In machine learning and data science, feature selection techniques are used often to find the most relevant attributes defining the data. What are the features of data? The data for use in Machine Learning is typically in the form of rows and columns. The rows define the values for a particular observation, while the columnsContinue reading “Feature Selection — I”
Category Archives: AI
Linear Regression for Data in Python
First the code then a description of the key points concerning Linear Regression. Let us consider the colon cancer data. The data has been taken in csv form. Here is a code in Python to compute Linear Regression based computations. The code wraps up all the internal processing behind Linear Regression. import pandas as pdimportContinue reading “Linear Regression for Data in Python”
Are Generative Models Mugging Parrots?
#AI #Generative_Models Some say these complex deep learning models are mere stochastic mugging parrots. Well, what is the answer? Yes or not exactly. Let’s argue about it. If you take one or two layers in the learning model, then you can say that yes there is some kind of mugging. But here in live models,Continue reading “Are Generative Models Mugging Parrots?”
The Master Robots: AI and Tech
#futurist #future #scific #ai #artificialintelligence This article presents soon-to-come robots. This is based on current developments in AI and Robotics. All these are possibilities for the future of Robotics, AI, and Tech. The future may not be exactly the same for these Robotics applications but somewhat may revolve around these facts as explained here inContinue reading “The Master Robots: AI and Tech”
Solution to Owning Arts — Traditional Artist versus Digital and AI Artist
Summary: In case artists are working in collaboration, one is a traditional artist and another is digital artist or AI artist, both can collaborate to make the art reach new heights with joint ownership and no tension of copywriting. This is a plausible solution to the future of artwork. This would need a platform whereContinue reading “Solution to Owning Arts — Traditional Artist versus Digital and AI Artist”
The Good AI and the Bad AI — Part I
Here is a description of what constitutes a Good AI and what forms part of the Bad AI. There has been tremendous progress in AI, irrespective of the fact that it is a good AI or it is a potentially harmful AI. Let us discuss what is in good AI and what is in badContinue reading “The Good AI and the Bad AI — Part I”
Causal Reasoning and LLM Paper Review
The following paper is discussed in this article. Causal Reasoning and Large Language Models: Opening a New Frontier for Causality. Kıcıman and Ness et al. (2023) Paper Review Causality — The automatic detection relationship between cause and effect. For illustration, consider two concepts that are discussed in some text, say medical text. Let the conceptsContinue reading “Causal Reasoning and LLM Paper Review”
80000 tested GPT but where are the test cases? Testing not enough, use test cases to train new GPT and automate testing
In an article it was relieved that 80000 Google Employees tested its GPT, which still makes errors in outputs. Now there are some key points. These points can be used on any GPT testing, not necessarily of capacity of 80000. When someone makes testing which is so huge, 80000 is a huge number, then oneContinue reading “80000 tested GPT but where are the test cases? Testing not enough, use test cases to train new GPT and automate testing”
Genetic Algorithm for Information Retrieval (Python): Introduction
Genetic Algorithm (GA) Genetic Algorithm is one of the nature inspired algorithm which works on Darwins theory of survival of fittest. The key operators that we have in Genetic Algorithms are These three operators also forms the basis reproduction and subsequent workings in natural process be it be in human biology or in botony andContinue reading “Genetic Algorithm for Information Retrieval (Python): Introduction”
80000 tested Google Bard, but what were results? Why it was prematurely released?
#AI #ProjectManagement Google leaders says 80,000 google employees tested Google AI Bard. But then what were results ? What was recall and precision? And if it was bad why was it released to use as a full fledged product? Why warnings are laid out now, that it wont work well? As now you know itContinue reading “80000 tested Google Bard, but what were results? Why it was prematurely released?”
Artificial Intelligence, Computer Science & Mathematics 