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.
Tesla releases demo video of its Optimus Gen 2 humanoid robot, showcasing significant hardware improvements. Skepticism remains after recent AI demonstration controversies.
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.
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.
Generative AI and large language models dominated enterprise trends this year, with companies like Amdocs, Dropbox, and SAP building customized applications using RAG and LLMs. Open-source pretrained models are set to revolutionize businesses' operational strategies, while off-the-shelf AI and microservices make it easier for developers to create complex applications.
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.
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.
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.
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 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.
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.
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.
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.
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.