ViewTube

1. We've covered how Ai Consultants create and build with Ai, but once the building is done, how do they use Ai to optimize and ...

MobileLLM from Meta is full of great lessons! The paper focuses on methods for an efficient architecture for mobile LLMs It ...

In this episode of *SciPulse,* we dive into a rigorous study investigating whether Large Language Models (LLMs) can truly ...

This is an introduction of the Julia language from the inter-discipline angle between Maths, Computer Science, Supercomputing, ...

Pricing optimization is a data science use case that is growing. In some areas, like many states in the United States, it is not ...

In this episode of SciPulse, we explore a major breakthrough in Transformer architecture: GRAPE (Group RepresentAtional ...

https://arxiv.org/pdf/2603.28052.

Exciting Journey from AI to Mathematics in Price Prediction! Hello LinkedIn community! I'm thrilled to share a new milestone in ...

... with the students that the letters in math are called variables and they uh can just they're like a mystery number that changes uh ...

Do you work with PyTorch? Would you like to have smarter, smaller, cheaper ML models? Would you like to have them today ...

Welcome to SciPulse. In this episode, we dive into a revolutionary research paper that challenges the necessity of expensive ...

Machine learning is tough, but you can learn it faster with the right approach. In this video, I share four key tips to help you to ...

Project Title: Data-Driven Clinician Scheduling Under Resource Uncertainty ‍⚕️ What's the Problem? Clinicians are pulled ...

... training setup you always be somewhere in between but this is like the optimization pressure that the mo that the model is under ...

In this video, I walk you through a real-world optimization problem step-by-step using inequalities, graphing, feasible regions, ...

Your model performs great on training data, but crashes on unseen data. Why? Welcome to Chapter 7 of Deep Learning ...

CUDA Agent is a breakthrough AI system that autonomously optimizes GPU kernels using large-scale reinforcement learning.

In this video, we'll learn Chain of Thought (CoT) Prompting — one of the most powerful Prompt Engineering techniques for ...

How did DeepSeek achieve massive efficiency gains with their V3 model? And are those gains all they're cracked-up to be?