To help us paint a clearer picture of the inner workings of data science, we are joined today by Elettra Damaggio, the Director of Data Science at StoneX Group Inc., a business that connects other companies and people to various markets. Elettra’s foundations in ML are in neural networks and when she joined StoneX, she was thrown into the deep end of data science.

As generative AI enjoys its time in the spotlight, exciting innovations are being developed for experts and also those with limited technical knowledge, and PartyRock from Amazon Web Services (AWS) is becoming a popular playground for both professional and novice developers.

Using Data Science to Solve Business Problems with AI with Seth Walker Episode 89: Show Notes. Today on How AI Happens, we are joined by Seth Walker from Carrier, one of the leading companies in generative AI creation, to discuss how he and his team use an agile and almost chaotic approach to solving business problems with AI. We delve into how to measure success when it comes to building AI models before our guest stresses the importance of prompt engineering skills. Finally, Seth tells us...

Whether you’re an individual or an organization, the recent advancements in AI are bound to have left you with a few mixed feelings: from concerns over the unanticipated harms that could arise with this new technology, to excitement for all the opportunities it could bring. Joining us today to explore this topic is Philip Moyer, VP of Google Cloud's Global AI Business.

Joelle explains how she ended up at Meta and what her role as VP of AI Research entails before telling us what fascinated her most about AI robotics, why elegance is a key factor in her work, how asking the right questions opens the right doors, and the FRESCO philosophy that forms the foundation off of which Joelle makes all her business decisions.

Mara explains how the team at Amii decides when ML is and isn't appropriate to use. We discuss Amii’s process and its ultimate goal, along with common challenges their partners face when implementing AI solutions.

After attending Meta's event celebrating 10 Years of AI progress at FAIR, Rob shares what he learned with Sama's Director of Machine Learning, Jerome Pasquero, for some much needed technical insight.

The application of AI technologies within industry is growing in popularity. It has the capacity to transform traditional industries while paving the way for innovation in a rapidly evolving landscape. In this episode, we are joined by Bryan DeBois, Director of Industrial AI at RoviSys, to discuss the realm of Industrial AI and its range of applications. RoviSys is a company that specializes in providing automation and information solutions to various industries. It focuses on developing...

Jason & Duncan discuss the results of Sama's ML Pulse Report, focusing on how to measure model effectiveness, how to increase confidence when moving models into production, and whether they believe generative AI is worth the hype.

Ian shares how AMD partnerships are making powerful models available to the general public and large tech companies alike. Also, will LLMs disrupt search? Clippy is back, and he's BAD.

Doug explains how Amazon CodeWhisperer was designed to save engineering time, and reflects on what it means for something to be truly "generative"

Dalia reflects on the evolving nature of data science, discussing the skills and qualities that are now more crucial than ever for excelling in the field. We also explore why creativity is essential for problem-solving, the value of starting simple, and how to stand out as a data scientist before she explains her unique root cause analysis framework.

In this episode, Colin explains how AgriSynth is “getting humans out of the way” with its closed-loop control system and offers some insight into the sheer volume of data required to train its AI models.

Healthy data culture and practices are essential for modern businesses. They promote informed decision-making, efficiency, innovation, and accountability while helping organizations stay competitive and adaptable in a data-driven world. In this episode, we tackle the age-old struggle many companies face: how to unleash the potential of data while overcoming the hurdles that stand in the way of building a truly healthy data culture. To help us navigate this topic is Jennifer Stirrup, a...

Mike breaks down some of the key AI solutions being used at BNY Mellon and shares his thoughts on the many possible future implementations of these emerging technologies. He also unpacks how their enterprise AI team chooses what to prioritize before addressing the importance of demystifying AI capabilities — both within and outside of an organization.

Alex and his team are keen on using AI to increase proficiency at Mercedes while being hyperaware of using this new technology in the most responsible way possible. In our conversation, we learn why Mercedes-Benz thought it necessary to have an entire team dedicated to AI, how they assign AI teams to specific departments in the company, and how the output of descriptive analytics has been improved by machine learning.

Tarun is the VP of Project Management, Data, and AI at IBM, and he is here today to tell us how IBM is keeping up with (and innovating its own) technological trends. We learn of the common struggles in AI and ML, why you need to understand the problem you’re trying to solve before using any new technology, how IBM and Watsonx are helping businesses to tell their own unique AI stories, and why using a consultative method to introduce new users to AI is the most effective method.

We are joined today by Veritone's own Head of Engineering & Product, Chris Doe, to discuss AI applications in enterprise and what is top of mind for companies when it comes to incorporating these emerging technologies. In our conversation, Chris breaks down how Veritone is helping its clients navigate the expansive landscape of AI cognitive engines and why now is the ideal time to test and define proof of concept for generative AI.

Valeria holds a PhD. in informative systems and has a wealth of knowledge and experience in the topic of responsible AI. She shares the findings of her doctoral research at the University of Auckland, what drew her to responsible AI, and how she encourages AI leaders to prioritize ethical design.

Anna Patterson is the Founder and Managing Partner of Gradient Ventures, a full-service seed and series A fund. We discuss the contrast between an AI winter and the standard hype cycles that exist, her thoughts on sectors that were initially under-hyped, how she navigates hype cycles, and why English is the next programming language.

Tulia offers insight into Wayfair’s ML-driven decision-making processes, how they implement AI and ML for preventative problem-solving and predictive maintenance, and how they use data enrichment and customization to help customers navigate the inspirational (and sometimes overwhelming) world of home decor.

Today on How AI Happens, we are joined by Bob Bress, the Vice President and Head of Data Science at FreeWheel, where he leads a team of data science experts in developing and implementing complex analytical solutions for leading-edge technology and advertising programs

Piero Molino, the CEO and Co-Founder at Predibase and the creator of Ludwig.ai discusses the various ways he applied AI at Uber, his background in machine learning, and leveraging AI to automate processes. We also unpack the benefits of configuration-based systems, democratizing data science tools, the ethical side of AI and data science, and why diverse teams are essential.

In this episode of How AI Happens, we are joined by autonomous vehicle experts Rav Babbra and Chess Stetson. Respectively, Rav and Chess are the COO and Founder/CEO of dRisk and in this episode, they discuss their work at dRisk and their mission to solve a critical aspect of autonomous driving: making AVs 100x safer than human drivers.