Across the democratic world, elections focus sharply on quality-of-life issues. Voters’ concerns over persistently high youth unemployment rates contributed to an unexpectedly poor showing for Indian Prime Minister Narendra Modi’s Bharatiya Janata Party (BJP)1. In France, President Emmanuel Macron will… Read More »For a Great Society, Look No Further Than Liberal Philosophy
On a May 5th interview with CNN’s Fareed Zakaria1, Admiral James Stavridis, NATO’s former Supreme Allied Commander Europe, outlined a vision for how Artificial Intelligence (AI) could affect America’s and allied nations’ military preparedness. He noted that predictive maintenance models… Read More »The Risks Facing a Transnational AI Strategy
Author’s Note: As an Artificial Intelligence (AI) practitioner, I constantly think about compute capacity. Testing production-ready, robust infrastructure to serve and monitor Large Language Model (LLM) apps is one of my key responsibilities as an engineer with FoundationaLLM. My experience… Read More »The Future of Federal Supercomputing
In February of this year, the leadership of the U.S. House of Representatives announced a task force to investigate concerns surrounding Artificial Intelligence (AI), chaired by Republican Jay Obernolte and Democrat Ted Lieu, according to reporting by Reuters. Observers of… Read More »A Historical Perspective on the U.S. House of Representatives’ AI Task Force
Introduction Matrix multiplication is among the most foundational of algorithms in scientific computing, used in fields ranging from computational fluid dynamics to artificial intelligence. Naturally, building high-performance implementations is of great concern to engineers. The massive parallelism provided by GPUs… Read More »Accelerating Matrix Multiplication using FPGAs
Introduction Open-source base LLMs, like Facebook’s LLaMA or Microsoft’s Phi models, provide an excellent starting point for natural language processing tasks. Typically, however, these models aren’t well-suited for domain-specific tasks; developers must fine-tune a subset of the model’s weights to… Read More »Fine-tuning LLMs with QLoRA
I recently collaborated with one of my colleagues to implement a Convolutional Neural Network for a quality control Kaggle challenge. Questions or comments? Let us know on GitHub!
Motivation In a previous post, we learned the theory behind Wheatstone bridges and how we could use them to interface with RTDs. Our next step is building something useful with temperature data, a task that microcontrollers are well-suited for. Despite… Read More »Using DMA with the STM32 Microcontroller
Introduction Currently, I’m building a circuit to measure temperature using a resistive temperature device (RTD). Like their name implies, RTDs change resistance in response to temperature changes; thus, the accuracy of a RTD setup is dependent on how accurately we… Read More »Using Wheatstone Bridges with RTDs
Inspiration Working in the cybersecurity field, I build alert pipelines that categorize threats based on predefined conditions. For example, was a certain IoC observed? Were any CrowdStrike policies activated? Neural networks can help us build better threat detection models by… Read More »Training a Neural Network for Cybersecurity