“It’s what you learn after you know it all that counts.” — John Wooden
Invention, meet your mother, Necessity. It’s an oft-told tale. A programmer hacks together a tool to solve a particular problem, then realizes the tool has broader applicability than he thought. He refines it a bit so it can be used over and over. … Read More → "Qeexo Takes Misery Out of EdgeML"
“The world is one big data problem.” – by Andrew McAfee, co-director of the MIT Initiative on the Digital Economy
In this week’s Fish Fry podcast, we investigate Intel’s Optane™ persistent memory and how this new innovative memory can help make actionable insights more approachable and make your next data-centric design a whole lot easier. We also take a closer look at … Read More → "The Dividends of Persistence: Intel’s Optane Memory and Advances in DNA Storage"
“One person’s data is another person’s noise.” – K.C. Cole
This week’s Fish Fry podcast is all about noisy neurons, cough signature identification, and how AI can help us stem the tide of COVID-19. First up, we check out new research from the German Center for Neurodegenerative Diseases that may have finally unlocked the mysteries of memory retention in people … Read More → "Hearing is Believing: Artificial Intelligence, Cough Patterns, and Stemming the Tide of COVID-19"
As I mentioned a couple of weeks ago in my Why, Hello FPGA and AI — How Nice to See You Together! column, on May 20th I gave my Read More → "Meandering Musings on Metastability"
Let’s face it. Just about anybody can throw a few billion transistors onto a custom 7nm chip, crank up the coulombs, apply data center cooling, put together an engineering team with a few hundred folks including world expert data scientists, digital architecture experts, software savants, and networking gurus, and come up with a pretty decent AI inference engine. There’s nothing to it, really. </ … Read More → "Endpoint AI FPGA Acceleration for the Masses"
“Nothing matters very much, and few things matter at all.” — Arthur Balfour
One thing that all machine learning developers agree upon: ML requires lots and lots of data. New ML processors have dozens – sometimes hundreds – of processor cores, huge caches, wide buses, and enormous appetites for bandwidth. The secret of ML is not that it’s so radically … Read More → "Tenstorrent Takes AI by Storm"
