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…

LangChain is an AI framework for developers to create applications using large language models. Here’s a step-by-step guide on how to use it. Set up the environment, integrate with model providers, use prompt templates, chain multiple models, deploy agents and tools, handle memory, load documents, organize with indexes. Source: MarkTechPost.

Ola CEO Bhavish Aggarwal unveiled ‘Krutrim AI’, a groundbreaking full-stack AI solution in India. The platform excels in understanding and generating content in 20 Indian languages, setting new linguistic inclusivity standards. With a vast training process, it surpasses GPT-4 in supporting Indic languages, heralding a new chapter in AI-driven innovation and cultural expression in India.

AI tools are revolutionizing the HR sector by enhancing efficiency and productivity. Some notable options include JuiceBox, offering AI-powered candidate sourcing and email templates; VanillaHR, providing AI analytics and video interviews; SkillPool, which automates resume screening; Arc, an AI-powered remote job marketplace; HollyHires for talent sourcing; Attract.ai, enabling diverse candidate discovery; and ChatGPT, which aids…

Researchers from Tsinghua Shenzhen International Graduate School, Shanghai AI Laboratory, and Nanyang Technological University have developed RTMO, a one-stage pose estimation framework that combines coordinate classification and dense prediction models to enhance accuracy and efficiency. RTMO achieves higher Average Precision on COCO and real-time performance, outperforming existing methods. More details in the paper https://arxiv.org/abs/2312.07526v1.

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 KG node similarity, addressing the challenge of high-dimensional features and limited samples. PLATO outperforms 13 baselines by up to…

Microsoft’s new Medprompt technique boosts GPT-4 to edge out Google’s Gemini Ultra on MMLU benchmark tests by a narrow margin. The technique involves dynamic few-shot learning, self-generated chain of thought prompting, and choice shuffle ensembling, proving older AI models can surpass expectations when prompted cleverly. The approach offers exciting possibilities but may require additional processing…

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 bias correction to overcome initial approximation challenges. The technique’s wide application scope and relevance in gradient descent algorithms are…

Researchers from Tencent AI Lab and The Chinese University of Hong Kong have introduced architectural guidelines for large-kernel CNNs. UniRepLKNet, a ConvNet model following these guidelines, excels in image recognition, time-series forecasting, audio recognition, and learning 3D patterns in point cloud data. The study also introduces the Dilated Reparam Block for enhancing large-kernel conv layers.