Large language model
Chase Dimond shares his journey to earning over 7 figures with a services agency, specifically an email marketing agency, advocating it as the best business model for beginners due to low startup costs, high demand, easy fulfillment, and high profit margins. He outlines four steps to success: choosing your service, building a notable track record,…
Lincoln Laboratory is working to reduce the energy requirements of AI models by promoting energy usage transparency and improving training efficiency.
This guide provides over 50 customizable AI-generated prompts for creating line art coloring book pages using Midjourney, Stable Diffusion, and DALL-E. The prompts span various themes suitable for both children and adults and are designed to output clean, thick-outlined images ideal for coloring. Tips for prompt adjustments and negative prompts are included for optimal results.
Artificial Intelligence, with advancements like GPT-4, has evolved into multimodal AI, integrating text, images, audio, and video for a holistic understanding akin to human perception. This allows for more accurate predictions and nuanced interactions across applications such as customer service, social media analysis, and training, significantly enriching AI’s interface with everyday life.
A study involving 32 papers reviewed the application of explainable AI in poverty estimation using satellite imagery and deep learning. It found that transparency, interpretability, and domain knowledge—key elements of explainable machine learning—vary and often fall below the necessary scientific standards for accurate insights into poverty and welfare.
The blog post introduces PyTorch, a key deep learning library used for creating and operating on tensors, the core components for neural network modeling. It provides a beginner-friendly guide on tensor properties and operations, like addition and multiplication, and connects tensor manipulation to deep learning application. It mentions resources for further learning, including a free…
Deep Learning advancements in AI, specifically in SLAM technology, have been made by University College London researchers with DSP-SLAM. This system accurately maps environments and tracks camera movement, utilizing object shape and pose estimation to improve scene representation significantly. It performs well across multiple input types and has excelled in reconstructing objects in tests.
Duck AI’s DuckTrack is an advanced tool for tracking user interactions, vital for training intelligent systems. It records various inputs including mouse and keyboard actions and integrates with major operating systems. While it faces challenges with double clicks and trackpad gestures, the tool excels in precision and is constantly improved through community participation. DuckTrack demonstrates…
Explore regularization methods to enhance Neural Network performance and avoid overfitting. Read more at Towards Data Science.
A sociologist highlights the ethical implications of machine learning in healthcare, criticizing United Healthcare’s use of AI to prematurely discharge patients, focused on cost savings rather than patient care. The AI model, influenced by economic incentives, risks life and quality of life, leading to unethical healthcare decisions and potential malpractice by ignoring doctors’ expertise.
Instead of fully retraining large language models (LLMs) for different tasks, LoRA adapters can be fine-tuned, allowing cost-effective task-specific adaptations. A novel approach described in the article enables combining multiple LoRA adapters to create a versatile adapter for multitasking, such as both chatting and translating, using a single LLM with a simple process of weighted…
This article provides data engineering interview preparation tips, covering common questions and answers. It highlights the importance of research, familiarity with data platform architecture types, coding skills, demonstrating confidence with DE tools, and knowledge of ETL. Scenario-based questions are typical, and demonstrating clear, methodical thinking is key.
EPFL and Apple researchers developed PaSS, a method enhancing language model efficiency by generating multiple tokens in parallel using one model. The approach speeds up generation by up to 30%, maintains model quality, and optimizes token predictability. Future work aims to refine this method with look-ahead tokens.
Amazon SageMaker Canvas now features extensive data preparation tools from SageMaker Data Wrangler, offering an intuitive no-code solution for data professionals to prepare data, build, and deploy machine learning models without coding. Users can import from 50+ sources, use 300+ built-in analyses, and balance datasets using natural language commands. This integration streamlines the journey from…
Large Language Models (LLMs) are influential tools in various applications such as conversational agents and content generation. Responsible and robust evaluation of these models is essential to prevent misinformation and bias. Amazon SageMaker Clarify simplifies LLM evaluation by integrating with SageMaker Pipelines, enabling scalable and efficient model assessments using structure configurations. Users, including model providers,…
Mira Murati is appointed CTO, while Greg Brockman reassumes the position of President. CEO Sam Altman and board chair Bret Taylor have released messages regarding these changes.
Researchers at UCSF compare human auditory processing with Deep Neural Networks (DNNs), revealing DNNs closely mimic brain responses to speech. They focus on cross-linguistic analyses, discovering that unsupervised learning in DNNs captures language-specific patterns. These findings outperform traditional models, offering insights into both neuroscientific processes and AI interpretability.
SageMaker’s new ‘smart sifting’ feature filters less informative data during training, potentially reducing deep learning model training costs by up to 35%. This online data sifting process requires no changes to existing training pipelines and aims to maintain model accuracy while improving cost-efficiency.
OpenAI’s GPT-4V(ision) sets the benchmark as a multimodal AI, processing text and images with advanced features like visual data interpretation and code writing. Accessible via GPT-Plus subscription and API waitlist, it enhances various domains but has limitations such as potential errors and bias. Users must ensure validation and consider privacy concerns.
MIT and Meta AI researchers developed a real-time object reorientation controller using a depth camera. This AI system efficiently manipulates diverse objects and generalizes to new shapes, indicating promising future applications in robotics. The controller is trained via reinforcement learning for direct real-world application, showing potential for precision improvement without added assumptions.