NVIDIA Studio accelerates content creation with new RTX GPU features and optimizations in creative apps like CyberLink PowerDirector and Adobe Substance 3D Modeler. Artists can now create physically accurate 3D replicas and improve video quality and encoding efficiency with NVIDIA technology.
Linguist Emily Bender and computer scientist Timnit Gebru critique language models as 'stochastic parrots' lacking true understanding. Auto-regressive models like GPT-4 struggle with basic generalization, displaying a 'Reversal Curse' in answering simple questions.
Non-negative matrix factorization (NMF) finds W and H matrices to approximate a source matrix V. Results show NMF is scenario-specific, not a general technique.
Information retrieval systems are evolving with AI solutions like Amazon Transcribe and Amazon Bedrock to efficiently search through audio files at scale. These services simplify the process of transcribing audio, cataloging content, and creating embeddings for easy querying.
AI can create images and sounds simultaneously, like corgis barking. Researchers at the University of Michigan explore this groundbreaking concept.
RAG combines retrieval and foundation models for powerful question answering systems. Automate RAG deployment with Amazon Bedrock and AWS CloudFormation for seamless setup.
Synthetic data raises concerns of model collapse in AI development, but study may not reflect real-world practices and advancements. Omission of standard mitigation techniques and quality control in study limits applicability to industry scenarios.
Elon Musk sues OpenAI CEO Sam Altman, alleging manipulation into co-founding the company. Legal battle reignited with new lawsuit in northern California court.
Fake AI vocals, including Donald Trump's, disrupt the Montego Bay clash scene, sparking debates on the future of the culture. The use of AI vocalists challenges authenticity and originality in the historic Sumfest Global Sound Clash tradition.
LLM prompts show brittleness in AI responses. Experiment with OpenAI's GPT-4o reveals 55% accuracy with original prompt.
Winnow binary classification is designed for binary predictor variables and labels. An example using a modified UCI Email Spam Dataset demonstrates the unique Winnow algorithm in action.
AI networks interconnect GPUs for large-scale distributed training at Meta, using RDMA over Ethernet for high-performance communication. Specialized RoCEv2 networks support various AI workloads, including GenAI, ranking, and natural language processing, with a dedicated backend network for training clusters.
Large language models (LLMs) are growing in size for better results, but with increased computational demands. Speculative sampling improves efficiency by verifying multiple tokens in parallel, enhancing hardware resource utilization.
Summary: Learn how to build a 124M GPT2 model with Jax for efficient training speed, compare it with Pytorch, and explore the key features of Jax like JIT Compilation and Autograd. Reproduce NanoGPT with Jax and compare multiGPU training token/sec between Pytorch and Jax.
LLMs can predict metadata for humanitarian datasets without fine-tuning, offering efficient and accurate results. GPT-4o shows promise in predicting HXL tags and attributes, simplifying data processing for humanitarian efforts.