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.
Dropbox faces backlash after enabling a default setting that shares user data with OpenAI for AI-powered search, but assures data is only shared when actively used and is deleted within 30 days. CEO Drew Houston apologizes for customer confusion and emphasizes that no customer data is automatically sent to third-party AI services.
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.
Large language models (LLMs) like GPT NeoX and Pythia are gaining popularity, with billions of parameters and impressive performance. Training these models on AWS Trainium is cost-effective and efficient, thanks to optimizations like rotational positional embedding (ROPE) and partial rotation techniques.
Moonshine Studio's 3D artist, Eric Chiang, creates an AI-powered virtual assistant named NANA using GPU-accelerated features and a GeForce RTX 4090 graphics card. NVIDIA Studio Drivers now support Reallusion iClone AccuFACE plugin and other enhancements, while the #WinterArtChallenge invites artists to share their winter-themed creations for a chance to be featured.
Conversational AI has evolved with generative AI and large language models, but lacks specialized knowledge for accurate answers. Retrieval Augmented Generation (RAG) connects generic models to internal knowledge bases, enabling domain-specific AI assistants. Amazon Kendra and OpenSearch Service offer mature vector search solutions for implementing RAG, but analytical reasoning questions requir...
Tesla releases demo video of its Optimus Gen 2 humanoid robot, showcasing significant hardware improvements. Skepticism remains after recent AI demonstration controversies.
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 article discusses the launch of ChatGPT and the rise in popularity of generative AI. It highlights the creation of a web UI called Chat Studio to interact with foundation models in Amazon SageMaker JumpStart, including Llama 2 and Stable Diffusion. This solution allows users to quickly experience conversational AI and enhance the user experience with media integration.
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.
MLOps is essential for integrating machine learning models into existing systems, and Amazon SageMaker offers features like Pipelines and Model Registry to simplify the process. This article provides a step-by-step implementation for creating custom project templates that integrate with GitHub and GitHub Actions, allowing for efficient collaboration and deployment of ML models.
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.
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.
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.