Show HN: PyNIFE. 400-900× speedup for embedding-based retrieval pipelines
github.com·22h·
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alright so learned the most used and imp terms in ai space (from @gkcs_)
threadreaderapp.com·18h
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Charting the future of AI, from safer answers to faster thinking
news.mit.edu·3d
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Physics as Code: Train AI with Differentiable Simulations
dev.to·35m·
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Show HN: Alignmenter – Measure brand voice and consistency across model versions
alignmenter.com·3h·
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Predictive Modeling of Dendritic Cell Maturation via Multimodal Integration
dev.to·3h·
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Robust Layerwise Scaling Rules by Proper Weight Decay Tuning
paperium.net·9h·
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Preventing AI Project Failures Through Effective Prompt Engineering
launchdarkly.com·16h·
Discuss: DEV
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Presentation: Achieving Precision in AI: Retrieving the Right Data Using AI Agents
infoq.com·2d
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Dynamic Adaptive Risk Assessment for Remote Autonomous Ship Control Utilizing Bayesian Federated Learning
dev.to·1h·
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BitNetMCU with CNN: >99.5% MNIST accuracy on a low-end Microcontroller
cpldcpu.com·5h
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AI Explained for Beginners: Prompt, Agent, MCP & Function Calling
dev.to·11h·
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50 % smaller LLM same PPL, experimental architecture
reddit.com·1d·
Discuss: r/LLM
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A Guide to the Best Java Machine Learning Libraries
dev.to·3d·
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As we delve into the realm of quantum machine learning (QML)
dev.to·8h·
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Evaluating Synthetic Data — The Million Dollar Question
towardsdatascience.com·2d
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Mathematicians Unveil a Smarter Way to Predict the Future
scitechdaily.com·11h
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Using Knowledge Elicitation Techniques To Infuse Deep Expertise And Best Practices Into Generative AI
forbes.com·19h
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**Practical Tip: Fine-Tuning LLMs for Improved Generalizabil
dev.to·1d·
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Continuous Autoregressive Language Models
shaochenze.github.io·5d·
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