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Researchers from System2 Research, the University of Cambridge, Monash University, and Princeton University have developed a fine-tuning approach called “FireAct” for language agents. Their research reveals that fine-tuning language models consistently improves agent performance. The study…

Large Language Models (LLMs) often struggle with numerical calculations involving large numbers. The xVal encoding strategy, introduced by Polymathic AI researchers, offers a potential solution. By treating numbers differently in the language model and using a…

Apple researchers, in collaboration with Carnegie Mellon University, have developed the Never-Ending UI Learner AI system. It continuously interacts with mobile applications to improve its understanding of UI design patterns and new trends. The system autonomously…

Researchers from Brown University have demonstrated that translating English inputs into low-resource languages increases the likelihood of bypassing the safety filter in GPT-4 from 1% to 79%. This exposes weaknesses in the model’s security measures and…

Researchers at Google have developed SANPO, a large-scale video dataset for human egocentric scene understanding. The dataset contains over 600K real-world and 100K synthetic frames with dense prediction annotations. SANPO includes a combination of real and…

Researchers have developed a programming model called DSPy that abstracts language model pipelines into text transformation graphs. This model allows for the optimization of natural language processing pipelines through the use of parameterized declarative modules and…

The text is about the new updates in Python SDK, AI-assisted labeling, and a growing library of generative models.

Researchers from the University of Texas at Austin and the University of Washington have developed a strategy called RECOMP (Retrieve, Compress, Prepend) to optimize the performance of language models by compressing retrieved documents into concise textual…

Researchers from Carnegie Mellon University, Google Research, and Google DeepMind have introduced a novel approach called Functional Interpolation for Relative Position Encoding (FIRE) to improve the ability of Transformer models to handle longer inputs. FIRE uses…

Deep fakes are a growing concern, particularly in the context of elections. Recent incidents in Slovakia, the UK, and Sudan have highlighted the threat of AI-generated fake audio clips. These clips are harder to detect and…

AI is driving innovation in technologies like Robotics, IoT, and Big Data. It can improve healthcare by detecting diseases faster, streamline drug discovery, and act as a virtual nurse. In transportation, AI is revolutionizing autonomous vehicles…

This text provides advice on selecting and reducing training time for neural networks. To learn more, visit the article on Towards Data Science.

The text is part 2 of a series on strategic data analysis. For further details, read on Towards Data Science.

The text is promoting an article on Towards Data Science that discusses PyTorch code.

Researchers from the University of Illinois at Urbana-Champaign have introduced LATS, a framework that harnesses the capabilities of Large Language Models (LLMs) for decision-making, planning, and reasoning. LATS utilizes techniques such as Monte Carlo tree search…

The rise of AI-generated voices on TikTok is causing concern as it facilitates the spread of misinformation. For example, an AI-generated voice sounding like former President Barack Obama defended himself against a baseless theory. This trend…

PB-LLM is an innovative approach for extreme low-bit quantization in Large Language Models (LLMs) while preserving language reasoning capabilities. It strategically filters salient weights during binarization, introduces post-training quantization (PTQ) and quantization-aware training (QAT) methods, and…

Researchers from Princeton University and Meta AI have developed MEMWALKER, a new method for analyzing lengthy texts. MEMWALKER breaks down the text into manageable segments, condenses the information from each segment, and constructs a tree structure.…

ToolJet is an open-source low-code framework that simplifies the development of internal tools in software organizations. It offers a drag-and-drop frontend builder, robust integration capabilities, and support for various data sources and hosting options. With its…

The text talks about quantization-aware fine-tuning and suggests further reading on Towards Data Science.