Counting Sand

AI Hot Sauce Taste Test Challenge

Key Topics AI-optimized vs Commercially Available Hot Sauce: Angelo and Petter perform a blind taste test with three different hot sauces, one of which is AI-optimized, to see if they can determine which one is created by AI. Background of the AI Hot Sauce Creators: A brief insight into the story of Shekeib and Shohaib, the two brothers who combined their passion for data science and business to create an AI-optimized hot sauce. Understanding Bayesian Optimization: A comprehensive discuss...

AI Hot Sauce Brothers Part 2

Introduction: Angelo and Shohaib discuss the inclusion of new ingredients in hot sauce batches. Shohaib explains the process of introducing new ingredients and the excitement surrounding it. Incorporating New Ingredients: Angelo asks about the approach to incorporating new ingredients: creating new models or expanding the feature space. Shohaib suggests keeping the base model and increasing the search space for new ingredients. Both options are considered, including transferring the op...

AI Hot Sauce Brothers - Part 1

Introduction Shekeib and Shohaib join the podcast as guests to talk about their experience with creating hot sauces using AI optimization. They created a special hot sauce, named "Counting Sauce," specifically for the podcast hosts. The Making of Counting Sauce This is a unique hot sauce that includes pineapple and mango flavors. The sauce was created as a token of appreciation for being featured on the podcast. Journey through Different Versions of the Sauce The hosts have tried vers...

Bonus: Season 2 Recap

In a time crunch? Check out the time stamps below: [00:45] - Moore's Law, where do we go from here? [03:00] - How do we improve data system efficiency? [10:30] - Purpose-built systems (FPGAs) [11:13] - Insights on (FPGAs) [13:32] - Event Streaming [17:50] - Data storage [18:34] - Google’s approach to data storage [19:00] - Downtime [21:06] - Serves impact on environment and solutions to optimize [23:00] - Improving data systems, machine learning, artificial intelligence [24:06] - ...

The End of Moore's Law Part 2

The last time we had Manos on the program, we talked about Moore's Law coming to an end. It's important to note that we can't rely on just sheer computing power doubling to be able to meet our ever-increasing demand for data. We must find new and exciting ways to collect and compute large amounts of data. In this episode of Counting Sand, we will dive deep into what does a database actually do? What is at the core of a data system? Most importantly, how can we use new and exciting techniques...

Dynamo: The Research Paper that Changed the World

The cycle between research and application is often too long and can take decades to complete. It is often asked what bit of research or technology is the most important? Before we can answer that question, I think it's important to take a step back and share the story of why we believe The Dynamo Paper is so essential to our modern world and how we encountered it.   Citations: DeCandia, G., Hastorun, D., Jampani, M., Kakulapati, G., Lakshman, A., Pilchin, A., ... & Vogels, W. (2007). Dyn...

The Promise of AI: Opportunities and Obstacles

This show often discusses artificial intelligence and ideas to consider as technology progresses. We have discussed the deep tech of how it works and its implications on privacy. In this episode, we'll talk about the complex and controversial topic of AI policy and speak about some of the things we should be worried about regarding its future.   In a time crunch? Check out the time stamps below: [01:15] - Guest Intro  [03:38] - Western technology leadership [04:50] - Regulating AI [11:...

Energy, Edge Computing, and Data Centers

What if there was a way to reduce the amount of energy consumed and produced from servers around the world. Would these new methods positively or negatively impact the environmental footprint of today’s big data ecosystems?   In a time crunch? Check out the time stamps below: [02:15] - Research Paper  [05:55] - Power consumption of data centers and methods to save energy  [08:50] - Server cooling methods  [12:00] - Energy production from data transportation  [13:55] - The impact of lo...

Cutting-Edge Data Systems: Machine Learning

Over the last couple of years, Harvard Data Systems Lab has been focused on cutting-edge research and applications of complex data systems, focusing on such areas as artificial intelligence and machine learning pipelines. In this episode of Counting Sand, Angelo and Stratos dive deep into what they have learned and what’s next in these fields.   In a time crunch? Check out the time stamps below: [01:00] - What’s new at Harvard Data Systems Lab? [08:20] - What are examples of general data...

Kafka Event Streaming Part 2

  Our Team: Host:Angelo Kastroulis Executive Producer: Náture Kastroulis Producer: Albert Perrotta Communications Strategist: Albert Perrotta Audio Engineer: Ryan Thompson Music: All Things Grow by Oliver Worth

Kafka Event Streaming

Our Team: Host:Angelo Kastroulis Executive Producer: Kerri Patterson Producer: Albert Perrotta Communications Strategist: Albert Perrotta Audio Engineer: Ryan Thompson Music: All Things Grow by Oliver Worth

Kafka Event Streaming Part 1

Is Kafka a one-size-fits-all solution? Or does this event sourcing software have an inherent set of strengths? Join Angelo and Kafka guru Anna McDonald as they share use cases and swap stories about how Kafka has radically changed the field of computer science.   In a time crunch? Check out the time stamps below: [00:54] - How did Kafka change the world? [04:40] - What is so great about big data technology? [07:00] - Outbox pattern 101 [10:45] - clinical decision support use case [13:...

Simulating Biological Systems Part 2

This episode touches on computer simulations, machine learning, and GPU's. How do these aspects of computer science relate and differ? Andy and John dive deep into how they push the boundaries of what is possible and practical in modern medicine by simulating biological systems. Our Team: Host:Angelo Kastroulis Executive Producer: Náture Kastroulis Producer: Albert Perrotta;  Communications Strategist: Albert Perrotta; Audio Engineer: Ryan Thompson Music: All Things Grow by Oliver Wor...

