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Google’s New AI System Outperforms Physicians in Complex Diagnoses

Imagine going to the doctor with a baffling set of symptoms. Getting the right diagnosis quickly is crucial, but sometimes even experienced physicians face challenges piecing together the puzzle. Sometimes it might not be something serious at all; others a deep investigation might be required. No wonder AI systems are making progress here, as we […]

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The Good-Enough Truth

Could Shopify be right in requiring teams to demonstrate why AI can’t do a job before approving new human hires? Will companies that prioritize AI solutions eventually evolve into AI entities with significantly fewer employees? These are open-ended questions that have puzzled me about where such transformations might leave us in our quest for Knowledge and ‘truth’

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When Predictors Collide: Mastering VIF in Multicollinear Regression

In regression models, the independent variables must be not or only slightly dependent on each other, i.e. that they are not correlated. However, if such a dependency exists, this is referred to as Multicollinearity and leads to unstable models and results that are difficult to interpret. The variance inflation factor is a decisive metric for

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An LLM-Based Workflow for Automated Tabular Data Validation 

This article is part of a series of articles on automating data cleaning for any tabular dataset: Effortless Spreadsheet Normalisation With LLM You can test the feature described in this article on your own dataset using the CleanMyExcel.io service, which is free and requires no registration. What is Data Validity? Data validity refers to data

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Sesame  Speech Model:  How This Viral AI Model Generates Human-Like Speech

Recently, Sesame AI published a demo of their latest Speech-to-Speech model. A conversational AI agent who is really good at speaking, they provide relevant answers, they speak with expressions, and honestly, they are just very fun and interactive to play with. Note that a technical paper is not out yet, but they do have a

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Learnings from a Machine Learning Engineer — Part 6: The Human Side

In my previous articles, I have spent a lot of time talking about the technical aspects of an Image Classification problem from data collection, model evaluation, performance optimization, and a detailed look at model training. These elements require a certain degree of in-depth expertise, and they (usually) have well-defined metrics and established processes that are within our control. Now it’s time

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