This particular blog talks about the math and AI intersection, AI and maths I am writing particular blogs that will provide information on the latest trends in this field
New mathematical model could ensure the safer use of AI and help protect privacy
Researchers at Imperial College London are trying to create a mathematical model to predict the risk of AI This model provides a scientific framework to system evaluate AI identification on a large scale. The goal is to balance data sharing for research and safeguard personal privacy.
Vanguards of HPC-AI: Sandia’s Erin Acquesta, Extroverted Mathematician and Emerging Leader
This blog tells about how a research scientist at Sandia National Laboratories began her career in HPC-AI as a data scientist and Sandia in 2016. she says that science and technology are interdependent each showing its potential and underscoring the other and also explains that the mathematical foundation behind AI
AI-paper-explores-quantization-techniques-and-their-impact-on-mathematical-reasoning-in-large-language-models
This article talks about how large language models are efficient in mathematical reasoning .it also talks about a system of evaluation of how the quantization affects the reasoning abilities on Math benchmark that gives step-by-step solution
Microsoft AI Introduces rStar-Math: A Self-Evolved System 2 Deep Thinking Approach that Significantly Boosts the Math Reasoning Capabilities of Small LLMs
This article talks about how Microsoft introduces the new star-Math a system designed to enhance the mathematical reasoning of small language models This star-Math lies in its ability to boost capabilities that challenge smallels to make them improved versions.
AI vs. supercomputers: New AI-based method solves complex equations faster and uses less computing power
This part talks about how the innovative approach not only accelerates problem-solving but also reduces computing power usage.it is more efficient than and faster than conventional supercomputing methods.
Elon Musk says AI has already gobbled up all human-produced data to train itself and now relies on hallucination-prone synthetic data
In this part, Elon shares that AI has consumed all available human data . Due to this he warns that it is risk that they can be hallucinating more than oftentimes
