Ray Ozzie - The Future of Intelligent Machines - [Invest Like the Best, EP.391]

Transcript from https://podmenti.com/t/4260cf0a3154ea06

I know firsthand how complex the tech stack is for asset management firms.
And seemingly every new tool and data source makes the problem even worse, adding more complexity, more headcount, and more risk.
Ridge line offers a better way forward, one unified platform that automates away the complexity across portfolio accounting.
Reconciliation, reporting, trading, compliance, and more, all at scale.
Ridge line is revolutionizing investment management, helping ambitious firms scale faster.
Operate smarter and stay ahead of the curve.
See what Ridgeline can unlock for your firm. Schedule a demo at ridgeline.ai.
Hello and welcome everyone. I'm Patrick O'Shaughnessy and this is Invest Like the Best.
This show is an open ended exploration of markets, ideas, stories, and strategies that will help you better invest both your time and your money.
Invest Like the Best is part of the Colossus family of podcasts, and you can access all our podcasts, including edited transcripts, show notes, and other resources to keep learning at joincolossis.com.
Patrick O'Shaughnessy is the CEO of Positive Sum.
All opinions expressed by Patrick and podcast guests are solely their own opinions and do not reflect the opinion of positive some.
This podcast is for informational purposes only and should not be relied upon as a basis for investment decisions.
Clients of Positive Sum may maintain positions in the securities discussed in this podcast.
To learn more, visit psum.vc.
My guest today is Ray Ozzie, one of the great technologists, software developers, and entrepreneurs of our time.
Ray is perhaps best known as the creator of Lotus Notes, a collaboration tool that revolutionized business communication in the nineteen nineties.
He later succeeded Bill Gates as chief software architect at Microsoft, where he played a key part in the development of Azure, Microsoft's cloud computing platform.
Ray's work has earned him numerous accolades, including induction in the Computer History Museum Hall of Fellows and the National Academy of Engineering.
Throughout his career, Ray has been at the forefront of technology innovation and paradigm shifts.
Founding multiple companies, including Irish Associates, Group Networks.
And most recently, Blues Wireless, which focuses on connectivity in the physical world.
His insights on cloud computing, collaboration tools, and the future of technology have shaped the industry for decades.
In our conversation, we explore Ray's journey through the evolving landscape of software development, his perspectives on the current state of technology, and his vision for the future of connectivity and collaboration. Please enjoy this fascinating discussion with Ray Ozzy.

Okay, Ray, we were just about to go down a story rabbit hole and I stopped you, but I'm gonna reignite the story.
Bring us to
the time you were in air aid shelter
Texting with your wife.
Hello, Patrick.
Yeah, this was just a few months ago.
I was in Ukraine and actually
Probably on a relative basis, the safest place I could be in Ukraine, which is Kiev. And I was there with a few.
Volunteers from Safecast, which is a nonprofit I'm involved in. And I was actually also there with my son, who works
For my company blues and
It was the middle of the night.
We're sitting there.
I'm alternating back and forth between
Telegram.
And an air alert app and
messages on my phone and my wife is
Like I don't understand why you had to be there. Why did you have to go?
This isn't gonna end well.
And
It was relatively peaceful, but
There were air raid sirens on the outside, from what I could see.
There was nothing happening in my immediate vicinity, but I was just
So immersed.
In what was going on.
We read about
What's happening in Ukraine from afar.
But it's a bit different.
when you're there, when these things are happening around you, when the infrastructure is being attacked, when
The power is going out, and you're hearing stories from everyone that you meet.
About their families, about their extended families, about their friends. It's just
Intense.
You've been really involved there.
for a while in a story that goes back to something you started back in two thousand and eleven.
But before we go back to two thousand and eleven and get into the technology story.
Maybe you could just give us a taste of what I would call the wild evolutions of the use of technology in warfare.
That you've seen in Ukraine
both from an offensive and defensive perspective.
Because again, you hear dispatches in the US at a distance and don't pay close attention. You've been up close and personal a lot.
Talk about the role of technology.
And
What the cutting edge feels like.
In that.
Very specific situation.
There's a lot going on over there. And if you take the time and interest
To read essentially, even though it's a horrible situation right now, it is essentially a proven ground.
For a term that I will refer to
Repeatedly, which is intelligent machines, intelligent cyber physical systems.
The use of AI
And machine learning.
as it pertains to machines low cost
Drone manufacturing.
The reason I was over there was because of radiation monitoring and the use of technology that we're working on throughout Ukraine. However
Technology is being used both for os offensive and defensive uses. I think everyone's pretty familiar with
How Starlink has
been essential.
To getting
Network connectivity.
in the field, both among the people and among the machines, but
There have been
Small startups that have formed that
Have covered a variety of technologies. One of them
being the use of
decentralized audio monitoring, whether through
Dedicated devices, or even one startup has done it through phones, cheap Android phones that they put out there.
And they listen, they use machine learning to train them to listen for the specific sounds of certain
drones and certain missiles.
And they correlate the trajectory and project.
the most likely impact points.
A combination of bots and people.
Publish on Telegram.
where these things might be going. They don't really
By the rules of engagement. They don't really
talk about the impact or not because you don't really know who's watching it.
Whether it's
Friend or foe.
who are monitoring these channels, but
It's really
A very intense environment. And they're also having to deal with
energy related issues. The power infrastructure is what's
under attack the most
Right now for the broadest part of Ukraine. And so people are having to deal with systems that are tethered to power.
Going out from time to time. Interestingly, at the current time, the cellular network
Is pretty reliable, I suspect, because it's in both sides' interest to keep it.
Up and running.
But that's also
A potential
Vulnerability.
When you think about
the role of the technology that you've developed. Maybe you can just explain
what it is and I'm fascinated by the cell phone example where you create this
I'll call it like a mesh network of signal and processing and then
action that happens on the back end of that.
Processing.
Maybe just explain
the nature of this mesh network idea, or you called them intelligent machines.
I think about it when we last talked about it as this incredible system.
