Unconventional AI confirms its massive $475M seed round
Led by Naveen Rao, the former head of AI at Databricks, the new hardware startup is valued at $4.5 billion.
Led by Naveen Rao, the former head of AI at Databricks, the new hardware startup is valued at $4.5 billion.
Autonomous vehicle (AV) stacks are evolving from many distinct models to a unified, end-to-end architecture that executes driving actions directly from sensor data. This transition to using larger models is drastically increasing the demand for high-quality, physically based sensor data for training, testing and validation. To help accelerate the development of next-generation AV architectures, NVIDIA today released NVIDIA Cosmos Predict-2 — a new world foundation model with improved future world state prediction capabilities for high-quality synthetic data generation […]
In the wilderness of the New World, the Plymouth Pilgrims had progressed from the false dream of communism to the sound realism of capitalism.
Discover how Podium used OpenAI’s GPT-5 to build “Jerry,” an AI teammate driving 300% growth and transforming how Main Street businesses serve customers.
Author(s): Manash Pratim Originally published on Towards AI. A tiny local language model now organizes my files in real time for free, offline, and with zero rules. My Downloads folder used to feel like a crime scene. iMAGE GENERATED USING AIThe article discusses the author’s experience with automating the organization of their Downloads folder using a local AI agent that analyzes new files and categorizes them appropriately without any predetermined rules. The system consists of a few components […]
India has given OpenAI, Google, and other AI firms 30 days to respond to its proposed royalty system for training on copyrighted content.
Master the essential skill of deploying machine learning models with courses, projects, examples, resources, and interview questions.
Technology and clearer regulation are finally making it possible for companies to earn a share of every resale.
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Home Table of Contents KV Cache Optimization via Tensor Product Attention Challenges with Grouped Query and Multi-Head Latent Attention Multi-Head Attention (MHA) Grouped Query Attention (GQA) Multi-Head Latent Attention (MLA) Tensor Product Attention (TPA) TPA: Tensor Decomposition of Q, K, V Latent Factor Maps and Efficient Implementation Attention Computation and RoPE Integration KV Caching and Memory Reduction with TPA PyTorch Implementation of Tensor Product Attention (TPA) Tensor Product Attention with KV Caching Transformer Block Inferencing Code Experimentation Summary […]