Machine Learning
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Transforming the Developer Experience for Every Engineering Role
In today’s fast-paced software development landscape, ambitious goals, complex technologies, and shifting priorities can lead to frustrated developer experience. However, the pressure to deliver faster, operate efficiently, and maintain robust security continues to intensify. What if there was a way to break through those barriers? A way to inject new energy into your projects, inspire…
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To Build A Better AI Helper, Start By Modeling The Irrational Behavior Of Humans
A new technique can be used to predict the actions of human or AI agents who behave suboptimally while working toward unknown goals. Adam Zewe | MIT NewsMIT News (https://news.mit.edu/2024/building-better-ai-helper-starts-with-modeling-irrational-behavior-0419) To build AI systems that can collaborate effectively with humans, it helps to have a good model of human behavior to start with. But humans tend to…
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On-Device ML Research With MLX And Swift
The Swift programming language has a lot of potential to be used for machine learning research because it combines the ease of use and high-level syntax of a language like Python with the speed of a compiled language like C++. MLX is an array framework for machine learning research on Apple silicon. MLX is intended for…
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AWS Is Readying LLM-Based Debugger For Databases To Take On OpenAI
AWS researchers have published a paper that pitches a proprietary LLM-based debugger, dubbed Panda, against OpenAI’s GPT-4. AWS researchers are working on developing a large language model-based debugger for databases in an effort to help enterprises solve performance issues in such systems. Dubbed Panda, the new debugging framework has been designed to work in a manner…
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AI Agents Help Explain Other AI Systems
MIT researchers introduce a method that uses artificial intelligence to automate the explanation of complex neural networks. Rachel Gordon | MIT CSAILhttps://news.mit.edu/2024/ai-agents-help-explain-other-ai-systems-0103 Explaining the behavior of trained neural networks remains a compelling puzzle, especially as these models grow in size and sophistication. Like other scientific challenges throughout history, reverse-engineering how artificial intelligence systems work requires…