BAML: The Programming Language for AI, with Vaibhav Gupta

Today's guest, Vaibhav Gupta, has developed BAML, the programming language for AI. If you are calling LLMs, you've gotta check BAML out for instant accuracy improvements and big (20-30%) cost savings.

More on charming and terrifically brilliant Vaibhav:

• Founder & CEO of Boundary (YC W23), a Y Combinator-backed startup that has developed a new programming language (BAML) that makes working with LLMs easier and more efficient for developers.

• Across his decade of experience as a software engineer, he built predictive pipelines and real-time computer vision solutions at Google, Microsoft and the renowned hedge fund The D. E. Shaw Group.

• Holds a degree in Computer Science and Electrical Engineering from The University of Texas at Austin.

This is a relatively technical episode. The majority of it will appeal to folks who interact with LLMs or other model APIs hands-on with code.

In today’s information-dense episode, Vaibhav details:

• How his company pivoted 13 times before settling upon developing a programming language for A.I.

• Why creating a programming language was "really dumb" but why it’s turning out to be brilliant, including by BAML already saving companies 20-30% on their AI costs.

• Fascinating parallels between today's A.I. tools and the early days of web development.

• His unconventional hiring process (I’ve never heard of anything remotely close to it) and the psychology behind why it works.

The SuperDataScience podcast is available on all major podcasting platforms, YouTube, and at SuperDataScience.com.

How to Ensure AI Agents Are Accurate and Reliable, with Brooke Hopkins

Agentic A.I. is powerful because it has infinite breadth of capability. But this is a double-edged sword: Agents entail great risk and testing their performance is tricky... until now — thanks to Brooke Hopkins, today's guest!

Brooke:

Is Founder & CEO of Coval (YC S24), a San Francisco-based startup that provides a simulation and evaluation platform for A.I. agents. A few days ago, they announced a $3.3m fundraise that includes heavyhitter VCs like General Catalyst, MaC and Y Combinator.

• Previously was Tech Lead and Senior Software Engineer at Waymo, where she worked on simulation and evaluation for Waymo’s self-driving cars.

• Before that, she was a Software Engineer at Google.

• She holds a degree in Computer Science and Mathematics from New York University’s Abu Dhabi campus.

Despite Brooke’s highly technical background, our conversation is largely conceptual and high-level, allowing anyone who’s interested in developing and deploying Agentic A.I. applications to enjoy today’s episode.

In today’s episode, Brooke details:

• How simulation and testing best practices inspired by autonomous-vehicle development are being applied by her team at Coval to make A.I. agents useful and trustworthy in the real world.

• Why voice agents are poised to be the next major platform shift after mobile, creating entirely new ways to interact with technology.

• How companies are using creative strategies like "background overthinkers" to make A.I. agents more robust.

• What the rise of A.I. agents means for the future of human work and creativity… indeed, how agents will transform all of society.

The SuperDataScience podcast is available on all major podcasting platforms, YouTube, and at SuperDataScience.com.

Exponential Views on AI and Humanity’s Greatest Challenges, with Azeem Azhar

Today, the famed futurist Azeem Azhar eloquently details the exponential forces that are overhauling society — and why A.I. is essential for solving humanity's biggest challenges. This is a special episode; don't miss it!

In case you aren't familiar with his legendary name already, Azeem:

• Is creator of the invaluable "Exponential View" newsletter (>100k subscribers).

• Hosts the "Exponential View" podcast (well-known guests include Tony Blair and Andrew Ng).

• Hosted the Bloomberg TV show "Exponentially" (guests include Sam Altman).

• Holds fellowships at Stanford University and Harvard Business School.

• Was Founder & CEO of PeerIndex, a venture capital-backed machine-learning startup that was acquired in 2014.

• He holds an MA in PPE (Politics, Philosophy and Economics) from the University of Oxford.

Today’s episode will appeal to any listener. In it, Azeem details:

• The exponential forces that will overhaul society in the coming decades.

• Why AI is essential for solving humanity's biggest challenges.

• His own cutting-edge, personal use of A.I. agents, LLMs, and automation.