That is nothing but the collection of very simple individual components, but it's the combined
mesh network again, I'll call it, that's so fascinating. And I'd love you to just explain literally what the technology that you've developed there
Is and does.
Sure, Patrick.
In a minute, I'll go back to the origin of my company and some of the things that we've developed, but essentially my company blues
It's core business is essentially enabling anybody who
has a physical product
to turn that into a data driven intelligence service. Very, very
easily and quickly so that they can think about the product that they're trying to
develop and not the difficulties and challenges of the technology backhauling data.
And so on. And one of the
devices that uh we have worked with a nonprofit Safecast to build is called RadNote and
It's essentially a standalone autonomous
radiation detector, a Geiger counter wrapped in some communication
And power management gear.
And essentially it's super easy to install the person who
And so as it just turns on the power and mounts it on a pole or a tree somewhere.
And it's solar powered.
It is disconnected from the power infrastructure. It's both solar powered and it's got a primary battery in case for some reason the person mounting it is under duress and they don't have time to site it the right way. It'll last up to ten years on a primary battery at a lower sampling rate.
But essentially it
measures periodically the radiation levels it reports
those radiation levels to the cloud.
The newer generation of it that we're working on, if it can't get at the cellular network, which it uses for backhaul, it will use satellite.
Two back haul.
At a lower frequency so that there's less data.
The device
dynamically adapts its sampling rate.
based on the amount of available energy and the communications radio access technology.
In the Ukraine we're working with a non profit over there.
who had approached Safecast.
To get these installed.
The reason it's essential both to the citizens and to the government is that the power infrastructure is under attack and
There is an extensive radiation monitoring network.
throughout Europe, throughout the world, but when the power infrastructure is taken out, most of those things go offline.
And having a backup.
is very important in the Ukraine.
I'm sure many of your
Listeners understand that Ukraine is where Chernobyl is, but it's also
The home to Zaporizha, which is the largest nuclear plant in the Ukraine.
And it has been taken by the Russians.
And it's being used by Russia as a launching point for missiles and drones.
Because they know that no same
military would attack
back a nuclear power plant, and so the citizens
Are fairly worried.
Whether it's
Will
Chernobyl come under attack again. It was one of the earliest things that was taken, then it was taken back.
By Ukraine.
If the power infrastructure is damaged around Zaporizha.
Will it cause the spent fuel
cool cooling systems to fail.
Will there be radiation leaks or will there be a nuclear device detonated? People are just concerned. And so the way that the rad note works, this device.
Із солепо.
It moderates how often
It samples or how often it uploads.
So let's say that perhaps by default it might upload
Once a day or once every twelve hours.
A large number of samples.
Well, if one of the devices happens to
report a higher radiation level.
It will increase the tempo of its uploading.
And it will notify
The devices
In the geographic region
Surrounding it.
To also increase their sampling rates.
To give the most relevant data.
balancing the energy usage and not so the people in the academic side
Call this uh swarm intelligence. It's a fancy world.
You can think of it as collaborative machine intelligence, but it's machines.
Operating
In networks among themselves.
To do intelligent things. And this is a very specific application of that type of thing, but the reason that I started blues is because I believe that ultimately
All physical devices are going to become intelligent machines where
That intelligence is in some mix
On the devices in the cloud, there's kind of a fusion.
Between
The devices and cloud and the devices and devices and how that fusion happens varies based on
The cost parameters of the device, what the use case is, and so on.
I'm gonna talk a ton about
machine swarm intelligence and
all the different applications that might unlock in the future. I think it's the most fascinating topic, but I always love origin stories and I'd love to hear how this idea
first came to you back in Japan in twenty eleven. Could you tell us that story?
Absolutely. Well, I had just left Microsoft at the beginning of two thousand eleven. I had a little bit of
Time in my hands and what happened in March of twenty eleven.
Is something
Many people remember there was a tsunami that hit Japan.
And that took out Fukushima
nuclear plants and a few of them melted down.
People were
Terrified.
In Japan.
People around the world were worried.
Oh, after Chernobyl there were plumes that went over many parts of Europe.
When Fukushima happened, clearly there was a plume.
that radiation was released.
However the
Location of that plume where it
Flowed.
Because of the prevailing winds.
the degree to which debris was still pouring out of the reactors themselves.
It was all a mystery because
TEPCO, the power company in the Japanese government.
frankly, had their hands full dealing with
The event their top priority was not.
Reporting data so that people around the world
Could see it and
The government was beginning to do relocations of people.
from place to place. And this just made people
More nervous.
Are we being relocated to the right place?
Who should be relocated? Is it gonna reach Tokyo?
These were just all questions people had, and so
I believe probably within three or four days of the meltdowns, whether it was by email or messages or other mechanisms.
Many people in tech tried to say, What can we do to help?
And so
I think it was the first week of April.
Which was a couple weeks after the event.
About thirty of us flew to Tokyo.
And just met.
A digital garage in Tokyo just to see what the talk about what could we do.
The
task just within a day or two, it became clear that
The most useful thing that we could do.
would be to
Find a way to measure radiation extensively on the ground and to publish that.
On the net.
There were a couple of people who were
scientists who
We're competent enough to understand.
The mechanisms by which the body
absorbs or interacts with radiation, but that wasn't
our primary job. We thought if we could competently measure the radiation and publish it.
Then people who were experts could look at it and make their own assessments. And so
We very quickly
within f a few days put together a prototype with a laptop and a commercial Geiger counter.
Some GPS hardware that we got at Akihabra.
Strapped it onto a car.
And just started driving around.
Japan.
into the exclusion zone as close as we could.
And very rapidly
began to generate a very
High quality map.
Of
the various radiation levels. So for the technologists who are listening.
Essentially
the nature of the device was that it would measure every five seconds and correlate load
Initially onto an S D card.
a log that would log correlate time GPS location and radiation level gamma.
And if you go to Safecast.org and click maps.
And explore what you'll see is that Safecast
Today
is the world's largest open radiation
data set that exists. Certainly every road in Japan
But also many, many, many other places globally.
