Artificial Intelligence
The growth of deep learning has led to its use in various fields, like data mining and natural language processing, as well as in addressing inverse imaging problems. To enhance the reliability of deep neural networks, researchers at UCLA have developed a cycle-consistency-based uncertainty quantification method, which can improve network dependability in inverse imaging and…
Recent advancements in image generation have led to the availability of top-tier models on open-source platforms. Challenges persist in text-to-image systems, but efforts to address diverse inputs and single-model outcomes are underway. Researchers have proposed DiffusionGPT, an all-encompassing generation system, showcasing superior performance across diverse prompts and domains.
Large Language Models (LLMs) have advanced in AI and NLP. Fireworks.ai introduced FireLLaVA under Llama 2 Community License, addressing restrictions of Vision-Language Model LLaVA. It supports multi-modal AI development, using OSS models for training data. FireLLaVA demonstrates better performance on benchmarks and offers vision-capable APIs, marking a significant advancement in multi-modal AI.
Google has introduced three generative AI features to revamp Chrome: Tab Organizer, Custom Themes, and “Help me write.” Tab Organizer simplifies tab management by grouping related tabs, while Chrome suggests and creates tab groups. Custom Themes allow users to create personalized themes with AI, and “Help me write” assists in drafting web content. These additions…
SPARC, a method developed by Google DeepMind, pretrains fine-grained multimodal representations from image-text pairs by using fine-grained contrastive alignment and contrastive loss between global image and text embeddings. It outperforms other approaches in image-level tasks like classification and region-level tasks such as retrieval, object detection, and segmentation, and enhances model faithfulness and captioning in foundational…
The UK’s National Cyber Security Centre (NCSC) released a report on the impact of AI on cyber threats. The report highlights AI’s dual role in cyber security as both beneficial for defense and a potential risk for more sophisticated attacks. It emphasizes increased cyber attack frequency, variable impact based on actor capabilities, and AI’s role…
The einx Python library offers a streamlined approach to complex tensor operations using Einstein notation. With support for major tensor frameworks, it facilitates concise expressions and just-in-time compilation for efficient execution. Its simple installation and vast manipulation capabilities make it a valuable asset for deep learning applications across various domains.
Artificial Intelligence has seen a revolution due to deep learning, driven by neural networks and specialized hardware. The shift has advanced fields like machine translation, natural language understanding, and computer vision, influencing diverse areas such as robotics and biology. The research highlights the transformative impact of AI in information retrieval and its versatile applications across…
The article discusses the roller-coaster ride of robotaxis in the US, focusing on rebuilding public trust and finding a realistic business model. It also compares the US and Chinese markets, highlighting China’s proactive regulation and the potential for American and Chinese companies to compete in the Middle East. The piece also touches upon current events…
Google Research has introduced Lumiere, a revolutionary text-to-video diffusion model. It can generate realistic videos from text or image inputs, outperforming other models in motion coherence and visual consistency. Lumiere offers various features including text-to-video, image-to-video, stylized generation, and video editing capabilities. Its innovative approach received high user preference in a recent study, showcasing its…
Large Language Models (LLMs) are gaining traction, but effective methods for their development and operation are lacking. LMSYS ORG introduces SGLang, a language enhancing LLM interactions, and RadixAttention, a method for automatic KV cache reuse, optimizing LLM performance. SGLang enables simpler and faster LLM programming, outperforming current systems by a factor of up to five…
Recent advancements in conversational question-answering (QA) models, particularly the introduction of the ChatQA family by NVIDIA, have significantly improved zero-shot conversational QA accuracy, surpassing even GPT-4. The two-stage instruction tuning method enhances these models’ capabilities and sets new benchmarks in accuracy. This represents a major breakthrough, with potential implications for conversational AI’s future.
Wearable sensor technology has revolutionized healthcare, intersecting with large language models (LLMs) to predict health outcomes. MIT and Google introduced Health-LLM, evaluating eight LLMs for health predictions across five domains. The study’s innovative methodology and the success of the Health-Alpaca model demonstrate the potential of integrating LLMs with wearable sensor data for personalized healthcare.
Researchers from Washington University in St. Louis’s McKelvey School of Engineering have developed the Visual Active Search (VAS) framework, leveraging computer vision and adaptive learning to enhance geospatial exploration for combating illegal poaching and human trafficking. The framework has shown superior capabilities in detection and offers promise for broader applications in various domains.
“VMamba” is a new visual representation learning architecture developed by a team of researchers at UCAS, Huawei Inc., and Pengcheng Lab. It addresses the limitations of Vision Transformers (ViTs) and Convolutional Neural Networks (CNNs) by combining their strengths without inheriting their computational and representational inefficiencies. The model’s innovative Cross-Scan Module (CSM) and selective scan mechanism…
Zhipu AI unveiled GLM-4 in Beijing, a new model addressing challenges in Large Language Models. It supports a 128k token context length, achieving nearly 100% accuracy with long inputs and introducing the GLM-4 All Tools for autonomous complex task execution. Its multimodal capabilities and versatility make it a competitive choice for businesses, challenging existing models…
The rise of AI-generated deep fakes, known as “liar’s dividend,” is troubling as it impacts politics, society, and individuals. Deep fakes can distort truth and manipulate public perception, with experts struggling to reliably differentiate real from fake content. Efforts to curb deep fakes have been ineffective, raising concerns about the destabilization of truth.
CognoSpeak, developed by the University of Sheffield, is an AI tool for faster dementia and Alzheimer’s diagnosis. It analyzes speech patterns and cognitive tests, demonstrating accuracy comparable to traditional assessments. The tool is undergoing broader trials in UK memory clinics and shows potential to reduce waiting times and provide early treatment. AI supports neurological disorders…
MathVista is introduced as a comprehensive benchmark for mathematical reasoning in visual contexts. It amalgamates challenges from various multimodal datasets, aiming to refine mathematical reasoning in AI systems. Researchers from UCLA, University of Washington, and Microsoft extensively evaluate foundation models and highlight the potential of GPT-4V in achieving a state-of-the-art accuracy of 49.9%.
This text discusses the advancements in language modeling through the use of large language models (LLMs) and the challenges faced in optimizing these models for distributed training. It introduces an innovative asynchronous method that combines delayed Nesterov momentum updates and dynamic local updates, showcasing significant improvements in training efficiency for language models.