Large language model
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 summaries. Their approach employs both extractive and abstractive compressors and demonstrates improved efficiency and reduced computational costs. The compressors…
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 progressive interpolation with functional relative position encoding to enhance the generalization of the models. It outperforms existing techniques in…
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 can have serious consequences, including election manipulation and violence. Efforts to combat deep fakes include proposed legislation and the…
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 and assisting with navigation. AI also enhances education by improving learning experiences. Despite its usefulness, concerns about AI include…
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 (MCTS) to explore decision paths and integrates external feedback for adaptive problem-solving. Experimental evaluations across various domains demonstrate the…
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 is not limited to politics but also includes false claims about celebrities and various topics. Companies and experts are…
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 offers accessible code for further exploration. This advancement contributes significantly to LLM network binarization.
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. This approach allows for rapid processing of texts and the identification of crucial information without user fine-tuning. MEMWALKER outperformed…
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 rich library of components and collaborative features, ToolJet enables quick and easy tool development while minimizing engineering effort.
The text talks about quantization-aware fine-tuning and suggests further reading on Towards Data Science.
Meta is using its Prophet package to enhance time series machine learning models.
Luke Farritor, a computer science student at the University of Nebraska–Lincoln, has used machine learning to decipher a carbonized scroll from ancient Herculaneum that was previously unreadable. His algorithm identified Greek letters on the papyrus, including the word “purple.” This breakthrough could revolutionize our understanding of ancient history and literature. AI is also being used…
DiffPoseTalk is a pioneering solution in the field of speech-driven expression animation. It uses diffusion models to generate realistic facial animations and head poses based on spoken language input. The system incorporates a speaking style encoder to capture the unique style of each individual. DiffPoseTalk excels in generating diverse and natural-looking animations by approximating the…
eBay, Amazon, and Shopify are incorporating AI features to assist users in listing products and completing mundane tasks. These tools help sellers generate detailed product descriptions quickly and accurately. AI tools on platforms like Shopify are also automating tasks such as creating email campaigns and generating responses to customer queries, reducing labor-intensive workloads.
CD Projekt, the developers of Cyberpunk 2077, utilized AI technology to bring back the voice of the late Miłogost Reczek for their game Phantom Liberty. Instead of re-recording all of Reczek’s lines with a different actor, the company used voice-cloning software from Respeecher to transform new dialogue recorded by a voice actor into Reczek’s distinct…
Recent developments in text-to-image generation have allowed for the creation of detailed graphics from natural language descriptions. However, these models often do not produce high-quality raster images for scientific figures. As a result, vector graphics, which offer better geometric precision and text readability, are encouraged. Researchers are investigating the usage of visual languages, such as…
The #30DayChartChallenge is a community-driven challenge that takes place each year in April. Participants create data visualizations based on daily prompts. The author participated in the challenge to learn the Observable Plot library and improve their data visualization skills. They provide tips for planning, reusing data, defining objectives, embracing the learning process, and celebrating achievements.…