Generative AI models like Claude 2 and Llama 2 can perform tasks on text data, but what about multimodal data? This article presents a solution using Amazon Titan Multimodal Embeddings model and LLaVA 1.5 to perform generative tasks on text and visual elements, including tables and graphs, in slide decks.
The article in Microsoft Visual Studio Magazine discusses the implementation of matrix inverse using the Householder version of the QR algorithm in C#. The demo includes a small matrix example and verifies the result by computing the inverse multiplied by the original matrix.
This article provides a hands-on tutorial using Facebook Prophet for time series analysis, aimed at removing entry barriers. Prophet is an open-source tool by Facebook that produces accurate time series forecasts with ease, making it ideal for business applications.
The article explores the math behind the Adam optimizer, explaining why it is the most popular optimizer in deep learning. It delves into the mechanics of Adam, highlighting its adaptive learning rates and its ability to adjust its step size based on the complexity of the data.
A data science associate used NLP techniques to analyze Reddit discussions on depression, exploring gender-related taboos around mental health. They found that zero-shot classification can easily produce similar results to traditional sentiment analysis, simplifying the process and eliminating the need for a training dataset.
ChatGPT is leaking private conversations, including login credentials and personal details, as revealed by screenshots. The leaked information involves usernames and passwords linked to a pharmacy prescription drug portal's support system, highlighting serious security concerns.
OpenAI and Common Sense Media have joined forces to create AI guidelines and educational materials for parents, educators, and teens, including family-friendly GPTs in OpenAI's GPT store. Common Sense Media aims to help teens and families safely utilize AI, expanding from their reviews of films and TV shows to AI assistants.
The article discusses the challenges of implementing matrix inversion code and presents a demo of four different C# functions using various algorithms. The author emphasizes the complexity and flexibility of the LUP, QR, and SVD algorithms, as well as the specific use case of the Cholesky algorithm.
Learn how to create and style inset axes in matplotlib with this tutorial, which covers 4 methods for creating insets and 2 ways to style zoom insets using leader lines or color-coded overlays. The tutorial also introduces the outset library for multi-scale data visualization.
Unlocking Performance: Benchmarking and Optimizing Endpoint Deployment in Amazon SageMaker JumpStart
This article explores the complex relationship between latency and throughput when deploying large language models (LLMs) using Amazon SageMaker JumpStart. Benchmarking of LLMs like Llama 2, Falcon, and Mistral variants reveals the impact of model architecture, serving configurations, instance type hardware, and concurrent requests on performance.
Developers of open world video games and analytics managers both face the challenge of balancing exploration and exploitation. To solve this tension, they can build alternative paths, offer knowledge management systems, foster online communities, and make continuous improvements. Salespeople, like gamers, have main quests in the form of specific metrics they need to track, so creating simple an...
This article explores methods for creating fine-tuning datasets to generate Cypher queries from text, utilizing large language models (LLMs) and a predefined graph schema. The author also mentions an ongoing project that aims to develop a comprehensive fine-tuning dataset using a human-in-the-loop approach.
MIT scientists have developed two machine-learning models, the "PRISM" neural network and a logistic regression model, for early detection of pancreatic cancer. These models outperformed current methods, detecting 35% of cases compared to the standard 10% detection rate.
MIT neuroscientists have discovered that sentences with unusual grammar or unexpected meaning generate stronger responses in the brain's language processing centers, while straightforward sentences barely engage these regions. The researchers used an artificial language network to predict the brain's response to different sentences.
Atacama Biomaterials, a startup combining architecture, machine learning, and chemical engineering, develops eco-friendly materials with multiple applications. Their technology allows for the creation of data and material libraries using AI and ML, producing regionally sourced, compostable plastics and packaging.