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great looking for sighing all the wrong

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restarting okay good morning everybody

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okay so just some quick definitions psy

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is an umbrella term that covers

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telepathy clairvoyance precognition and

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psychokinesis parapsychology is the

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scientific study of psy and also topics

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relating to post-mortem survival today

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I'm only going to talk about psy and not

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survival so over the years

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parapsychologists have been rallying

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around standardized protocols to test

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various aspects of psy and that's a good

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thing

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standardization is helpful you can do

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meta-analysis on your data you can

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replicate in different labs typically a

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way a typical experiment would work as

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we'd recruit people from a general

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population and we would run them through

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si mode protocol but when we do this

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what we find is that not everyone's data

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actually produces evidence for psy so

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being scientists were very clever and we

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have figured out ways that we might be

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able to optimize our populations to find

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high performers and so some of those

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ways short of full genetic testing and F

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MRIs might include things like belief

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whether or not people meditate levels of

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creativity previous eye experience and

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so on in addition we become good at

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looking at target optimization and the

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roles of researchers in the in their

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experiments so even when we optimize for

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all these things we still end up with a

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portion of our selected optimized

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population whose data don't necessarily

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support evidence for psy

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I find this very annoying and this is

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the thing I've been sort of obsessing

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out over so we end up with these two

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populations

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are optimized subset of our optimized

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population that isn't doesn't do well on

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a test and then this whole other group

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of people that for some reason don't do

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well on these tests at all and so I'm

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really interested in understanding why

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that is so in this talk I'm going to

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give some examples of where I'm seen

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that sort of play out in my own research

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and some a new research project that we

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hope will sort of look into this a

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little bit more so the first example I

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want to give is a project a joint

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research project between Julia Moss

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bridge and the Moss bridge Institute and

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the wind bridge Institute where I work

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and that's not confusing at all anyway

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and so we haven't formally published

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these data yet so I'm not gonna go into

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a lot of detail but there's one aspect

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of this experiment that I wanted to talk

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about which is relevant so at the

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beginning of our experiment after we

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selected our population we asked all of

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our participants to fill out a survey

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and on what and rate their frequency of

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precognitive experiences so on one end

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we're like no I've never had a

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precognitive experience on the other end

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they often have pre cognitive

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experiences so this is the results of

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that survey would basically 29 percent

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of the people in our population where

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frequent Precog errs and I'm like those

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are our peeps that's gonna be good but

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when we run the experiment and look at

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the results of the data what we find

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that of these frequent Precog errs only

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39% showed a result and 61% failed

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sorry that's that's wrong our test

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wasn't designed in a way that allowed us

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to capture what these people were

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experiencing so in some some extent for

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as a general test this didn't quite cut

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it but we were testing for something

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very specific in another set of

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experiments I've been working on for a

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while I've been using real-time 3d

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virtual reality systems to develop SCI

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testing and training

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applications and these have run across a

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number of different scenarios mostly

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dealing with first responders and

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search-and-rescue applications we've

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also been doing things with threat

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avoidance and asset recovery I can't

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talk about all this stuff today but I'm

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going to focus on the threat avoidance

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piece so this is a pretty

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straightforward simulation you have an

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operator the goal is to move the

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operator safely from point A to point B

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in the simulation the operator has to

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make intuitive choices about which way

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to go so they avoid roadside bombs

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basically and so in the first round of

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experiments we use these operators and

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they were relying on their own intuitive

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abilities to safely navigate the space

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and what we found is that this worked

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spectacularly poorly and what we found

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is that the operators were incredibly

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good at finding these bombs and and if

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you think about it it sort of makes

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sense because the people that would be

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attracted to being involved in this kind

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of experiment they're a little bit

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adrenaline junkies and so the way the

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experiment works is if you successfully

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get to the end nothing happens you get a

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pat on the head and you're rewarded for

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your ability to not get hurt but what

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makes more sense is the reason why these

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people were finding these explosives is

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that when you bump into one there's an

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adrenaline rush it's a surprise you get

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a visceral hit and so it really appealed

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to the people that were actually doing

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the experiment so I had to take a step

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back and rethink this because unlike

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Dean I don't have a lot of research

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assistants so I've involved in all of

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our experiments so for the second round

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I said I decided maybe we could pair the

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the operators in the experiment with

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intuitive's

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remote location watching the operators

