Guest post by Alex Nikic In the past few years, Generative AI technology has advanced rapidly, and businesses are increasingly adopting it for a variety of tasks. While GenAI excels at tasks such as document summarisation, question answering, and content generation, it lacks the ability to provide reliable forecasts for future events. GenAI models are not designed for forecasting, and along with the tendancy to hallucinate information, the output of these models should not be trusted when planning key business decisions. For more details, a previous article on our blog explores in-depth the trade-offs of GenAI vs Traditional Machine Learning approaches.
This new video explains natural language processing: what it is, how it works, and what can it do for your organisation. Natural Language Processing (NLP) is a branch of Artificial Intelligence (AI) that focuses on giving computers the ability to understand human language, combining disciplines like linguistics, computer science, and engineering.
This free A/B test calculator will help you compare two variants of your website, A and B, and tell you the probability that B is better. You can read more about A/B testing in our earlier blog post on the subject. You may also be interested in our Chi-Squared sample size calculator which will help you calculate the minimum sample size needed to run a Chi-Squared test, given an expected standardised effect size.
See also: Fast Data Science A/B test Calculator (Bayesian) A/B testing is a way you can test two things, Thing A, and Thing B, to see which is better. You most commonly hear about A/B testing in the context of commercial websites, but A/B testing can be done in a number of different contexts, including offline marketing, and testing prices.
Explainable AI for Businesses Guest post by Vidhya Sudani Introduction AI is moving rapidly and it can be hard to understand how an AI model works and what decisions it makes. Businesses are increasingly turning to Explainable AI (XAI) to demystify the “black box” nature of traditional machine learning models.
You are probably familiar with traditional databases. For example, a teacher at a school will need to enter students’ grades into a system where they get stored, and at the end of the year the grades would need to be retrieved to create the report card for each student. Or an employee database might store employees’ home addresses, pay grades, start dates, and other crucial information. Traditionally, organisations use a structure called a relational database, where different types of data are stored in different tables, with links between them, and they can be queried using a special language called SQL.
A problem we’ve come across repeatedly is how AI can be used to estimate how much a project will cost, based on information known before the project begins, or soon after it starts. By “project” I mean a large project in any industry, including construction, pharmaceuticals, healthcare, IT, or transport, but this could equally apply to something like a kitchen renovation. This is a very typical business application of AI.
What is generative AI consulting? We have been taking on data science engagements for a number of years. Our main focus has always been textual data, so we have an arsenal of traditional natural language processing techniques to tackle any problem a client could throw at us.
Image above: the winning teams and participants in the Harmony AI hackathon on 3 June 2024 AI Hackathons: A Playground for Innovation What is an AI hackathon? A hackathon is an event that may last for a day or several days where people collaborate to solve a problem. The word “hackathon” is a portmanteau of “hack” and “marathon”. The first hackathon was held in 1999 by OpenBSD in Calgary, Canada[1]. Initially, hackathons were used for software development problems, but now organisations are running hackathons for a much more eclectic range of tasks, such as planning the marketing strategy of a nonprofit, and now there are AI hackathons.
What we can do for you
