In the drive to remain competitive, businesses today are turning to AI to help them minimize cost and maximize efficiency. It’s incumbent on them to find the most suitable AI model—the one that will help them achieve more while spending less. For many businesses, the migration from OpenAI’s model family to Amazon Nova represents not …
This week, Palo Alto-based startup Genspark released what it calls Super Agent, a fast-moving autonomous system designed to handle real-world tasks across a wide range of domains – including some that raise eyebrows, like making phone calls to restaurants using a realistic synthetic voice.Read More
A DOGE operative at the Department of Veterans Affairs appears to be trying to use an AI tool to write code for the agency’s systems, among other proposals.
A trio of AI researchers at Google’s Google DeepMind, working with a colleague from the University of Toronto, report that the AI algorithm Dreamer can learn to self-improve by mastering Minecraft in a short amount of time. In their study published in the journal Nature, Danijar Hafner, Jurgis Pasukonis, Timothy Lillicrap and Jimmy Ba programmed …
Read more “Google’s AI Dreamer learns how to self-improve over time by mastering Minecraft”
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Every year, AWS Sales personnel draft in-depth, forward looking strategy documents for established AWS customers. These documents help the AWS Sales team to align with our customer growth strategy and to collaborate with the entire sales team on long-term growth ideas for AWS customers. These documents are internally called account plans (APs). In 2024, this …
Read more “How AWS Sales uses generative AI to streamline account planning”
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Organizations increasingly adopt machine learning solutions into their daily operations and long-term strategies, and, as a result, the need for effective standards for deploying and maintaining machine learning systems has become critical.
We’re exploring the frontiers of AGI, prioritizing technical safety, proactive risk assessment, and collaboration with the AI community.
Many robotics tasks, such as path planning or trajectory optimization, are formulated as optimal control problems (OCPs). The key to obtaining high performance lies in the design of the OCP’s objective function. In practice, the objective function consists of a set of individual components that must be carefully modeled and traded off such that the …
Read more “Interpreting and Improving Optimal Control Problems With Directional Corrections”