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remotely and then giving feedback

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to the operators about how to navigate

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the space and this actually worked much

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better our success rates were getting

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higher but the intuitive's didn't like

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this at all

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they were really uncomfortable with the

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real-time video aspect and the whole

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guns and bombs thing really wasn't

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sitting comfortably with this population

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and I said well that's a really

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interesting challenge how do we

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incorporate the talents of intuitive's

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in a way that works for them on an

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emotional and psychological level but

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still meet the objectives of our test

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which is to safely navigate our

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operators across the space in real-time

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so I became really interested in this

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idea of proxy tasking and so I ended up

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developing a second app specifically for

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the intuitive's and so instead of the

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intuitive seeing our friend with an m4

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they got to see this dog and instead of

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navigating this post-apocalyptic

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landscape they got to see this little

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island with a forest on it and so again

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in the third round of experiments we had

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our operator in our intuitive's and the

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intuitive's were navigating the dog

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through the island space and the

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operators were in the simulation and

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there was a real-time feedback loop

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between the two and the results from

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this while still very preliminary are

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these are the best results so far we

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seem to be getting much higher accuracy

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rates the intuitive seem much happier

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and of course the operators have sort of

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stopped blowing themselves up on purpose

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okay so the interesting bit from my

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perspective is that we basically had

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this simulation which had the the sorry

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we had the simulation of the threat

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avoidance simulation and we had these

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two very different populations that were

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interacting with that simulation and

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having different results and different

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feelings

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about it and it wasn't until we

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basically tweaked the facade of that

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application that we suddenly got really

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good responses and data and evidence

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force I out of this other intuitive

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population so that drove drew me back to

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this annoying thing and I started to

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think well could we instead of using

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these standardized protocols could we

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give each participant their own highly

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individualized task optimized for SCI

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modality motivation and other

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personality variables and so we're

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starting to see this move away from

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certain kinds of standardization and

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other fields so an education for example

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the SATs were recently tweaked to

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account for people's social economic

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factors that might impact their scores

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and also in education the GREs were

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recently dumped from a bunch of

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universities as requirements for

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admission because initially they weren't

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really good predictors of how people

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would do in grad school and then in

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healthcare we're seeing sort of this

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interest to move away from standards of

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care to highly specialized treatments

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based on genetics and other factors so

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what would it mean could we take this

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idea of high high specialization and

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apply it to SCI research and if we were

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to do that would we would we be able to

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capture evidence for SCI in new

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populations create opportunities for

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personal SCI exploration provide new

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tools for application development so I

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came up with this project with the not

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so exciting name of the site asked

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optimization project and it's very

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simple we recruited a bunch of

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participants at the moment we're giving

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everyone the BFI ten the Machiavellian

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scale and the emotional the empathy

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potion and I'm doing this specifically

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at this time because I really want to

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leverage off of what

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learned from our intuitive's and

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operators in the other experiment and

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the threat avoidance experiment once we

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have our participants we'll break them

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randomly assign them to two groups we'll

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let them play a series of games these

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games are optimized to appeal to people

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with these certain personality I don't

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wanna use the word traits but I'm going

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to use the word traits and a

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counterbalance fashion and then we'll

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analyze the data so what are these games

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that we're talking about so we're going

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to continue to work on things like

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virtual reality and augmented reality

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games apps and other online activities

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that people can do but I have to admit

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I'm a little app doubt there's this

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really and it makes sense to use apps

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you can get a lot of online experiments

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you can get a lot of people through you

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can you get accuracy of protocol and all

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those kinds of things but I start to

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feel like we're moving away from the

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human components that for me is what SCI

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is really all about it's this human

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interaction piece that I feel is really

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missing so I started developing

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literally in the last like three or four

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weeks a series of board games that allow

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groups of people to come together and

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try to experience their own SCI and I

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think this is really interesting because

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when you get people together they're in

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their own you're in bio fields that

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you're sharing your there's the

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opportunity for spontaneous side to

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express itself and things like that so

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these games which actually brought if

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anybody's interested we talk about it

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later

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our series of flex and they're still in

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00:12:37,689 --> 00:12:35,730
the design phases we've we literally

280
00:12:40,819 --> 00:12:37,699
just did this over the last few weeks

281
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they're a series of flexible components

