How AI Happens

The rapid evolution of technology excites Anthony, especially in AI. User preferences are shifting towards more human-like AI interactions. Empathy in AI is crucial for better customer service experiences. The partnership between Amdocs and NVIDIA emphasizes the importance of software efficiency Software and hardware advancements must progress in parallel to maximize productivity. Physical AI inte...

Mica shares the methods behind Augury’s fault testing processes, why they use the highest quality data available, how in-house experts help them filter their data reliably, and their approach to communicating with customers. Our conversation also explores the balance between edge computing and cloud computing, and why both are necessary for optimal performance and monitoring. Key Points From This...

Srini highlights the importance of integrating these agents into real-world applications, enhancing productivity and user experiences across industries. Srini also delves into the challenges of building reliable, ethical, and secure AI systems while fostering developer innovation. His insights offer a roadmap for harnessing advanced agents to drive meaningful technological progress. Don’t miss thi...

 We explore the current trends of AI-based solutions in retail, what has driven its adoption in the industry, and how AI-based customer service technology has improved over time. We also discuss the correct mix of technology and humans, the importance of establishing boundaries for AI, and why it won't replace humans but will augment workflow. Hear examples of AI retail success stories, what compa...

We hear about Nitzan’s AI expertise, motivation for joining eBay, and approach to implementing AI into eBay's business model. Gain insights into the impacts of centralizing and federating AI, leveraging generative AI to create personalized content, and why patience is essential to AI development. We also unpack eBay's approach to LLM development, tailoring AI tools for eBay sellers, the pitfalls o...

Satya unpacks how Unilever utilizes its database to inform its models and how to determine the right amount of data needed to solve complex problems. Dr. Wattamwar explains why contextual problem-solving is vital, the notion of time constraints in data science, the system point of view of modeling, and how Unilever incorporates AI into its models. Gain insights into how AI can increase operational...

Jing explains how Vanguard uses machine learning and reinforcement learning to deliver personalized "nudges," helping investors make smarter financial decisions. Jing dives into the importance of aligning AI efforts with Vanguard’s mission and discusses generative AI’s potential for boosting employee productivity while improving customer experiences. She also reveals how generative AI is poised to...

Key Points From This Episode: Ram Venkatesh describes his career journey to founding Sema4.ai.  The pain points he was trying to ease with Sema4.ai. How our general approach to big data is becoming more streamlined, albeit rather slowly.  The ins and outs of Sema4.ai and how it serves its clients.  What Ram means by “agent” and “agent agency” when referring to machine learning copilots. The differ...

Pascal & Yannick delve into the kind of human involvement SAM-2 needs before discussing the use cases it enables. Hear all about the importance of having realistic expectations of AI, what the cost of SAM-2 looks like, and the the importance of humans in LLMs. Key Points From This Episode: Introducing Pascal Jauffret and Yannick Donnelly to the show. Our guests explain what the SAM-2 model is.  A...

Today we are joined by Siddhika Nevrekar, an experienced product leader passionate about solving complex problems in ML by bringing people and products together in an environment of trust.  We  unpack the state of free computing, the challenges of training AI models for edge, what Siddhika hopes to achieve in her role at Qualcomm, and her methods for solving common industry problems that developer...

Today we are joined by Developer Advocate at Block, Rizel Scarlett, who is here to explain how to bridge the gap between the technical and non-technical aspects of a business. We also learn about AI hallucinations and how Rizel and Block approach this particular pain point, the burdens of responsibility of AI users, why it’s important to make AI tools accessible to all, and the ins and outs of G{C...

Key Points From This Episode: Drew and his co-founders’ background working together at RJ Metrics. The lack of existing data solutions for Amazon Redshift and how they started dbt Labs. Initial adoption of dbt Labs and why it was so well-received from the very beginning. The concept of a semantic layer and how dbt Labs uses it in conjunction with LLMs. Drew’s insights on a recent paper by Apple on...