And there's a time axis also because essentially
Over the many years that we've been measuring radiation.
We've measured the same place many places many times. And so you can actually
look at the levels and see where they've decreased where the
Radioactivity has gone
Into the soil.
And so on. But
This ended up
being a very, very useful data set. This isn't just data for data sake.
You can see if you look at the maps today.
You can see where the plume
Went. It went slightly northwest of
The plants.
You can actually see that unfortunately some people
We're probably relocated from places that were.
More safe.
To places that were less safe.
If we had known at the time in the days following it
where that radiation was going. Now the levels
were not life threatening. The most life threatening aspect of Fukushima ended up being
The worry.
And the concern
And the stress that it put on people.
And the way that it
Broke up families because
Unusual culturally, but
The people who were from the region
were looked down upon
Differently.
by people who were not from the regions that were more heavily irradiated.
People lost their jobs, and so there were many, many, many impacts.
But
Stepping way back.
What that
Experience taught me.
Was the importance of environmental data.
The importance of having
Baseline
Environmental data when there is no issue.
The importance of using
commercial off the shelf.
Inexpensive sensors
To
Instrument the world.
So that
We can
know more about our environment, so we can be more in touch with our environment, so we can understand.
What is anomalous.
If you go back to Flint, Michigan, and look at what happened with water quality there.
Who would have thought
That
Probably I mean it was heavy metal sensors at the time were not
that inexpensive, but you have to ask yourself the question.
If the water quality infrastructure
If the water distribution infrastructure had been monitored.
Would we have discovered certain things earlier?
Streams today.
The soil.
The air quality.
Even sound.
levels.
within urban areas.
There's really no reason at this point in history
Anymore.
Why we shouldn't be
Broadly
Monitoring the earth and listening to what it has to say to us.
One of the investment ideas that
we've always loved is the notion of products that bring things from static to streaming. And obviously that's literally
What all of this is an example of, and what blues does. Can you talk about the technical challenge?
or challenges that you encountered starting back in Japan through to the present day.
of making a machine intelligent because
It seems obvious like if you could just snap your fingers and have every
machine capable of taking readings, streaming that data up.
that there's tons of applications where it would be valuable, but the world isn't wired up that way. So there's some sort of friction. Maybe start with why it's an interesting
technology challenge to enable this and then we'll get to
What it might
offer us in the world if we could connect all these machines up and make them smart.
Absolutely. Well
When I say intelligent machines, there's a lot.
That is
packed inside those terms. Yeah, yeah. We tend now because everyone's talking about AI
LMs and so on.
We tend to focus on the word intelligent.
But in reality it means
As I said, number one the fusion between the cloud and the machine.
It is very difficult to imagine
These days.
And moving forward.
A standalone machine.
Pretty much everything now takes advantage of the fact that we have got ubiquitous
networking and so connecting intelligent ma machines, of course
Mien
Connected machines, machines that generate data, machines that are secure.
So that they are not subject to attack and take over machines that
As appropriate.
encode their data confidentially machines that
Have
strong identities so that we understand the provenance of the data.
And of course, yes, finding the right
Balance of putting
edge inference into the machine itself or
potentially uploading the data raw and doing the inference.
Up in the cloud, sometimes it's appropriate to do detection and alerts on the device, sometimes not.
Intelligent machines also
I have to manage
their energy much as we do.
If it's tethered, if it's plugged in.
It's got an ample supply of energy.
If it's remote in the environment.
It's gonna have to use some sort of energy harvesting. There is solar, of course.
And wind
But there's also harvesting
New technologies for harvesting wireless, grabbing broadcast waves over the air.
And grabbing a little bit of energy off those waves and store it using charge pumps to store it. There are all sorts of
New ways of doing this.
But in essence the challenge that
I started seeing at
But the shame was that
The initial devices that we used were
Essentially battery powered for short term.
drives in cars.
The most we were ever measuring was four hours, six hours, something like that. Batteries are fine.
They were standalone in that they recorded to SD cards.
It was a fairly straightforward use case in the initial generation of devices.
The
Second generation of devices
were a little bit different. We had the opportunity

deeply into the exclusion zone where the radiation levels were extremely high.
The way that we got in there was
Interesting the residents of Japan
Who had been relocated.
Are afforded the opportunity to visit their homes once a year. And so we were able to get
Equipment.
deep into the exclusion zone. However
At the time we were first deploying, there was no power.
There was no cellular actually at the first time, and so backhauling
The data.
was extremely challenging.
As was power management. Now this group of volunteers.
That were working on these devices, it was a mix of
Hardware packers.
Software hackers, some people who had cloud expertise at the time.
Many people who were great
community people who reached out to the residents and so on. But I would say it was mostly
The number of professionals, deep professionals.
In software.
In firmware and hardware.
Was less than the number of well intentioned amateurs.
That group
While passionate had a really difficult time.
Getting this autonomous solar powered
It was a little bit more
more difficult of a challenge, both at the hardware and formal level.
So I thought, how hard can this be? And I had started back in the seventies as a double E and I learned
Software
Over time I thought, how hard can this be?
So I got my hands dirty and uh turns out it was hard. Yeah. Well yeah, I learned why it could be hard. I mean to a professional software engineer
It was fairly straightforward. I mean it's just the building state machines, understanding
how much energy was in the battery, what the charge rates are gonna be.
looking doing roll moving averages of charge rates over periods of time so you could understand if you were an extended cloudy period.
cranking down the sampling rates and so on.
But it was also very challenging building
low power hardware.
I had never developed low power hardware and this is microamp level, not nanoamp, but certainly not milliamp.
A level draws.
building the entire system so that it would
conserved power.
And furthermore, it was building an enclosure.
That would withstand the elements.
And survive.
With one visit.
Per year.
We only had one opportunity to visit these devices. So between the radio access technology challenge.
Given that there was no cellular
And the energy management and the physical it was just tough. And
I learned by trying to build this thing over many months
That it shouldn't be this hard.
I've been in technology for many years and
Things really only take off when they are made easy enough.
