This AI Paper from China Developed an Open-source and Multilingual Language Model for Medicine
Recent advancements in healthcare leverage LLMs like GPT-4, MedPalm-2 and open-source alternatives such as Llama 2. While these models, including PMC-LLaMA, MedAlpaca, and ChatDoctors, excel in English-language applications and even…
Deciphering the Impact of Scaling Factors on LLM Finetuning: Insights from Bilingual Translation and Summarization
The intricacies in unlocking the latent potential of Large Language Models (LLMs) for specific tasks remain a complex challenge even after all the state-of-the-art achievements these models have shown throughout…
Jeff Vogt joins Alaska Communications as Chief Operating Officer
Alaska Communications, a leading connectivity solutions provider to the Alaska consumer and business markets, is pleased to welcome industry leader Jeff Vogt as chief operating officer. Vogt will report to…
This Machine Learning Paper Presents a General Data Generation Process for Non-Stationary Time Series Forecasting
One of the cornerstone challenges in machine learning, time series forecasting has made groundbreaking contributions to several domains. However, forecasting models can’t generalize the distribution shift that changes with time…
Google DeepMind Introduces Two Unique Machine Learning Models, Hawk And Griffin, Combining Gated Linear Recurrences With Local Attention For Efficient Language Models
Artificial Intelligence (AI) and Deep Learning, with a focus on Natural Language Processing (NLP), have seen substantial changes in the last few years. The area has advanced quickly in both…
Redefining Compact AI: MBZUAI’s MobiLlama Delivers Cutting-Edge Performance in Small Language Models Domain
In recent years, the AI community has witnessed a significant surge in developing large language models (LLMs) such as ChatGPT, Bard, and Claude. These models have demonstrated exceptional capabilities, from…
Can AI Think Better by Breaking Down Problems? Insights from a Joint Apple and University of Michigan Study on Enhancing Large Language Models
In the rapidly evolving field of artificial intelligence, the development and application of large language models (LLMs) stand at the forefront of innovation, offering unparalleled data processing and analysis capabilities.…
Automated Prompt Engineering: Leveraging Synthetic Data and Meta-Prompts for Enhanced LLM Performance
Engineering effective prompts for LLMs is crucial yet challenging due to their sensitivity to prompts and the ambiguity of task instructions. Recent studies propose using meta-prompts that learn from past…
Microsoft Researchers Propose ViSNet: An Equivariant Geometry-Enhanced Graph Neural Network for Predicting Molecular Properties and Simulating Molecular Dynamics
Researchers from Microsoft attempt to solve the challenge faced in predicting molecular properties and simulating molecular dynamics by presenting a method, ViSNet, that results in more accurate predictions. Predicting molecular…
Efficiently Processing Extended Contexts in Large Language Models: Dual Chunk Attention for Training-Free Long-Context Support
From producing writing that resembles that of a human being to comprehending subtleties of language, Large Language Models (LLMs) have played a key role in attaining state-of-the-art performance in various…