Advancements in Artificial Intelligence (AI) have been driven by large language models (LLMs) and reinforcement learning from human feedback (RLHF). However, the challenge lies in optimizing the learning process from human feedback. A novel approach using double Thompson sampling and epistemic neural networks shows promise in overcoming these limitations, offering efficient exploration to enhance LLMs.
The text provides a guide on formatting text in Character.AI, covering various styles like bold, italics, strikethrough, lists, clickable links, and more using both a text formatting tool and Markdown commands. It also explains how to add text formatting to Character.AI characters and suggests trying out the provided tools.
This tutorial provides step-by-step instructions on how to delete your Character.ai account both via the website and the mobile app. It includes detailed guidance on logging in, accessing profile settings, and confirming the account deletion. The irreversible nature of the action is emphasized, and users are reassured that they can download their data.
The field of Artificial Intelligence (AI) aims to automate computer operations with autonomous agents. Carnegie Mellon University researchers have introduced VisualWebArena, a benchmark to evaluate multimodal web agents’ performance on complex challenges. This assesses agents’ abilities in reading image-text inputs, understanding natural language instructions, and conducting tasks on websites. Research highlights the superiority of Vision-Language…
This AI paper from Apple and Georgetown University introduces a new benchmark for evaluating context understanding in large language models (LLMs). It addresses the challenges of machine interpretation of human language and underscores the complexity of context comprehension in natural language processing. The benchmark assesses the models’ proficiency in various contextual tasks and aims to…
A groundbreaking methodology introduces a compact model for optical flow estimation, using a spatial recurrent encoder network with Partial Kernel Convolution (PKConv) and Separable Large Kernel (SLK) modules. This innovative approach efficiently captures essential image details while maintaining low computational demands. Empirical evaluations demonstrate the model’s superior generalization performance in diverse datasets, marking a significant…
The London Underground conducted a year-long AI surveillance trial at Willesden Green Tube station, monitoring passengers’ behaviors, safety, and potential criminal activities through live CCTV footage. The AI issued over 44,000 alerts, including fare evasion, safety hazards, and aggressive behaviors. However, concerns were raised about privacy invasion and inaccurate results, leading to the need for…
OpenAI’s CEO, Sam Altman, is orchestrating a staggering funding initiative to raise between $5-7 trillion. This investment aims to expand high-performance AI hardware production to address the skyrocketing demand. Altman is engaging potential investors and government officials to alleviate the supply-demand imbalance hindering AI progress. The grand plan signifies a significant leap for OpenAI and…
Generative AI is disrupting the creative industry, leading to anxiety and real impacts. Events like the Writers Guild of America strike and layoffs in big companies have highlighted the looming threat. Studies project significant job disruptions, with California at the epicenter. The AI’s impact spans film, TV, music, gaming, and more, triggering existential debates about…
Researchers from the National Research Council Canada experimented with four large vision-language models to assess racial and gender bias. They found biases in the models’ evaluation of scenarios in images based on race and gender. Their experiments used a dataset called PAIRS and revealed biases in occupation scenarios and social status evaluations, raising the need…
The advent of large language models (LLMs) has transformed natural language processing, but their high computational demand hinders real-world deployment. A study explores the viability of smaller LLMs, finding that compact models like FLAN-T5 can match or surpass larger LLMs’ performance in meeting summarization tasks. This breakthrough offers a cost-effective NLP solution with promising implications.
Google, led by CEO Sundar Pichai, is shifting focus towards AI chatbot technology with Gemini. This innovative tool aims to offer a versatile and interactive way of accessing information, including text, voice, and images. Google is experimenting with various formats for Gemini and plans to offer advanced features through a subscription model, reflecting a strategic…
This week’s AI news covers a range of topics, including AI’s involvement in defense applications and its impact on carbon emissions. Efforts to combat AI-generated fake content are also discussed, along with developments in AI image generation and its application in different industries. The post concludes with a selection of engaging AI stories.
Physics-informed neural networks (PINNs) integrate physical laws into learning, promising predictive accuracy. However, their performance declines due to multi-layer perceptron complexities. Physics-informed machine learning efforts are ongoing, but PirateNets, designed by a research team, offer a dynamic framework to overcome PINN challenges. It integrates random Fourier features and shows superior performance in addressing complex problems…
Stanford researchers have introduced RAPTOR, a tree-based retrieval system that enhances large language models with contextual information. RAPTOR utilizes a hierarchical tree structure to synthesize information from diverse sections of retrieval corpora, and it outperforms traditional methods in various question-answering tasks, demonstrating its potential for advancing language model capabilities. [47 words]
Large Language Models (LLMs) have become crucial for Natural Language Processing (NLP) tasks. However, the lack of openness in model development, particularly the pretraining data composition, hinders transparency and scientific advancement. To address this, a team of researchers has released Dolma, a large English corpus with three trillion tokens, and a data curation toolkit to…
The Frontiers of General Artificial Intelligence Technology Exhibition in Beijing unveiled a virtual robot toddler named Tong Tong, developed by the Beijing Institute for General Artificial Intelligence. Tong Tong exhibits human-like abilities and behaviors, mirroring those of a 3-4 year old child. Chinese researchers aim to create thousands of powerful autonomous robots by 2025.
MIT researchers have revealed how utilizing symmetry in datasets can reduce data needed for training models. They employed Weyl’s law, a century-old mathematical insight, to simplify data input into neural networks. This breakthrough has potential implications in computational chemistry and cosmology, and it was presented at the December 2023 Neural Information Processing Systems conference.
The Post-Industrial Summit 2024, hosted by the Post-Industrial Institute and SRI International in Menlo Park, CA on February 28-29, explores AI’s transformative impact on businesses. With insights from executives and experts from leading organizations, the summit focuses on responsible and ethical AI implementation, frameworks for next-generation AI, and the larger economic context driving AI advancement.…
Deep active learning combines traditional neural network training with strategic data sample selection, leading to improved model performance, efficiency, and accuracy in various applications.