Goldman Sachs automated trading replaces 600 traders with 200 engineers

Post by walshemj » Tue, Feb 07, 2017, 10:23 PM UTC

burkaman wrote: post #11

tomelders wrote: post #4

A agency that I once worked for was asked to create a presentation of the future of trading for a well known trading platform. It was the typical fluff around voice interfaces, augmented reality, VR and all that drivel. But we all knew what the future really meant - taking people out of the equation - but we also knew that the people paying for the presentation didn't want to hear that. When people talk about the ris…

Isn't this type of trading sort of unique in how easy it is to consume the data? Even in other investing areas, people who just "look at data and make decisions" cannot be easily replaced until computers can read and understand natural language and understand the state of the world. I can't immediately think of anything else this type of automation could apply to.

Post by eru » Tue, Feb 07, 2017, 10:28 PM UTC

lsaferite wrote: post #49

onion2k wrote: post #40

Earlier quoted context omitted.

because when you can write a computer program with an AI you can make the AI write the AI and you have general AI There doesn't need to be a single AI to create the entire app. An AI to model data structure, an AI to build an interface, an AI to consume external APIs, etc. We already mostly bolt libraries together to make software; it doesn't take a huge leap for those libraries to be generated by machine learning. B…

I have a feeling someone said the same thing 10 or 20 years ago.

Post by ebiester » Tue, Feb 07, 2017, 10:31 PM UTC

extr wrote: post #59

teachrdan wrote: post #42

Earlier quoted context omitted.

Another obvious example is actuaries and any number of other analysts in the insurance industry. According to Google[1], actuaries earn an average of just over $97k/year. While this may not strictly be an "investing area," it's a clear target for automation. 1. https://www.google.com/search?q=actuaries

Part of the reason actuaries make so much is that they are certified and legally required to sign off on analysis, similar to the way civil engineers put their signature (and reputation) on their work. But you would be surprised how many decisions come down to "actuarial judgement", having good business sense, intimate knowledge of insurance rules and regulations...and not doing anything special with the data. Hell,…

Post by eru » Tue, Feb 07, 2017, 10:33 PM UTC

blazespin wrote: post #20

fun fact: Advanced AI techniques work in very high dimensional spaces in such a way that it's impossible to clearly understand why a program reaches a conclusion that it does. Market trading is about allocating capital that decides how labor itself is allocated. So, increasingly, we have computers that are telling people what to work on and we don't know why they are making those decisions. We could remove the comput…

Post by tomelders » Tue, Feb 07, 2017, 10:44 PM UTC

burkaman wrote: post #31

tomelders wrote: post #15

Earlier quoted context omitted.

Not really. The world is data. Anything you need to know about the world is in a table somewhere, and the web has done a great job of making the planets data accessible to machines. Other areas may be more complex, but complexity isn't as big a barrier as it may seem. Also, those areas are probably not as complex as people think they are. I'm reminded of the AI that started making breakthroughs in oncology by looking…

> Anything you need to know about the world is in a table somewhere No it isn't. If I read an article about the Volkswagen emissions scandal, what table do I look in to figure out how much consumers will care, and how aggressive various governments will be with their punishment? When Disney buys the rights to Star Wars, where should I look to see if it's worth what they paid for it? Should I rely on data from 30 year…