Large language model
Researchers from Stanford University have developed two advanced pose-sampling protocols, GLOW and IVES, which enhance molecular docking by improving accuracy in ligand binding poses. These protocols outperform basic methods, particularly in challenging scenarios and when dealing with AlphaFold benchmarks. IVES can generate multiple protein conformations, which is advantageous for geometric deep learning. Additionally, GLOW and…
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The recent report from ResumeBuilder indicates that 37% of business leaders have witnessed AI replacing workers in their companies in 2023, while Asana’s research highlights the potential for AI to automate 29% of employees’ tasks. Various experts offer perspectives on the impact, with discussions around AI’s potential to create higher-value work and promote “human-centered AI.”…
The EU’s historic AI Act established a legal framework with varying levels of scrutiny based on risk categories. Concerns were raised about its impact on European competitiveness, especially for generative AI. Public reactions and industry responses have been mixed, reflecting concerns about stifling innovation and the EU’s ability to compete globally in the tech industry.
The article discusses the advancements in Natural Language Processing (NLP) with a focus on Large Language Models (LLMs) and their application in the medical field. It outlines the popularity and challenges of medical LLMs, and a study’s five main questions, aiming to improve the design and application of medical LLMs. The study encourages in-depth analysis…
Upstage introduces Solar-10.7B, a groundbreaking language model with 10.7 billion parameters, balancing size and performance. It employs the Llama 2 architecture and Upstage Depth Up-Scaling technique, outperforming larger models. The fine-tuned SOLAR-10.7B-Instruct-v1.0 excels in single-turn conversations with a Model H6 score of 74.20, showcasing adaptability and efficiency. This marks significant advancements in language model development.
OpenAI has partnered with Axel Springer to provide global news summaries to ChatGPT users, aiming to support independent journalism in the age of AI. The partnership will offer content from media brands, including Politico and Business Insider, and address concerns about biased news and the impact of AI on journalism. This signifies a new approach…
Kinara introduces the Ara-2 processor, boasting eightfold performance improvement over its predecessor. It caters to large language models and generative AI on-device, offering distinct functionalities. Ara-2 enhances object detection, recognition, and tracking, and is anticipated to outperform graphics processors. Kinara plans to unveil multiple iterations of the Ara-2 processor at CES 2024.
Large language models like GPT-3 require substantial energy for training and operational needs, with varying consumption based on factors such as size and task complexity. Researchers at the University of Michigan and the University of Washington have introduced Perseus, an optimization framework to minimize excessive energy consumption without compromising model efficiency, offering potential sustainability benefits.…
This study addresses the complex challenge of enhancing real-world video quality by introducing a local-global temporal strategy within a latent diffusion framework. Incorporating text prompts and noise manipulation, the model achieves state-of-the-art video super-resolution performance with remarkable visual realism and temporal coherence. The approach demonstrates significant potential for advancing video enhancement technology.
Researchers at UC Santa Cruz have developed “snnTorch,” an open-source Python library simulating spiking neural networks inspired by the brain’s efficient data processing. With over 100,000 downloads and applications in NASA projects and chip optimization, the library also provides educational resources for brain-inspired AI enthusiasts, marking a transformative phase in computational paradigms.
NVFi addresses the challenge of understanding and predicting dynamics in evolving 3D scenes critical for augmented reality, gaming, and cinematography. Existing models struggle to learn these properties from multi-view videos. NVFi aims to bridge this gap by incorporating disentangled velocity fields from multi-view video frames, showcasing proficiency in future frame prediction and scene decomposition.
Google Researchers have introduced MedLM, a foundation of models fine-tuned for healthcare. It consists of two models with separate endpoints, offering flexibility for different use cases. MedLM has collaborated with organizations like HCA Healthcare, BenchSci, Accenture, and Deloitte to improve performance and efficiency in healthcare projects. Google plans to expand MedLM suite for more capabilities,…
Researchers address the diagnostic complexity and therapeutic challenges of combined hepatocellular-cholangiocarcinoma (cHCC-CCA) through the application of artificial intelligence (AI). Their study explores the potential of AI to reclassify cHCC-CCA tumors as either pure hepatocellular carcinoma (HCC) or intrahepatic cholangiocarcinoma (ICCA), offering improved prognostication and molecular insights. The AI model demonstrates high efficacy in discerning between…
RAND Corporation, linked to tech billionaires’ funding networks, had significant involvement in drafting President Biden’s AI executive order. The order, influenced by effective altruism, introduced comprehensive AI reporting requirements. RAND’s ties to Open Philanthropy and AI enterprises have raised concerns about potential research skewing. The AI industry’s intersection with effective altruism, commercialization, and ethics remains…
The text discusses the application of various outlier detection algorithms to batting statistics from the Major League Baseball’s 2023 season. The algorithms compared are Elliptic Envelope, Local Outlier Factor, One-Class Support Vector Machine, and Isolation Forest. The analysis provides insights into player performance and identifies outliers based on metrics such as on-base percentage (OBP) and…
The article provides a comprehensive overview of modern data warehouse solutions, including their benefits over other data platform architectures. It emphasizes the importance of flexible data processing, scalability, and improved business intelligence. The article also discusses the integration of these solutions with various tools and platforms, as well as DevOps practices for data pipelines.
The article discusses visualizing bi-directional trade flow between countries using Python maps. It covers the process from finding coordinates of arrows to creating necessary dictionary objects, along with detailed code snippets. The author plans to demonstrate visualizing net trade flow in the second part of the series. The article provides a comprehensive guide for Python-based…
The article discusses the challenges and solutions for optimizing the performance and cost of running Large Language Models (LLMs). It highlights the high expenses of using OpenAI APIs and the trend of companies hosting their own LLMs to reduce costs. The focus is on algorithmic improvements, software/hardware co-design, and specific techniques such as quantization, attention…
The text delves into the idea of using Taylor Series and Fourier Series as alternatives to neural networks. It emphasizes their application in approximating functions and their similarities to neural network structures. The author discusses the limitations of Taylor and Fourier Series and why neural networks are still essential. The piece also promotes the author’s…