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Mar 3, 2014 · 24m · mad

Michael Schmidt, SiSense // Data Driven NYC 24 // February 2014 (Hosted by FirstMark Capital)

Michael Schmidt · 20m spoken Matt Turck · 45s spoken
0:00 / 0:00
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At Data Driven NYC, Nutonian CEO Michael Schmidt presents how symbolic regression and the Eureqa platform automate mathematical discovery to transform complex data into transparent, actionable models for both scientific research and enterprise analytics.

How this conversation actually went

Every chapter scored 0–10 on four independent dynamics. Hover any point for the reasoning behind the score. Matt holds 3.4% of the talking time here. How this is scored →

Matt as informed peer 0.1 Guest teaching 2.8 Guest disagreement 0.0 Matt pushing back 0.0
05100:0010:0020:000:41–3:08 · Matt as informed peer 0/10 The Media Concept of the Robotic Data Scientist Michael Schmidt presents a monologue on his graduate research and how media outlets sensationalized symbolic regression as a robotic scientist. As the host does not speak during this presentation segment, host scores are zero.3:08–7:06 · Matt as informed peer 0/10 Overview and Global Adoption Statistics of Eureqa Schmidt explains Eureqa's growth statistics and quizzes the audience on double pendulum physics, gently correcting guesses about angular momentum to explain energy conservation. Because this is a monologue presentation, host metrics remain at zero.7:06–9:46 · Matt as informed peer 0/10 How Symbolic Regression Searches Non-Linear Mathematical Equations Schmidt details how symbolic regression uses binary tree structures to search non-linear equations without requiring new physical experiments. The host does not intervene during this technical monologue.9:46–12:54 · Matt as informed peer 0/10 Balancing Complexity and Accuracy along the Pareto Frontier The guest explains the Pareto frontier trade-off between model complexity and statistical accuracy. Host metrics remain zero due to the unbroken presentation format.12:54–15:05 · Matt as informed peer 0/10 Market Demand and Strategic Positioning for Actionable Models Schmidt outlines Nutonian's positioning between predictive machine learning and data visualization. Host participation is absent during this segment.15:05–17:10 · Matt as informed peer 0/10 Live Demo Importing Multi-Format Data in Eureqa Schmidt conducts a live demonstration showing how Eureqa ingests spreadsheet data, forum text, and boolean variables. Host scores remain zero for this monologue demo.17:10–19:42 · Matt as informed peer 0/10 Live Demo Executing Formula Searches and Model Reports The guest demonstrates running a formula search in Eureqa and highlights how the software automatically extracted the 9.8 gravitational constant from raw data. The host remains silent.19:42–22:35 · Matt as informed peer 0/10 Enterprise Industry Use Cases and Scientific Research Impact Schmidt details real-world enterprise implementations across Dow Chemical, the US Air Force, and retail sales analytics. The host does not interrupt the presentation.22:35–24:45 · Matt as informed peer 1/10 Nutonian Product Roadmap and Concluding Presentation Remarks Host Matt Turck re-enters with a humorous remark about being back in physics class and manages a brief Q&A, where audience member Ryan asks about random signal handling and Schmidt explains how Eureqa defaults to predicting the mean for junk input.0:41–3:08 · Guest teaching 2/10 The Media Concept of the Robotic Data Scientist Michael Schmidt presents a monologue on his graduate research and how media outlets sensationalized symbolic regression as a robotic scientist. As the host does not speak during this presentation segment, host scores are zero.3:08–7:06 · Guest teaching 4/10 Overview and Global Adoption Statistics of Eureqa Schmidt explains Eureqa's growth statistics and quizzes the audience on double pendulum physics, gently correcting guesses about angular momentum to explain energy conservation. Because this is a monologue presentation, host metrics remain at zero.7:06–9:46 · Guest teaching 3/10 How Symbolic Regression Searches Non-Linear Mathematical Equations Schmidt details how symbolic regression uses binary tree structures to search non-linear equations without requiring new physical experiments. The host does not intervene during this technical monologue.9:46–12:54 · Guest teaching 3/10 Balancing Complexity and Accuracy along the Pareto Frontier The guest explains the Pareto frontier trade-off between model complexity and statistical accuracy. Host metrics remain zero due to the unbroken presentation format.12:54–15:05 · Guest teaching 2/10 Market Demand and Strategic Positioning for Actionable Models Schmidt outlines Nutonian's positioning between predictive machine learning and data visualization. Host participation is absent during this segment.15:05–17:10 · Guest teaching 2/10 Live Demo Importing Multi-Format Data in Eureqa Schmidt conducts a live demonstration showing how Eureqa ingests spreadsheet data, forum text, and boolean variables. Host scores remain zero for this monologue demo.17:10–19:42 · Guest teaching 3/10 Live Demo Executing Formula Searches and Model Reports The guest demonstrates running a formula search in Eureqa and highlights how the software automatically extracted the 9.8 gravitational constant from raw data. The host remains silent.19:42–22:35 · Guest teaching 3/10 Enterprise Industry Use Cases and Scientific Research Impact Schmidt details real-world enterprise implementations across Dow Chemical, the