Why choose MLY?

Explorance MLY

What is Explorance MLY

Explorance MLY is a Machine Learning solution (ML) built to enable Higher Education and HR leaders to listen at scale to the voice of students and employees.

MLY’s primary strengths are its specialized categorization and actionable insights. Built to understand the student and employee experience, the analysis results in more targeted and relevant insights with themes and terminology specific to the topic. Additionally, MLY enables the actionability of the insights through its Recommendations and Alerts models, providing a starting point for the most critical themes that arise from the data.

Overall

MLY does not create anything new, because that is not its intended purpose. It focuses on analyzing student and employee feedback to better understand the meaning and sentiment of the data – helping organizations improve their processes and experiences.

ChatGPT

What is ChatGPT

ChatGPT is a “Generative AI” solution (GenAI) that aims to create new content from scratch, based on context and websites, textbooks, and articles found on the Internet.

Intended Purpose

ChatGPT's primary strength lies in its conversational abilities, allowing users to interact with the program in diverse ways, mainly for creative purposes. However, it can mimic MLY to an extent, as the quality of results can vary depending on the prompt, leading to inconsistency in outcomes.

Overall

ChatGPT is most commonly used to create or generate something entirely new. Although the platform can imitate MLY, the results do not have the depth and precision that MLY has.

Large Language Models (LLM)

What are Large Language Models (LLM)

LLM are large deep learning (DL) models pre-trained on vast amounts of data to recognize and generate text, among other complex tasks.

Intended Purpose:

LLM are often used for a broad range of language tasks including summarization, translation, and other diverse challenges. Similarly to Explorance MLY, LLM can analyze feedback data and provide specific insights if needed. However, the models will have to undertake extensive pre-training on a diverse set of data to understand the nuances and context in the specific topics that MLY specializes in – student and employee experience.

Overall

LLM can be applied to a larger spectrum of tasks as it is not solely focused on feedback analysis. Although it can perform similar tasks to MLY, it requires training and is likely to lack the focused depth and specialization that MLY comes with.