Past episodes listed in reverse chronological order. We have high-quality transcripts for a few episodes (see here).


198. Yishay CarmielAI and the Future of Speech Technologies

197. Casey EllisThe Future of Cybersecurity – Generative AI and its Implications

196. Daniel LentonIvy – The One-Stop Interface for AI Model Deployment and Development

195. Andrew BurtNavigating the Risk Landscape – A Deep Dive into Generative AI

194. Michele CatastaSoftware Development with AI and LLMs

193. Alex ChaoA Lightweight SDK for Integrating AI Models and Plugins

192. Steve HsuUsing LLMs to Build AI Co-pilots for Knowledge Workers

191. Brian RaymondETL for LLMs

190. Emil EifremThe Future of Graph Databases

189. David TalbyDelivering Safe and Effective LLM and NLP Applications with LangTest

188. Jeff JonasUsing Data and AI to Democratize Entity Resolution and Master Data Management

187. Jerry LiuAn Open Source Data Framework for LLMs

186. Tim DavisRedefining AI Infrastructure

185. Andrew FeldmanThe Rise of Custom Foundation Models

184. Louis BrandyThe Future of Vector Databases and the Rise of Instant Updates

183. Amin AhmadLLMs Are the Key to Unlocking the Next Generation of Search

182. Jonas AndrulisBuilding and Deploying Foundation Models for Enterprises

181. Alex RemediosBuilding Robust AI Infrastructure for Critical Solutions

180. Patrick Hall and Agus SudjiantoMachine Learning for High-Risk Applications

179. Omar MaherBoosting Perception With Synthetic Data

178. Simon ChanRevolutionizing B2B: Unleashing the Power of AI and Data

177. Gev SogomonianAI Metadata

176. Raymond Perrault2023 AI Index

175. Hagay LupeskoCustom Foundation Models

174. Jakub ZavrelUncovering and Highlighting AI Trends

173. Chris WigginsHow Data and AI Happened

172. Paras Jain and Sarah WoodersBlazing fast bulk data transfers between any cloud

171. Pablo VillalobosExhaustion of High-Quality Data Could Slow Down AI Progress in Coming Decades

170. Jinsung Yoon and Sercan ArikGenerating high-fidelity and privacy-preserving synthetic data

169. Brandon JenkinsHow technology is disrupting the venture capital industry

168. Zongheng Yang2023 Running Machine Learning Workloads On Any Cloud

167. Jesse Anderson, Evan Chan, and Ben Lorica2023 Trends in Data Engineering and Infrastructure

166. Gabriela Zanfir-Fortuna and Andrew BurtPreparing for the Implementation of the EU AI Act and Other AI Regulations

165. Dylan PatelThe Open Source Stack Unleashing a Game-Changing AI Hardware Shift

164. Peter Norvig and Alfred SpectorData Science and AI in Context

163. Percy LiangEvaluating Language Models

162. Ben Lorica, Mikio Braun, and Jenn Webb2023 Opportunities and Trends – Data, Machine Learning, and AI

161. Mark ChenExploring DALL·E 2


160. Wendy Foster and Olivia LiaoData Science at Shopify and Stitch Fix

159. Shayan MohantyBuilding a data management system for unstructured data

158. Frank LiuA Cloud Native Vector Database Management System

157. Ira CohenWhat’s Next for Machine Learning in Time Series

156. Roy SchwartzEfficient Methods for Natural Language Processing

155. Andrew Burt and Bob FridayResponsible and Trustworthy AI (Thanksgiving holiday episode)

154. Hung BuiBuilding a premier industrial AI research and product group

153. Bob van LuijtAn open source, production grade vector search engine

152. Federico Garza and Max Mergenthaler CansecoA comprehensive suite of open source tools for time series modeling

151. Christopher NguyenBuilding Safe and Reliable AI applications

150. Ram SriharshaA new storage engine for vectors

149. Karthik RamasamyProject Lightspeed: Next-generation Spark Streaming

148. Piotr ŻelaskoThe Unreasonable Effectiveness of Speech Data

147. Yaron SingerMachine Learning Integrity

146. Yashar BehzadiSynthetic data technologies can enable more capable and ethical AI

145. Sadegh RiaziConfidential Computing for Machine Learning

144. John BohannonApplied NLP Research at Primer

143. Jon UdellUsing SQL to Retrieve Data from APIs and Web Services

142. Aadyot BhatnagarMachine Learning for Time Series Intelligence

141. Maarten GrootendorstUnleashing the power of large language models

140. Hamza Tahir and Adam ProbstBuilding production-ready machine learning pipelines

139. Omri AlloucheMachine Learning at Gong

138. Danny Bickson and Amir AlushData Infrastructure for Computer Vision

137. Mark ChenHow DALL·E works

136. Jules Damji and Richard LiawScalable, end-to-end machine learning, for everyone

135. Rick LamersOrchestration and Pipelines for Data Scientists

134. Devin PetersohnDataframes at scale