That
Essentially people can focus on their use cases instead of
All the technology elements.
In this particular case.
The first device we built was called the Solar Cast. It would
measure radiation and air quality level and
Transparent data over Laura.
And then up in the hills.
Surrounding the exclusion zone, we built little Laura gateways.
Laura is a
I believe the acronym is from long range, but it's uh radio technology, very low bandwidth that operates in the nine hundred megahertz.
ISM ban, they call it the ISM ban in the US, but industrial scientific and medical band.
But it's an unlicensed band Wi Fi.
Where
Anybody can use that band, but depending on the encoding
It can be used for
Very long range or very deep penetration. They're both very useful. And Laura
Is it proprietary technology from a company called SemTech.
That wraps a little modem.
that encodes and decodes that technology
For use by
Little
IoT apps.
In our case at Safecast, we
Use Arduino.
as the operating environment and IDE for the MCU.
And we would
package up and compress and send that data.
In little two hundred byte
Packets.
Up to the hills where they then
Went into a raspberry pie gateway.
And we're in using Bolena operating in a distributed operating environment to manage the gateways.
And to then bring it to our cloud based service.
And then over time.
When the cellular networks came back up
We actually hadn't
ful designed the device yet, so we made them both Laura and
Cellular
Capable.
Who's extreme working? There are still many
Oh, these devices
That if you go to the Safecast map, you'll see
Are still broadcasting those radiation levels.
But I felt that it was just too difficult.
And I had not even
Gotten into
The security aspects of it. The devices that we developed for SACAST.
It was all out in the open. The identity of the device is very crude. It was just simple identifiers that we assigned into them.
It was not
Professional grade.
I
Had
Just come from Microsoft. And whether it was I IBM before that or Microsoft, I had many friends and colleagues.
who built systems for large enterprises
I built a system that
called Azure that people may have heard of that people may have heard of that a number of those customers were using for their cloud services. I called them up and I said
Aren't you guys
Connecting devices, IoT devices to the cloud, whether AWS or Azure.
And
What I found was a litany of
Failed projects, enterprises who had started
prototyping, getting physical devices connected to the cloud
Generally using Wi Fi.
And the prototypes were very easy to build.
But over time they learned
of the challenges that
Wi-Fi doesn't work for commercial products. And then when they tried to use cellular, they had similar challenges to what we ran into.
Dealing with carriers to get the appropriate data plans was not right, getting devices certified was difficult.
So I started a company.
Blues to try to make that easier.
Maybe just talk us through the stack here.
'Cause we've referenced a lot of layers of it. You've talked about LoRa, you've talked about cellular, talked about Wi Fi, you've talked about satellite. It seems like such a straightforward task to just have a thing on a piece of hardware and send some data up.
And capture that data. Obviously, blues is entirely predicated on making it really easy. But what is that stack of hierarchy?
That you had to build for V one of the device.
And then we'll talk about how it can be used.
So success. Let's just keep in mind what success is. Success at the highest level.
Is to enable
Companies of any size either to build physical products from scratch or to transform existing physical products.
Into data driven intelligence services. People want to understand.
the nature of devices generally for two reasons, either to
Do preventative maintenance.
Meaning understand
whether those things are operating correctly, anticipate their failures, and so on.
Or to improve the customer experience. There's something about
The product
Whose experience could be better.
If you service enable it.
The customer environment is that
We want people to be able to focus on their use case. They are
Professionals in some domain.
They might
Manufacturer refrigerators, manufacture generators, and so on.
And they want to focus on that use case. They just want to get
The data to the cloud.
At the lowest level?
There is hard work.
Because it's a physical device.
And so today, because the hardware industry tends to
Have evolved as a component.
industry the components that are involved
R
Things like
modems modem is a modulator demodulator it's a thing that
encodes data.
For transmission, either on a wire or
on a wireless network.
In order to power a modem.
It takes energy, so there is a power supply involved.
If you're going to send data
Two somewhere.
You need a protocol stack to encode the data that
goes over the wire or over the air.
And depending on the type of radio.
Those protocols may vary.
Sending something over satellite.
You want it to be very small and you want it to be packet oriented. There is a protocol stack.
If you want to do it securely.
You have to
In modern
Cloud based systems, you want to have digital identity.
In some way, shape, or form. So
How are you going to get digital certificates?
loaded onto those devices. This is an extremely
challenging thing, especially if you're not familiar with that domain.
People are very familiar with
Certificates and digital identity.
In web browsers, we everyone uses SSL or
TLS
To secure connections.
How are you gonna get those?
those the route certificates and certificates in general digital identities onto devices.
So this is
A challenge. Putting hardware secure elements onto a device is a challenge. So
Anyway.
These things stack up, and then when it comes time to actually
Have a service that
transmits
Cellular is the most powerful
Technology, in my opinion.
That's out there because it's one of the few.
Technologies where
In order to do cellular, you've already got a secure element on the device.
To do digital identity.
We call them SIMs, SIM cards, or SIM chips.
You can put cellular into a device.
And most everywhere on earth that there are people, not so much rural there may be cellular coverage problems, but most places where there are people
There is some sort of cellular coverage and you don't have to configure it.
Like you have to do with a Wi Fi network. You don't have to build your own
tower network like you do with something like Laura.
or Wi Fi where you have to install your own gateways.
It's already done for us.
However, in order to use cellular, you have to get your device certified by carriers.
So that it doesn't abuse
Whether intentionally or mistakenly
the shares of the cellular network. So all of these things.
stack up. And so my concept in
Doing blues.
Was that we
Would
Create
A
Fused.
Hardware, software
Service.
Offering.
The hardware offering is called the note card.
The service covering is called the note hub.
But essentially
The hardware manufacturer would design their product.
They would put the note card in it and
We would offer note cards.
with different radio access technologies, different types of cellular
GSM, LTE, you know, two G, three G four G five G
Those
Note cards.
Or Laura
Or a satellite.
The little note card would have on it.
The SIM, the secure element.
It would have flash memory.
