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Reinforcement Learning Triples Spot’s Running Speed

Flipboard

The gait is not biological, but the robot isnt biological, explains Farbod Farshidian , roboticist at the RAI Institute. The best Farshidian can categorize how Spot is moving is that its somewhat similar to a trotting gait, except with an added flight phase (with all four feet off the ground at once) that technically turns it into a run.

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AI for Universal Audio Understanding: Qwen-Audio Explained

AssemblyAI

This approach eliminates the scalability constraints of prior models, such as the need for manual task categorization or reliance on dataset identifiers during training, aimed at preventing a one-to-many interference problem , typical of multi-task training scenarios.

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Can CatBoost with Cross-Validation Handle Student Engagement Data with Ease?

Towards AI

This story explores CatBoost, a powerful machine-learning algorithm that handles both categorical and numerical data easily. CatBoost is a powerful, gradient-boosting algorithm designed to handle categorical data effectively. CatBoost automatically transforms them, making it ideal for datasets with many categorical variables.

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One-Way ANOVA vs. Two-Way ANOVA: Key Differences Explained

Pickl AI

Summary: This blog explains the differences between one-way ANOVA vs two-way ANOVA, their definitions, assumptions, and applications. Step 3: Organise Your Data Structure your data with: One categorical independent variable (e.g., Step 3: Organise Your Data Set up your dataset with: Two categorical independent variables (e.g.,

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SEC’s climate disclosure rule proposal explained

IBM Journey to AI blog

Scope 3 emissions disclosure Envizi’s Scope 3 GHG Accounting and Reporting module enables the capture of upstream and downstream GHG emissions data, calculates emissions using a robust analytics engine and categorizes emissions by value chain supplier, data type, intensities and other metrics to support auditability.

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HARPA AI Review: How I Finally Tamed My Tab Overload

Unite.AI

The way it categorizes incoming emails automatically has also helped me maintain that elusive “inbox zero” I could only dream about. It also supports 18 different writing styles categorized into four groups. It explains why something might need changing! But it doesn't just flag issues.

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Amazon AI Introduces DataLore: A Machine Learning Framework that Explains Data Changes between an Initial Dataset and Its Augmented Version to Improve Traceability

Marktechpost

Additionally, by displaying the potential transformations between several tables, DATALORE’s LLM-based data transformation generation can substantially enhance the return results’ explainability, particularly useful for users interested in any connected table. Check out the Paper. Also, don’t forget to follow us on Twitter.