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O’Reilly Media – The Sens-AI Framework: Teaching Developers to Think with AI
Developers are doing incredible things with AI. Tools like Copilot, ChatGPT, and Claude have rapidly become indispensable for developers, offering unprecedented speed and efficiency in tasks like writing code, debugging tricky behavior, generating tests, and exploring unfamiliar libraries and frameworks. When it works, it’s effective, and it feels incredibly satisfying. But if you’ve spent any…
Latest from MIT Tech Review – Designing better products with AI and sustainability
On a mission to reduce the environmental impact of manufacturing components, Siemens turned its attention to the design of a robot gripper. Making up just 2% of the robot, the impact of this hand-like device may seem inconsequential. But, reducing its weight by 90% and the number of constituent parts by 84% can save up to 3…
UC Berkeley – Interactive Fleet Learning
Figure 1: “Interactive Fleet Learning” (IFL) refers to robot fleets in industry and academia that fall back on human teleoperators when necessary and continually learn from them over time. In the last few years we have seen an exciting development in robotics and artificial intelligence: large fleets of robots have left the lab and entered…
O’Reilly Media – What We Learned from a Year of Building with LLMs (Part II)
Read Part I of this series here and stay tuned for Part III.To hear directly from the authors on this topic, sign up for the upcoming virtual event on June 20th, and learn more from the Generative AI Success Stories Superstream on June 12th. A possibly apocryphal quote attributed to many leaders reads: “Amateurs talk strategy and…
Latest from MIT Tech Review – AI is changing how we study bird migration
A small songbird soars above Ithaca, New York, on a September night. He is one of 4 billion birds, a great annual river of feathered migration across North America. Midair, he lets out what ornithologists call a nocturnal flight call to communicate with his flock. It’s the briefest of signals, barely 50 milliseconds long, emitted…
Latest from MIT : How to build AI scaling laws for efficient LLM training and budget maximization
When researchers are building large language models (LLMs), they aim to maximize performance under a particular computational and financial budget. Since training a model can amount to millions of dollars, developers need to be judicious with cost-impacting decisions about, for instance, the model architecture, optimizers, and training datasets before committing to a model. To anticipate…