[R] An open source dataset of aesthetic image variations (Apache 2.0)

[R] An open source dataset of aesthetic image variations (Apache 2.0)

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Paper: https://arxiv.org/pdf/2602.01666 Dataset: https://huggingface.co/datasets/moonworks/lunara-aesthetic-image-variations Colab notebook: https://colab.research.google.com/drive/1xrtJNS4rljgVa_6UKCuanyS2syJ0QZ7b After part I saw many downloads on huggingface, we’re now sharing part II. While part I focused on aesthetic art styles, part II focuses on contextual variations, a key component of learning in Moonworks Lunara model. The dataset consists of original images and artwork created by Moonworks and their aesthetic contextual variations generated by Lunara, a sub-10B model with diffusion mixture architecture. We hope the dataset can be used to train […]

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The life of a prescription at Amazon Pharmacy

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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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ContextCite: Attributing Model Generation to Context

ContextCite: Attributing Model Generation to Context

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   Code     Demo     Paper Language models may need external information to provide a response to a given query. A user would provide this information to a language model as context and then expect the model to interact with this context when responding to the query. For example, suppose that I want to use an AI assistant like ChatGPT to help me plan a trip to see a solar eclipse this week. I would first […]

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Researchers Use Diffusion Models to Simulate DOOM Gameplay in Real Time

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Table of Links ABSTRACT 1 INTRODUCTION 2 INTERACTIVE WORLD SIMULATION 3 GAMENGEN 3.1 DATA COLLECTION VIA AGENT PLAY 3.2 TRAINING THE GENERATIVE DIFFUSION MODEL 4 EXPERIMENTAL SETUP 4.1 AGENT TRAINING 4.2 GENERATIVE MODEL TRAINING 5 RESULTS 5.1 SIMULATION QUALITY 5.2 ABLATIONS 6 RELATED WORK 7 DISCUSSION, ACKNOWLEDGEMENTS AND REFERENCES 2 INTERACTIVE WORLD SIMULATION An Interactive Environment E consists of a space of latent states S, a space of partial projections of the latent space O, a partial projection […]

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20 Must Visit SQL Questions For Interviews

20 Must Visit SQL Questions For Interviews

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Author(s): Ananya Originally published on Towards AI. Q1. Find the total number of orders placed by a customer (101) in a day. Table: Order_Details cust_id | order_id | order_date Code: select date_trunc(‘day’, order_date) as day, cust_id as customers count(distinct order_id) as orders from Order_Details where cust_id = 101 group by 1 Q2. Find the Monthly Cart Conversion Rate for a store with store code ‘APJ’ Event can be add_to_cart or checkout — item is added to cart and […]

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Best B2B Data Providers in 2026

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In a modern company, business-to-business (B2B) data empowers both marketing and sales teams to reach the right audience and convert leads, but to nail it, you need the right vendor. That’s why this guide will look into the ten best B2B data providers that can fuel your business strategy and help you expand your customer base. Key takeaways Top B2B data vendors go beyond professional contacts and provide multi-point firmographics, technographics, chronographic data, and intent signals. Most providers […]

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Apple unites with Google for the first time to fix its AI problem, using Gemini

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Google and Apple are one of the top rivals in the tech industry. In the past, both companies have fired shot at each other through their software, smartphones or ecosystems. However, there’s one department in which Google is absolutely dominating Apple. Well, I’m talking about AI here. Apple’s AI effort has been a flop all this while. The company’s latest iPhone come with some sprinkle of AI features, but they are nowhere when it comes to Gemini. Apple […]

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Object Detection Part 4: Fast Detection Models

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In Part 3, we have reviewed models in the R-CNN family. All of them are region-based object detection algorithms. They can achieve high accuracy but could be too slow for certain applications such as autonomous driving. In Part 4, we only focus on fast object detection models, including SSD, RetinaNet, and models in the YOLO family.

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[R] I solved CartPole-v1 using only bitwise ops with Differentiable Logic Synthesis

[R] I solved CartPole-v1 using only bitwise ops with Differentiable Logic Synthesis

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Bitwise CartPole-v1 controller getting perfect score Yeah I know Cart Pole is easy, but I basically distilled the policy down to just bitwise ops on raw bits. The entire logic is exactly 4 rules discovered with “Differentiable Logic Synthesis” (I hope this is what I was doing): rule1 = (angle >> 31) ^ 1 rule2 = (angular >> 31) ^ 1 rule3 = ((velocity >> 24) ^ (velocity >> 23) ^ (angular >> 31) ^ 1) & 1 […]

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SPD Learn: A Geometric Deep Learning Python Library for Neural Decoding Through Trivialization

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Implementations of symmetric positive definite (SPD) matrix-based neural networks for neural decoding remain fragmented across research codebases and Python packages. Existing implementations often employ ad hoc handling of manifold constraints and non-unified training setups, which hinders reproducibility and integration into modern deep-learning workflows. To address this gap, we introduce SPD Learn, a unified and modular Python package for geometric deep learning with SPD matrices. SPD Learn provides core SPD operators and neural-network layers, including numerically stable spectral operators, […]

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