133. Nick SchrockSoftware-defined Assets

132. Edmon BegoliAdversarial Machine Learning

131. Haytham AbuelfutuhOrchestrating Machine Learning Applications

130. Hilary MasonNarrative AI

129. Oren RazonMachine Learning Model Observability

128. Jeremiah LowinDataflow Automation

127. Sebastian RaschkaPractical Machine Learning and Deep learning

126. Ade Fajemisin and Donato MaragnoMachine Learning for Optimization

125. Barret Zoph and Liam FedusEfficient Scaling of Language Models

124. Olivia LiaoData Science at Stitch Fix

123. Jack ClarkThe 2022 AI Index

122. Ajay Kulkarni and Mike FreedmanWhy You Need A Time-Series Database

121. Wendy FosterData Science at Shopify

120. Elham Tabassi and Andrew BurtAn AI Risk Management Framework

119. Amit Sharma and Emre KicimanAn open source and end-to-end library for causal inference

118. Leo MeyerovichThe Graph Intelligence Stack

117. Dia Trambitas-Miron and David TalbyNLP and Language Models in Healthcare and the Life Sciences

116. Simon CrosbyDelivering Continuous Intelligence at Scale

115. Nicholas BoucherImperceptible NLP Attacks

114. Anjali SamaniEvolving Data Science Training Programs

113. Savin GoyalBuilding Machine Learning Infrastructure at Netflix and beyond

112. Moshe WasserblatDemocratizing NLP

111. Gaurav ChakravortyMachine Learning at Discord

110. Mike TungApplications of Knowledge Graphs

109. Ben Lorica and Mikio Braun in conversation with Jenn WebbKey AI and Data Trends for 2022


108. Connor Leahy and Yoav ShohamLarge Language Models

107. Azeem AhmedData and Machine Learning Platforms at Shopify

106. Christopher NguyenWhat is AI Engineering?

105. Anshul PandeyNLP and AI in Financial Services

104. Che SharmaModern Experimentation Platforms

103. Nic Hohn and Max PumperlaReinforcement Learning in Real-World Applications

102. Nikhil MuralidharMLOps Anti-Patterns

101.  Pardhu Gunnam and Mars LanWhy You Need a Modern Metadata Platform

100. Yoav ShohamMaking Large Language Models Smarter

99. Jeremy StanleyAI Begins With Data Quality

98. Michel TricotModernizing Data Integration

97.  Hamel HusainDeploying Machine Learning Models Safely and Systematically

96.  Bob FridayLarge-scale machine learning and AI on multi-modal data

95.  Viviana AcquavivaMachine Learning in Astronomy and Physics

94.  Viral ShahThe Unreasonable Effectiveness of Multiple Dispatch

93.  Jike Chong and Yue Cathy Chang in conversation with Jenn Webb and Ben LoricaHow To Lead In Data Science

92.  Paco Nathan in conversation with Jenn Webb and Ben LoricaWhy interest in graph databases and graph analytics are growing

91.  Tara Kelly in conversation with Jenn Webb and Ben LoricaThe State of Data Journalism

90.  Rayid Ghani and Andrew BurtAuditing machine learning models for discrimination, bias, and other risks

89.  Charles MartinAn oscilloscope for deep learning

88.  Jesse Anderson in conversation with Jenn Webb and Ben LoricaWhat’s new in data engineering

87.  Sean Taylor in conversation with Jenn Webb and Ben LoricaChanges to the data science role and to data science tools

86.  Steven Feng and Eduard HovyData Augmentation in Natural Language Processing

85.  Brad KingStorage Technologies for a Multi-cloud World

84.  Chris White in conversation with Jenn Webb and Ben LoricaTowards a next-generation dataflow orchestration and automation system

83.  Reza Hosseini and Albert ChenBuilding a flexible, intuitive, and fast forecasting library

82.  Sercan ArikNeural Models for Tabular Data

81.  Connor LeahyTraining and Sharing Large Language Models

80.  Paolo Cremonesi and Maurizio Ferrari DacremaQuestioning the Efficacy of Neural Recommendation Systems

79.  Hyun KimAutomation in Data Management and Data Labeling

78.  Nicolas HohnReinforcement Learning For the Win

77.  Andrew BurtHow Companies Are Investing in AI Risk and Liability Minimization

76.  Travis AddairThe Future of Machine Learning Lies in Better Abstractions

75.  Yonatan Geifman and Ran El-YanivWhy You Should Optimize Your Deep Learning Inference Platform

74.  Jerry Overton in conversation with Jenn Webb and Ben LoricaAI Beyond Automation

73.  Steve TouwInjecting Software Engineering Practices and Rigor into Data Governance

72.  Davit BuniatyanBuilding a data store for unstructured data and deep learning applications

71.  Zhe ZhangHow Technology Companies Are Using Ray

70.  Abe GongData quality is key to great AI products and services

69.  Parisa RashidiMachine Learning in Healthcare

68.  Simon Rodriguez in conversation with Jenn Webb and Ben LoricaMeasuring the Impact of AI and Machine Learning Research

