The article discusses the growing disconnect between clinical practice and AI research in healthcare, emphasizing the lack of clinician participation and collaboration. It highlights the need for a practical approach in identifying actual problems and evaluating if AI can develop better solutions in healthcare.
AI experimenters have quickly taken advantage of three early Mickey Mouse cartoons entering the public domain in the US, using an AI model trained on those cartoons to create new still images of Mickey Mouse, Minnie Mouse, and Peg Leg Pete. While the results are sometimes garbled, this early experimentation showcases the potential of integrating public domain characters into the AI space.
Boost the performance of supervised fine-tuned models using Reinforcement Learning from Human Feedback (RLHF) to address biases and toxicity. NeuralHermes-2.5, fine-tuned using Direct Preference Optimization (DPO), significantly improves base model performance on the Open LLM Leaderboard.
The article explores how the Python package mlscorecheck can be used to test the consistency of reported machine learning performance scores and experimental setups. The mlscorecheck package provides numerical techniques to determine if the reported scores could be the result of the claimed experiment.
Recent research explores how decision trees and random forests, commonly used in machine learning, suffer from bias due to the assumption of continuity in features. The study proposes simple techniques to mitigate this bias, with findings showing a 0.2 percentage point deterioration in performance when attributes are mirrored.
This article explores acceleration techniques in neural networks, emphasizing the need for faster training due to the complexity of deep learning models. It introduces the concept of gradient descent and highlights the limitations of its slow convergence rate. The article then introduces Momentum as an optimization algorithm that uses an exponentially moving average to achieve faster convergence.
2024 could be the tipping point for Music AI, with breakthroughs in text-to-music generation, music search, and chatbots. However, the field still lags behind Speech AI, and advancements in flexible and natural source separation are needed to revolutionize music interaction through AI.
Principal component analysis (PCA) is a complex technique used for dimensionality reduction, with two main techniques: classical and non-classical. The article discusses the challenges of implementing PCA using the classical technique and demonstrates a C# implementation on a subset of the Iris Dataset.
Learn how to create zoom plots in matplotlib to enhance data visualization, focusing on rainfall data from Texas. This tutorial provides a code-oriented approach, highlighting the little shower, big rainstorm, and light precipitation events.
Build your own voice-activated coding assistant using an open-source Large Language Model (LLM) like HuggingFace. This project allows you to interact vocally with the LLM while keeping your work private.
The article demonstrates how to implement an ArgSort() function using the C# language, providing code examples for both arrays and lists. It highlights the availability of a C# Array.Sort(a,b) overload that allows sorting based on values in an array.
The article discusses the author's student project on forecasting crop yield and crop price using various statistical methods, emphasizing the importance of choosing a topic of interest. The project received a high score and the author provides tips for starting a successful project, including conducting a literature review.
The article discusses the author's implementation of matrix inverse using QR decomposition and highlights the different algorithms and variations involved in computing the inverse of a matrix. The demo showcases the computation of a 4x4 matrix's inverse and verifies the result by multiplying it with the original matrix to obtain the identity matrix.
The article discusses the importance of project prioritization in the analytics world and suggests using a mental model to make better decisions. It emphasizes the risks associated with projects and the need to consider impact and time constraints when prioritizing.
Gaussian splatting is a fast and interpretable method for representing 3D scenes without neural networks, gaining popularity in a world obsessed with AI models. It uses 3D points with unique parameters to closely match renders to known dataset images, offering a refreshing alternative to complex and opaque methods like NeRF.