Meet Denario — An AI Assistant for Every Step of the Scientific Process
simonsfoundation.org·2d
🤖AI Curation
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Gemini Deep Research comes to Google Finance, backed by prediction market data
arstechnica.com·1h
🤖AI Curation
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From a Curious Outsider to a GreptimeDB Advocator Journey into Contribution
greptime.com·1d·
Discuss: Hacker News
🧬Bitstream Evolution
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TypeScript’s rise in the AI era: Insights from Lead Architect, Anders Hejlsberg
github.blog·5h·
Discuss: Hacker News
🔄Language Evolution
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Context Engineering with Real-Time, Processed Data
confluent.io·1d·
Discuss: Hacker News
🌊Streaming Systems
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The Learning Loop and LLMs
martinfowler.com·2d·
🧩WASM Components
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Create flashcards and quizzes in the NotebookLM app.
blog.google·5h
🏛Digital humanities
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From the depths to discovery: Tiny limpet reveals big secrets of the deep sea
phys.org·7h
🦴Binary Paleontology
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Automated Discovery of Conservation Laws via Hybrid Neural ODE-Transformers
arxiv.org·2d
🌀Differential Geometry
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Automated Sentiment-Driven Resource Allocation for Community Resilience Planning
dev.to·2d·
Discuss: DEV
🎛️Feed Filtering
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Jensen Huang Gets It Wrong
oreilly.com·11h
🌍Cultural Algorithms
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Bio-Inspired Neuron Synapse Optimization for Adaptive Learning and Smart Decision-Making
arxiv.org·2d
🧠Neural Codecs
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KGBridge: Knowledge-Guided Prompt Learning for Non-overlapping Cross-Domain Recommendation
arxiv.org·1d
🎯Content Recommendation
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Accelerated Dielectric Barrier Coating Optimization via Multi-Modal Data Fusion & Bayesian Hyperparameter Tuning
dev.to·3d·
Discuss: DEV
🧠Machine Learning
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Building an AI-Powered Recipe Assistant with Agentic Postgres: A Deliciously Data-Driven Adventure 🍳🤖
dev.to·2d·
Discuss: DEV
🧮Algorithmic Cooking
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Tech With Tim: 3 Unique Python Features You NEED To Know
dev.to·1d·
Discuss: DEV
🌀Brotli Internals
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We Tested 6 AI Models on 3 Advanced Security Exploits: The Results
dev.to·10h·
Discuss: DEV
🔒WASM Capabilities
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Augmenting learning in neuro-embodied systems through neurobiological first principles
arxiv.org·2d
🔲Cellular Automata
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A Comparative Analysis of LLM Adaptation: SFT, LoRA, and ICL in Data-Scarce Scenarios
arxiv.org·2d
💻Local LLMs
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