67.   Ryan WisneskyThe Mathematics of Data Integration and Data Quality

66.  Jian PeiPricing Data Products

65.  Sharon Zhou in conversation with Jenn Webb and Ben LoricaChallenges, Opportunities, and Trends in EdTech

64.  Alex Wong and Sheldon FernandezTowards Simple, Interpretable, and Trustworthy AI

63.  Assaf Araki and Ben Lorica in conversation with Jenn WebbThe Rise of Metadata Management Systems

62.  Michael MahoneyTools for building robust, state-of-the-art machine learning models

61.  Sonal Goyal and Ben Lorica in conversation with Jenn WebbCreating Master Data at Scale with AI

60.  Bruno Fernandez-RuizBringing AI and computing closer to data sources

59.  Bharath RamsundarDeep Learning in the Sciences

58.  Ira CohenTaking business intelligence and analyst tools to the next level

57.   Omer DrorData exchanges and their applications in healthcare and the life sciences


56.   Ben Lorica and Mikio Braun in conversation with Jenn WebbKey AI and Data Trends for 2021

55.   Jesse Anderson and Ben Lorica in conversation with Jenn WebbA Unified Management Model for Successful Data-Focused Teams

54.   Dan Geer and Andrew BurtSecurity and privacy for the disoriented

53.   Rumman ChowduryThe State of Responsible AI

52.   Jack MorrisImproving the robustness of natural language applications

51.   Yishay CarmielEnd-to-end deep learning models for speech applications

50.   Ram ShankarSecuring machine learning applications

49.   Marco RibeiroTesting Natural Language Models

48.   Xiyin ZhouDetecting Fake News

47.   Neil ThompsonThe Computational Limits of Deep Learning

46.   Piero MolinoMaking deep learning accessible

45.   Mayank KejriwalBuilding and deploying knowledge graphs

44.   Murat ÖzbayoğluFinancial Time Series Forecasting with Deep Learning

43.   Viral ShahA programming language for scientific machine learning and differentiable programming

42.   Kira RadinskyUsing machine learning to modernize medical triage and monitoring systems

41.   Max PumperlaConnecting Reinforcement Learning to Simulation Software

40.   Weifeng ZhongUsing machine learning to detect shifts in government policy

39.   Ofer RazonWhat is AI Assurance?

38.   Alan NicholBest practices for building conversational AI applications

37.   Paco Nathan and Ben Lorica in conversation with Jenn WebbTools for scaling machine learning

36.   Joel GrusFrom Python beginner to seasoned software engineer

35.   Bruno GonçalvesAssessing Models and Simulations of Epidemic Infectious Diseases

34.   Karthik Ramasamy and Arun KejariwalImproving the hiring pipeline for software engineers

33.   Lauren KunzeHow to build state-of-the-art chatbots

32.   Ameet TalwalkarDemocratizing Machine Learning

31.   Denise GosnellHow graph technologies are being used to solve complex business problems

30.   Amy HeineikeMachines for unlocking the deluge of COVID-19 papers, articles, and conversations

29.   Christopher NguyenDesigning machine learning models for both consumer and industrial applications

28.   Matthew HonnibalBuilding open source developer tools for language applications

27.   Chris WigginsViewing machine learning and data science applications as sociotechnical systems

26.   Andrew BurtIdentifying and mitigating liabilities and risks associated with AI

25.   Arun Verma (in conversation with Jenn Webb) → How machine learning is being used in quantitative finance

24.   Harish DoddiUnderstanding machine learning model governance

23.   Wes McKinneyImproving performance and scalability of data science libraries

22.   Pete WardenWhy TinyML will be huge

21.   Evan SparksAn open source platform for training deep learning models

20.   Kenneth StanleyAlgorithms that continually invent both problems and solutions

19.   Bruno GonçalvesComputational Models and Simulations of Epidemic Infectious Diseases

18.   Robert MunroHuman-in-the-loop machine learning

17.   Chris NicholsonNext-generation simulation software will incorporate deep reinforcement learning

16.   Solmaz ShahalizadehBusiness at the speed of AI: Lessons from Shopify

15.   Edo LibertyHow deep learning is being used in search and information retrieval

14.   Alejandro SaucedoThe responsible development, deployment and operation of machine learning systems

13.   Edmon BegoliHyperscaling natural language processing

12.   Krishna GadeWhat businesses need to know about model explainability

11.   Dean WamplerScalable Machine Learning, Scalable Python, For Everyone

10.  Dafna ShahafComputational humanness, analogy and innovation, and soft concepts

9.    David TalbyBuilding domain specific natural language applications

8.    Morten DahlThe state of privacy-preserving machine learning

7.     Sijie GuoTaking messaging and data ingestion systems to the next level

6.    Bahman BahmaniBusiness at the speed of AI: Lessons from Rakuten

5.    Nir ShavitThe combination of the right software and commodity hardware will prove capable of handling most machine learning tasks


4.    Ben and Mikio BraunKey AI and Data Trends for 2020

3.    Rajat MongaThe evolution of TensorFlow and of machine learning infrastructure

2.    Reza ZadehBuilding large-scale, real-time computer vision applications

1.    Paco NathanTaking stock of foundational tools for analytics and machine learning