282
00:12:45,619 --> 00:12:43,290
that allow us to test different the game

283
00:12:47,509 --> 00:12:45,629
mechanics and play styles so we can

284
00:12:48,860 --> 00:12:47,519
tweak things like the timing whether

285
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it's a single-player activity

286
00:12:53,809 --> 00:12:51,569
multiplayer a competitive so on and then

287
00:12:55,819 --> 00:12:53,819
we can also tweak the activities to

288
00:12:59,559 --> 00:12:55,829
whether it's generally is pee test or

289
00:13:01,819 --> 00:12:59,569
telepathy test Prieta Precog PK etc

290
00:13:02,620 --> 00:13:01,829
although I try not to get too hung up on

291
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that

292
00:13:10,300 --> 00:13:07,190
separations in modality so I do have

293
00:13:13,090 --> 00:13:10,310
some very very preliminary findings from

294
00:13:16,389 --> 00:13:13,100
people using these two games as they're

295
00:13:18,070 --> 00:13:16,399
still in the design phase so the first

296
00:13:20,590 --> 00:13:18,080
bit the first thing we sort of learned

297
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is that people with lower empathy scores

298
00:13:25,269 --> 00:13:22,880
tend to do better on competitive games

299
00:13:28,000 --> 00:13:25,279
that are Precog based and they tend to

300
00:13:32,079 --> 00:13:28,010
be really good at macro pique tests

301
00:13:33,699 --> 00:13:32,089
specifically dice rolling on the flip

302
00:13:36,160 --> 00:13:33,709
side of that we found that people with

303
00:13:37,630 --> 00:13:36,170
higher higher end a--they scores do

304
00:13:40,870 --> 00:13:37,640
better in cooperative collaborative

305
00:13:43,540 --> 00:13:40,880
games co-op games but they tend to do

306
00:13:48,340 --> 00:13:43,550
really poorly on the peak a macro pique

307
00:13:49,600 --> 00:13:48,350
tests and then we had a third so one of

308
00:13:51,820 --> 00:13:49,610
the other games we started to play with

309
00:13:55,449 --> 00:13:51,830
was this game that I kind of love but

310
00:14:00,340 --> 00:13:55,459
it's called psychic spy and your goal is

311
00:14:03,670 --> 00:14:00,350
to prevent your your opponent from

312
00:14:05,920 --> 00:14:03,680
guessing your secrets and it's sort of a

313
00:14:07,720 --> 00:14:05,930
telepathy based game and unfortunately

314
00:14:09,640 --> 00:14:07,730
no one has done well in this game it's

315
00:14:12,300 --> 00:14:09,650
all so I've been coming in a chance and

316
00:14:17,110 --> 00:14:12,310
I got to figure out why that's happening

317
00:14:18,610 --> 00:14:17,120
so again as I said all this stuff has

318
00:14:21,070 --> 00:14:18,620
sort of been happening over the last few

319
00:14:23,769 --> 00:14:21,080
weeks and sort of what I realized a

320
00:14:25,660 --> 00:14:23,779
little bit late in the game was that

321
00:14:28,030 --> 00:14:25,670
essentially what we're doing at the end

322
00:14:31,329 --> 00:14:28,040
of the day is we're taking tests and

323
00:14:33,519 --> 00:14:31,339
we're gamifying them so it probably

324
00:14:35,079 --> 00:14:33,529
would be a really good idea in addition

325
00:14:37,390 --> 00:14:35,089
to our standard psychological measures

326
00:14:39,790 --> 00:14:37,400
to have a good idea of how people

327
00:14:41,590 --> 00:14:39,800
interact with games what they like about

328
00:14:43,540 --> 00:14:41,600
games what they don't like about games

329
00:14:45,610 --> 00:14:43,550
so on and so forth and so there's some

330
00:14:48,190 --> 00:14:45,620
online measures that let us create gamer

331
00:14:50,199 --> 00:14:48,200
motivation profiles so I think in

332
00:14:51,550 --> 00:14:50,209
addition we're gonna start looking at

333
00:14:53,890 --> 00:14:51,560
these data these are just three examples

334
00:14:57,250 --> 00:14:53,900
from three different participants I'm