So that it could do buffering of data coming from the host MCU.
It would it be protocol agile.
So that the person doing the host MCU wouldn't have to worry.
About
Either security or how to encode the bits and bytes.
To get them efficiently to the cloud.
And then essentially it would just work so that the person could
Worry about their use case and
Worry about the cloud service that they're trying to do.
And we would take care of
Everything in the middle.
Your home.
career. If I think about it at the
biggest possible sense.
It seems to be about
Enabling
Connectivity and collaboration in some very, very broad sense. If you think about Lotus Notes, if you think about Azure, if you think about Taco, if you think about groove networks.
Everything sort of has this common theme of
Using technology to
Hook.
things or people up and help them work together more efficiently.
We're gonna go back to Azure and all those other exciting chapters and the lessons you've learned watching technology paradigm shifts, which is something I think
You're in the top point oh one percent of people on the planet to explain and riff on.
But I want you to imagine first I'll call it the five year hence future or something like that.
Where
because of what you're up to
The world of machines can be more connected, gathering more data, using more data. I'm, of course, interested in how you think this might impact.
artificial intelligence, whether or not maybe this is a source of data to train more models on, and so forth.
But just imagine the the intermediate term future for us.
and why the promise of connected swarm machine intelligence is so interesting. And maybe now's the time to get into some of your favorite early examples that you've seen of things that get enabled
You're a builder of enabling technologies, so
I'm always interested to know what
is being enabled at the frontier that you're seeing because of a solution like this.
Let me just step back and lay out a little bit of background here.
What excites me as a technologist that's been in the industry for a long time is
Not so much just technology for technology's sake or
specific use cases.
I get
Really excited.
Bye.
Broad, broad, broad use.
Of
A technology by the masses.
And
When I say the masses
What people generally think of is consumers, but what I really mean is that there are an extremely large number of small to medium sized enterprises
Globally.
If you think about
small businesses, even just in manufacturing physical products.
By unit count, small to medium sized enterprises are constant about ninety-nine point nine percent.
Of all manufacturing firms. By revenue, it's probably thirty five to forty percent.
Even earlier in my career.
If you look at the world of tech, there's big tech.
And there is the rest.
And there are a lot of companies
in the rest. And if you look at
Just anything, like
spread sheets or
email or any kind of communication tools.
There was a фейz.
Uh computing, just simply computing.
At first the largest corporations
We're able to afford getting mainframe computers.
And then over time.
Companies like DEC and Data General and Prime
brought computing down into the super mini computer and mini computer
Size realm.
Which
Enabled more and more companies of different sizes to get access to it. Eventually the personal computer revolution.
Help everyone.
And the spreadsheet especially became
An empowering tool by which everyone
Enjoyed the benefits of that technology.
With regard to physical devices, we
Have been in a situation
Since probably
the early two thousands where the largest companies the
Automotive and John Deere.
Began experimenting
With
cyber physical systems with putting
communications technology and IoT technology
Into physical devices.
In cars it began with On Star.
Some of your listeners may remember this. You press a button
And suddenly people would know where you are.
And this was a very fancy technology in the early days.
But
Increasingly generation after generation
It turned into more.
It became
integrated with the maintenance value proposition of cars.
It became integrated with the entertainment.
Value proposition of cars. Many people aren't even aware of this, but many cars have two modems in them now.
One is paid for.
Completely subsidized by auto manufacturers.
And they
Get
engine performance data they monitor the
Performance of the vehicle.
It's not supposed to go into that realm, but they
Gather that data and they sell it to the dealers.
And they have part of their value proposition.
And their business model has changed over time.
As independent
From the modem.
That gives you a Wi Fi hotspot or that refreshes the maps.
John Deere, they've gotten a lot of
negative press in the past years because
Building.
Essentially closed systems that have caused many farmers to rebel because it's really transformed the nature of farming. But
In essence, they were innovators.
In
instrumenting farm machinery.
with location
With
Things related to the preventative maintenance of the vehicles.
It's really transformed.
In many ways
The production of food
And those are big companies that could afford to do this. They have
Gargantuan R D budgets.
Like many Silicon Valley companies
They can hire the best of the best. They can hire the best security people.
The best people who understand
Power management.
radio access technologies and so on.
But my question from where I've come from
Is how does this
Technology evolved.
to allow all small to medium sized enterprises
To manufacture physico goods.
to enjoy the benefits of
Building intelligent machines and intelligent services. Again, this happens in every sector.
All of us when the web
first came out, hard to remember, but we ran
email servers within our
Small businesses.
We ran
Little payroll systems and accounting systems
on servers within our departments eventually
Because of the democratization of technology
Those things became SaaS services.
They became
Part of the cloud.
And now
No one would think of doing those things if you're a small to mean sized enterprise.
No one would host their own systems because you can't hire the security people. And why would you?
Why would you
Host your own
Email system.
As an SME.
When you are a company building
Refrigerators.
Generators, propane tanks.
What you care about is
That value proposition and
How your systems
serve your customers and
So
Essentially what these folks just want is a data pump. They want the data.
To go from the devices to the cloud and increasingly
They are also wanting to do things like edge inference. They are wanting to
Detect anomalies.
Either by putting some intelligence onto the device
Or by getting the the data in the cloud.
And doing that inference up there.
That's what we would like to do
To help them do.
You've seen
several of the most interesting major technology disruptions and been a part of creating the solutions. You wrote an incredibly famous memo called Internet Services Disruption, and I think it was two thousand five, something like that, which predated your creation of Azure at Microsoft. Can you just summarize
That was maybe the most important
transition other than the one we're going through right now with AI in this whole history.
What did you see back then? And maybe this is an excuse just to talk about technology paradigm shifts.
in general, which I know is a topic that
You're passionate about and have ushered lots of them in through history. But maybe zoom in on that Azure, what it was that you saw, why you wrote that.
specific memo to the senior team at Microsoft and then what happened immediately afterwards. And then I want to use those lessons to apply to today.
I started at Microsoft in April of two thousand five.
