10 GitHub Repositories to Master Machine Learning Deployment
Master the essential skill of deploying machine learning models with courses, projects, examples, resources, and interview questions.
Master the essential skill of deploying machine learning models with courses, projects, examples, resources, and interview questions.
The real-time headphone translations experience keeps each speaker’s tone, emphasis, and cadence intact, so it’s easier to follow the conversation and tell who’s saying what.
How companies like Bank of America, Boeing, and Walmart are using virtual reality, augmented reality, and mixed reality to develop employees.
Author(s): Sayan Chowdhury Originally published on Towards AI. Understanding the OG Perceptron Neural networks look complex from the outside, but at their core they are built from one simple unit. This unit is called the perceptron. The OG 😀The article explains the perceptron, the simplest form of a neural network, which serves as a tiny decision maker by taking a set of inputs to decide between two outcomes. It discusses how perceptrons inspired modern deep learning systems, focusing […]
The new LiteRT NeuroPilot Accelerator from Google and MediaTek is a concrete step toward running real generative models on phones, laptops, and IoT hardware without shipping every request to a data center. It takes the existing LiteRT runtime and wires it directly into MediaTek’s NeuroPilot NPU stack, so developers can deploy LLMs and embedding models with a single API surface instead of per chip custom code. What is LiteRT NeuroPilot Accelerator? LiteRT is the successor of TensorFlow Lite. […]
India has given OpenAI, Google, and other AI firms 30 days to respond to its proposed royalty system for training on copyrighted content.
BBVA is expanding its work with OpenAI through a multi-year AI transformation program, rolling out ChatGPT Enterprise to all 120,000 employees. Together, the companies will develop AI solutions that enhance customer interactions, streamline operations, and help build an AI-native banking experience.
In the wilderness of the New World, the Plymouth Pilgrims had progressed from the false dream of communism to the sound realism of capitalism.
How do you keep RAG systems accurate and efficient when every query tries to stuff thousands of tokens into the context window and the retriever and generator are still optimized as 2 separate, disconnected systems? A team of researchers from Apple and University of Edinburgh released CLaRa, Continuous Latent Reasoning, (CLaRa-7B-Base, CLaRa-7B-Instruct and CLaRa-7B-E2E) a retrieval augmented generation framework that compresses documents into continuous memory tokens and then performs both retrieval and generation in that shared latent space. […]
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