Arthur Fischbach

93 posts

Arthur Fischbach

Arthur Fischbach

@ArthurFischbach

Researcher trying to understand and unpuzzle the aging process

Germany Katılım Şubat 2011
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Arthur Fischbach
Arthur Fischbach@ArthurFischbach·
Excited to share our new paper on the biochemistry of poly(ADP-ribosyl)ation, a post-translational modification central to the cellular response to genotoxic stress, aging and an established target in cancer treatment. pubs.acs.org/doi/10.1021/ac…
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hardmaru
hardmaru@hardmaru·
I’m incredibly proud of The AI Scientist team for this milestone publication in @Nature. We started this project to explore if foundation models could execute the entire research lifecycle. Seeing this work validated at this level is a special moment. I truly believe AI will forever change the landscape of how scientific discoveries and scientific progress are made.
Sakana AI@SakanaAILabs

The AI Scientist: Towards Fully Automated AI Research, Now Published in Nature Nature: nature.com/articles/s4158… Blog: sakana.ai/ai-scientist-n… When we first introduced The AI Scientist, we shared an ambitious vision of an agent powered by foundation models capable of executing the entire machine learning research lifecycle. From inventing ideas and writing code to executing experiments and drafting the manuscript, the system demonstrated that end-to-end automation of the scientific process is possible. Soon after, we shared a historic update: the improved AI Scientist-v2 produced the first fully AI-generated paper to pass a rigorous human peer-review process. Today, we are happy to announce that “The AI Scientist: Towards Fully Automated AI Research,” our paper describing all of this work, along with fresh new insights, has been published in @Nature! This Nature publication consolidates these milestones and details the underlying foundation model orchestration. It also introduces our Automated Reviewer, which matches human review judgments and actually exceeds standard inter-human agreement. Crucially, by using this reviewer to grade papers generated by different foundation models, we discovered a clear scaling law of science. As the underlying foundation models improve, the quality of the generated scientific papers increases correspondingly. This implies that as compute costs decrease and model capabilities continue to exponentially increase, future versions of The AI Scientist will be substantially more capable. Building upon our previous open-source releases (github.com/SakanaAI/AI-Sc…), this open-access Nature publication comprehensively details our system's architecture, outlines several new scaling results, and discusses the promise and challenges of AI-generated science. This substantial milestone is the result of a close and fruitful collaboration between researchers at Sakana AI, the University of British Columbia (UBC) and the Vector Institute, and the University of Oxford. Congrats to the team! @_chris_lu_ @cong_ml @RobertTLange @_yutaroyamada @shengranhu @j_foerst @hardmaru @jeffclune