US Air Force, and retail sales analytics. The host does not interrupt the presentation.22:35–24:45 · Guest teaching 3/10 Nutonian Product Roadmap and Concluding Presentation Remarks Host Matt Turck re-enters with a humorous remark about being back in physics class and manages a brief Q&A, where audience member Ryan asks about random signal handling and Schmidt explains how Eureqa defaults to predicting the mean for junk input.0:41–3:08 · Guest disagreement 0/10 The Media Concept of the Robotic Data Scientist Michael Schmidt presents a monologue on his graduate research and how media outlets sensationalized symbolic regression as a robotic scientist. As the host does not speak during this presentation segment, host scores are zero.3:08–7:06 · Guest disagreement 0/10 Overview and Global Adoption Statistics of Eureqa Schmidt explains Eureqa's growth statistics and quizzes the audience on double pendulum physics, gently correcting guesses about angular momentum to explain energy conservation. Because this is a monologue presentation, host metrics remain at zero.7:06–9:46 · Guest disagreement 0/10 How Symbolic Regression Searches Non-Linear Mathematical Equations Schmidt details how symbolic regression uses binary tree structures to search non-linear equations without requiring new physical experiments. The host does not intervene during this technical monologue.9:46–12:54 · Guest disagreement 0/10 Balancing Complexity and Accuracy along the Pareto Frontier The guest explains the Pareto frontier trade-off between model complexity and statistical accuracy. Host metrics remain zero due to the unbroken presentation format.12:54–15:05 · Guest disagreement 0/10 Market Demand and Strategic Positioning for Actionable Models Schmidt outlines Nutonian's positioning between predictive machine learning and data visualization. Host participation is absent during this segment.15:05–17:10 · Guest disagreement 0/10 Live Demo Importing Multi-Format Data in Eureqa Schmidt conducts a live demonstration showing how Eureqa ingests spreadsheet data, forum text, and boolean variables. Host scores remain zero for this monologue demo.17:10–19:42 · Guest disagreement 0/10 Live Demo Executing Formula Searches and Model Reports The guest demonstrates running a formula search in Eureqa and highlights how the software automatically extracted the 9.8 gravitational constant from raw data. The host remains silent.19:42–22:35 · Guest disagreement 0/10 Enterprise Industry Use Cases and Scientific Research Impact Schmidt details real-world enterprise implementations across Dow Chemical, the US Air Force, and retail sales analytics. The host does not interrupt the presentation.22:35–24:45 · Guest disagreement 0/10 Nutonian Product Roadmap and Concluding Presentation Remarks Host Matt Turck re-enters with a humorous remark about being back in physics class and manages a brief Q&A, where audience member Ryan asks about random signal handling and Schmidt explains how Eureqa defaults to predicting the mean for junk input.0:41–3:08 · Matt pushing back 0/10 The Media Concept of the Robotic Data Scientist Michael Schmidt presents a monologue on his graduate research and how media outlets sensationalized symbolic regression as a robotic scientist. As the host does not speak during this presentation segment, host scores are zero.3:08–7:06 · Matt pushing back 0/10 Overview and Global Adoption Statistics of Eureqa Schmidt explains Eureqa's growth statistics and quizzes the audience on double pendulum physics, gently correcting guesses about angular momentum to explain energy conservation. Because this is a monologue presentation, host metrics remain at zero.7:06–9:46 · Matt pushing back 0/10 How Symbolic Regression Searches Non-Linear Mathematical Equations Schmidt details how symbolic regression uses binary tree structures to search non-linear equations without requiring new physical experiments. The host does not intervene during this technical monologue.9:46–12:54 · Matt pushing back 0/10 Balancing Complexity and Accuracy along the Pareto Frontier The guest explains the Pareto frontier trade-off between model complexity and statistical accuracy. Host metrics remain zero due to the unbroken presentation format.12:54–15:05 · Matt pushing back 0/10 Market Demand and Strategic Positioning for Actionable Models Schmidt outlines Nutonian's positioning between predictive machine learning and data visualization. Host participation is absent during this segment.15:05–17:10 · Matt pushing back 0/10 Live Demo Importing Multi-Format Data in Eureqa Schmidt conducts a live demonstration showing how Eureqa ingests spreadsheet data, forum text, and boolean variables. Host scores remain zero for this monologue demo.17:10–19:42 · Matt pushing back 0/10 Live Demo Executing Formula Searches and Model Reports The guest demonstrates running a formula search in Eureqa and highlights how the software automatically extracted the 9.8 gravitational constant from raw data. The host remains silent.19:42–22:35 · Matt pushing back 0/10 Enterprise Industry Use Cases and Scientific Research Impact Schmidt details real-world enterprise implementations across Dow Chemical, the US Air Force, and retail sales analytics. The host does not interrupt the presentation.22:35–24:45 · Matt pushing back 0/10 Nutonian Product Roadmap and Concluding Presentation Remarks Host Matt Turck re-enters with a humorous remark about being back in physics class and manages a brief Q&A, where audience member Ryan asks about random signal handling and Schmidt explains how Eureqa defaults to predicting the mean for junk input.