In this episode, you’ll hear about Meeri's incredible career, insights from the recent AI Pact conference she attended, her company's involvement, and how we can articulate the reality of holding companies accountable to AI governance practices. We discuss how to know if you have an AI problem, what makes third-party generative AI more risky, and so much more! Meeri even shares how she thinks the...

In this episode, Dr. Zoldi offers insight into the transformative potential of blockchain for ensuring transparency in AI development, the critical need for explainability over mere predictive power, and how FICO maintains trust in its AI systems through rigorous model development standards. We also delve into the essential integration of data science and software engineering teams, emphasizing th...

Jay breaks down the critical role of software optimizations and how they drive performance gains in AI, highlighting the importance of reducing inefficiencies in hardware. He also discusses the long-term vision for Lemurian Labs and the broader future of AI, pointing to the potential breakthroughs that could redefine industries and accelerate innovation, plus a whole lot more.  Key Points From Thi...

Melissa explains the importance of giving developers the choice of working with open source or proprietary options, experimenting with flexible application models, and choosing the size of your model according to the use case you have in mind. Discussing the democratization of technology, we explore common challenges in the context of AI including the potential of generative AI versus the challeng...

 VP of AI and ML at Synopsys, Thomas Andersen joins us to discuss designing AI chips. Tuning in, you’ll hear all about our guest’s illustrious career, how he became interested in technology, tech in East Germany, what it was like growing up there, and so much more! We delve into his company, Synopsys, and the chips they build before discussing his role in building algorithms.  Key Points From This...

Developing AI and generative AI initiatives demands significant investment, and without delivering on customer satisfaction, these costs can be tough to justify. Today, SVP of Engineering and General Manager of Xactly India, Kandarp Desai joins us to discuss Xactly's AI initiatives and why customer satisfaction remains their top priority.  Key Points From This Episode: An introduction to Kandarp a...

 Srujana is Vice President and Group Director at Walmart’s Machine Learning Center of Excellence and is an experienced and respected AI, machine learning, and data science professional. She has a strong background in developing AI and machine learning models, with expertise in natural language processing, deep learning, and data-driven decision-making. Srujana has worked in various capacities in t...

Our guest goes on to share the different kinds of research they use for machine learning development before explaining why he is more conservative when it comes to driving generative AI use cases. He even shares some examples of generative use cases he feels are worthwhile. We hear about how these changes will benefit all UPS customers and how they avoid sharing private and non-compliant informati...

Martin shares what reinforcement learning does differently in executing complex tasks, overcoming feedback loops in reinforcement learning, the pitfalls of typical agent-based learning methods, and how being a robotic soccer champion exposed the value of deep learning. We unpack the advantages of deep learning over modeling agent approaches, how finding a solution can inspire a solution in an unre...

Jia  shares the kinds of AI courses she teaches at Stanford, how students are receiving machine learning education, and the impact of AI agents, as well as understanding technical boundaries, being realistic about the limitations of AI agents, and the importance of interdisciplinary collaboration. We also delve into how Jia prioritizes latency at LiveX before finding out how machine learning has c...

  Key Points From This Episode: Reid Robinson's professional background, and how he ended up at Zapier.  What he learned during his year as an NFT founder, and how it serves him in his work today. How he gained his diverse array of professional skills. Whether one can differentiate between AI and mere automation.  How Reid knew that partnering with OpenAI and ChatGPT would be the perfect fit.  The...

 In this episode of How AI Happens, Justin explains how his project, Wondr Search, injects creativity into AI in a way that doesn’t alienate creators. You’ll learn how this new form of AI uses evolutionary algorithms (EAs) and differential evolution (DE) to generate music without learning from or imitating existing creative work. We also touch on the success of the six songs created by Wondr Searc...

Jacob shares how Gong uses AI, how it empowers its customers to build their own models, and how this ease of access for users holds the promise of a brighter future. We also learn more about the inner workings of Gong and how it trains its own models, why it’s not too interested in tracking soft skills right now, what we need to be doing more of to build more trust in chatbots, and our guest’s sum...