Companies today are incorporating artificial intelligence into every corner of their business. The trend is expected to continue until machine-learning models are incorporated into most of the products and services we interact with every day. As those models become a bigger part of our lives, ensuring their integrity becomes more important. That’s the mission of…
Launched in November 2022, ChatGPT is a chatbot that can not only engage in human-like conversation, but also provide accurate answers to questions in a wide range of knowledge domains. The chatbot, created by the firm OpenAI, is based on a family of “large language models” — algorithms that can recognize, predict, and generate text…
Posted by Ted White and Ofer Naaman, Staff Research Scientists, Google Quantum AI The Google Quantum AI team is building quantum computers with superconducting microwave circuits, but much like a classical computer the superconducting processor at the heart of these computers is only part of the story. An entire technology stack of peripheral hardware is…
Posted by Jinsung Yoon and Sercan O. Arik, Research Scientists, Google Research, Cloud AI Team Anomaly detection (AD), the task of distinguishing anomalies from normal data, plays a vital role in many real-world applications, such as detecting faulty products from vision sensors in manufacturing, fraudulent behaviors in financial transactions, or network security threats. Depending on…
For enterprises looking to shift from hardware investments to services and beyond, a change in technology and data infrastructure could be key. One approach is a focus on the “New IT,” a term coined by Lenovo, that features five elements: client, edge and cloud, network, and intelligence to meet business goals. “The mission of the…
From AI-powered platforms that can detect abnormal activities in supermarkets, to edge servers helping preserve biodiversity in remote locations, today’s technologies drive innovation in ways never before imaginable. “Innovation serves the purpose of making our life better, our work more productive, and our planet more sustainable,” says Yang Yuanqing, CEO and chairman of Lenovo. Technology…
Posted by Sanjiv Kumar, VP and Google Fellow, Google Research (This is Part 4 in our series of posts covering different topical areas of research at Google. You can find other posts in the series here.) The explosion in deep learning a decade ago was catapulted in part by the convergence of new algorithms and…
This story originally appeared in The Algorithm, our weekly newsletter on AI. To get stories like this in your inbox first, sign up here. Last week, OpenAI unveiled a tool that can detect text produced by its AI system ChatGPT. But if you’re a teacher who fears the coming deluge of ChatGPT-generated essays, don’t get the party…
Large language models like OpenAI’s GPT-3 are massive neural networks that can generate human-like text, from poetry to programming code. Trained using troves of internet data, these machine-learning models take a small bit of input text and then predict the text that is likely to come next. But that’s not all these models can do….
One reason deep learning exploded over the last decade was the availability of programming languages that could automate the math — college-level calculus — that is needed to train each new model. Neural networks are trained by tuning their parameters to try to maximize a score that can be rapidly calculated for training data. The…