Nvidia released Chat With RTX, a personalized AI chatbot that runs on PCs with Nvidia RTX graphics cards, using Mistral or Llama open-weights LLMs to search and answer questions about local files. This setup enables conversations with the AI model using local files as a dataset, providing quick and contextually relevant answers.
Amazon SageMaker Canvas provides a no-code interface for domain experts to create powerful analytics and ML models, addressing the skillset dilemma in data-driven decision-making. This post demonstrates how SageMaker Canvas can be used for anomaly detection in the manufacturing industry, helping to identify malfunctions or unusual operations of industrial machines.
Google has released Gemini Pro 1.5, a new AI language model that uses less compute power but achieves comparable quality to its predecessor, Ultra 1.0. This comes just a week after the launch of Ultra 1.0, which was touted as a key feature of Google's Gemini Advanced tier subscription service.
This article discusses the importance of high-quality data and reducing labeling errors in pose estimation models. It demonstrates how a custom labeling workflow in Amazon SageMaker Ground Truth can streamline the labeling process and minimize errors, ultimately reducing the cost of obtaining accurate pose labels.
Generative AI solutions are revolutionizing industries by understanding natural language, automating processes, and enhancing customer experiences. Amazon Bedrock offers a comprehensive platform for personalized generative AI applications, utilizing prompt engineering techniques to optimize user inputs and improve efficiency.
Broadcom's recent changes include layoffs, discontinuing perpetually licensed versions of VMware products, and ending partner programs. Now, they are discontinuing the free version of VMware's ESXi hypervisor, impacting home users.
OpenAI is testing a new feature for ChatGPT that allows it to remember details between conversations, enhancing its long-term memory capabilities. This experimental feature is currently available to a limited number of users, aiming to improve the model's context retention beyond a session.
MIT researchers have developed a solution called StreamingLLM that prevents chatbots like ChatGPT from collapsing during long conversations, allowing for efficient AI assistants. By tweaking the key-value cache, the method enables the chatbot to maintain a nonstop conversation, making it 22 times faster than alternative methods.
The article discusses the implementation of the matrix inverse function using the LUP algorithm, with a focus on removing nested helper functions for improved efficiency. It also mentions interesting tradeoffs between using nested functions and straight code.
Unknown attackers are targeting hundreds of Microsoft Azure accounts, including those of senior executives, in a campaign to steal sensitive data and financial assets from organizations. The attackers are using personalized phishing lures and shared documents to compromise the accounts of individuals with various roles and responsibilities.
Booking.com collaborated with AWS Professional Services to use Amazon SageMaker and modernize their ML infrastructure, reducing wait times for model training and experimentation, integrating essential ML capabilities, and reducing the development cycle for ML models. This improved their search experience and benefited millions of travelers worldwide.
Several companies showcased AI-related ads at Super Bowl LVIII, including Microsoft, which highlighted its AI assistant, Copilot, in a commercial emphasizing its ability to solve various problems and empower individuals. The ad features defiant text overlaid on scenes of people overcoming obstacles, with Copilot generating solutions like creating storyboard images and writing code.
This article explores the challenge of unobserved confounding in observational studies and the importance of sensitivity analysis. It presents a simple linear method to assess the impact of unobserved confounders on estimates. The results highlight the potential bias in model estimates and the need to consider unobserved confounding when interpreting findings.
Discover how transformers and topic modeling can help interpret and understand the semantic structures of big data. Explore the operational definitions of topics and the spatial definition of semantics, and see their practical application in a case study.
The article discusses the evolution of GPT models, specifically focusing on GPT-2's improvements over GPT-1, including its larger size and multitask learning capabilities. Understanding the concepts behind GPT-1 is crucial for recognizing the working principles of more advanced models like ChatGPT or GPT-4.