https://
dev-discuss.pytorch.org/t/using-nsight
-systems-to-profile-gpu-workload/59
… by @ptrblck_de https://
dev-discuss.pytorch.org/t/rfc-performa
nce-profiling-at-scale-with-detailed-nvtx-annotations/2224
…
MACHINE LEARNING
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GPU Workload Profiling with PyTorch and NVTX Annotations
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Fine-tuning Flux LoRA for PS1 video game style
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Some first tests with making a flux kontext lora for a PS1 style. I used face to many to make a dataset with 12 image pairs. Example: https://
replicate.com/p/z2e7ern65hrm
c0cqqd4vmrkqjg
… I used the fal trainer at 1000 steps ($2.50), took about 20 mins. Prompt:
"make it a ps1 video game" Left: Pro
Right: -
New Mathematics of Machine Learning Book Release Available Now
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New release, now available! Mathematics of Machine Learning Order here: https://
packtpub.com/en-us/product/
mathematics-of-machine-learning-9781837027873?utm_medium=affiliate&utm_campaign=e1397f0b-52c9-8731-1019-60b63c72c74a&utm_term=5b056f65-afab-5c56-1f0a-5fd88167b4b5&utm_content=B32104
… via @PacktDataML #ad ——————
#DataScientist #DataScience #AI #ML #MachineLearning #Calculus #Probability #LinearAlgebra #Mathematics -
Key AI Researchers and Contributors in Machine Learning
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just off the top of my head: yann lecun, leon bottou, andrew tulloch, horace he, alban desmaison, edward yang
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Building a Responsible AI-Ready Workforce for the Future
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Building a responsible AI-ready workforce for the future
#AI #AIio #AIInnovation #ML #DataScience #Futureofwork @timnitgebru @oriolvinyalsml @ceobillionaire @soumithchintala @waitin4agi_ @sallyeaves @bernardmarr -
Model Weights File Formats in Machine Learning: Storage and Deployment
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Model Weights File Formats in Machine Learning Model weights matter more than ever as AI scales. From storing and sharing to deploying trained models across platforms, file formats like .pt, .ckpt, .h5, and more ensure reproducibility and performance. Check out our blog to
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AI as Scientific Co-Creator Pushing Research Boundaries
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At the cutting edge, AI is already being used in scientific research to push the boundaries of what we thought was possible. It’s not just an assistant anymore – it’s becoming a co-creator. And as that loop between human ingenuity and machine capability tightens, the ceiling on… pic.twitter.com/gnqaYXbcBJ
— Nina Schick (@NinaDSchick) 28 juin 2025At the cutting edge, AI is already being used in scientific research to push the boundaries of what we thought was possible. It’s not just an assistant anymore – it’s becoming a co-creator. And as that loop between human ingenuity and machine capability tightens, the ceiling on
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Inhibitory Neurons in Biological vs Artificial Neural Networks
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3/ ANNs model excitatory neurons. But there also exist inhibitory neurons! These reduce the likelihood of firing. We don't model inhibitory neurons in typical artificial NNs. Glutamate is the neurotransmitter involved in excitatory processes, and GABA for inhibitory ones.
→ View original post on X — @petitegeek, 2025-06-28 14:21 UTC
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Human Brain Dynamics: Feedback Loops Beyond Feed-Forward Neural Networks
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2/ The human brain is not a purely feed-forward network like an ANN. It's a dynamical system with feedback loops. For instance, a seizure involves a cycle of uncontrolled activation, which afaik can't happen in your typical ANN
→ View original post on X — @petitegeek, 2025-06-28 14:21 UTC
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Temporal Synchronization in Biological vs Artificial Neural Networks
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1/ In humans, the timing of input into a neuron matters. If you have two action potentials entering a soma, arriving at the same time could cause it to fire. BUT the same inputs with some delay between each other might not. In a typical artificial NN, timing doesn't matter.
→ View original post on X — @petitegeek, 2025-06-28 14:21 UTC