• Why there's no 'solid ground' in the future of work and how we can adapt.

The SuperDataScience podcast is available on all major podcasting platforms, YouTube, and at SuperDataScience.com.

Generative AI for Business, with Kirill Eremenko and Hadelin de Ponteves

Craving an intro to building and deploying commercially successful Generative A.I. applications? In today's episode, superstar data-science instructors Kirill and Hadelin (>5 million students between them) will fill you in!

Kirill Eremenko is one of our two guests today. He's:

• Founder and CEO of SuperDataScience, an e-learning platform.

• Founded the SuperDataScience Podcast in 2016 and hosted the show until he passed me the reins four years ago.

Our second guest is Hadelin de Ponteves:

• Was a data engineer at Google before becoming a content creator.

• In 2020, took a break from Data Science content to produce and star in a Bollywood film featuring "Miss Universe" Harnaaz Sandhu.

Together, Kirill and Hadelin:

• Have created dozens of data science courses; they are the most popular data science instructors on the Udemy platform, with over five million students between them!

• They also co-founded CloudWolf, an education platform for quickly mastering Amazon Web Services (AWS) certification.

• And, in today’s episode, they announce (for the first time anywhere!) another (brand-new) venture they co-founded together.

Today’s episode is intended for anyone who’s interested in real-world, commercial applications of Generative A.I. — a technical background is not required.

In today’s episode, Kirill and Hadelin detail:

• What generative A.I. models like Large Language Models are and how they fit within the broader category of “Foundation Models”.

• The 12 crucial factors to consider when selecting a foundation model for a given application in your organization.

• The 8 steps to ensuring foundation models are deployed commercially successfully.

• Many real-world examples of how companies are customizing A.I. models quickly and at remarkably low cost.

The SuperDataScience podcast is available on all major podcasting platforms, YouTube, and at SuperDataScience.com.

In Case You Missed It in December 2024

Today's "In Case You Missed it Episode"... is one not to miss! Several of the most fascinating conversations I've ever had on the SuperDataScience Podcast I host happened in December.

The specific conversation highlights included in today's episode are:

1. The legendary Dr. Andrew Ng on why LLM cost doesn't matter for your A.I. proof of concept.

2. Building directly on Andrew's segment, CTO (and my fellow Nebula.io co-founder) Ed Donner on how to choose the right LLM for a given application.

3. Extremely intelligent and clear-spoken Dr. Eiman Ebrahimi (CEO of Protopia AI) on the future of autonomous systems and data security in our Agentic A.I. future.

4. From our 2024 recap episode, Sadie St. Lawrence's three biggest A.I. "wow" moments of the year... as well as the biggest flop of the year. (One company was behind both!)

5. Harvard/MIT humanist chaplain Greg Epstein (and bestselling author on tech in society) on the ethics of accelerating A.I. advancements. Should we, for example, consider slowing A.I. progress down?

The SuperDataScience podcast is available on all major podcasting platforms, YouTube, and at SuperDataScience.com.

Quantum ML: Real-World Applications Today, with Dr. Florian Neukart

In today's episode, extremely clear-spoken Dr. Florian Neukart — a world-leading expert on quantum computing — details real-world problems we can tackle with Quantum ML and how you can get started with QML today!

Florian:

• Is Chief Product Officer and Member of the Board at Terra Quantum AG, a leading quantum-computing startup headquartered in Switzerland and Germany.

• Assistant Professor of quantum computing at Leiden University in the Netherlands.

• Holds a PhD in Quantum Computing and Machine Learning.

Today’s episode gets a bit technical at some parts — particularly near the beginning — with respect to the mechanics of quantum computing and Quantum ML (QML) but, by and large, the episode should be fascinating to any interested listener.

In today’s episode, Florian details:

• How a new generation of hybrid quantum-classical systems has made quantum computing practical for real-world applications.

• An overview of the available quantum computing chips, including Willow, Google’s new quantum chip, which has been making a big splash.

• The race to develop "quantum-proof" encryption.

• The breadth of real-world problems that can be tackled with quantum machine learning today.

• How quantum ML could unlock personalized medicine, nuclear fusion energy and revolutionary space technologies.