speaking balance: gold is Matt, purple is the guest (3 minute bins)

0:00 · Matt 21.7% · guest 78.3%0:00 · Matt 21.7% · guest 78.3%3:00 · Matt 0% · guest 100%3:00 · Matt 0% · guest 100%6:00 · Matt 0% · guest 100%6:00 · Matt 0% · guest 100%9:00 · Matt 0% · guest 100%9:00 · Matt 0% · guest 100%12:00 · Matt 0% · guest 100%12:00 · Matt 0% · guest 100%15:00 · Matt 0% · guest 100%15:00 · Matt 0% · guest 100%18:00 · Matt 0% · guest 100%18:00 · Matt 0% · guest 100%21:00 · Matt 6.4% · guest 93.6%21:00 · Matt 6.4% · guest 93.6%24:00 · Matt 2% · guest 98%24:00 · Matt 2% · guest 98%
Sharpest disagreement ▶ 8:00 Dismissing incorrect audience mathematical guesses

In a completely non-combative talk, Schmidt's mildest pushback is quickly rejecting incorrect audience guesses during a math illustration ('No, not the sigmoid').

 Hardest push from Matt ▶ 23:20 Host enforcing strict time constraints for Q&A

Matt Turck steps in at the end of the presentation to cap the live session, restricting audience participation to 'one quick one' before directing further discussion to offline networking.

 Biggest teaching moment ▶ 3:45 Educating the room on conserved physical quantities

Schmidt quizzes the audience on double pendulum dynamics and corrects guesses regarding angular momentum by explaining energy conservation principles.