Simulating Biological Systems Part 1

The episode starts by asking the question, what if we could use computer science to shorten the amount of time it takes to discover new medications? Angelo then shares, "If we meditate on that for just a second, our minds might wander over into the world of machine learning and artificial intelligence, where we can imagine a world where these complicated neural networks or other types of AI are trying to discover a new kind of chemical compound. We might even think about the far future thing...

Galaxy Evolution

The episode touches on the wondrous journey a galaxy undergoes as it evolves through its life cycle. Angelo starts off the episode by asking the question, what's an early-type galaxy? Paolo Bonfini  explains that although you may think that early-type galaxies would be galaxies early in their evolution, they're not, they're galaxies a little later. They're the ultimate evolution of two galaxies coming together.  Based on the topics touched on in Paolo's paper he then explains the role that ...

The End of Moore's Law - What's Next?

Angelo begins this episode with the predictions of Moore’s Law.  In the early years, systems were restricted based on the CPUs ability to keep up.  As the CPUs continued to advance, the bottlenecks ended up around data movement.  Data movement of information from disc to memory and memory to cache become the big bottlenecks. Then of course, disks got faster and eventually you'd have so much RAM on a machine that it was just memory movement inside of RAM.  Eventually, we believe the bottlenec...

Bonus: Season 1 Recap

Angelo begins this episode with reflections on history and what brought us to the AI Winter.  Why do we need a balance between research and practice?  You don’t want to rediscover what has already been discovered or settle for something that could be better if you took the time to research a bit more.   In episode 4 we meet Angelo’s friend Andy Lee who talks about computer science predicting our biological age.  Andy actually met Greg Fahy who talked about longevity.  The study focused on i...

Machine Learning: Your Right to Explainability

How do we make the next generation of machine learning models that are explainable? How do you start finding new kinds of models that might be explainable? Where do you even start thinking about that process from a research perspective? Nikos begins with a discussion on how we make decisions in general.  In the scientific world, we mostly reason through statistical or cause-and-effect type scenarios.  We can predict outcomes and train our models to produce the results we traditionally expec...

The Boundaries of Personal Data

Angelo and Manos' connection began in the 265 Course at Harvard University on Big Data Systems. This course inspired Angelo's thesis. The two discuss Manos' papers and how the future of Big Data is on the boundaries of Moore's Law. If you think about LSM trees (Log-Structured Merge Trees) and compacting data, what is considered acceptable deletion when users ask for their data to be removed? Is it when the data is removed from the identifying user that is good enough? In the analysis of Big ...

How did COVID-19 change the way doctors make decisions?

Angelo begins this episode with a few questions about the changes caused by COVID-19, specifically around the patient data gathering, such as blood pressure. With telemedicine practice, how reliable is the data, who is legally responsible for the accuracy of the data gathered, and how exactly do clinical decision support (CDS) tools adjust with this new change in a traditional clinician workflow? Angelo explores more on the topic of IoT devices and the data brought into medical decisions. A...

Ep06 Teaser

Rosenblatt's Perceptron: What Can Neural Networks Do For Us?

In any discussion of artificial intelligence and machine learning today, artificial neural networks are bound to come up. What are artificial neural networks, how have they developed, and what are they poised to do in the future? Host Angelo Kastroulis dives into the history, compares them to biological systems that they are meant to mimic, and talks about how hard problems like this one need to be handled carefully. Angelo begins with a discussion of how biological neural networks help mak...

Can Computer Science Help Us Live Longer?

Can computer science help us live longer? It is a complex question that requires an understanding of our anticipated lifespan and how the health of our body at this moment compares to the average person our age, what some would call calculating our biological age. What computer science stands to help with is understanding how better to pinpoint that biological age and what factors may play into holding off the aging process. Guest Andy Lee, of NeuroInitiative and Vincere Biosciences, speaks ...

How Can Computer Science Improve Life?

On the most recent episode, host Angelo Kastroulis made a case computer science as a potential force for good. In this continuation of the theme, he talks about why excellence is a value to strive toward and how it differs from perfection, how simplifying the question can lead to a more valuable answer, and how questions about personalized medicine point to the potential for quantum to make big improvements to life. Angelo begins with a revelation that excellence is value that he holds dear...

Can Computer Science Make Life Better?

Can computer science improve our lives? Most people who work in the field would like to think so. Host Angelo Kastroulis, CEO of the Carrera Group, considers the ways that computer science is poised to make our lives better but also introduces caveats such as bias in machine learning. Along the way he sets up future episodes’ themes—including predictive analytics, simulation, and health decision support systems—that he will dive into with more technical detail. Acknowledging that technology...

Can Computer Science Make Life Better

Can computer science improve our lives? Most people who work in the field would like to think so. Host Angelo Kastroulis, CEO of the Carrera Group, considers the ways that computer science is poised to make our lives better but also introduces caveats such as bias in machine learning. Along the way he sets up future episodes’ themes—including predictive analytics, simulation, and health decision support systems—that he will dive into with more technical detail. Acknowledging that technology...

Inspired by Archimedes...Counting Sand

How much sand would it take to fill the universe? And what does this 2,000-year-old question have to do with a podcast on today’s big data challenges? In this kick-off episode of the Counting Sand podcast, host Angelo Kastroulis, CEO of Carrera Group, explains how an early research paper by Archimedes of Syracuse has much in common with his own approach to today’s big questions in data science and how the paper provides not only a metaphor for how we can meld research and practice in tacklin...

Introducing Counting Sand

How many grains of sand are there in the universe? To answer that hard question, Archimedes had to invent an entire number system and only then could he attempt the computation. Today’s data challenges make that look easy. On the COUNTING SAND podcast, host Angelo Kastroulis tackles the hard problem of how to make meaning of all the data available today. Every few episodes, Angelo will introduce a new theme at the heart of big data and IT infrastructure and highlight the most cutting-edge ...