• How you can get started with quantum ML yourself today.

The SuperDataScience podcast is available on all major podcasting platforms, YouTube, and at SuperDataScience.com.

2025 AI and Data Science Predictions, with Sadie St. Lawrence

Happy New Year! To prepare you for 2025, today's guest is the clairvoyant Sadie St. Lawrence, who predicts what the biggest A.I. trends will be in the year ahead. We also pick the A.I. winners and losers of 2024.

In a bit more detail, in today’s episode (which will appeal to technical and non-technical listeners alike):

• We cover how Sadie’s predictions for 2024 (which she made a year ago on this show) panned out.

• We award our “wow moment” of 2024, our comeback of the year, our disappointment of the year and our overall winner of 2024.

• And then, of course, we speculate on the five biggest trends to prepare for in 2025.

As with our 2022, 2023 and 2024 predictions episode, our special guest again this year is Sadie St. Lawrence, who is:

• A data science and machine learning instructor whose content has been enjoyed by over 600,000 students.

• The Founder and CEO of the Human Machine Collaboration Institute as well as being founder and chair of Women In Data™️, a community of over 60,000 women across 55 countries.

• Serves on multiple start-up boards.

• Hosts the Data Bytes podcast.

The SuperDataScience podcast is available on all major podcasting platforms, YouTube, and at SuperDataScience.com.

Happy Holidays from the SuperDataScience Podcast

2024 was unquestionably the fastest-moving year yet for A.I. innovation. In particular, we witnessed the meteoric rise of generative AI from its largely-proof-of-concept phase to being commercially indispensable. According to survey results, nearly two-thirds of organizations are now regularly using generative A.I. – a number that has almost doubled since a year earlier. From enhancing product development to facilitating medical breakthroughs, generative AI has become a cornerstone of innovation across industries. For those of who practice data science hands-on, GenAI has proved itself to be near-magical at composing functional code and debugging our errors.

Indeed, as we’ll discuss in detail in next Tuesday’s episode with Sadie St. Lawrence, this year GenAI models crossed reliability and accuracy thresholds, enabling it to power independently acting AI agents, even multi-agent systems that can tackle complex tasks without human supervision. 2025 looks set to be the year Agentic AI takes center stage, the next phase in A.I. transforming every industry and overhauling our way of life; if we get the tricky parts right, then for the better for all of us on this planet.

I hope you’ve enjoyed our exploration of these developments (and much more!) in depth over the course of the year through our podcast episodes, allowing you to hear directly from leading experts and practitioners like Andrew Ng, Bernard Marr and Sol Rashidi. Our discussions have covered a wide range of topics, from the industrialization of data science processes to the ethical considerations surrounding AI implementation.

Through exploring the tricky bits like ethics and equity alongside the breathtaking technological breakthroughs, I hope that overall we’ve left you feeling optimistic about our capacity as a species to get this tech revolution right and have it benefit all of us. This holiday season, I hope you’ll also be able to sit with these positive vibes, get some time away from your screened devices and enjoy the wonder of life — including how lucky we are to be alive at this extraordinary time in history — with your loved ones.

From all of us here at the SuperDataScience Podcast, happy holidays!

The SuperDataScience podcast is available on all major podcasting platforms, YouTube, and at SuperDataScience.com.

AI Engineering 101, with Ed Donner

My holiday gift to you is my Nebula.io co-founder Ed Donner, one of the most brilliant, articulate people I know. In today's episode, Ed introduces the exciting, in-demand "A.I. Engineer" career — what's involved and how to become one.

After working daily alongside this world-class mind and exceptional communicator for nearly a decade, it is at long last my great pleasure to have the extraordinary Ed as my podcast guest. Ed:

• Is co-founder and CTO of Nebula, a platform that leverages generative and encoding A.I. models to source, understand, engage and manage talent.

• Previously, was co-founder and CEO of an A.I. startup called untapt that was acquired in 2020.

• Prior to becoming a tech entrepreneur, Ed had a 15-year stint leading technology teams on Wall Street, at the end of which he was a Managing Director at JPMorganChase, leading a team of 300 software engineers.

