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Owl Posting

owlposting.com

essays about biology and ml, written for and by owls. Click to read Owl Posting, by Abhishaike Mahajan, a Substack publication with tens of thousands of subscribers.

ScienceAI / MLEssays / personal

’24’25’26
Posts
92 from 8 Mar 2024 to 21 Sep 2026
Posting
weekly (27 in the last year)
Kind
personal blog
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https://www.owlposting.com/feed

2026 20

  1. Are organoids useful for Alzheimer’s research?
  2. Where have organoids actually been useful?
  3. Why haven't organoids solved all of drug discovery?
  4. How to design a cancer vaccine (and vastly improve them): Alex Rubinsteyn & Ben Vincent
  5. The makings of a good bioweapon
  6. How to build a cancer vaccine, and whether they will work this time
  7. The ballad of TIGIT
  8. How financial architectures shaped (and will continue to shape) Chinese drug development
  9. Perturb-MARS: Reading mouse experiments through a human lens
  10. Curious cases of financial engineering in biotech
  11. The printing press for biological data (Sterling Hooten)
  12. On creating 'new knobs of control' in biology
  13. Owl Posting turns two
  14. Reasons to be pessimistic (and optimistic) on the future of biosecurity
  15. Neurotechnology? For Cancer? (Ben Woodington & Elise Jenkins)
  16. Heuristics for lab robotics, and where its future may go
  17. AI After Drug Development
  18. Questions to ask when evaluating neurotech approaches
  19. The truth behind the 2026 J.P. Morgan Healthcare Conference
  20. A 2026 look at three bio-ML opinions I had in 2024

2025 40

  1. The origin of rot
  2. The ML drug discovery startup trying really, really hard to not cheat (Leash Bio)
  3. What if we could grow human tissue by recapitulating embryogenesis? (Matthew Osman & Fabio Boniolo)
  4. We don't know what most microbial genes do. Can genomic language models help? (Yunha Hwang, Ep #7)
  5. Human art in a post-AI world should be strange
  6. Bringing organ-scale cryopreservation into existence (Hunter Davis, Ep #6)
  7. Can machine learning enable 100-plex cryo-EM structure determination? (Ellen Zhong, Ep #5)
  8. Cancer has a surprising amount of detail
  9. The optimistic case for protein foundation model companies
  10. Ask not why would you work in biology, but rather: why wouldn't you?
  11. RNA structure prediction is hard. How much does that matter?
  12. How do you use a virtual cell to do something actually useful?
  13. A compilation of eleven stories
  14. The DNA protection company (Alan Tomusiak, Ep #4)
  15. A vibe check on the San Francisco biotech scene
  16. Mapping the off-target effects of every FDA-approved drug in existence (EvE Bio)
  17. Joining Noetik
  18. Comments on 'Endometriosis is an incredibly interesting disease'
  19. Endometriosis is an incredibly interesting disease
  20. Administering immunotherapy in the morning seems to really, really matter. Why?
  21. A body most amenable to experimentation
  22. Drugs currently in clinical trials will likely not be impacted by AI
  23. Will protein design tools solve the snake antivenom shortage?
  24. What could Alphafold 4 look like? (Sergey Ovchinnikov, Ep #3)
  25. On painful books
  26. A retrospective on writing a technical blog for a year
  27. What happened to pathology AI companies?
  28. Optogenetics could change the world. So why hasn’t it?
  29. Roundup #4 (Feb 23-Mar 15, 2025)
  30. Opinionated advice for writing about science
  31. A socratic dialogue over the utility of DNA language models (Part 2 of 2)
  32. Roundup #3 (announcements, links, jobs)
  33. A socratic dialogue over the utility of DNA language models (Part 1 of 2)
  34. AI-Designed Enzymes
  35. Roundup #2 (announcements, links, jobs)
  36. How do you make a 250x better vaccine at 1/10 the cost? Develop it in India. (Soham Sankaran, Ep #2)
  37. Reinforcement Learning by AI Punishment
  38. Roundup #1 (announcements, links, and jobs)
  39. Is there such a thing as an impossible protein?
  40. Better antibodies by engineering targets, not engineering antibodies (Nabla Bio)

2024 32

  1. A primer on machine learning in cryo-electron microscopy (cryo-EM)
  2. Can o1-preview find major mistakes amongst 59 NeurIPS '24 MLSB papers?
  3. A retrospective on filming a science podcast
  4. Can AI improve the current state of molecular simulation? (Corin & Ari Wagen, Ep #1)
  5. Why Recursion Pharmaceuticals abandoned cell painting for brightfield imaging
  6. Interesting links #3
  7. There aren't enough smart people in biology doing something boring
  8. Interesting links #2
  9. The unreasonable effectiveness of plasmid sequencing as a service (Plasmidsaurus)
  10. Models of Life
  11. Interesting links #1
  12. Generative ML in chemistry is bottlenecked by synthesis
  13. Fictional parasites very different from our own
  14. Things I learned talking to the new breed of scientific institution
  15. Creating the largest protein-protein interaction dataset in the world (A-Alpha Bio)
  16. A socratic dialogue over why drugs work at all
  17. A primer on the current state of longevity research
  18. Wet-lab innovations will lead the AI revolution in biology
  19. Scaling microbial metagenomic datasets (Basecamp Research)
  20. Why write about biotech startups?
  21. A primer on GFP and esmGFP
  22. Five things to keep in mind while reading biology ML papers
  23. A primer on why microbiome research is hard
  24. Molecular dynamics data will be essential for the next generation of ML protein models
  25. A primer on molecular dynamics
  26. Some of my favorite pessimistic scientific articles
  27. A primer on why computational predictive toxicology is hard
  28. A primer on the next generation of antibodies
  29. A primer on machine learning in antibody engineering
  30. Token:parameters in protein language models
  31. A primer on scRNA-seq foundation models
  32. RFDiffusion: (5) anecdotal observations over a year