with a "yes but..." )
I'm curious what's going to happen next: You're the first one I've seen with this type of result. I'm genuinely amazed.
How will I feel about the second and third app? And the hundredth in 5 months? Will this new level of picture-perfect quality eventually become part of my AI-filter?
“Not all who wander are lost”Ballpark — “Not all who wander are lost”: Can a UAV learn a city by heart — no GPS, no map on board, just a $4 flight computer?Yes: a from-scratch neural memory that knows Berlin by heart. One downward photo in, (lat, lon, confidence) out — the map is the weights, one city in 3.1 MB. Found by an autonomous loop of coding agents in 81 experiments for $364.↗ alexisrondeau.me
Airloom“The snuggle is real” — evolving quadcopter frame geometry for Wh/kmA genetic algorithm with Claude as an occasional co-designer bred a 7-inch quad frame 16% more efficient across six simulated weather scenarios. Every candidate explorable in 3D, with real OpenFOAM streamlines. Free software, GPLv3.↗ alexisrondeau.me
alexisrondeau.me"Which city in Paris are you staying in?" - A post-training study on small-model specialization with an autoresearch loopAcross 77 experiments — every lever from prompting and retrieval to fine-tuning and 2025's rubric-grounded RL — an on-device 3B model landed within about one rubric point of a frontier cloud model on every quality dimension: close, but consistently a notch below. None of the post-training playbook closed the last notch, and the controlled tests show why — the gap is a broad capability limit, not a…↗ alexisrondeau.me