I had known Bill Gates Steve Balmer since when I was at Software Arts working on VisaCalc.
We can go back and visit that era, but I knew many, many technologists at Microsoft and
Bill and Steve essentially said, look, we've been through many shifts.
We have
So many things going on at the company. We're in a great cash position.
Right now, but
Bill in particular.
Like Andy Grove, he has this perpetual view that
The paranoid view.
That
Two guys in a garage, or somebody is gonna discover this thing that's gonna take the company down.
And I was coming in, they knew I was coming in from the outside. I had a different perspective.
In any company, there is a danger, particularly a successful company, there's a danger of only ever seeing
things incrementally as a function of the status quo.
So they said if you believe that there is
A big disruptive change happening.
Lay it out and fix it.
Lay it out and prepare us for it.
Now, when I had been working on at Groove gave me some opinions. Groove was the company that was bought by Microsoft that brought me there in 2005.
Groove was actually a collaboration tool.
That was based on a peer to peer
Architecture this is the Napster era.
But it was also the dawn of the web era, you know, ninety seven was when I had founded Groove.
And I became very aware.
Both because of my enterprise customers and defense customers.
That there was this hybrid thing going on where
People were forming teams.
And communicating peer to peer.
directly, but
People were also talking to companies.
In a hub and smoke manner.
Enterprises
I began to form this mental model.
Of every enterprise having
Being a hub.
And doing all of their customer service in a very broad way from the cloud from the center.
And people forming teams and using the internet to do those team infrastructures. Groove itself became part of SharePoint, and that was more the team side.
But
Where that memo came from
Was the fact that when I looked at Microsoft, it was
I don't think the word stuck is quite the right word, but
They were centered on
A previous era in all of their product lines.
Microsoft Office
Was
Built for a box.
Yeah.
The box was a PC.
It was software you put on the box to deliver its value proposition standalone.
Windows server
Was a box value proposition. You put the box.
In a department, or you put a bunch of the boxes.
into a managed service provider
And you served
Hundreds or thousands
of users from those boxes
Івен ЕксБОС а бокс.
That serves.
Gaming in the home.
It was a very box mentality.
In the meantime
Here is a company
Google.
Who's at the bleeding edge of
A completely new era, they were born into a services era.
And
I believe you have to take on
The mentality of the era.
And then try to back solve
What
That future environment is going to be like
As opposed to
trying to incrementally get there.
So when I wrote that memo
I looked at each business unit and I said, What would
A that future world look like? What does it look like?
for a connected Xbox world. So that means Xbox Live. What does it mean for a connected productivity?
World.
That would be
What today we call Office three sixty five at the time we call it
Office live.
What would a connected computation and storage
operating environment.
be like, well that is what eventually became Azure.
And that memo
Was a way of
Me communicating that vision to the company.
In a way that was culturally compatible with the way that that culture
receives
Disruptions. Bill had written
Several different memos at the time.
When I came in, Bill had asked me to assume his role because he
was on his way out to do work on the foundation.
So he gave me
A lot of coaching on that when I
took on his role as chief software architect.
So that was kind of the kickoff of that era.
What do you remember most learning from him and how he operated?
learning in that hand off and then working with him afterwards.
Is there anything portable to others that you think if others just adopted this mentality or way of working?
they would do a better job than they're doing now'cause obviously Bill is famous for
Just incredible productivity and paranoia, I guess is the word you used. Is there anything else that you remember from
Working with him.
That
Would interest or surprise people, do you think?
Bill is a very unique individual.
We've talked about a number of different aspects that he
has and that the combination of Bill and Steve
had over time some of the patterns that you would recognize are
Bill and Steve are a hacker hustler.
Pair.
They did very, very well in that realm.
On the other hand, Bill himself
was very unique in the industry.
In the early days when I was growing up, because he was one of the few
Who understood
All three of
Technology.
The market, the technology use case.
and business.
All three of those.
In one
individual.
Another aspect of Bill that in recent weeks has gotten a lot of fair play is founder mode.
He's very detailed.
oriented and he had no fear
Of diving into the deep detail.
Um
technology he would create groups in the company would
over a very long period of time create forcing functions by scheduling meetings with Bill.
Where he would grill people.
With questions at every level of the staff.
Steve did the exact same thing.
On the business side, Steve
When he held global business reviews.
Understood that
Biz
at levels of details better than
Pretty much anybody in many cases better than the business leaders themselves.
It's quite a unique organization and I've competed very, very hard with Microsoft.
They were the arch enemy when I was
Doing lotus notes.
Even though I knew the people very, very well.
Exchange SharePoint was the direct
competitor of what I had done at Lotus Notes, but I'm extremely pleased to see what Satya and the organization the senior leadership has done.
To fulfill
The promise of what we had dreamt about in that era when I had
Written that memo.
What I did was kick off.
That era.
What has become of it really is
So many people deserve so much credit for what that organization has become.
I went and read the whole thing yesterday.
And
I encourage people to read it.
The main reason that it was surprising to me
How incredibly detailed it was. It's quite long.
And
It goes segment by segment.
Not just to say at a high level here's an opportunity that we should think about, but very, very detailed specifics.
around what's changing and what might be the oppos zone of opportunity for each part, as you laid out, of Microsoft.
If you could imagine writing a similar memo today just to the world.
To all these businesses.
the whole set of companies that might use and deploy technology to make their product or make their product better.
What do you think the key points would be that you would point out that everyone needs to be mindful of
You sat there in the cloud transition in the early days and then created Azure, one of the great businesses of all time, along with AWS.
And now we seem to have a new set of enabling technologies, whether it's blues to make machines intelligent, whether it's LLMs to make
Everything embedded with reasoning capabilities or a better search capabilities.
If you were writing that memo to the world today, what do you think its key points might be?
I think I would open by saying what the key enabling technologies are.
Certainly today.
One of the
Most significant
is AI, AI and ML, much as cloud was
And enabling technology there.
Another enabling technology
That is I think
too easily dismissed is something that Chris Anderson referred to as
The peace dividend.
