wtf now my agents found the first bacteria to use new stop codons!!
After this TAG result, a chat w/ friend inspired the question: do any bacteria use other stop codons?
Overnight, my guys found myxobacteria that stop at TTA, normally read as an amino acid.
Evidence:
1) These bacteria lost the tRNA that normally reads TTA as leucine.
2) Their RF2, the protein that recognizes stop codons, has two changes: one in its codon-reading tip (SPF → SPY) and one nearby (L → F). No other species in GTDB has both.
3) We compared the same genes in these bacteria and their closest relatives. Where a relative's gene ends at a normal stop but the gene here keeps going, the very next codon is TTA 11% of the time (252 of 2,339 genes). In the relatives, it's 0.05% (1 of 2,025).
4) TTA swaps with the normal stop codons. Where one of these genomes ends a gene at TTA, another genome from the same group ends that gene at a normal stop 78% of the time.
Method:
Claude agents on my Mac mini scanned all 199,923 bacterial and archaeal genomes in GTDB for amino-acid codons unusually common near the ends of genes, where a hidden stop would sit. In 4,599 genomes, they then matched each gene to corresponding proteins and checked which codon sits exactly where the known protein ends.
Closest prior work:
TTA works as a stop in some mitochondria and plastids (Barcytė et al. 2025), and CGA was proposed as a stop in Asgard archaea (Melnykov 2026, PNAS), but none in bacteria until now.
One of these bacteria, 1-FT3.2, is kept alive in Finland (Demina et al. 2025). Possibly its proteins can be measured to confirm this.
I discovered the first bacteria that no longer use TAG as a stop codon.
Almost all life ends its genes with the same 3 "stop" signals: TAA, TAG and TGA.
Bacteria were known to reassign TGA since the 80s. Archaea reassigning TAG was published in Science last year.
🧬 1/n
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Data and code: github.com/ry-xu/genome-rese…
I think at this point, getting this in front of people in the field is the most important next step. To validate results, discuss followups, and hopefully collaborate.
Please reach out if you find this interesting or if you know someone who would.
@phylogenomics @jcamthrash @OmicsOmicsBlog
ryan retweeted
Intellectual obesity is what happens when you consume too much and produce too little.
While this is fresh... my AI agents recently ALSO found possibly unmapped sites in Mexico.
Not Maya though, these are in the Huasteca. Dozens of raised earth platforms in a cow pasture.
Could also be modern earthworks - unverified and reported to INAH.
I discovered the first bacteria that no longer use TAG as a stop codon.
Almost all life ends its genes with the same 3 "stop" signals: TAA, TAG and TGA.
Bacteria were known to reassign TGA since the 80s. Archaea reassigning TAG was published in Science last year.
🧬 1/n
Following the 2025 work, the next step may be to confirm this in a lab and measure their proteins to see which amino acids actually sit at TAG positions.
Happy to discuss this work with anyone, and open to collaboration.
Data and code: github.com/ry-xu/bacteria-ta…
🧬 n/n
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aliens could land tmr and it would be the 4th most surprising thing that's happened recently
All 5 genetic “letters” of DNA and RNA discovered in a 4.5-billion-year-old asteroid sciencedaily.com/releases/20…
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I found 12 new ISS photos of Red Sprites (on top of the 35 already tagged by NASA) by scanning 1.9 million untagged ISS night photos.
Red sprites are beautiful electric discharges occurring ~50-90 km above thunderstorms, and last for barely a frame.
Ground photo: Paul M. Smith
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All 12:
ISS043-E-262974
ISS053-E-162720, 236710, 264396, 288056, 361847
ISS055-E-35007, 47451, 91395
ISS068-E-1270
ISS074-E-774567, 780091
Images: NASA Johnson Space Center (eol.jsc.nasa.gov)
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They thought he was speaking gibberish but he was just Hungarian 😭
András Toma, the last WW2 POW, being released. Toma was captured in 1945, and locked up in insane asylum for speaking gibberish. In 2000, he was accidentally discovered by a Slovak, who recognized he's speaking Hungarian. Toma was successfully identified and returned home.
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Looking at the reasoning trace, astra identified the games by:
1) which of the 10x10 grid cells had strong weights
2) which actions had large biases
E.g.
- Pong: only up and down actions have strong biases
- Breakout: bottom row for paddle, bricks at top
- Freeway: strong bias towards moving upwards
- Pac-Man: maze is visible from grid input weights
Still cool, but probably a game enthusiast would have figured it out in a few minutes in a similar way.
We asked GPT-6 Astra to edit Qwen3.5-0.8B weights to improve math.
It directly changed only 0.016% of weights, fixing 0.8B's reasoning loops & improving math up to 6x and even instruction following 3x, without gradients or training.
We call this Weight-Space Programming: frontier LLMs can now natively read/write neural network weights! 🧵
Blog: rikiyat.github.io/blog/weigh…
Readers added context they thought people might want to know
LLM was given weights explicitly as text in prompt and used code/forward passes (per authors' logs) to ablate Qwen looping direction, a known thinking-mode issue per model card. Primarily fixed repetition in that mode, not general 'natively' improving weights/math.
rikiyat.github.io/blog/weight-sp…
github.com/RikiyaT/lm_und…
huggingface.co/Qwen/Qwen3.5-0…
huggingface.co/RikiyaT/Qwen3.…
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This made me check whether today was April 1st.
I can see how this could be done with a lot of reasoning.
If Astra could, on zero-thinking mode, identify the Atari game based on weights or write functional rl policies, this would shatter my world view on the strength of LLMs.
We asked GPT-6 Astra to edit Qwen3.5-0.8B weights to improve math.
It directly changed only 0.016% of weights, fixing 0.8B's reasoning loops & improving math up to 6x and even instruction following 3x, without gradients or training.
We call this Weight-Space Programming: frontier LLMs can now natively read/write neural network weights! 🧵
Blog: rikiyat.github.io/blog/weigh…
Readers added context they thought people might want to know
LLM was given weights explicitly as text in prompt and used code/forward passes (per authors' logs) to ablate Qwen looping direction, a known thinking-mode issue per model card. Primarily fixed repetition in that mode, not general 'natively' improving weights/math.
rikiyat.github.io/blog/weight-sp…
github.com/RikiyaT/lm_und…
huggingface.co/Qwen/Qwen3.5-0…
huggingface.co/RikiyaT/Qwen3.…













