XQuant Breaking the Memory Wall for LLM Inference with KV Cache Rematerialization
COMPUTING
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Edge AI Model Quantization: Shrinking Footprint While Preserving Accuracy
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Deploying AI on the edge? Then you know the challenge: preserving accuracy while shrinking your model footprint. Some of our community members are sharing quantisation workflows that really deliver, and others, like the awesome team at @DeGirum
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LFM2-VL Support Added for GGUF and llama.cpp
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LFM2-VL support with GGUF and llama.cpp 🥳
— Maxime Labonne @ ICLR (@maximelabonne) 18 août 2025
You can now run these tiny, hyper-efficient VLMs on your watch!
We released quantized checkpoints for LFM2-VL-450M and LFM2-VL-1.6B on @huggingface pic.twitter.com/DfK3p1MA08LFM2-VL support with GGUF and llama.cpp You can now run these tiny, hyper-efficient VLMs on your watch! We released quantized checkpoints for LFM2-VL-450M and LFM2-VL-1.6B on @huggingface
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JAX adoption challenges: GPU and TPU experience insights
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the jax topic didn't even come to my table (I'm also out on leave). afaik the biggest pushback to using jax came from msl folks who had to use jax+gpus in their previous place of employment and didn't think it was great on a few important dimensions.
the jax+tpus experience -
Moderna and IBM Partner on Quantum Computing for mRNA Drug Design
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Breakthrough: @moderna_tx and @IBM are teaming up to supercharge mRNA drug design using quantum computing. By leveraging variational quantum algorithms (VQAs), they’re tackling the challenge of predicting #mRNA secondary structures—key to accelerating next-gen therapies.
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AI Model Training Energy Requirements Forecasted by Epoch
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A whitepaper from Epoch AI, a company that tracks AI trends, and the Electric Power Research Institute attempts to forecast the energy that will be required to build future AI models.
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Quantum Machine Learning and Optimization in Finance Book
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Get future-ready with this book >> "Quantum #MachineLearning and Optimization in #Finance" (494 pages; 2nd Edition): http://
amzn.to/4lNlBt5 v/ @PacktDataML ————
#DataScientist #DataScience #AI #ML #ORMS #QuantumComputing #ComputationalScience #Fintech #CFO #CTO #Startup -
Machine Learning for Streaming Data with Python Online Solutions
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#MachineLearning for Streaming Data with #Python — build practical online Machine Learning solutions: http://
amzn.to/40ztysN
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#DataScience #ML #AI #StreamAnalytics #EdgeComputing #Edge #EdgeAI #TimeSeries #IoT #IIoT #DataScientist #AnomalyDetection -
SLMs offer efficiency; LLMs require massive resources. Keep improving.
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clean point, slms got that efficiency while llms need a whole server farm to stretch, keep stacking those gains