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Rackbound
@rackbound.bsky.social
The backend of biotech. AI, datacenters, and the systems powering the future of life sciences.
Isomorphic Labs cloud-native stack runs thousands of GPUs orchestrating AlphaFold 3 at scale, shifting drug discovery from petri dishes to #HPC clusters. #drugdiscovery #AI #cloud www.rackbound.com/inside-isomo...
Inside Isomorphic Labs Cloud-Native HPC Architecture for AI Drug Discovery
Isomorphic Labs emerged as a distinctly digital creation, a direct outgrowth of Google's DeepMind and its computational biology ambitions. It's a biotech company, yes, but an unusual one. Unlike trad...
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July 8, 2025 at 7:13 PM
Viome Life Sciences is running 10 quadrillion RNA data points through Microsoft Azure using Ultra Disk #Storage and memory-optimized VMs. A cool case of pure #bioinformatics compute at massive scale. www.rackbound.com/azure-captur...
Azure Captures Viome’s 10-Quadrillion-Point RNA Dataset
When you’re operating at 10 quadrillion biomolecular data points, terms like scale and complexity almost lose their punch. Right down the street from Microsoft, Bellevue-based Viome Life Sciences, ta...
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July 8, 2025 at 6:00 PM
Almost a million CPU hours, 500M parameters, and billions of RNA tokens later, ArsenalBio’s gx1 transformer is rewriting T-cell biology. www.rackbound.com/a-million-cp...
A Million CPU Hours Later, AI Cracks Open the T-Cell Code
Sophia Panagiotopoulou makes it look so straightforward. Engineer T cells, sequence RNA, crunch the numbers, and let AI spit out targets. Boom, done. But behind all of this is an intense, computatio...
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July 4, 2025 at 2:35 AM
When your LLM, folding sim, and Torch model all want the same GPU, pooling isn't optional. Time-sliced driver-level vGPU sharing is how life sciences compute grows without growing racks. www.rackbound.com/how-to-share... #AI #biotech
How to Share a GPU Without Starting a War
The GPUs are here, but not enough of them. That's the truth for most mid-sized biotech and life sciences compute clusters, anyway. You’ve got your eight A100s, maybe sixteen if you're lucky, sitting...
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June 27, 2025 at 3:29 PM
Meta’s move to Passive Optical Networks (PON) ditches dense copper chaos for sleek fiber simplicity, exactly the #datacenter scale and agility life sciences shops need. www.rackbound.com/the-suburban... #AI
The Suburban Broadband Tech That Could Shift Life Sciences Datacenters
Mike ("MJ") Joseph stepped onto the stage recently and began unpacking Meta’s bold pivot toward Passive Optical Networking (PON) within its hyperscale datacenters, it seemed unlikely that anyone prese...
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June 27, 2025 at 1:23 AM
Pharma giants are building their own #AI models and legacy datacenters can't keep up. The future? Ultra-dense GPUs, massive memory, and FullFlat optical networks designed from scratch for trillion-parameter models. www.rackbound.com/an-ai-datace...
An AI Datacenter Blueprint for Drug Discovery at Scale
The funny thing about revolutions (and yes, the transition to AI-driven drug discovery certainly qualifies) is how they unfold gradually, right under our noses. If you had blinked sometime around, sa...
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June 23, 2025 at 1:21 AM
From MIT AI Conference - industry leaders emphasized medical AI’s urgent need for precision, transparency, and rigorous validation. The future isn't #robots replacing #doctors, but trusted #AI tools empowering clinicians. #PrecisionMedicine - www.rackbound.com/some-insight...
Some Insights from the MIT AI Conference
At last week’s MIT AI Conference, a panel of scientists and industry leaders gathered to tackle a deceptively simple question: how do we build artificial intelligence that clinicians can trust? More ...
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June 23, 2025 at 12:12 AM
When GPUs hit the wall in life sciences, waferscale architectures could deliver the scale and radical efficiency. Hey, it's just physics. www.rackbound.com/can-wafersca...
Can Waferscale Computing Crack the Life Sciences Bottleneck?
At the bleeding edge of drug discovery, researchers are facing a new kind of bottleneck. Models balloon to trillions of parameters, datasets surge into exabyte territory, and suddenly the GPU-driven d...