 Matt holds his own ▶ 23:20 Host humorously contextualizing the technical depth

Matt Turck expertly re-engages the audience after a dense mathematical demo by lightheartedly noting 'didn't realize you'd be back to physics class tonight, huh?'
the scores for every segment, with the reasoning behind each
ChapterTopicMatt as informed peerGuest teachingGuest disagreementMatt pushing backWhy
The Media Concept of the Robotic Data Scientist 0200 Michael Schmidt presents a monologue on his graduate research and how media outlets sensationalized symbolic regression as a robotic scientist. As the host does not speak during this presentation segment, host scores are zero.
Overview and Global Adoption Statistics of Eureqa 0400 Schmidt explains Eureqa's growth statistics and quizzes the audience on double pendulum physics, gently correcting guesses about angular momentum to explain energy conservation. Because this is a monologue presentation, host metrics remain at zero.
How Symbolic Regression Searches Non-Linear Mathematical Equations 0300 Schmidt details how symbolic regression uses binary tree structures to search non-linear equations without requiring new physical experiments. The host does not intervene during this technical monologue.
Balancing Complexity and Accuracy along the Pareto Frontier 0300 The guest explains the Pareto frontier trade-off between model complexity and statistical accuracy. Host metrics remain zero due to the unbroken presentation format.
Market Demand and Strategic Positioning for Actionable Models 0200 Schmidt outlines Nutonian's positioning between predictive machine learning and data visualization. Host participation is absent during this segment.
Live Demo Importing Multi-Format Data in Eureqa 0200 Schmidt conducts a live demonstration showing how Eureqa ingests spreadsheet data, forum text, and boolean variables. Host scores remain zero for this monologue demo.
Live Demo Executing Formula Searches and Model Reports 0300 The guest demonstrates running a formula search in Eureqa and highlights how the software automatically extracted the 9.8 gravitational constant from raw data. The host remains silent.
Enterprise Industry Use Cases and Scientific Research Impact 0300 Schmidt details real-world enterprise implementations across Dow Chemical, the US Air Force, and retail sales analytics. The host does not interrupt the presentation.
Nutonian Product Roadmap and Concluding Presentation Remarks 1300 Host Matt Turck re-enters with a humorous remark about being back in physics class and manages a brief Q&A, where audience member Ryan asks about random signal handling and Schmidt explains how Eureqa defaults to predicting the mean for junk input.

Statements from this episode (8)

Assertion Not checkable as stated
Data Driven NYC meetup turnout is sometimes 50% of registered attendees
“Sometimes, you know, 50% of people actually show up.”
Matt Turck Mar 3, 2014 ▶ 0:26
Assertion Not checkable as stated
Nutonian's Eureqa software is installed on 50,000 systems across 90 countries
“So we've been installed over, I think we're up to about 50,000 systems now in about 90 countries, and we're growing by about, you know, 1500 new users, new trials of the software per month.”
Michael Schmidt Mar 3, 2014 ▶ 3:24
Assertion Contradicted
Nutonian's Eureqa software is cited in 80,000 independent peer-reviewed publications
“Seeing all the publications that are coming off where they're citing us in the results, so up to 80,000 independent peer-reviewed, you know, publications where we're directly citing the results of this cutting edge research.”
Michael Schmidt Mar 3, 2014 ▶ 3:36
Assertion Supported
Michael Schmidt's graduate research on symbolic regression was published in Science
“We got published in Science.”
Michael Schmidt Mar 3, 2014 ▶ 5:45
Disclosure
Nutonian represents equations as binary trees in memory for symbolic regression
“We're searching the space of non-linear equations, where we represent these as a binary tree in memory, where every operation is, you know, every node is an operation, like a mathematical operation”
Michael Schmidt Mar 3, 2014 ▶ 8:40
Assertion Not checkable as stated
Michael Schmidt: Fitting data with complex machine learning models is solved
“So, one interesting thing is it's actually really, really easy to fit data. It's actually, it's quite boring. You know, you have, you know, a really large, complex model. Maybe it's a neural network. Maybe it's a random forest. Or maybe it's just a really larg…”
Michael Schmidt Mar 3, 2014 ▶ 9:47
Disclosure
Nutonian's Eureqa software is free for academic research
“If you're academia, you can use it for free, you know, for all your research, and I encourage you guys to do that.”
Michael Schmidt Mar 3, 2014 ▶ 15:24
Assertion Not checkable as stated
Nutonian helped the U.S. Air Force detect material cracks 10x faster
“One of our other biggest customers is the Air Force, and this is a case where they do a ton of work trying to detect when failures happen, and there's a lot of things that go into failures, and actually being able to detect when cracks form, microscopic cracks…”
Michael Schmidt Mar 3, 2014 ▶ 20:48
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