335
00:14:58,870 --> 00:14:57,260
over on the far my right and these are

336
00:15:00,490 --> 00:14:58,880
some volunteers that let me look at

337
00:15:02,230 --> 00:15:00,500
their data and their similarities but

338
00:15:05,560 --> 00:15:02,240
there's also a lot of differences so

339
00:15:08,530 --> 00:15:05,570
building taking these variables into

340
00:15:11,110 --> 00:15:08,540
account as we develop new games and as

341
00:15:13,019 --> 00:15:11,120
we look at the data it was probably

342
00:15:15,570 --> 00:15:13,029
going to be pretty helpful

343
00:15:17,880 --> 00:15:15,580
so speaking of data

344
00:15:18,720 --> 00:15:17,890
so the final bit is about data what

345
00:15:21,750 --> 00:15:18,730
about how we're going to think about

346
00:15:24,510 --> 00:15:21,760
analyzing these data and as we collect

347
00:15:26,400 --> 00:15:24,520
more data the relationships between all

348
00:15:30,390 --> 00:15:26,410
these different variables maybe not just

349
00:15:33,150 --> 00:15:30,400
whole readings or whole survey scores

350
00:15:35,100 --> 00:15:33,160
but maybe item-by-item scores these

351
00:15:38,850 --> 00:15:35,110
relationships may end up being kind of

352
00:15:40,920 --> 00:15:38,860
complex this may provide an opportunity

353
00:15:42,840 --> 00:15:40,930
to apply machine learning to create

354
00:15:45,270 --> 00:15:42,850
predictive models allowing us to better

355
00:15:48,180 --> 00:15:45,280
determine which tasks are better for

356
00:15:50,510 --> 00:15:48,190
which people and ultimately this may

357
00:15:53,490 --> 00:15:50,520
produce more robust experimental results

358
00:15:55,590 --> 00:15:53,500
and allow us to develop more highly

359
00:15:57,810 --> 00:15:55,600
customized applications which allow

360
00:16:01,380 --> 00:15:57,820
people to better utilize AI in their

361
00:16:04,830 --> 00:16:01,390
daily lives so just some quick

362
00:16:06,360 --> 00:16:04,840
acknowledgments first of all every thank

363
00:16:07,620 --> 00:16:06,370
you to everyone who's been supporting

364
00:16:09,390 --> 00:16:07,630
the wind bridge Institute for the past

365
00:16:11,100 --> 00:16:09,400
11 years

366
00:16:12,870 --> 00:16:11,110
it's amazing to me I get to get up every

367
00:16:15,300 --> 00:16:12,880
morning and do this work I'm humbled and

368
00:16:16,680 --> 00:16:15,310
proud of that of course dr. Julie by

369
00:16:19,040 --> 00:16:16,690
Scholl my wife

370
00:16:22,050 --> 00:16:19,050
our volunteers Ryan Michael and Katie

371
00:16:24,420 --> 00:16:22,060
Julia Moss bridge for continued

372
00:16:27,060 --> 00:16:24,430
enthusiasm around various aspects of my

373
00:16:29,730 --> 00:16:27,070
research and being just a generally

374
00:16:31,380 --> 00:16:29,740
great collaborator of course the SOC

375
00:16:33,360 --> 00:16:31,390
program committee for allowing me the

376
00:16:34,830 --> 00:16:33,370
opportunity to speak today and just

377
00:16:36,870 --> 00:16:34,840
another quick note to all the people

378
00:16:38,550 --> 00:16:36,880
working behind the scenes at this

379
00:16:41,130 --> 00:16:38,560
conference as an attendee and a speaker

380
00:16:42,510 --> 00:16:41,140
this has been really smooth I pry know

381
00:16:45,360 --> 00:16:42,520
that there's a ton of work that goes

382
00:16:48,040 --> 00:16:45,370
into this so with that I will attempt to

383
00:16:55,550 --> 00:16:48,050
answer questions thank you

384
00:17:02,310 --> 00:16:59,640
so I have two comments one is about a

385
00:17:05,670 --> 00:17:02,320
demographic that you might not be aware

386
00:17:08,640 --> 00:17:05,680
of there is evidence that there is a

387
00:17:10,980 --> 00:17:08,650
genetic variation in humans and at least

388
00:17:13,380 --> 00:17:10,990
40 other species called highly sensitive

389
00:17:14,699 --> 00:17:13,390
trait which is actually known to you

