MaskLLM: A Learnable AI Method that Facilitates End-to End Training of LLM Sparsity on Large-Scale Datasets

Jagged Intelligence The term coined by Andrej Karpathy to describe the dual nature of modern AI systems Modern AI systems, particularly large language models (LLMs), excel in complex tasks but struggle with seemingly basic ones. This…

A new approach to creating mesmerizing optical illusions has emerged, eschewing assumptions about human perception by using a text-to-image diffusion model. This method generates multi-view illusions, including visual anagrams, polymorphic jigsaws, and even three to four…

Practical AI Solutions for Real-Time Voice Processing Enhancing Communication and Efficiency With speech-to-speech technology, better communication and access within diverse applications are facilitated, including voice recognition, language processing, and speech synthesis. The focus is on creating…

The Evolution of Robotics The development of robotics has faced challenges due to slow and costly training methods. Traditionally, engineers had to manually control robots to gather specific training data. However, with the introduction of Aria…

Apple is sponsoring the in-person NeurIPS conference in New Orleans from December 10-16, fostering research exchange on neural information processing in various disciplines. The summary doesn’t include Apple’s specific workshop and event schedules.

Transforming LLMs with Intelligent Agents The rise of Large Language Models (LLMs) has significantly advanced AI. One powerful application of LLMs is the development of Agents. These Agents mimic human reasoning and can tackle complex tasks…

AI-generated counterfeit nudes of students from Westfield High School in New Jersey, US, were distributed among peers. The school has not disclosed specific details or taken disciplinary action, citing confidentiality concerns. Similar incidents have occurred in…

Researchers from Tsinghua University and ByteDance have developed SALMONN, a multimodal language model (LLM) that can recognize and comprehend various audio inputs, including voice, audio events, and music. They also propose a low-cost activation tuning technique…

Understanding the Role of Board Games in AI Development Board games have played a crucial role in advancing AI by providing structured environments for testing decision-making and strategy. Games like chess and Connect Four have unique…

Understanding the decision-making processes of Large Language Models (LLMs) is crucial for mitigating potential risks in high-stakes applications. A study by researchers from MIT and the University of Cambridge explores the universality of individual neurons in…

Practical Solutions for Running Large Language Models on Commodity Hardware Deploying advanced machine learning models on resource-constrained devices like edge devices, mobile platforms, or low-power hardware has been challenging due to the computational and memory resources…

Introduction to Arch 0.1.3 The integration of AI agents into workflows has created a need for smart communication, data management, and security. As more AI agents are used, ensuring they communicate securely and efficiently is crucial.…

Google’s highly anticipated AI system, Gemini, has been significantly delayed and will now be launched in early 2024. The delay highlights Google’s struggle to match the hype around OpenAI’s ChatGPT. Despite efforts like releasing Bard and…

Researchers have developed a NeRF-based mapping method called H2-Mapping to generate high-quality, dense maps in real-time applications. They propose a hierarchical hybrid representation that combines explicit octree SDF priors and implicit multiresolution hash encoding. The method…

Introducing deepset-mxbai-embed-de-large-v1: A Revolutionary German/English Embedding Model Deepset and Mixedbread have collaborated to launch an innovative open-source German/English embedding model, deepset-mxbai-embed-de-large-v1, aiming to address the dominance of English in AI. This model, built on intfloat/multilingual-e5-large, has…

The emergence of language models in AI necessitates alignment with human values. Researchers introduced Contrastive Unlikelihood Training (CUT) to achieve this, contrasting appropriate and inappropriate responses. The novel method significantly improves model performance, demonstrating potential for…

This tutorial provides an end-to-end guide on implementing object detection using KerasCV, specifically RetinaNet, to identify healthy and diseased plant leaves. The process involves inspecting and preprocessing data, setting up RetinaNet with a YOLOv8 backbone, training…