Real-time water quality monitors with AI help assess immediate risk of illness from bacteria in southern England's swimming spots. Wessex Water's sensors accurately predict high bacteria levels 87% of the time at pilot study site Warleigh Weir.
Llama 3.1's multilingual LLMs, available on Amazon SageMaker JumpStart, offer optimized generative AI models for developers and businesses. SageMaker JumpStart provides access to pre-trained foundation models, allowing for customization and secure deployment in a dedicated VPC environment.
Elon Musk launches "world's most powerful AI training cluster" in Memphis with xAI, X, and Nvidia collaboration. Skeptics question Musk's claims amidst past issues with xAI's Grok chatbot.
Samsung's Z Flip 6 debuts with enhanced battery, camera, screen, and AI features, making it a compact clamshell powerhouse for 2024. The sleek folding phone boasts a faster chip, longer battery life, and top-tier specs, including a 6.7in FHD+ 120Hz AMOLED display and Qualcomm Snapdragon 8 Gen 3 processor.
Researchers at the University of Hull developed a method to detect AI-generated deepfake images by analyzing reflections in human eyes. This technique utilizes tools from astronomy to scrutinize the consistency of light reflections in eyeballs, potentially revolutionizing deepfake detection.
MIT CSAIL researchers developed MAIA, an automated agent that interprets AI vision models, labels components, cleans classifiers, and detects biases. MAIA's flexibility allows it to answer various interpretability queries and design experiments on the fly.
Team NVIDIA emerged victorious at the Amazon KDD Cup 2024, showcasing their expertise in generative AI across multiple challenging categories, including text generation and name entity recognition. Their innovative approach, using the Qwen2-72B LLM and QLoRA technique, outperformed competitors by fine-tuning models on eight NVIDIA A100 Tensor Core GPUs, demonstrating their ability to handle rea...
Runway's Gen-3 Alpha text-to-video synthesis model creates HD clips from prompts. It excels at mixing concepts but struggles with generalization beyond training data.
Neural network implementation for predicting income based on demographic data is complex but rewarding. Data encoding, training process, and network creation are crucial steps in achieving accurate predictions.
Meta introduces Llama 3.1 405B AI model, claiming it competes with OpenAI and Anthropic in various tasks. The new open-source system is set to challenge established competitors in the AI field.
MIT engineers have identified new materials for fast proton conduction, essential for clean energy technologies like fuel cells. Current high-temperature inorganic materials may be replaced by lower-temperature alternatives for more efficient and durable applications.
Researchers from MIT and ETH Zurich developed an AI model to identify different stages of DCIS from breast tissue images, potentially streamlining diagnosis and treatment. By analyzing the spatial organization of cells, the model could help clinicians predict which DCIS cases may progress to invasive cancer, paving the way for more efficient and personalized care.
Machine-learning models can improve fairness by introducing randomization, preventing systemic injustices in resource allocation. Researchers from MIT and Northeastern University present a framework for introducing randomization without sacrificing efficiency or accuracy.
LightGBM used for anomaly detection in Autoencoder class. Models predict values based on other columns to identify anomalies.
AI and accelerated computing by NVIDIA are enhancing energy efficiency across industries, recognized by Lisbon Council Research. Transitioning to GPU-accelerated systems can save over 40 terawatt-hours of energy annually, with real-world examples like Murex and Wistron showcasing significant gains in energy consumption and productivity.