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CREMA by UNC-Chapel Hill: A Modular AI Framework for Efficient Multimodal Video Reasoning

In artificial intelligence, integrating multimodal inputs for video reasoning stands as a frontier, challenging yet ripe with potential. Researchers increasingly focus on leveraging diverse data types – from visual frames and audio snippets to more complex 3D point clouds – to enrich AI’s understanding and interpretation of the world. This endeavor aims to mimic human…

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How to Forecast Time Series Data Using any Supervised Learning Model | by Matthew Turk | Feb, 2024

Featurizing time series data into a standard tabular format for classical ML models and improving accuracy using AutoML Source: Ahasanara AkterThis article delves into enhancing the process of forecasting daily energy consumption levels by transforming a time series dataset into a tabular format using open-source libraries. We explore the application of a popular multiclass classification…

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Huawei Researchers Introduce a Novel and Adaptively Adjustable Loss Function for Weak-to-Strong Supervision

The progress and development of artificial intelligence (AI) heavily rely on human evaluation, guidance, and expertise. In computer vision, convolutional networks acquire a semantic understanding of images through extensive labeling provided by experts, such as delineating object boundaries in datasets like COCO or categorizing images in ImageNet.  Similarly, in robotics, reinforcement learning often relies on…

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Navigating Data Science Jobs in 2024: Roles, Teams, and Skills | by TDS Editors | Feb, 2024

Whether you’re applying to your first internship to running a multidisciplinary team of analysts and engineers, data science careers come with their own specific set of challenges. Some of these might be more exciting than others, and others can be downright tedious—that’s true in any job, of course—but we believe in framing all of these…

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Meta Reality Labs Introduce Lumos: The First End-to-End Multimodal Question-Answering System with Text Understanding Capabilities

Artificial intelligence has significantly advanced in developing systems that can interpret and respond to multimodal data. At the forefront of this innovation is Lumos, a groundbreaking multimodal question-answering system designed by researchers at Meta Reality Labs. Unlike traditional systems, Lumos distinguishes itself by its exceptional ability to extract and understand text from images, enhancing the…

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QLoRA — How to Fine-Tune an LLM on a Single GPU | by Shaw Talebi | Feb, 2024

Imports We import modules from Hugging Face’s transforms, peft, and datasets libraries. from transformers import AutoModelForCausalLM, AutoTokenizer, pipeline from peft import prepare_model_for_kbit_training from peft import LoraConfig, get_peft_model from datasets import load_dataset import transformers Additionally, we need the following dependencies installed for some of the previous modules to work. !pip install auto-gptq !pip install optimum !pip…

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