IoT

Business-to-business (B2B) payments can be a complex task for many businesses. Traditional payment methods often involve dealing with a myriad of processing options and managing numerous accounts, vendors, and payment recipients. Integrated payables address this issue by streamlining and simplifying the payment process into a single-source platform. Integrated payables are a technological solution for payment processing…

The process of managing B2B payments has become increasingly complex with the need to handle cross-border transactions, myriad payment processing options, and the task of keeping all these straight and error-free. This issue affects a range of payment recipients and vendors. However, technological innovations are simplifying this process through the implementation of integrated payables. These…

Understanding and addressing users’ needs and struggles are essential for business success. A specific type of survey - churn surveys, designed for customers who have stopped using a service, can provide a wealth of insights into customer behavior. But the real value comes from turning these insights into actions that drives sustainable growth and revenue. One…

The article "Language processing in humans and computers: Part 2" by Dusko Pavlovic discusses chatbots, their origins, functioning, and the challenges they face. The author compares chatbots to search engines, both of which are built on web crawlers and process data scraped from the web. Chatbots, unlike search engines, are an interface of a language…

This article discusses five ways to use large language models (LLMs) locally to maintain data privacy and easily generate context-aware responses. Using these models allows you to bypass online use, where your privacy may be compromised, and operate on your laptop without external tracking. The first software is GPT4ALL, an open-source tool that facilities easy download…

Linear regression, a common teaching tool in data science, can be ineffective in complex modeling scenarios. This article introduces a solution to improve the application: penalization or regularization techniques, specifically, the elastic net regression. This method involves using a blend of ridge and lasso regression penalties. Ridge and lasso regression are regularization methods used in data…

This blog explains how to improve Large Language Models (LLMs) with Retrieval-Augmented Generation (RAG) using an innovative Python library called LlamaIndex. The author first shows the necessary Python libraries and their related installation commands. The next step is to set up the knowledge base, which involves defining various parameters for the embedding model, chunk size,…

Anthropic has recently unveiled its new series of AI models – Claude 3. These models have performed exceptionally well during benchmark tests, surpassing other models such as GPT-4 and Gemini. Claude 3 models are highly advanced large language models (LLMs) presented in three variants: Haiku, Sonnet, and Opus. Each variant comes with unique traits and…

In recent years, researchers have increasingly applied natural language processing (NLP) techniques to the field of time series. Large language models (LLMs) have made a significant impact in NLP with their reasoning capabilities and generalization. Efforts have started to repurpose these LLMs for time series forecasting, leading to the creation of Time-LLM. Time-LLM, rather than being…