Results 81 to 90 of about 63,129 (302)

AP‐Lab: An AI‐Driven Autonomous Pilot‐Scale Platform Bridging Materials Discovery and Industrial Manufacturing

Advanced Science, EarlyView.
AP‐Lab bridges materials discovery and industrial manufacturing by coupling proprietary datasets with an application benchmark (PCR Ct). A closed‐loop optimization workflow integrates ML, LLM, and autonomous synthesis/testing to refine magnetic nanoparticles–based nucleic‐acid extraction systems.
Zhan‐Long Wang, Zhifen Ma, Wenxing Song, Guolai Jiang, Boshi Jiang, Mingyang Jiang, Weiliang Shu, Bing Wang, Zhiyuan Wan, Shengyong Geng, Zhen Zhao, Wenhua Zhou, Xue‐Feng Yu   +12 more
wiley   +1 more source

An Evaluation of LLMs and Google Translate for Translation of Selected Indian Languages via Sentiment and Semantic Analyses

IEEE Access
Large Language models (LLMs) have been prominent for language translation, including low-resource languages. There has been limited study on the assessment of the quality of translations generated by LLMs, including Gemini, GPT, and Google Translate ...
Rohitash Chandra, Aryan Chaudhari, Yeshwanth Rayavarapu   +2 more
doaj   +1 more source

Electrode‐Engineered Dual‐Mode Multifunctional Lead‐Free Perovskite Optoelectronic Memristors for Neuromorphic Computing

Advanced Electronic Materials, EarlyView.
A lead‐free perovskite memristive solar cell structure that call emulate both synaptic and neuronal functions controlled by light and electric fields depending on top electrode type. ABSTRACT Memristive devices based on halide perovskites hold strong promise to provide energy‐efficient systems for the Internet of Things (IoT); however, lead (Pb ...
Michalis Loizos, Konstantinos Rogdakis, Konstantinos Chatzimanolis, Katerina Anagnostou, Emmanuel Kymakis   +4 more
wiley   +1 more source

Aligning large language models and geometric deep models for protein representation

Patterns
Summary: In this study, we explore the alignment of multimodal representations between large language models (LLMs) and geometric deep models (GDMs) in the protein domain. We comprehensively evaluate three LLMs with four protein-specialized GDMs.
Dong Shu, Bingbing Duan, Kai Guo, Kaixiong Zhou, Jiliang Tang, Mengnan Du   +5 more
doaj   +1 more source

Principles of Large Language Models (LLM)

Journal of Numerical and Applied Mathematics
This paper explores the operational principles of large language models (LLMs), focusing in particular on the mechanism of next-token generation within the process of autoregressive modeling. It outlines the theoretical foundations of neural language models, the transformer architecture with its self-attention mechanism, and the roles of tokenization ...
openaire   +1 more source

Emerging Memory and Device Technologies for Hardware‐Accelerated Model Training and Inference

Advanced Electronic Materials, EarlyView.
This review investigates the suitability of various emerging memory technologies as compute‐in‐memory hardware for artificial intelligence (AI) applications. Distinct requirements for training‐ and inference‐centric computing are discussed, spanning device physics, materials, and system integration.
Yoonho Cho, Dae‐won Kim, Yujin Kim, Jung‐Heum Na, Yuwon Jeong, Dong‐Yeop Lee, Shinhyun Choi   +6 more
wiley   +1 more source

Secret Use of Large Language Model (LLM)

Proceedings of the ACM on Human-Computer Interaction
The advancements of Large Language Models (LLMs) have decentralized the responsibility for the transparency of AI usage. Specifically, LLM users are now encouraged or required to disclose the use of LLM-generated content for varied types of real-world tasks. However, an emerging phenomenon, users' secret use of LLM ,
Zhiping Zhang, Chenxinran Shen, Bingsheng Yao, Dakuo Wang, Tianshi Li   +4 more
openaire   +2 more sources

Generative Artificial Intelligence Shaping the Future of Agri‐Food Innovation

AgriFood: Journal of Agricultural Products for Food, EarlyView.
Emerging use cases of generative artificial intelligence in agri‐food innovation. ABSTRACT The recent surge in generative artificial intelligence (AI), typified by models such as GPT, diffusion models, and large vision‐language architectures, has begun to influence the agri‐food sector.
Jun‐Li Xu, Dimitrios Argyropoulos, Tamíris da Costa   +2 more
wiley   +1 more source

Masked language models directly encode linguistic uncertainty [PDF]

, 2022
Large language models (LLMs) have recently been used as models of psycholinguistic processing, usually focusing on lexical or syntactic surprisal. However, this approach casts away representations of utterance meaning (e.g., hidden states), which are ...
Federmeier, Kara D., Hubbard, Ryan J., Jacobs, Cassandra   +2 more
core   +1 more source

Determinants of Knowledge and Usage of Generative Artificial Intelligence in Agricultural Extension: Evidence From Tennessee Extension Personnel

Agribusiness, EarlyView.
ABSTRACT This paper examines the determinants of generative AI (GenAI) knowledge and usage among agricultural extension professionals. Drawing on survey data from agricultural extension personnel in Tennessee, we employ regression analyses and latent Dirichlet allocation (LDA) for topic modeling of open‐ended responses to study the knowledge and usage ...
Abdelaziz Lawani, Jason de Koff, James Muriuki, Anna‐Liisa Ihuhwa   +3 more
wiley   +1 more source