
Biologist lost somewhere between the scales | Biology x ML @TechnionLive previously @BIUPasteur @lpiparis_ @Biologie_UNIGE Opinions are my own& mostly wrong
Haifa, Israel
Joined March 2019
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Excited to see our data-to-paper framework out @NEJM_AI !
ai.nejm.org/doi/full/10.1056…
Our data-to-paper AI is officially out!
ai.nejm.org/doi/10.1056/AIoa…
Autonomously analyzes data and writes human-verifiable papers!
Fun AI-human copiloting!
Papers are "data-chained": click-traced to the raw code.
Try it out:
github.com/Technion-Kishony-…
@TalIfargan @LostInTranscrip
Feels like a #terraformingmars card
Today, Pioneer Labs is announcing our first step towards terraforming Mars. 🚀🌼
With equipment that fits in just a single rocket launch, we can convert Martian dirt, water, and air into enough building materials to construct a small city on Mars.
To do it, we made the first microbe for Mars. We found the best microbe on Earth and used evolution to teach it how to source all of its nutrients directly from Martian materials.
The first astronauts will be greeted with safe shelter already filled with water, oxygen, and rocket fuel for the return journey.
This is the first step toward using biology to make Mars a friendly place for life. It lets us live off the land and helps us build the next great frontier.
It's the first of five organisms we need to green Mars ⬇️
Lukas Hafner retweeted
We speak at ≈ 8k words per hour.
300b tokens ≈ 230b words ≈ 10'000 years speaking 8h per day.
Lukas Hafner retweeted
re "disclosing AI use in papers" discussion that re-emerges: please lets not do it
as a reviewer or a reader of a paper, i do not care what part of the ideation, research, proof, implementation or writing was done by AI, and how the credit is split between the AI and human author.
at the end of the day, humans sign on the resulting paper, and this is all i care about. that they stand behind the text they produced. i don't care if the idea is theirs or came from the AI or is a shared process. i do care that they found it compelling enough to publish.
in any case i don't trust the authors to accurately describe how the idea evolved between them and the AI: even if they do try and be honest, i think in most cases its a complex process the author themselves don't fully understand.
when i work with a student, i certainly do want them to explain how they used AI and which parts of the work, idea or argument are primarily AI driven. but this is in order to guide and improve the student's work and process, not because i care about the credit assignment. it's part of their training and my mentoring, and should not leak into the final work. the readers and reviewers should not be bothered with it.
so please. let just have people submit work without the silly AI disclosures, and be very trigger-happy on rejecting papers that are clear AI slop, or that are hard to evaluate due to what may be improper AI use.
(in the short term, we will likely see an increase in conference submissions that have the same idea, coming from different authors having a similar process with a shared AI. i think this will sort itself in the long run by reducing the credit assigned to such works in the community, but in the short term we may want the conference management software to actively look for such similar submission, and maybe review them in bulk)
Lukas Hafner retweeted
This is so inginius (and I am worried likely true): "in the future our entire work will just be to prove we are human". What a cool and scary idea; perfect for a Black Mirror episode!
Replying to @netflix
@netflix
1/ Black Mirror episode pitch: In the future, AI does all the work. Humans just live off universal basic income.
Except there's one taks left: proving you're not a robot.
And it's slowly eating people's entire lives (if you have a phone, maybe you can relate!)
🤖 Made with AI
4/ Here's the twist: the offboarded aren't just surviving in the shadows of the cities. Freed from the relentless grind of authentication, many of them are thriving! Poorer, but freer - while the "IDs" spend their days trapped in self-driving taxis, buried in verification loops.
Lukas Hafner retweeted
Most experiments fail, and negative results rarely get published. This means LLMs are unaware of the outcomes of most experiments.
With AI getting better and better: will "taste" become the "key" human skill; e.g. the sense of knowing what is "good" and/or "true"?
Lukas Hafner retweeted
1/ Do you have a favorite protein you wish you could dissect residue by residue? 🔬 Excited to share our platform for mutational scanning at endogenous loci in yeast (no ectopic expression needed!) doi.org/10.1101/2025.09.09.6…
Lukas Hafner retweeted
🌎👩🔬 For 15+ years biology has accumulated petabytes (million gigabytes) of🧬DNA sequencing data🧬 from the far reaches of our planet.🦠🍄🌵
Logan now democratizes efficient access to the world’s most comprehensive genetics dataset. Free and open.
doi.org/10.1101/2024.07.30.6…
Lukas Hafner retweeted
How do we build AI systems that enable deeper, not just faster, science? I came across a very thought-provoking article by @nisheethvinoi on “What Counts as Discovery?”
Lukas Hafner retweeted
Legitmately thrilled to share our latest work, in which @fernpizza solved an experimental challenge in plasmid biology as old as the field: measuring how plasmids compete and evolve within individual cells!
Replying to @fernpizza @baym
Here we show that within-cell competition is key to plasmid evolution. Link to the paper! (2/n) biorxiv.org/content/early/20…
Lukas Hafner retweeted
📢 First paper from my Postdoc is out. The field of stem cell-based embryo models is flourishing. These models mimic critical stages of embryo development, providing powerful tools to study processes that are tricky to dissect in natural embryos. Many approaches are being used to investigate them—what was ours? 👇
nature.com/articles/s41467-0…
Lukas Hafner retweeted
Listen to this one to hear a debate about some of the best medical AI papers of the past few years, lots of laughter, and a rare long-form glimpse into @zakkohane’s special mentoring style.
Dr. @zakkohane discusses the evolving landscape of AI in medicine and shares insights on health care system challenges, the Human Values Project, and his perspectives on the most significant AI developments of 2024. Listen to the full episode: nejm.ai/ep26
Lukas Hafner retweeted
Original Article by @TalIfargan et al.: Autonomous LLM-Driven Research — from Data to Human-Verifiable Research Papers nejm.ai/4f8JAPA
#ArtificialIntelligence
Lukas Hafner retweeted
Indeed, mistakes in research are inevitable, but the key is to leverage AI to address them more effectively and expose them transparently. We should harness AI to make science more reproducible and verifiable.
Lukas Hafner retweeted
A study by @TalIfargan and colleagues demonstrates a potential for AI-driven acceleration of scientific discovery in biomedical research and beyond, while enhancing, rather than jeopardizing, traceability, transparency, and verifiability. nejm.ai/4f8JAPA





