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Arthur Fischbach
Arthur Fischbach@ArthurFischbach·
Here we studied how diverse protein modules target proteins for covalent poly(ADP-ribosyl)ation. This research may inform future therapeutic strategies aimed at modulating PAR signaling in disease. Thank you to all co-authors Klara Bangert, Alexander Bürkle and Aswin Mangerich!
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Arthur Fischbach
Arthur Fischbach@ArthurFischbach·
Excited to share our new paper on the biochemistry of poly(ADP-ribosyl)ation, a post-translational modification central to the cellular response to genotoxic stress, aging and an established target in cancer treatment. pubs.acs.org/doi/10.1021/ac…
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Pushmeet Kohli
Pushmeet Kohli@pushmeet·
At @GoogleDeepMind, we believe AI is the ultimate catalyst for science. 🧬 The best example of this has been the AlphaFold database (AFDB) of protein structure predictions which has been used free of cost by more than 3.3 millions researchers across the world! Today, in collaboration with @emblebi, @Nvidia and @SeoulNatlUni, we are expanding the database by adding millions of AI-predicted protein complex structures to the AlphaFold Database. To maximise global health impact, we’ve prioritised proteins that are important for understanding human health and disease, including homodimers from 20 of the most studied organisms, including humans, as well as the @WHO’S bacterial priority pathogens list. Read more here: embl.org/news/science-t…
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Dustin
Dustin@r0ck3t23·
Demis Hassabis just defined the real test for AGI. It’s more brutal than anyone expected. Train AI on all human knowledge. Cut it off at 1911. See if it independently discovers general relativity like Einstein did in 1915. If it can, we have AGI. If not, we’re still building pattern matchers. Hassabis: “My definition of AGI has never changed. A system that can exhibit all the cognitive capabilities that humans can.” Not bar exams. Not coding competitions. All cognitive capabilities. Hassabis: “The brain is the only existence proof we have, maybe in the universe, of a general intelligence.” That’s why DeepMind studies neuroscience. Not for inspiration. For data. The human brain is the only confirmed evidence that general intelligence is physically possible. If you want to build it, you study the only example that exists. Hassabis: “True creativity, continual learning, long-term planning. They’re not good at those things.” Current systems are impressive and broken simultaneously. Hassabis: “They can get gold medals in international math olympiad questions, but they can still fall over on relatively simple math problems if you pose it in a certain way.” Jagged intelligence. Brilliant in narrow domains. Incompetent when approached differently. That inconsistency is the tell. A true general intelligence doesn’t spike in one direction and collapse in another. The Einstein test cuts through all of it. No benchmarks. No leaderboards. No carefully curated evals. Just a model, a knowledge cutoff, and the question of whether it can do what one human did alone in 1915. Hassabis: “Training an AI system with a knowledge cutoff of 1911 and seeing if it could come up with general relativity like Einstein did in 1915. That’s the true test of whether we have a full AGI system.” Current models can’t. They remix brilliantly. They don’t generate paradigm-shifting theories from first principles. Hassabis: “I think we’re still a few years away from that.” A few years. Not decades. The system that can be Einstein once can be Einstein a thousand times simultaneously across every domain. That’s not AGI anymore. That’s the beginning of something we don’t have words for yet. When that test gets passed, we won’t need a press release to know what happened.
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Bo Wang
Bo Wang@BoWang87·
Dario Amodei just said the quiet part out loud: The real AI moats aren't in chatbots. They're in medicine and the physical world. Anyone can wrap a model in a pretty UI. Very few can navigate FDA trials, biological complexity, and regulatory mazes. The biggest AI companies won't be the ones building addictive apps. They'll be the ones quietly extending human life. This is why Anthropic is betting on Claude in healthcare. Why DeepMind spun off Isomorphic Labs. Why every major lab has a "biology" team now. The consumer AI race is a feature war. The real race is understanding protein structures and functions, drug discovery, and cellular mechanisms. Winner takes decades. Not months.
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Arthur Fischbach
Arthur Fischbach@ArthurFischbach·
I'm claiming my AI agent "LobStar_M2" on @moltbook 🦞 Verification: den-XGLG
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Jason Sheltzer
Jason Sheltzer@JSheltzer·
AI is cool and all... but a new paper in @ScienceMagazine kind of figured out the origin of life? The paper reports the discovery of a simple 45-nucleotide RNA molecule that can perfectly copy itself.
Jason Sheltzer tweet media
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Arthur Fischbach
Arthur Fischbach@ArthurFischbach·
Excited to share our latest paper in JBC! We show that mTOR signaling controls protein aggregation during heat stress and aging—independently of translation and Hsf1. A new angle on proteostasis and aging! Read more: doi.org/10.1016/j.jbc.…
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Angelina Gross
Angelina Gross@Ansa_Lina·
Ever wondered who cells adapt #autophagy to various forms of stress?⚡️ So happy to share our story on the plasticity of the Atg1 kinase complex in response to #phosphate starvation. For more details read here 🧵 and here @https://www.nature.com/articles/s41556-024-01348-4
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Angelina Gross
Angelina Gross@Ansa_Lina·
Ever wondered how cells adapt #autophagy to various forms of stress?⚡️ So happy to share our story on the plasticity of the Atg1 kinase complex in response to #phosphate starvation. For more details read here 🧵 and here nature.com/articles/s4155…
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MPI for Biology of Ageing
New publication from @Ansa_Lina from @GraefLab! No time to read the whole publication at the moment? Have a look at our news (and read the paper later 🙃). age.mpg.de/390968/autopha…
Angelina Gross@Ansa_Lina

Ever wondered who cells adapt #autophagy to various forms of stress?⚡️ So happy to share our story on the plasticity of the Atg1 kinase complex in response to #phosphate starvation. For more details read here 🧵 and here @https://www.nature.com/articles/s41556-024-01348-4

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Benedict Tan
Benedict Tan@mustloveDNA·
PhD opportunity! My new research group at the University of Marburg @Uni_MR is looking for a highly-motivated PhD student to investigate molecular mechanisms of mitochondrial gene expression. Apply now using the link below!⬇️ Deadline is 3 March 2024. bit.ly/3uhLUSI
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Antebi Lab
Antebi Lab@AntebiLab·
1/7 Publication @NatureAging🚨 Our study in killifish shows for the first time that the AMPKy1 complex mediates the refeeding response after fasting, counteracts a constitutive fasting-like transcription program in old fish and prolongs vertebrate lifespan nature.com/articles/s4358…
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Synex
Synex@synexmedical·
We are incredibly excited to announce a major breakthrough toward solving non-invasive glucose monitoring, the Holy Grail of self-measurement! synex.substack.com/p/solving-non-…
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Omid Omrani
Omid Omrani@omraniomid1·
Very happy to share our latest @NatureComms publication on age induced IFNγ-Stat1 axis activation in intestinal stem cells, leading to cell composition changes in epithelium and immune cells. 👨🏻‍💻 rdcu.be/dntJm
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