Microsoft's Orca-2 LLM is a significant development, showcasing the possibility of creating effective, small, fine-tuned language models. The use of synthetic training data generated by other LLMs is a fascinating concept with significant implications for the future.
Generative AI has unlocked potential in AI, including text generation and code generation. One area evolving is using NLP to generate SQL queries, making data analysis more accessible to non-technical users.
Discover how to achieve parameter efficiency in finetuning with LoRA, including strategies for adapting linear modules and optimizing learning rates. This article explores the deliberate design decisions that can enhance model performance, GPU memory utilization, and training speed, offering a nuanced understanding and greater control.
Pedro Soares, aka Blendeered, showcases his stunning NVIDIA-themed New Year's celebration animation, highlighting the power of technological innovation and NVIDIA Studio's impact on content creation. Using Blender and the NVIDIA GeForce RTX 4090 GPU, Blendeered creates a futuristic city scene with real-time rendering, OptiX ray tracing, and AI-powered tools like NVIDIA Canvas.
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.
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.
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.
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.