• He holds a Master’s in Physics from the University of Oxford.

Today’s episode will appeal most to hands-on practitioners, particularly those interested in becoming an A.I. Engineer or leveling up their command of A.I. Engineering skills.

In today’s episode, Ed details:

• What an A.I. Engineer (also known as an LLM Engineer) is.

• How the data indicate A.I. Engineers are in as much demand today as Data Scientists.

• What an A.I. Engineer actually does, day to day.

• How A.I. Engineers decide which LLMs to work with for a given task, including considerations like open- vs closed-source, what model size to select and what leaderboards to follow.

• Tools for efficiently training and deploying LLMs.

• LLM-related techniques including RAG and Agentic A.I.

The SuperDataScience podcast is available on all major podcasting platforms, YouTube, and at SuperDataScience.com.

Making Enterprise Data Ready for AI, with Anu Jain and Mahesh Kumar

Today's episode features execs (from fast-growing, VC-backed A.I. startups) Anu Jain and Mahesh Kumar elucidating how enterprises can prepare and manage their data for powerful A.I. applications.

In a bit more detail, today's guests are:

• Anu Jain — CEO of Nexus Cognitive.

• Mahesh Kumar — CMO (with an engineering background and he still writes code!) of Acceldata.

This episode was filmed live at Insight Partners' ScaleUp:AI conference in New York last month.

The episode features highlights of a session I hosted at ScaleUp:AI on "Managing Data to Embrace an A.I.-First Mindset for Enterprises”. It should be interesting to folks looking to make A.I. implementations effective in large organizations that have lots of data.

In the episode, Anu and Mahesh detail:

• How a tiny data error can lead to millions of dollars in losses for an enterprise.

• Why data storage isn't a major cost driver anymore (and what is!)

• What the heck data governance actually is and why it matters.

The SuperDataScience podcast is available on all major podcasting platforms, YouTube, and at SuperDataScience.com.

Tech is Our New Religion And It Needs Reformation, with Greg Epstein

In today's fascinating episode, Harvard/MIT's humanist chaplain (and bestselling author!) Greg Epstein details how tech has become our foremost religion... and why this new religion needs reformation 😈

More on Greg:

• Serves as humanist chaplain at both Harvard University and the Massachusetts Institute of Technology.

• Wrote the bestselling book “Good without God: What a Billion Nonreligious People Do Believe."

Today’s episode focuses largely on Greg’s latest book, "Tech Agnostic", and should be interesting to everyone. In today’s episode, Greg details:

• How technology has supplanted traditional religion as society's most powerful belief system.

• Why Silicon Valley's promise of technological salvation parallels religious prophecies.

• The concerning parallel between AI's "singularity" and religious end-of-times narratives.

• How we can embrace technological progress while maintaining our humanity.

• Why building genuine human connections matters more than chasing technological utopias.

The SuperDataScience podcast is available on all major podcasting platforms, YouTube, and at SuperDataScience.com.

In Case You Missed It in November 2024

We had a ton of laughs and I had some seriously mind-expanding moments thanks to my guests on the SuperDataScience Podcast last month. ICYMI, today's episode highlights the most riveting moments from November.

The specific conversation highlights included in today's episode are:

1. Deepali Vyas, Global Head of Data and A.I. at executive-search giant Korn Ferry, on how A.I. is transforming recruitment and how job-seekers can stay ahead of the curve.

2. Jess Ramos, data analyst and leading content creator on data careers, on where to start if you yourself are seeking a career in data.

3. Bryan McCann, co-founder and CTO of the rapidly-scaling A.I. platform You.com, on why machines will make much better scientists than humans... and how they will surpass human scientists surprisingly soon.

4. Martin Goodson, CEO of the prestigious British A.I. firm Evolution AI, on how the public figures who are speaking most loudly about A.I. are probably not the people we should be listening to.

The SuperDataScience podcast is available on all major podcasting platforms, YouTube, and at SuperDataScience.com.

