Wake me up when they do Moltbook but in Project Genie
COMPUTING
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RTL outperforms with 10x fewer parameters
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The results are absolutely wild: • 10x fewer parameters than independent models
• Higher accuracy than single-mask approaches
• Works across vision, speech, even coordinate-based representations At 75% sparsity, RTL beats everything while using only 38K parameters vs 314K -
Samsung’s RTL: Tailored Subnetworks for Data Classes
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The problem with current pruning methods: They assume ONE mask works for all data. Like forcing every student to learn math the same way. Samsung's RTL (Routing the Lottery) discovers specialized subnetworks – each tailored to specific classes, clusters, or conditions.
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Samsung disproves Lottery Ticket Hypothesis
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Samsung just broke the Lottery Ticket Hypothesis Everyone's been searching for ONE winning subnetwork in neural networks. Turns out we should've been finding MULTIPLE specialized ones. This changes everything about neural network pruning
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NVIDIA Introduces NVQLink to Connect Quantum Computing and GPU
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NVIDIA Introduces NVQLink — Connecting #Quantum and #GPU Computing for 17 Quantum Builders and Nine Scientific Labs https://
nvidianews.nvidia.com/news/nvidia-nv
qlink-quantum-gpu-computing
… @nvidia #Quantum #CES2026 #AI #IoT #GTC -
Laser-Powered Drones Achieve Infinite Flight with Wireless Charging
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Drones could achieve 'infinite flight' after engineers create laser-based wireless power system that charges them from the ground | Live Science https://
share.google/7WbNmZzYRsh8ua
ndp
… #drone #dronetech #Engineering #EngineeringExcellence -
Comprehensive Guide to Supercomputing for AI Architectures and Scaling
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Supercomputing for AI – Foundations, Architectures, and Scaling Deep Learning. [804-page masterpiece] Read it online: https://
jorditorresbcn.github.io/supercomputing
-for-ai-book/
… Buy it: https://
amzn.to/4qS4pFz GitHub repo: https://
github.com/jorditorresBCN
/supercomputing-for-ai
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In-house inference kernels migration to GB 200 hardware
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Enjoy! Baked with our in-house inference kernels. We're going to migrate all our inference to GB 200s soon. More details soon.
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Edinburgh EPCC Open-Sources Cerebras CS-3 Programming Libraries
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The @EPCCed at the University of Edinburgh—one of Europe’s leading supercomputing centers—has developed new high-level libraries to program the Cerebras CS-3 and just open-sourced them for everyone else to use. When they measured the performance against GPU and CPU clusters,
