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Why can't AI do Math?
New research explains why AI is. not good at math
Chester Beard
September 26, 2024
News
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AI For Good
Insecticide-treated bed nets have been the primary vector control intervention for malaria prevention since their widespread implementation in the 1990s. Despite this, the World Health Organization continues to report significant annual morbidity and mortality rates, with hundreds of millions of cases and hundreds of thousands of deaths attributed to malaria globally.
Zzapp Malaria is pioneering an innovative approach by leveraging artificial intelligence to enhance malaria control strategies.
Technical implementation:
The company has developed a sophisticated AI-driven software ecosystem, comprising a central analytical engine interfaced with a mobile application. This system employs advanced machine learning algorithms to process high-resolution satellite imagery and topographical data, enabling precise geospatial modeling of mosquito population dynamics and identifying malaria transmission hotspots with high accuracy.
Key features and outcomes:
* The AI engine generates optimized, location-specific vector control protocols, which are disseminated in real-time to field operatives via the mobile interface, facilitating rapid and targeted interventions.
* In a proof-of-concept deployment on São Tomé Island over an eight-month period, the Zzapp system demonstrated remarkable efficacy:
- 75% reduction in local mosquito population density
- 52% decrease in malaria case incidence
Cost-effectiveness analysis indicates that the Zzapp system achieves a 2:1 improvement in resource utilization compared to traditional bed net distribution strategies.
This revised version uses more technical language and provides a bit more detail on the AI system's functionality, making it more suitable for a technically-inclined audience. Would you like me to adjust anything further?
Prompt
Thin picture frame in the center, standing on floor in tokyo loft
--no plants--ar 3:4--style raw--v 6.1
Non-Image Prompt
Prompt: I want you to act as a text based excel. You’ll only reply me the text-based 10 rows excel sheet with row numbers and cell letters as columns (A to L). First column header should be empty to reference row number. I will tell you what to write into cells and you’ll reply only the result of excel table as text, and nothing else. Do not write explanations. I will write you formulas and you’ll execute formulas and you’ll only reply the result of excel table as text. First, reply me the empty sheet.
Researching Why LLMs struggle with Math
Large language models (LLMs) have made remarkable strides in recent years, yet they still face challenges with math word problems. While many studies have focused on evaluating LLMs' performance in this area, exciting new research from the Mohamed Bin Zayed University of Artificial Intelligence (MBZUAI) is shedding light on why LLMs struggle with these problems, paving the way for future improvements.
The details: Researchers at MBZUAI tested various open-source LLMs on complex math word problems, particularly those requiring real-world knowledge and multi-step solutions.
* The study identified specific areas where LLMs face difficulties, providing valuable insights for future enhancements.
* Lengthy problems with "low readability scores" and those requiring real-world knowledge were found to be particularly challenging for current LLMs.
* Problems involving a large number and diversity of mathematical functions also proved difficult for the models to solve accurately.
Why it matters: This research not only highlights the current limitations of LLMs underlying popular chatbots but also opens up promising avenues for improvement. As the concept of GenAI math tutors gains traction, these findings could guide the development of more effective and capable AI systems in educational settings.
The insights from this study offer a roadmap for researchers and developers to enhance LLMs' mathematical reasoning capabilities. By addressing the identified weaknesses, future iterations of AI models could potentially overcome these hurdles, leading to more robust and reliable AI-assisted learning tools.
To learn more about MBZUAI's groundbreaking research and its implications for the future of AI in education, visit their website.