390
00:17:16,079 --> 00:17:14,709
know encompass a number of different

391
00:17:18,569 --> 00:17:16,089
brain traits now since its original

392
00:17:20,910 --> 00:17:18,579
discovery I'm one of the people who has

393
00:17:23,069 --> 00:17:20,920
this trait so that's like one in five

394
00:17:24,300 --> 00:17:23,079
people in this room and so I would think

395
00:17:27,179 --> 00:17:24,310
that there's gonna be an overlap between

396
00:17:29,160 --> 00:17:27,189
highly sensitive people and intuitive I

397
00:17:30,990 --> 00:17:29,170
mean people who don't want to you know

398
00:17:32,460 --> 00:17:31,000
run through a simulator and get vertigo

399
00:17:33,930 --> 00:17:32,470
and being bombs I would definitely in

400
00:17:36,540 --> 00:17:33,940
that category but I think that they may

401
00:17:39,450 --> 00:17:36,550
not be fully overlapping and so having

402
00:17:40,950 --> 00:17:39,460
some sort of testing for that may be

403
00:17:42,090 --> 00:17:40,960
useful that's a demographic to

404
00:17:44,700 --> 00:17:42,100
understand what they need in games

405
00:17:46,890 --> 00:17:44,710
absolutely my general goal is to make

406
00:17:49,590 --> 00:17:46,900
psy experiences available to as many

407
00:17:51,870 --> 00:17:49,600
people as possible so I try to stay away

408
00:17:54,540 --> 00:17:51,880
from things that include you know

409
00:17:56,220 --> 00:17:54,550
genetic full genetic testing or F MRIs

410
00:17:57,780 --> 00:17:56,230
or things like that but yeah you're

411
00:18:01,590 --> 00:17:57,790
absolutely correct there's far more

412
00:18:03,270 --> 00:18:01,600
subtlety in people's variations than

413
00:18:05,520 --> 00:18:03,280
what I'm specifically trying to capture

414
00:18:07,800 --> 00:18:05,530
here but we need to start somewhere and

415
00:18:10,380 --> 00:18:07,810
I already leverage I already have some

416
00:18:11,640 --> 00:18:10,390
data around certain populations and I

417
00:18:15,720 --> 00:18:11,650
just want to continue to build off that

418
00:18:18,270 --> 00:18:15,730
that's my second quick comment is sorry

419
00:18:20,160 --> 00:18:18,280
is that playing games is a different

420
00:18:22,470 --> 00:18:20,170
motivation than real life I've been able

421
00:18:25,020 --> 00:18:22,480
to create extreme things to happen in

422
00:18:26,850 --> 00:18:25,030
real life like causing a u-haul truck

423
00:18:29,670 --> 00:18:26,860
that had run out of gas carrying several

424
00:18:30,810 --> 00:18:29,680
tons to go for about five extra miles to

425
00:18:32,700 --> 00:18:30,820
get to the grass station when it was

426
00:18:34,080 --> 00:18:32,710
definitely empty and it literally

427
00:18:35,100 --> 00:18:34,090
stalled the moment we pulled in I'm not

428
00:18:36,990 --> 00:18:35,110
gonna be able pull that off in a game

429
00:18:39,000 --> 00:18:37,000
there's just not that motivation so it

430
00:18:40,230 --> 00:18:39,010
might be useful to consider the

431
00:18:41,670 --> 00:18:40,240
difference in motivation you're

432
00:18:44,010 --> 00:18:41,680
absolutely correct and as a highly

433
00:18:46,350 --> 00:18:44,020
sensitive person you know that you have

434
00:18:49,440 --> 00:18:46,360
that ability what I'm trying to do is

435
00:18:51,930 --> 00:18:49,450
sort of use this as a gateway drug to

436
00:18:53,490 --> 00:18:51,940
give people some confidence that they

437
00:18:55,020 --> 00:18:53,500
can experience SCI on their own because

438
00:18:57,030 --> 00:18:55,030
I run into a lot of people that are like

439
00:18:59,340 --> 00:18:57,040
I'm a psychic brick I can't do this

440
00:19:02,040 --> 00:18:59,350
stuff guess what with the right set and

441
00:19:04,290 --> 00:19:02,050
setting and some encouragement from

442
00:19:05,600 --> 00:19:04,300
people around you you may actually

443
00:19:09,270 --> 00:19:05,610