From the smartphone wars.
Which is
The inexpensive ubiquitous
semiconductor technology. If you can imagine it.
In hardware now.
You can build it, whereas that was only really possible.
In software before.
So I would begin by framing these things and I would say
Because it it's very difficult for people to conceptualize this.
They need to
Be reminded.
There will be a point in the not too distant future.
That all of these exciting enabling technologies will be
Commodity.
AI technology
Are going to be no different.
then relational database technologies were
Back in the day. They will be
runtime libraries that can be built into every
application solution there will be open
models that are available.
And the question isn't really
How are you gonna make money from the technology?
The question is how is that technology going to reshape
society and business
And so
After the framing
I would go
Use case by use case.
And try to jump.
to the future.
And look backward.
And say
Within this use case.
How will it be fundamentally transformed?
If you were born
Ten years from now.
Fifteen years from now.
And
All of that.
Technology is humdrum.
What would it look like? How would it transform the customer experience?
How would it transform the developer experience? How would it transform
business value propositions within different industries.
Within Microsoft it was
Division by division.
Because those were the relevant use cases. What's exciting to me.
Is
Visiting
На час софтвер уз кейси.
But also hardware use cases.
In mine, you've got manufacturing, transportation.
Logistics, the environment.
Sustainability
Is something that
is weaving itself
through so many different sectors, energy and sustainability.
Sector by sector.
How have these new technologies how will AI and
The semiconductor revolution
And the revolution in wireless technology
Impact
Each of those use cases.
And then
If you can envision those use cases
You will immediately see the opportunities.
As to
What role you personally or your company can have.
In addressing
Those use cases. The reason I did it
In the memo.
Was because people have
A much easier time understanding how
Something can be actionable.
The more you localize it, the more you can contextualize it in terms that people live on a day to day basis.
Could you give us one example?
Of
What would excite you the most if I could drop
uh note card into every device in X Fleet.
of machines in the world.
Is there one that comes to mind that would just be the most exciting for you to just snap your fingers and have that be true and have data be streaming from that fleet of devices up to the note hub and to the cloud?
It's a really difficult question to answer because
From where I sit.
The reason we're doing it is because I believe the number of use cases is inherently broad.
Just like software itself.
And
The things that
excite me the most emotionally, perhaps as a citizen.
Are the environment and sustainability related use cases. I mean, maybe I should just summarize a little bit of how.
People are using it.
We have a company.
called true manufacturing a large customer who's
A private
Manufacturing business in the Midwest in Missouri, founded in nineteen forty. They build high-end commercial refrigeration.
Ice making
kitchen equipment. They need
Embedded intelligence.
in their equipment.
Both for preventative maintenance and
To
Improve the customer experience.
So they used to just ship these refrigerators, whether it's to a
Small
Sandwich shop where you see one cooler with drinks in it.
Or it could be somebody like a Walmart or a Target where you see rows and rows.
A glass.
Windows those used to be shipped.
As I was saying about Microsoft, like boxes.
And the company itself never actually had touch.
with the ultimate customer. They sold to a distribution channel.
And the distribution channel then sells
To the customer.
In this new era.
The manufacturer
Every manufacturer
Even if they have a multi tier distribution network.
That's an opportunity.
To understand how their product is being used.
What the failures are, what they aren't, in order to help the channel understand and the customer themselves how to repair them better.
They can tune the energy management of those.
Devices
dynamically based on
The actual in situ loads.
And they can give a better customer experience in the true manufacturing case.
Some of those coolers are holding
Beer and some are holding vaccines.
They can tell those customers
About spoilage.
And give them actual data. And it's transforming.
Their business.
Another one, American Crane.
Is a small business that makes
Very large cranes.
Department of Energy, Department of Defense, for all sorts of
Sectors they embed
Intelligence into the cranes.
One of the ones that's most exciting to me.
It's a company I can't name, but
It's one of the world's largest automotive and truck battery manufacturers. They manufacture the batteries that go
In long haul trucks.
And in cars, but the trucks are
To me the most interesting
Because by embedding a battery management system
And
Cloud backhaul.
into every battery.
You can help the customer understand.
When it's best to power the truck.
By battery?
Or by fuel.
You can save fuel and extend the battery life.
Bye.
Understanding the drainage patterns of those batteries.
Some day we are not going to even
Consider the concept.
Of somebody buying a battery.
Or a propane to if you're on the east coast, many people use
Propane tanks or oil tanks.
The concept of having one of those things
That is not cloud connected.
And doesn't have built into its value proposition
The data
Is gonna be simply unheard of.
We have one customer.
Again, hard to conceptualize.
It's one of the world's
Largest
Hortipotty manufacturers.
Ha ha.
And why would you connect?
A porta potty. Can use our imaginations. Yeah. You know where they are?
You know if some kid has kicked it over?
You know the number of door opens and closes, you know the
Using gas sensors, the relative smell, you can
Change the value proposition for the customers.
And improve the products.
Fundamentally.
And this will be simply ubiquitous.
Healthcare.
We have a number of customers.
On the healthcare side.
Some of this started during COVID.
Where
A very innovative
Entrepreneur in the Caribbean.
Where they don't have as much hospital infrastructure.
Build.
Equipment that they would put for in home care that would let doctors remotely
Monitor
A broader population.
We have one customer.
So far ocean.
Who actually motivated us to do satellite where they have embedded these little buoys people think of
Weather boo is as few and large.
In the ocean.
But they
Airdrop.
small buoys into the ocean, and they're the world's largest privately owned
network now of ocean sensors
They're doing this for sustainability. They help
Maritime shipping.
Optimize the loading and unloading and the traffic patterns of where they go.
Based on really micro optimizing
What the ocean patterns are like in real time.
At any given point in time. And for some buoys.
That happened to be near the coast, within several miles of the coast.
They happen to automatically use cellular.
For the ones that are in blue water.
They automatically can use satellite.
So anyway, I'm
Obviously super excited about this.
At a very high level again.
I believe people are very excited about
LLMs and chatbots. And that's
The center of conversation.
