Reading Research Papers in the Age of LLMs
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.
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The cost of thinking
Large language models (LLMs) like ChatGPT can write an essay or plan a menu almost instantly. But until recently, it was also easy to stump them. The models, which rely on language patterns to respond to users’ queries, often failed at math problems and were not good at complex reasoning. Suddenly, however, they’ve gotten a lot better at these things. A new generation of LLMs known as reasoning models are being trained to solve complex problems. Like humans, […]
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The Real Meaning of Thanksgiving: The Triumph of Capitalism over Collectivism
In the wilderness of the New World, the Plymouth Pilgrims had progressed from the false dream of communism to the sound realism of capitalism.
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How to Build a Meta-Cognitive AI Agent That Dynamically Adjusts Its Own Reasoning Depth for Efficient Problem Solving
In this tutorial, we build an advanced meta-cognitive control agent that learns how to regulate its own depth of thinking. We treat reasoning as a spectrum, ranging from fast heuristics to deep chain-of-thought to precise tool-like solving, and we train a neural meta-controller to decide which mode to use for each task. By optimizing the trade-off between accuracy, computation cost, and a limited reasoning budget, we explore how an agent can monitor its internal state and adapt its […]
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Was the Big Unread Bill a poison pill?
Will it destroy federal legitimacy The post Was the Big Unread Bill a poison pill? appeared first on Downsize DC.
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3 Questions: How AI is helping us monitor and support vulnerable ecosystems
A recent study from Oregon State University estimated that more than 3,500 animal species are at risk of extinction because of factors including habitat alterations, natural resources being overexploited, and climate change. To better understand these changes and protect vulnerable wildlife, conservationists like MIT PhD student and Computer Science and Artificial Intelligence Laboratory (CSAIL) researcher Justin Kay are developing computer vision algorithms that carefully monitor animal populations. A member of the lab of MIT Department of Electrical Engineering and […]
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Emergent Introspective Awareness in Large Language Models
An overview, summary, and position of cutting-edge research conducted on the emergent topic of LLM introspection on self internal states
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Simpler models can outperform deep learning at climate prediction
Environmental scientists are increasingly using enormous artificial intelligence models to make predictions about changes in weather and climate, but a new study by MIT researchers shows that bigger models are not always better. The team demonstrates that, in certain climate scenarios, much simpler, physics-based models can generate more accurate predictions than state-of-the-art deep-learning models. Their analysis also reveals that a benchmarking technique commonly used to evaluate machine-learning techniques for climate predictions can be distorted by natural variations in […]
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Expert Available: Why Do We Love Upsets in Sports But Fear Them in Tech?
As sports fans throughout the country gear up for rivalries and the playoffs this holiday season, Cato Institute senior fellow in technology policy Jennifer Huddleston’s new blog, titled What Sports Can Teach Us About Competition Policy, compares competition in sports to competition in the technology market: lead , “Competition doesn’t only exist on the field. It also exists in the market. So why then do we seem not to greet technology disruptors’ success with the same sense of pride and […]
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Optimizing PyTorch Model Inference on CPU
Flyin’ Like a Lion on Intel Xeon The post Optimizing PyTorch Model Inference on CPU appeared first on Towards Data Science.
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