How We Are Testing Our Agents in Dev
Testing that your AI agent is performing as expected is not easy. Here are a few strategies we learned the hard way. The post How We Are Testing Our Agents in Dev appeared first on Towards Data Science.
Testing that your AI agent is performing as expected is not easy. Here are a few strategies we learned the hard way. The post How We Are Testing Our Agents in Dev appeared first on Towards Data Science.
What comes after Transformers? Google Research is proposing a new way to give sequence models usable long term memory with Titans and MIRAS, while keeping training parallel and inference close to linear. Titans is a concrete architecture that adds a deep neural memory to a Transformer style backbone. MIRAS is a general framework that views most modern sequence models as instances of online optimization over an associative memory. Why Titans and MIRAS? Standard Transformers use attention over a […]
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Thomas Massie shows the way The post Is there an Epstein connection to our Downsize strategy? appeared first on Downsize DC.
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The artificial intelligence models that turn text into images are also useful for generating new materials. Over the last few years, generative materials models from companies like Google, Microsoft, and Meta have drawn on their training data to help researchers design tens of millions of new materials. But when it comes to designing materials with exotic quantum properties like superconductivity or unique magnetic states, those models struggle. That’s too bad, because humans could use the help. For example, […]
In this article, I discuss the main problems of standard LLMs (OpenAI and the likes), and how the new generation of LLMs addresses these issues. The focus is on Enterprise LLMs. LLMs with Billions of Parameters Most of the LLMs still fall in that category. The first ones (ChatGPT) appeared around 2022, though Bert is an early precursor. Most recent books discussing LLMs still define them as transformer architecture with deep neural networks (DNNs), costly training, and reliance […]
The Rev. Dr. Richard Turnbull, long-time friend of the Acton Institute, sadly died on November 26, not long after being diagnosed with terminal cancer. Many friends, colleagues, and collaborators joined a Whatsapp group to pray for Richard and his family in his final weeks, and the affection and admiration that so many people had for him was clearly expressed over those weeks. Continue Reading…
OpenAI says that Dresser will be responsible for the company’s revenue strategy in enterprise and customer success.
How I keep up with papers with a mix of manual and AI-assisted reading The post Reading Research Papers in the Age of LLMs appeared first on Towards Data Science.