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June 20, 2025 at 4:40 PM
SandboxAQ just released 5.2 million synthetic 3D molecules to turbocharge AI drug discovery. Built with NVIDIA GPUs, grounded in real binding data, and free to use. www.rackbound.com/sandboxaq-li...
SandboxAQ Lives in the Future That Trains on Synthetic Molecules
In the endlessly recursive world of drug development, where billions are burned chasing molecules that never make it to market, the idea of conjuring promising compounds from nothing has always been m...
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June 19, 2025 at 3:11 AM
Advarra just dropped an #AI Council with Sanofi, Recursion and others to drag clinical trials out of the Wild West and into the age of rules, rigor, and real-world AI. www.rackbound.com/the-governan...
The Governance Era Arrives for AI in Clinical Trials
The biotech industry, never short on acronyms or ambition, has been flirting with artificial intelligence for years. Models have already been shaping protocol designs, accelerated site selection, and...
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June 19, 2025 at 1:31 AM
Xaira just dropped X-Atlas/Orion, the largest genome-wide Perturb-seq dataset yet, covering 8 million cells. It's public, powerful, and poised to reshape how #AI predicts #biology. www.rackbound.com/xaira-droppe...
Xaira Dropped a Dataset that Might Just Change Biology Forever
Xaira just dropped X-Atlas/Orion—the largest genome-wide Perturb-seq dataset ever, covering 8 million cells. It's public, powerful, and poised to reshape how AI predicts biology. Launching a biotech ...
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June 18, 2025 at 5:41 PM
Fauna Bio is betting evolution already cracked biology’s toughest problems. Their new #AI engine, Fauna Brain, turns nature’s wildest genetic secrets into therapeutic targets in minutes and costs pennies. www.rackbound.com/fauna-bios-w... #drugdiscovery #pharma #biotech
Fauna Bio's Wild Bet? Cracking Evolution's Code with AI at Nature’s Edge
Fauna Bio is betting evolution already cracked biology’s toughest problems. Their new AI engine, Fauna Brain, turns nature’s wildest genetic secrets into therapeutic targets in minutes and costs penni...
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June 17, 2025 at 9:22 PM
Recursion Pharma's stack is bioIT future spelled out clearly from automated labs through edge #GPU compute streaming #Kafka Kubernetes orchestration and #cloud TPUs The architecture isn't just efficient it's inevitable. www.rackbound.com/recursion-dr...
Recursion Drew The Blueprint of Future BioIT Infrastructure
Recursion Pharma's stack is bioIT future spelled out clearly from automated labs through edge GPU compute streaming Kafka Kubernetes orchestration and cloud TPUs The architecture isn't just efficient ...
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June 16, 2025 at 3:15 PM
BioIT isn’t starved for data. It’s choking on chaos. No shared formats. No clean metadata. No real interoperability. And if we don’t fix that, AI stays blind. www.rackbound.com/why-interope... #software #AI
Why Interoperability Still Fails in 2025
BioIT isn’t starved for data. It’s choking on chaos. No shared formats. No clean metadata. No real interoperability. If we don’t fix that, AI stays blind. The scene is not particularly dramatic, unle...
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June 16, 2025 at 2:11 AM
BioNeMo isn’t open, cheap, or fully explainable. It runs best on NVIDIA hardware and wraps biology in black-box APIs. Still, it’s quietly becoming the stack real pipelines depend on. www.rackbound.com/bionemo-isnt... #lifesciences #biotech
BioNeMo Isn’t a Model. It’s a Stack
BioNeMo isn’t open, cheap, or fully explainable. It runs best on NVIDIA hardware and wraps biology in black-box APIs. Still, it’s quietly becoming the stack real pipelines depend on. If you’ve ever t...
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June 15, 2025 at 11:36 PM
A new #biotech #AI model uses attention to design proteins by context, not rules. EMOCPD doesn’t simulate, it listens. Rackbound breaks it down. www.rackbound.com/the-attentio...
The Attention Span of a Protein Designer
Most of what passes for protein design these days is better described as substitution. You take a known backbone, swap in plausible residues based on energy or evolutionary alignment, and run it thro...
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June 14, 2025 at 1:22 AM