Stop Tuning Your Prompts, Start Tuning Your Eigenvalues
Why the “hidden dimension” of your model is broken, and how Singular Value Decomposition explains why your prompts don’t work Continue reading on Towards AI »
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Hierarchical Federated Learning with SignSGD: A Highly Communication-Efficient Approach
Hierarchical federated learning (HFL) has emerged as a key architecture for large-scale wireless and Internet of Things systems, where devices communicate with nearby edge servers before reaching the cloud. In these environments, uplink bandwidth and latency impose strict communication limits, thereby making aggressive gradient compression essential. One-bit methods such as sign-based stochastic gradient descent (SignSGD) offer an attractive solution in flat federated settings, but existing theory and algorithms do not naturally extend to hierarchical settings. In particular, the […]
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The Remote Developer’s Survival Guide: 10 Technical Strategies to Prevent Burnout
Software development is a very stressful job. There is so much to learn and so little time. Anxiety and fear of missing out make you feel like no matter how hard you work to stay ahead, it will never manage to catch up. Remote work has transformed the landscape of software development, offering unprecedented flexibility and autonomy. Yet this very freedom can become a double-edged sword, leading to isolation, blurred boundaries, and ultimately, burnout. With statistics showing that up […]
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Schr”odinger bridge problem via empirical risk minimization
arXiv:2602.08374v1 Announce Type: new Abstract: We study the Schr”odinger bridge problem when the endpoint distributions are available only through samples. Classical computational approaches estimate Schr”odinger potentials via Sinkhorn iterations on empirical measures and then construct a time-inhomogeneous drift by differentiating a kernel-smoothed dual solution. In contrast, we propose a learning-theoretic route: we rewrite the Schr”odinger system in terms of a single positive transformed potential that satisfies a nonlinear fixed-point equation and estimate this potential by empirical risk minimization […]
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The life of a prescription at Amazon Pharmacy
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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A Semi-Supervised Pipeline for Generalized Behavior Discovery from Animal-Borne Motion Time Series
arXiv:2602.02618v1 Announce Type: new Abstract: Learning behavioral taxonomies from animal-borne sensors is challenging because labels are scarce, classes are highly imbalanced, and behaviors may be absent from the annotated set. We study generalized behavior discovery in short multivariate motion snippets from gulls, where each sample is a sequence with 3-axis IMU acceleration (20 Hz) and GPS speed, spanning nine expert-annotated behavior categories. We propose a semi-supervised discovery pipeline that (i) learns an embedding function from the labeled subset, […]
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A Guide to One-Shot Learning
Passport checks at airports, automatic turnstiles in office centers, signature verification – all these tasks require face or object recognition. Historically, deep learning algorithms use a lot of labeled training data for simple tasks like identifying objects in photos or recognizing faces. But in the above situations, we normally do not possess a large variety of photos for each person for training the AI. Therefore, we need an ML algorithm that would be able to perform recognition with […]
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OpenAI Closes Historic $110 Billion Funding Round Backed by Amazon, NVIDIA, and SoftBank
OpenAI is one of the biggest AI companies to exist at this point, with rivals like Google, Anthropic, Meta, and others competing alongside it. However, OpenAI now has what it takes to scale its AI footprint and push even further toward excelling in the race for AI models. Here, we are talking about investment, and that too a massive one. As reported earlier this month, Sam Altman-led OpenAI today announced that it has closed one of the biggest […]
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[R] K-Splanifolds: Advancing General Purpose Regression with Linear-Time Parametric Spline Manifolds
I cooked up a new fast geometric regression algorithm and show that it is a suitable replacement for MLPs. Check out the paper: https://doi.org/10.5281/zenodo.18673034 Whats inside? New research indicates that many representations within LLMs create geometric structures to model language. ( https://arxiv.org/abs/2601.04480 , https://arxiv.org/abs/2510.26745 ) MLPs store geometric representations in highly inefficient ways, so I say it is time to look for new methods that encode regressions directly in geometry. Enter K-Splanifolds, a fast high dimensional spline manifold […]
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The AI Agent Revolution: How to Build the Workforce of Tomorrow
For your convenience, all the code and instructions on how to run each Python script are provided in the following repository: https://github.com/thomascherickal/ai-agents-examples If you want to get the full hands-on experience, simply run the following command in the terminal: git clone https://github.com/thomascherickal/ai-agents-examples.git And follow the instructions in the README.MD to get started. Linux is the best platform to do this, and you will need an OpenAI API key and other API keys as well. Introduction to AI Agents […]
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