LM Studio is a tool that allows local machine usage of large language models like GPT-x, LLaMA-x, and Orca-x, offering a clean and intuitive UI for exploring models and conducting reasoning tasks. However, its creator and potential connections with other companies remain unclear.
LLMs like Llama 2, Flan T5, and Bloom are essential for conversational AI use cases, but updating their knowledge requires retraining, which is time-consuming and expensive. However, with Retrieval Augmented Generation (RAG) using Amazon Sagemaker JumpStart and Pinecone vector database, LLMs can be deployed and kept up to date with relevant information to prevent AI Hallucination.
NVIDIA celebrates milestone with 500 RTX games and applications, revolutionizing gaming graphics and performance. Ray tracing and DLSS technologies have transformed visual fidelity and boosted performance in titles like Cyberpunk 2077 and Minecraft RTX.
The US Federal Trade Commission warns against QR code scams that can take control of smartphones, make fraudulent charges, or obtain personal information. Scammers are targeting QR codes on parking lot kiosks, leading to look-alike sites that funnel funds to fraudulent accounts.
The rise of AI-powered text-to-image generation has resulted in a flood of low-quality images, causing skepticism and misdirection. However, a new phenomenon of AI-powered text-to-CAD generation has emerged, with major players like Autodesk, Google, OpenAI, and NVIDIA leading the way.
Summarization is essential in our data-driven world, saving time and improving decision-making. It has various applications, including news aggregation, legal document summarization, and financial analysis. With advancements in NLP and AI, techniques like extractive and abstractive summarization are becoming more accessible and effective.
Spectral clustering is a complex machine learning technique that uncovers patterns in data. Implementing it involves computing affinity and Laplacian matrices, eigenvector embeddings, and performing k-means clustering.
Mistral AI announces Mixtral 8x7B, an AI language model that matches OpenAI's GPT-3.5 in performance, bringing us closer to having a ChatGPT-3.5-level AI assistant that can run locally. Mistral's models have open weights and fewer restrictions than those from OpenAI, Anthropic, or Google.
GeForce NOW adds 17 new games, including The Day Before and Avatar: Frontiers of Pandora, with over 500 games now supporting RTX ON. Ultimate members can experience cinematic ray tracing and stream at up to 4K resolution, while Priority members can build and survive at 1080p and 60fps.
Mathew Schwartz, an assistant professor at the New Jersey Institute of Technology, is using NVIDIA Omniverse and OpenUSD to help designers address the challenge of accessibility in building design. Schwartz's team developed open-source code that generates a complex accessibility graph, providing feedback on human movement and energy expenditure. With Omniverse, designers can visualize the graph...
Vodafone is transforming into a TechCo by 2025, with plans to have 50% of its workforce involved in software development and deliver 60% of digital services in-house. To support this transition, Vodafone has partnered with Accenture and AWS to build a cloud platform and engaged in an AWS DeepRacer challenge to enhance their machine learning skills.
Getir, the ultrafast grocery delivery pioneer, has implemented an end-to-end workforce management system using Amazon Forecast and AWS Step Functions, resulting in a 70% reduction in modelling time and a 90% improvement in prediction accuracy. This comprehensive project calculates courier requirements and solves the shift assignment problem, optimizing shift schedules and minimizing missed orders.
Data projects often fail to deliver real-life impact due to macro-elements such as data availability, skillset, timeframe, organizational readiness, and political environment. The availability and accessibility of relevant data are fundamental, and if data is unattainable, the feasibility of the project should be reconsidered.
This article explores the importance of classical computation in the context of artificial intelligence, highlighting its provable correctness, strong generalization, and interpretability compared to the limitations of deep neural networks. It argues that developing AI systems with these classical computation skills is crucial for building generally-intelligent agents.
The article explores common data clustering techniques, with a focus on spectral clustering. Using k-means to compute cluster labels from eigenvectors is found to be the best approach, despite variations and complexities.