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We're at the threshold of understanding intelligence itself. The convergence of neuroscience and AI has created an unprecedented opportunity — but our research ecosystem isn't built to seize it. We need a new model that matches the scale of our ambition... 🧵
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David A. Markowitz retweeted
Neurotech is Humanity’s Next Frontier!
I’ve been investing in neurotech since 2021 and working with teams building BCIs, NeuroAI, and connectomics. It now feels like AI did in ~2019.
We are entering an extraordinary era: neurotech already restores functions, it can enhance our evolve what it means to be human.
PLC Neurotech is the fund backing the extraordinary founders and defining companies of this booming industry.
I’ve been investing in neurotech since 2021 and working with teams building BCIs, NeuroAI, and connectomics. It now feels like AI did in ~2019.
We are entering an extraordinary era: neurotech already restores functions, it can enhance our evolve what it means to be human.
PLC Neurotech is the fund backing the extraordinary founders and defining companies of this booming industry.
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David A. Markowitz retweeted
Great to see how some of our early work layed the foundation for this impressive breakthrough
This new post from @neuralink combines POYO-style spike tokenisation with a Mamba backbone, akin to our POSSM architecture, and explores self-supervised learning for these models, as we did recently with MOJO. Exciting to see these ideas supporting real-time BCI use! 🧵
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David A. Markowitz retweeted
In my inaugural Substack post, I explore the role of philanthropy in promoting AI moonshots.
Although the private sector will invest in many AI applications, philanthropy can play a critical role in harnessing AI to accelerate the development of vaccines for diseases of the poor, climate-resilient crops, and safe replacements for “forever” chemicals. Philanthropists can have an enormous impact by supporting the “public goods” for these applications, such as open datasets and well-designed benchmarks.
I am very excited by the partnerships that @RenPhilanthropy has with philanthropists to use AI to double the rate of student learning outcomes in middle school math, expand access to benefits for low-income families, fight climate change, develop targeted cancer therapies, and transform fundamental math. Link in the reply.
Although the private sector will invest in many AI applications, philanthropy can play a critical role in harnessing AI to accelerate the development of vaccines for diseases of the poor, climate-resilient crops, and safe replacements for “forever” chemicals. Philanthropists can have an enormous impact by supporting the “public goods” for these applications, such as open datasets and well-designed benchmarks.
I am very excited by the partnerships that @RenPhilanthropy has with philanthropists to use AI to double the rate of student learning outcomes in middle school math, expand access to benefits for low-income families, fight climate change, develop targeted cancer therapies, and transform fundamental math. Link in the reply.
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David A. Markowitz retweeted
How to make frontier AI models safer and accelerate drug discovery with the connectome. We are featured in this @IFP article by @AdamMarblestone & @Andrew_C_Payne
2. @AdamMarblestone & @Andrew_C_Payne on how to map the mammalian brain’s connectome to solve fundamental problems in neuroscience, psychology, and AI robustness: ifp.org/mapping-the-br…
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Feels like we're reaching a tipping point for technologies that will unlock whole brain emulation, e.g. a team from China just announced an optical method for cellular resolution monitoring of activity across mesoscale networks than span the whole mouse brain. 👇
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Devastating loss for neuroscience and ultimately for AI safety. Hearing that Lichtman's NIH grant to scale up EM connectomics by 10x beyond MICrONS was just canceled. Essential work for scaling EM to whole brains and for training a large workforce to support connectomics.
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This multi-institutional program also involves Princeton, MIT, and Cambridge University, with *$3M in co-funding* by several participant orgs. news.harvard.edu/gazette/story/…
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If you could deeply phenotype a whole brain - mapping all ultrastructure and connectivity, plus in situ proteomics, metabolomics, transcriptomics - would that be sufficient to constrain a model of its function under all conditions? What's the minimal data needed for emulation?
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The answer, I am convinced, is yes, and all the technologies needed to deeply phenotype a whole brain exist today. This is a viable path to whole brain emulation, with no physiology or behavioral experiments required.
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Gratified by today's news of a $155M seed round for DNA data storage newco Atlas, built on technologies developed under @IARPAnews MIST program. It validates my "if we de-risk it investors will come" thesis. Also means my public service has now driven >$1B of economic activity 🙂
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*predicted structures
Still a wonderful resource, but impt to note that AlphaFold only gives good predictions when there is an already known structure with similar sequence. Does poorly for proteins that arise from hypermutation (Abs) as well as many disease-linked mutants.
Still a wonderful resource, but impt to note that AlphaFold only gives good predictions when there is an already known structure with similar sequence. Does poorly for proteins that arise from hypermutation (Abs) as well as many disease-linked mutants.
Google’s AI outfit and the European Molecular Biology Laboratory’s European Bioinformatics Institute (EMBL-EBI) announced Thursday that DeepMind’s Alphafold database now contains the structures of more than 200 million proteins.
endpts.com/deepminds-alph…
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Protein crystallographers weigh in: "Some AlphaFold predictions match experimental maps closely, but most differ on a global scale" ... "and on a local scale" ... "even in parts of AlphaFold models that were predicted with high-confidence."
biorxiv.org/content/10.110…
biorxiv.org/content/10.110…
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(coda to 👆 tweet thread from 2022) ...and now it seems these limitations persist with AlphaFold3 x.com/genologos/stat…
Are AlphaFold3 and other protein-ligand structure predictors mostly memorizing their training data?
New study suggests yes. Predictions are much less accurate on new structures that are dissimilar to structures in the training set.
biorxiv.org/content/10.110…
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David A. Markowitz retweeted
My rule of thumb for successful ARPA programs is "If it doesn't constantly feel like everyone is on the verge of failure and you need to troubleshoot everything, then you haven't set appropriately ambitious goals." I call it the Art of the Impossible 🙂
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David A. Markowitz retweeted
Video thread containing the individual videos that accompanied the MICrONS paper package out last week. Not science explainer videos, more like "A trailer for a paper...Not intended to be a replacement for reading, but hopefully they make you want to:
nature.com/immersive/d428…
nature.com/immersive/d428…
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I received an email that I've personally been nominated for "2025 Breakthrough of the Year" for MICrONS, by a science org I won't call out here. 🧵
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They thanked me for my integrity and asked if I could instead please nominate ONE researcher who "best represents the academic contributions of the initiative – particularly someone who played a central role in the recent publications." 🤦♂️ 3/
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I've said it publicly before and I'll say it again: science awards that preferentially recognize individuals are an anachronism. This just doesn't reflect how much of today's impactful science gets done. 4/
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The public, free, and effortless accessibility of IARPA MICrONS data is nothing short of amazing. Several years ago, I asked @JeffDean and @stardazed0 if we could share this resource as a public good through GC and without hesitation @Google said yes. 👏👏
How does the brain work?
Scientists are closer to the answer with the largest wiring diagram and functional map of a mammalian brain to date. 🧵
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David A. Markowitz retweeted
“The MICrONS advances published in this special issue of Nature are a watershed moment for neuroscience, comparable to the Human Genome Project in their transformative potential"
How does the brain work?
Scientists are closer to the answer with the largest wiring diagram and functional map of a mammalian brain to date. 🧵
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