Meet MiniChain: A Tiny Python Library for Coding with Large Language Models

The Natural Language Generation (NLG) field, situated at the intersection of linguistics and artificial intelligence, has been revolutionized by Large Language Models (LLMs). Recent advancements have led to the need for robust evaluation methodologies, with an…

Advancements in Knowledge Distillation and Multi-Teacher Learning: Introducing AM-RADIO Framework Knowledge Distillation has become a prominent technique for transferring knowledge from a “teacher” to a smaller “student” model, surpassing the teacher’s performance. This approach has extended…

Researchers from Stanford University have introduced a new deep-learning framework for tabular data called PLATO, leveraging a knowledge graph (KG) for auxiliary domain information. It regulates a multilayer perceptron (MLP) by inferring weight vectors based on…

The article discusses the use of exponential moving average in time series analysis and its application in approximating parameter changes over time. It explores the motivation behind the method, its formula and mathematical interpretation, and introduces…

Understanding the Future Token Prediction Model (FTP) The traditional design of language models like GPT faces challenges in maintaining coherent and relevant content over extended text. This issue arises because they predict one token at a…

Integrating No-Code AI in Non-Technical Higher Education Practical Solutions and Value Recent developments in ML underscore its ability to drive value across diverse sectors. To make ML more accessible to non-STEM students, a case-based approach utilizing…

OpenAI has responded to The New York Times copyright lawsuit, asserting its aim to support a healthy news ecosystem and create mutually beneficial opportunities. It believes training AI models with publicly available data is fair use.…

Neural MMO 2.0 is an advanced multi-agent environment for reinforcement learning research. It offers a flexible task system that allows users to define diverse objectives and reward signals. The platform has undergone a complete rewrite and…

The Segment Anything Model (SAM) has achieved cutting-edge outcomes in image segmentation tasks with the SA-1B visual dataset as its foundation. However, the high cost of the SAM architecture impedes practical adoption. Recent publications propose cost-effective…

The University of Hong Kong, XLang Lab, Salesforce Research, Sea AI Lab, University of Washington, and MIT CSAIL have developed Lemur and Lemur-Chat, two state-of-the-art models for language agents. By combining natural language and coding abilities,…

The Practical Solution: LongVILA for Long-Context Visual Language Models Revolutionizing Long Video Processing The challenge of enabling visual language models to process extensive contextual information in long video sequences can be addressed by LongVILA. This innovative…

TLDR This article introduces key considerations for developing non-English Retrieval Augmented Generation (RAG) systems, covering syntax preservation, data formatting, text splitting, embedding model selection, vector database storage, and generative phase considerations. The guide emphasizes the importance…

Challenges in Vision-Language Models (VLMs) Vision-language models (VLMs) struggle to generalize well beyond their training data while keeping costs low. Techniques like chain-of-thought supervised fine-tuning (CoT-SFT) often lead to overfitting, where models excel on familiar data…

Efficient Long-Context Inference with LLMs Understanding KV Cache Compression Managing GPU memory is essential for effective long-context inference with large language models (LLMs). Traditional techniques for key-value (KV) cache compression often discard less important tokens based…

ProteinZen: A New Approach to All-Atom Protein Structure Generation The Challenge Generating accurate all-atom protein structures is a complex task in protein design. While current models have improved in creating backbone structures, they struggle to achieve…

The human brain is a complex organ that processes information hierarchically and in parallel. Can these techniques be applied to deep learning? Yes, researchers at the University of Copenhagen have developed a neural network called Neural…