Welcome to the first edition of HackerNoon Projects of the Week, where we spotlight standout projects from the Proof of Usefulness Hackathon, HackerNoon’s competition designed to measure what actually matters: real utility over hype. n n Each week, we’ll highlight projects that demonstrate clear usefulness, technical execution, and real-world impact – backed by data, not buzzwords. This week, we’re excited to share three projects that have proven their utility by solving concrete problems for real users: Pantry Pilot, RecomendeMe, […]

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The life of a prescription at Amazon Pharmacy From pricing estimation and regulatory compliance to inventory management and chatbot assistants, machine learning models help Amazon Pharmacy customers stay healthy and save time and money. Conversational AI Alexandre Alves Anita Vila September 30, 01:32 PM October 02, 11:42 AM Pharmacies play a vital role in ensuring patients health, but the process of dispensing medications is far more complex than it may appear. At Amazon Pharmacy, we are using artificial […]

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AGI is here! When exactly it arrived, we’ll never know; whether it was one company’s Pro or another company’s Pro Max (Eddie Bauer Edition) that tip-toed first across the line … you may debate. But generality has been achieved, & now we can proceed to new questions. […] The key word in Artificial General Intelligence is General. That’s the word that makes this AI unlike every other AI: because every other AI was trained for a particular purpose. Consider landmark models across the decades: […]

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arXiv:2603.22302v1 Announce Type: new Abstract: With the development of information technology, the application of artificial intelligence and machine learning in the field of education shows great potential. This study aims to explore how to utilize K-means clustering algorithm to provide accurate career guidance for college students. Existing methods mostly focus on the prediction of career paths, but there are fewer studies on the fitness of students with different combinations of characteristics in specific career directions. In this study, […]

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arXiv:2602.15868v1 Announce Type: new Abstract: Large language models (LLMs) exhibit failure modes on seemingly trivial tasks. We propose a formalisation of LLM interaction using a deterministic multi-tape Turing machine, where each tape represents a distinct component: input characters, tokens, vocabulary, model parameters, activations, probability distributions, and output text. The model enables precise localisation of failure modes to specific pipeline stages, revealing, e.g., how tokenisation obscures character-level structure needed for counting tasks. The model clarifies why techniques like chain-of-thought […]

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For centuries, mathematicians worked on problems where the convergence is either smooth or does not happen. Now the concept of chaotic convergence is mainstream, popularized by the stochastic gradient descent in deep neural networks, central to LLMs. In my most recent book here, I discuss many cases involving various types of chaotic convergence. In some examples, the chaos exhibits a fractal structure. In others, patterns are strikingly similar to quantum dynamics. This article — a new addition to […]

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arXiv:2504.03097v2 Announce Type: replace Abstract: In this paper, we study the problem of multivariate shuffled linear regression, where the correspondence between predictors and responses in a linear model is obfuscated by a latent permutation. Specifically, we investigate the model $Y=tfrac{1}{sqrt{1+sigma^2}}(Pi_* X Q_* + sigma Z)$, where $X$ is an $n*d$ standard Gaussian design matrix, $Z$ is an $n*m$ Gaussian noise matrix, $Pi_*$ is an unknown $n*n$ permutation matrix, and $Q_*$ is an unknown $d*m$ on the Grassmanian manifold […]

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