produce data that's

444
00:19:11,640 --> 00:19:09,280
conducive but thank you mark my question

445
00:19:14,400 --> 00:19:11,650
is actually similar to hers did you take

446
00:19:15,660 --> 00:19:14,410
like age and sex into account I didn't

447
00:19:19,770 --> 00:19:15,670
see where maybe you'd done that if not

448
00:19:22,500 --> 00:19:19,780
yeah yeah we're yeah my son would love

449
00:19:24,930 --> 00:19:22,510
Mortal Kombat me you'd lose me at Mario

450
00:19:26,460 --> 00:19:24,940
Brothers right but but we also have so

451
00:19:28,350 --> 00:19:26,470
for example one of the simulations were

452
00:19:30,180 --> 00:19:28,360
working with is a financial investment

453
00:19:33,600 --> 00:19:30,190
one but that might be more appealing to

454
00:19:35,280 --> 00:19:33,610
you or a research yeah I don't know so

455
00:19:37,800 --> 00:19:35,290
you know so again it's all about

456
00:19:39,780 --> 00:19:37,810
understanding people's specific

457
00:19:41,760 --> 00:19:39,790
motivations I was dealing with the

458
00:19:44,250 --> 00:19:41,770
specific motivations of the population I

459
00:19:46,740 --> 00:19:44,260
had in hand but the broader spectrum of

460
00:19:48,570 --> 00:19:46,750
this is to really dig into the things

461
00:19:54,560 --> 00:19:48,580
that are exciting about people and

462
00:20:05,550 --> 00:20:01,680
forty seven quick comments for you no no

463
00:20:06,960 --> 00:20:05,560
I was joking one really cool thank you

464
00:20:09,990 --> 00:20:06,970
for presenting this oh thank you very

465
00:20:13,070 --> 00:20:10,000
much appreciate that too I particularly

466
00:20:16,650 --> 00:20:13,080
like the message that you're sending and

467
00:20:19,650 --> 00:20:16,660
that it's not all about some kind of

468
00:20:21,570 --> 00:20:19,660
pre-established categories it's going to

469
00:20:22,980 --> 00:20:21,580
be very easy for people to sort of

470
00:20:24,840 --> 00:20:22,990
decide well I can't do this because I

471
00:20:26,820 --> 00:20:24,850
don't have this particular gene or I

472
00:20:28,230 --> 00:20:26,830
don't have whatever and not recognize

473
00:20:31,440 --> 00:20:28,240
that that may be a small piece in a much

474
00:20:33,770 --> 00:20:31,450
larger puzzle that really dictates us so

475
00:20:36,330 --> 00:20:33,780
again kudos I really love the message

476
00:20:38,490 --> 00:20:36,340
and then the third which was actually

477
00:20:41,460 --> 00:20:38,500
the reason I got up here was just a

478
00:20:46,380 --> 00:20:41,470
quick observation that the one game that

479
00:20:48,150 --> 00:20:46,390
had no results was founded on greed no

480
00:20:50,790 --> 00:20:48,160
it's absolutely true but greed is

481
00:20:53,610 --> 00:20:50,800
actually a powerful powerful motivator

482
00:20:56,040 --> 00:20:53,620
for some people yeah maybe just now for

483
00:20:57,660 --> 00:20:56,050
my particular population but but but it

484
00:21:01,170 --> 00:20:57,670
there are a lot of powerful motivators

485
00:21:04,200 --> 00:21:01,180
and it may be that greed is one that

486
00:21:05,850 --> 00:21:04,210
deliberately might hinder some of these

487
00:21:08,130 --> 00:21:05,860
things in comparison to others that's a

488
00:21:08,850 --> 00:21:08,140
really good point thank you very much hi

489
00:21:11,430 --> 00:21:08,860
York

490
00:21:11,830 --> 00:21:11,440
hello I'm glad I already have your

491
00:21:14,680 --> 00:21:11,840
comment

492
00:21:17,380 --> 00:21:14,690
information because I love what you're

493
00:21:19,149 --> 00:21:17,390
doing with the games and you can expect

494
00:21:22,390 --> 00:21:19,159
some communications from me in the near

495
00:21:25,360 --> 00:21:22,400
future but for right now I just wanted

496
00:21:29,159 --> 00:21:25,370
to know given the emphasis or given the

497
00:21:33,190 --> 00:21:29,169
apparent effect of empathy and

