Machine Intelligence and Risk Management

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[00:02:19] – (first question) – Looking at Jeremiah’s background and how he got started in a place where he could work in artificial intelligence

[00:04:43] – The first exposure to necessary approximations and how that led to building models

[00:06:10] – His time at Amaranth and how that led him to getting an advanced degree

[00:08:35] – How does machine learning relates back to the simplest of models and where it goes from there.

[00:10:50] – How does machine learning help break down data sets more quickly

[00:13:35] – Explaining this concept with the example of google’s exploration of machine learning in translation.

[00:16:30] – Google has had a huge leap in accuracy as they had time into their models and a recurring neural network

[00:18:01] – The creation of the Lowin Data Company, what they do, and what has worked for them

[00:21:01] – The Chinese Room Argument (John Searle)

[00:22:19] – The Turing Test

[00:22:55] – What will all this machine learning mean in terms of replacing jobs in society

[00:26:27] – What are the jobs that will tough to replace with a machine

[00:28:02] – Cultivating relationships and the movie Her

[00:29:46] – Why AI machines aren’t intelligent

[00:32:39] – Defining intelligence in machines as possible decision making or leaps of intuition

[00:33:30] – Could discovery by a machine be the sign of intelligence in machines

[00:35:55] – What can we learn from the findings of Lowin Data Company that can be applied to our own ability to learn and improve ourselves

[00:38:35] – What led Jeremiah to start Lowin Data

[00:41:17] – Jeremiah’s working definition of risk

[00:44:34] – The tenements of risk management

[00:46:22] – A big part of risk management is shifting the distribution around

[00:49:59] – How much of this is quantitative vs qualitative

[00:53:14] – Why one of the most important skills in risk management is uncovering unknown unknowns and how Jeremiah applies this in his day-to-day job

[00:56:58] – Getting information out of a closed system

[00:59:59] – How often did Jeremiah’s involvement in a portfolio have a major impact on the decisions that were made

[01:02:13] – What are the dimensions that Jeremiah plots out in his 3D graph that he uses to analyze a portfolio

[01:05:15] – Where does Jeremiah fall when it comes to a simple index portfolio verse a more active portfolio

[01:08:23] – What has driven the change that has led people away from active managed funds

[01:11:01] – Has anything changed internally among hedge fund managers that could lead to a shift towards more passively managed funds

[01:14:11] – Will artificial intelligence based tools become a bigger part of the investing process going forward?

[01:17:52] – Looking at Jeremiah’s most memorable day

[01:20:36] – Kindest thing anyone has ever done for Jeremiah