Safe, Fast and Efficient AI, with Protopia’s Dr. Eiman Ebrahimi

Nearly all A.I. projects get stuck in "POC Purgatory" because of complex trade-offs between cost, speed and security. Thankfully, today's guest — Dr. Eiman Ebrahimi — cogently provides a path to production A.I. heaven.

Eiman is extremely intelligent and well-spoken; don't miss this episode! It was a delight developing this episode with him and I learned a ton from his gifted mind throughout the process.

Eiman:

• Is CEO of Protopia AI, venture capital-backed startup based in Austin that converts sensitive data into a special, stochastic format that improves A.I. model accuracy, protects privacy and reduces compute costs.

• Prior to founding Protopia, spent a decade at NVIDIA as Senior Research Scientist and Computer Architect.

• Holds a PhD in Computer Engineering from The University of Texas at Austin.

Today’s episode is relatively technical so might appeal most to technical listeners, but Eiman is such a terrific communicator that anyone interested in A.I. might love it.

In today’s episode, Eiman details:

• How he went from optimizing GPU performance at NVIDIA to revolutionizing A.I. data security.

• Why many promising A.I. projects get stuck in what he calls "proof of concept purgatory" - and how to escape it.

• Gripping, deep detail on the real-world tradeoffs between the cost, speed and security of running A.I. models in production.

• How to make your enterprise A.I. products profitable.

• Why having your own private server doesn't make your A.I. system as secure as you think.

• What Alan Watts' philosophy teaches us about entrepreneurship and innovation.

The SuperDataScience podcast is available on all major podcasting platforms, YouTube, and at SuperDataScience.com.

Flexible AI Deployments Are Critical, with Chris Bennett and Joseph Balsamo

Today's episode features heavyhitters from Dell (Chris Bennett) and Iternal (Joseph Balsamo) detailing why we must have flexibility in our A.I. model deployment (and why generative A.I. is overhyped)!

In a bit more detail, today's guests are:

• Chris Bennett: Global CTO for Data & A.I. Solutions at Dell Technologies

• Joseph Balsamo: Sr VP of Product Development at Iternal Technologies

This episode was filmed live at Insight Partners' ScaleUp:AI conference in New York a few weeks ago. Thanks to George Mathew, Jennifer Jordan, Kristen Zeck and Deanna Uzarski for inviting me and making the magic of this session happen.

The SuperDataScience podcast is available on all major podcasting platforms, YouTube, and at SuperDataScience.com.

Andrew Ng on AI Vision, Agents and Business Value

My guest today is the inimitable Andrew Ng! In his trademark, clear-spoken style, Andrew gives us a glimpse of the Agentic A.I. future, particularly how the coming Vision Agent tsunami will change the world.

I suspect pretty much everyone knows Dr. Ng already, but just in case:

• As director of Stanford University's AI Lab, his research group played a key role in the development of deep learning (which led to him to founding the influential Google Brain team) as well as educating millions on machine learning (and leading to him co-founding Coursera).

• Is Managing General Partner of AI Fund, a world-leading A.I. venture studio.

• Was CEO (is now Executive Chairman) of LandingAI, a computer-vision platform that specializes in domain-specific Large Vision Models (analogous to LLMs for language).

• Founded DeepLearning.AI, which provides excellent technical training on ML, deep learning (of course!), generative A.I. and many other associated subjects.

• Was co-CEO (as well as co-founder and chairman) of Coursera, which brought online learning from 300 leading universities to over 100 million students.

This episode was recorded live at the ScaleUp:AI conference in New York a few weeks ago. Thanks to George Mathew and Jennifer Jordan for inviting me back to the conference to interview Andrew :)

In today’s, Andrew details:

• Why a cheaper A.I. model with smart agentic A.I. workflow might outperform more expensive, more advanced models.

• The surprising truth about A.I. API costs that most businesses don't realize.• How Marvin Minsky's "Society of Mind" theory from the 1980s is making an unexpected comeback in modern A.I.

• A groundbreaking new way to process visual data that goes beyond traditional computer vision.

• Why unstructured data will be the key to A.I.'s next big revolution.

The SuperDataScience podcast is available on all major podcasting platforms, YouTube, and at SuperDataScience.com.