498
00:21:35,110 --> 00:21:33,200
collaborative personality on sihit

499
00:21:37,630 --> 00:21:35,120
versus I miss I was a little bit

500
00:21:41,110 --> 00:21:37,640
surprised that there seemed to be a

501
00:21:43,060 --> 00:21:41,120
recent genre of games that was missing

502
00:21:45,810 --> 00:21:43,070
as far as I could tell from the stuff

503
00:21:48,669 --> 00:21:45,820
you'd been working on which is fully

504
00:21:50,620 --> 00:21:48,679
competitive games cooperative games

505
00:21:52,930 --> 00:21:50,630
where all of the players have to work

506
00:21:56,200 --> 00:21:52,940
together to beat a challenging board and

507
00:21:58,419 --> 00:21:56,210
they either all lose or all win we do

508
00:21:59,830 --> 00:21:58,429
have a model that does that clearly I

509
00:22:01,899 --> 00:21:59,840
couldn't talk about it there are there

510
00:22:03,789 --> 00:22:01,909
are literally 14 different variations

511
00:22:05,769 --> 00:22:03,799
these games currently and I was only

512
00:22:08,230 --> 00:22:05,779
able to show a few but yes fully

513
00:22:10,630 --> 00:22:08,240
collaborative against the game is one of

514
00:22:11,610 --> 00:22:10,640
the models we're looking at hi Julie oh

515
00:22:15,130 --> 00:22:11,620
hi mark

516
00:22:16,750 --> 00:22:15,140
did great was awesome um two things one

517
00:22:18,310 --> 00:22:16,760
thanks for saying kind things about me

518
00:22:21,909 --> 00:22:18,320
but also I'm gonna say some kind things

519
00:22:23,110 --> 00:22:21,919
about you publicly which Institute as

520
00:22:26,950 --> 00:22:23,120
far as I can tell is the most creative

521
00:22:29,320 --> 00:22:26,960
and and productive organization doing

522
00:22:30,970 --> 00:22:29,330
this kind of work it's amazing so thank

523
00:22:32,799 --> 00:22:30,980
you for that - I just want to support

524
00:22:36,580 --> 00:22:32,809
you in this looking at this peak a

525
00:22:38,200 --> 00:22:36,590
Precog negative correlation because I'm

526
00:22:39,610 --> 00:22:38,210
finding that - and I think that's really

527
00:22:43,930 --> 00:22:39,620
interesting and it speaks to sort of a

528
00:22:46,750 --> 00:22:43,940
size sensory sigh motor sort of skillset

529
00:22:51,190 --> 00:22:46,760
that seems to be mutually I don't know

530
00:22:53,769 --> 00:22:51,200
balanced Thank You Julia oh right thank

531
00:22:56,049 --> 00:22:53,779
you over the years I worked as a lot of

532
00:22:59,440 --> 00:22:56,059
people some that have reasonable talent

533
00:23:03,250 --> 00:22:59,450
at the start and others that don't and

534
00:23:06,250 --> 00:23:03,260
an informal protocol I found that if

535
00:23:09,519 --> 00:23:06,260
those that have good talent just simply

536
00:23:12,039 --> 00:23:09,529
sit back and focus on the intention of

537
00:23:14,950 --> 00:23:12,049
the one that's not a good performer to

538
00:23:17,200 --> 00:23:14,960
do well on the next round and just wish

539
00:23:21,220 --> 00:23:17,210
or hope or intend that person to do well

540
00:23:23,379 --> 00:23:21,230
he or she will so it's like a transfer

541
00:23:26,199 --> 00:23:23,389
temporarily maybe of

542
00:23:28,149 --> 00:23:26,209
side talent and in some instances it's

543
00:23:30,069 --> 00:23:28,159
actually lingered more than just simply

544
00:23:31,629 --> 00:23:30,079
for that experimental period I wonder if

545
00:23:32,709 --> 00:23:31,639
you've had that kind of experience uh

546
00:23:34,779 --> 00:23:32,719
you know I think that's fascinating

547
00:23:36,489 --> 00:23:34,789
actually no I haven't really thought

548
00:23:39,999 --> 00:23:36,499
about that but it makes total sense

549
00:23:42,729 --> 00:23:40,009
have you published this unfortunately no

550
00:23:44,829 --> 00:23:42,739
but I have written about it and here and

551
00:23:47,049 --> 00:23:44,839
there in pieces okay that's a