LongAlign: A Segment-Level Encoding Method to Enhance Long-Text to Image Generation

This article discusses four different methods of passing arguments to Python scripts. For more information, please read the full article on Towards Data Science.

The GovAI Summit 2023, on December 5-6 in Arlington, VA, will explore AI’s public sector impact, featuring keynotes by AI experts and industry leaders. Lane Dilg from OpenAI and others will discuss AI’s role in government,…

Practical Solutions and Value of OneEdit: A Neural-Symbolic Collaborative Knowledge Editing System Efficient Knowledge Management OneEdit integrates symbolic Knowledge Graphs (KGs) and neural Large Language Models (LLMs) to effectively update and manage knowledge through natural language…

Value functions are crucial in deep reinforcement learning, employing neural networks to align with target values. Challenges arise when upscaling value-based RL methods for extensive networks, like high-capacity Transformers, with regression. Researchers from Google DeepMind propose…

A smart and stretchable soft sensor has been developed for robotics and prosthetics. It provides touch sensitivity and dexterity to prosthetic arms and robotic limbs, enabling tasks like picking up soft fruit. The sensor skin is…

Data organisations often overlook the responsibilities of data consumers in data contracts. To maximize the value of data, data contracts should outline the consumer’s obligations in analyzing and applying the data. Neglecting consumer commitments can reduce…

This post outlines a solution for using Amazon Transcribe and Amazon Bedrock to automatically generate concise summaries of video or audio recordings. By leveraging a combination of speech-to-text capability and generative AI models, the solution aims…

Artificial intelligence scaling laws guide the development of Large Language Models (LLMs), facilitating the understanding of human expression. Current research explores the gaps between scaling studies and LLM training, predicting down-stream task performance. Experimentation with different…

Transforming Machine Learning with Automatic Differentiation Automatic differentiation has revolutionized machine learning by simplifying the process of calculating gradients. This innovation allows for efficient computation of Jacobian-vector and vector-Jacobian products without needing to construct large matrices,…

Meta’s AI image generator “Imagine with Meta AI” has transitioned from a social media feature to a standalone product. Despite its limits with text, the generator delivers high-quality images at 1280×1280 resolution. With a dataset of…

Advancements in text-to-video (T2V) synthesis using Stable Diffusion (SD) models have enabled automatic video generation from text prompts. Researchers at NVIDIA and Victoria University of Wellington introduced an interface allowing users to control object trajectories through…

Large language models utilizing the Mixture-of-Experts (MoE) architecture have significantly enhanced model capacity without a proportional increase in computational demands. However, this advancement presents challenges, particularly in GPU communication. In MoE models, only a subset of…

The GTA Benchmark: A New Standard for General Tool Agent AI Evaluation Practical Solutions and Value The GTA benchmark addresses the challenge of evaluating large language models (LLMs) in real-world scenarios by providing a more accurate…

Enhancing Efficiency in Deep Learning through Weight Quantization Enhancing Efficiency in Deep Learning through Weight Quantization Introduction In today’s competitive landscape, optimizing deep learning models for deployment in environments with limited resources is crucial. Weight quantization…

The Promise of Quantum Processing Units (QPUs) Practical Solutions and Value Quantum Processing Units (QPUs) represent a transformative leap in computational power, leveraging the principles of quantum mechanics to solve complex problems that classical computing struggles…

Japanese comics, or Manga, have a global fanbase but are inaccessible to visually impaired individuals due to their visual nature. The University of Oxford’s research team developed a tool named Magi, using machine learning to make…

Mirasol3B is a multimodal autoregressive model developed by Google that addresses the challenges of machine learning across different modalities. It uses a unique architecture to handle time-aligned and non-aligned modalities, such as video, audio, and text.…