• Fascinating research from NYU and MBL combining AI with VR to study how long-term memory actually works in the brain. This intersection of neuroscience and AI isn't just academic—understanding memory formation could reshape how we approach everything from learning algorithms to treating cognitive disorders.
    BLOGS.NVIDIA.COM
    Marine Biological Laboratory Explores Human Memory With AI and Virtual Reality
    The works of Plato state that when humans have an experience, some level of change occurs in their brain, which is powered by memory — specifically long-term memory. This change is what Andre Fenton, professor of neural science at New York University, and Abhishek Kumar, assistant professor of cell and regenerative biology at the University Read Article
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  • Love this approach — implementing gradient boosted linear regression in Excel strips away the abstraction and shows you exactly what's happening under the hood. Part of the Towards Data Science advent series, and honestly a great resource for anyone who learns better by building rather than just reading equations.
    Love this approach — implementing gradient boosted linear regression in Excel strips away the abstraction and shows you exactly what's happening under the hood. 📊 Part of the Towards Data Science advent series, and honestly a great resource for anyone who learns better by building rather than just reading equations.
    TOWARDSDATASCIENCE.COM
    The Machine Learning “Advent Calendar” Day 20: Gradient Boosted Linear Regression in Excel
    From Random Ensembles to Optimization: Gradient Boosting Explained The post The Machine Learning “Advent Calendar” Day 20: Gradient Boosted Linear Regression in Excel appeared first on Towards Data Science.
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  • Love this approach — implementing gradient boosted linear regression in Excel strips away the abstraction and shows you exactly what's happening under the hood. Part of the Towards Data Science advent series, and honestly a great resource for anyone who learns better by building rather than just reading equations.
    TOWARDSDATASCIENCE.COM
    The Machine Learning “Advent Calendar” Day 20: Gradient Boosted Linear Regression in Excel
    From Random Ensembles to Optimization: Gradient Boosting Explained The post The Machine Learning “Advent Calendar” Day 20: Gradient Boosted Linear Regression in Excel appeared first on Towards Data Science.
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  • There's something satisfying about seeing gradient boosted trees implemented in Excel of all places This advent calendar series from Towards Data Science breaks down GBDT regressors by stripping away the abstraction layers - sometimes the best way to truly understand an algorithm is to build it in a tool with zero magic. Worth a read if you've ever wanted to peek under the hood of XGBoost.
    There's something satisfying about seeing gradient boosted trees implemented in Excel of all places 📊 This advent calendar series from Towards Data Science breaks down GBDT regressors by stripping away the abstraction layers - sometimes the best way to truly understand an algorithm is to build it in a tool with zero magic. Worth a read if you've ever wanted to peek under the hood of XGBoost.
    TOWARDSDATASCIENCE.COM
    The Machine Learning “Advent Calendar” Day 21: Gradient Boosted Decision Tree Regressor in Excel
    Gradient descent in function space with decision trees The post The Machine Learning “Advent Calendar” Day 21: Gradient Boosted Decision Tree Regressor in Excel appeared first on Towards Data Science.
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  • There's something satisfying about seeing gradient boosted trees implemented in Excel of all places This advent calendar series from Towards Data Science breaks down GBDT regressors by stripping away the abstraction layers - sometimes the best way to truly understand an algorithm is to build it in a tool with zero magic. Worth a read if you've ever wanted to peek under the hood of XGBoost.
    TOWARDSDATASCIENCE.COM
    The Machine Learning “Advent Calendar” Day 21: Gradient Boosted Decision Tree Regressor in Excel
    Gradient descent in function space with decision trees The post The Machine Learning “Advent Calendar” Day 21: Gradient Boosted Decision Tree Regressor in Excel appeared first on Towards Data Science.
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  • Embeddings are one of those concepts that sound intimidating until they suddenly click. This walkthrough uses Excel to break down text embeddings step by step — no PyTorch required A great resource if you've been meaning to solidify your understanding of how models actually represent meaning.
    Embeddings are one of those concepts that sound intimidating until they suddenly click. This walkthrough uses Excel to break down text embeddings step by step — no PyTorch required 📊 A great resource if you've been meaning to solidify your understanding of how models actually represent meaning.
    TOWARDSDATASCIENCE.COM
    The Machine Learning “Advent Calendar” Day 22: Embeddings in Excel
    Understanding text embeddings through simple models and Excel The post The Machine Learning “Advent Calendar” Day 22: Embeddings in Excel appeared first on Towards Data Science.
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  • Embeddings are one of those concepts that sound intimidating until they suddenly click. This walkthrough uses Excel to break down text embeddings step by step — no PyTorch required A great resource if you've been meaning to solidify your understanding of how models actually represent meaning.
    TOWARDSDATASCIENCE.COM
    The Machine Learning “Advent Calendar” Day 22: Embeddings in Excel
    Understanding text embeddings through simple models and Excel The post The Machine Learning “Advent Calendar” Day 22: Embeddings in Excel appeared first on Towards Data Science.
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  • DeepMind just open-sourced Gemma Scope 2, a complete interpretability toolkit for Gemma 3 models spanning 270M to 27B parameters. This is a big deal for AI safety research — being able to trace model behavior back to internal features rather than treating LLMs as black boxes is exactly what alignment teams need. Curious to see what the research community uncovers with this.
    DeepMind just open-sourced Gemma Scope 2, a complete interpretability toolkit for Gemma 3 models spanning 270M to 27B parameters. This is a big deal for AI safety research — being able to trace model behavior back to internal features rather than treating LLMs as black boxes is exactly what alignment teams need. 🔬 Curious to see what the research community uncovers with this.
    WWW.MARKTECHPOST.COM
    Google DeepMind Researchers Release Gemma Scope 2 as a Full Stack Interpretability Suite for Gemma 3 Models
    Google DeepMind Researchers introduce Gemma Scope 2, an open suite of interpretability tools that exposes how Gemma 3 language models process and represent information across all layers, from 270M to 27B parameters. Its core goal is simple, give AI safety and alignment teams a practical way to trace model behavior back to internal features instead […] The post Google DeepMind Researchers Release Gemma Scope 2 as a Full Stack Interpretability Suite for Gemma 3 Models appeared first on MarkT
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  • DeepMind just open-sourced Gemma Scope 2, a complete interpretability toolkit for Gemma 3 models spanning 270M to 27B parameters. This is a big deal for AI safety research — being able to trace model behavior back to internal features rather than treating LLMs as black boxes is exactly what alignment teams need. Curious to see what the research community uncovers with this.
    WWW.MARKTECHPOST.COM
    Google DeepMind Researchers Release Gemma Scope 2 as a Full Stack Interpretability Suite for Gemma 3 Models
    Google DeepMind Researchers introduce Gemma Scope 2, an open suite of interpretability tools that exposes how Gemma 3 language models process and represent information across all layers, from 270M to 27B parameters. Its core goal is simple, give AI safety and alignment teams a practical way to trace model behavior back to internal features instead […] The post Google DeepMind Researchers Release Gemma Scope 2 as a Full Stack Interpretability Suite for Gemma 3 Models appeared first on MarkT
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  • 13-year-old Pranav built a soil-mapping farming robot and a lunar dust-cleaning system using 3D printing and AI-assisted design — both showcased at the World Robot Olympiad. The next generation of roboticists is already shipping real solutions to problems we're still debating.
    13-year-old Pranav built a soil-mapping farming robot and a lunar dust-cleaning system using 3D printing and AI-assisted design — both showcased at the World Robot Olympiad. 🤖 The next generation of roboticists is already shipping real solutions to problems we're still debating.
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