Right now.
When you think about the stories I was talking about Ukraine, when the stories I'm talking about are customers here.
I am excited about
Intelligent.
Cyber physical systems in a commercial sense.
Everything that you buy.
Will be in some
Way, shape, or form having a service based
Value proposition.
Much as I talked about
In that two thousand five memo.
I'd love to ask about
Timing.
When you think about
The history of AI
And for a long time it was called machine learning. You're one of the few that says ML alongside AI, because most people are just interested now in the new post-Chat GPT era. But this technology's been building for a long time and then it had an explosive moment.
And I think prior to Chat GPT you you might
Easily say it's been disappointing.
the amount of commercial applications of machine learning, at least from the perspective of the customer, it was fueling lots of stuff behind the scenes. Seems like IoT is somewhat similar in the sense that in 2015 or something, there was probably an IoT ETF. It was one of these themes that people talked about in technology as
This is coming, it's gonna be ubiquitous. And then maybe it was disappointing in some sense because it took longer.
And AI now seems to be on a similar trajectory, so these things are going in in close tandem.
What have you learned about that phenomenon where IoT was a big thing? Why wasn't it a bigger thing?
in twenty fifteen
What has changed now that
makes this incredible vision of a connected world.
A connected physical world that you've just laid out.
newly possible. I'm just fascinated by the timing of when these things take off versus when they're first talked about.
Well
Maybe I'm oversimplifying but let's start with AI.
The fundament is accessibility.
Machine learning.
has really been powerful and has had great returns.
within certain sectors, the people where you could hire data scientists, where you have a good flow of data.
Where you had
Enough of an investment.
to tag that data
So that you could
Very clearly lay out to the machine learning systems.
What an anomaly.
would look like and
There are many sectors in manufacturing
And others in logistics, where that data, where machine learning.
Even in medicine.
where that technology has been used.
But
Once you see a chatbot.
And
Everyone can just talk to it.
And understand
And get some value from it.
Suddenly people
Can imagine an impact.
In a form that they can understand.
And
Once Lama
was released and developers could start to see how they could integrate
These things with their own systems suddenly
Things take off at a rate.
That they just couldn't before.
With IOT
Let's not forget that there is hardware involved. And many of us
As you said, it's maybe ten, fifteen years ago. There was a lot of potential. And
The excitement again, I believe, is accessibility.
As long as it's a technology that can only be utilized
Bay Area companies or companies
That are extremely rich with big IT budgets.
It will not fulfill its promise.
Whereas once it becomes possible for
Most everyone to do it.
suddenly it's much more relevant.
I am mostly excited.
About
what I call commercial
IoT.
There is an entire sector where there's another
Even broader disillusionment
I think that is yet to come, which is consumer IoT smart home.
Technology. We're in a
phase right now where everybody's getting smart light bulbs where everybody's hooking things up to Wi-Fi.
And over time
Some of these things will lock in.
But there is gonna be a lot of disillusionment.
Because
People are connecting things just because they can, not because they should.
As people move from home to home.
And realize the amount of equipment they've got to retrain or reset and reconfigure.
Some of the bloom will be off the rose there, but on the commercial side
It's really taking off. We went from an era of
I think
early trial
That a trough of disillusionment.
As people couldn't figure out how to backhaul.
Now
Onto the general
satisfaction and excitement with the potential of the technology.
I always love that.
framing that Kevin Kelly has in that book. I think the book is called What Technology Wants.
And
What technology clearly wants today is data.
novel tokens to train models to
push through models to inference everywhere all the time.
How are you thinking about
LLMs, AI
And the way to commercially embed
these new technologies into your product or service.
You said something about Bill Gates, which I think is true of you as well, which is
Not just cool new technologies and
enabling technologies. But
things to do with them that are valuable to customers.
A commercial sense alongside a technology sense.
What advice would you give people out there that are building businesses, building products?
That are interested in AI and LLMs and all this stuff.
It's successfully commercially applying it'cause it seems like a common trap is what's the
Sports I watch some tennis this weekend and every ad is like AI this and AI that and it seems like it's pitching AI as the feature versus
The thing that AI enables, which seems like a big mistake.
Tell us how you're approaching this and thinking about this.
And how others might
successfully do the same.
Assuming it's going to be an embedded technology. I mean, let me actually step back.
There is artificial general intelligence and speculation about whether we're going to get to that point. And I'm really not talking
about that right now. When we're having this conversation, I'm really just talking about the
Technology
at its current or slightly projected level of maturity.
As I look at it right now.
I divide things into
LLMs as a human interface.
Accelerator.
Or supercharger.
Where
It can scale in ways that humans cannot.
In ingesting
large amounts of information.
And
There are questions that it's
Able to competently or semi competently
With the hallucination asterisk.
It can
Very competently
Answer a broad range of questions.
That
Today
It's very expensive.
To answer or may not be answered at all.
You see this in coding
A lot some people with regard to programming
Think about it writing the code, but in actual fact it also answers
Quick questions about
algorithms and
APIs
It's an amazing UI to
The world's API reference manuals.
That are out there and sector by sector.
This is true. Imagine
AI having ingested all case law.
Oh
schematics
That have been
Built by engineers.
It is really going to be a supercharger from a human interface perspective.
I believe the greatest
potential for entrepreneurs.
Right now.
is to look at it.
sector by sector and say what sector do you have
A personal interest or connection to
And how can you jump forward and envision?
That
sector transforming fundamentally
And then back.
Solving
What are the steps going from here to there?
In the IOT world
The way that I'm looking at it
Is both from a human interface perspective.
And from
The classic perspective, which is
Anomaly.
detection.
The past way.
Of
Using machine learning is to manually tag
data and to generate very clean data sets.
And then
Use machine learning algorithms.
To do that.
I'm sure that's still happening in many sectors, particularly life critical.
Sectors.
But
The modern thing to do.
Is to just gather as much data as you can.
Don't even clean it.
Just gather data, gather data.
If you have the transport bandwidth
Bring that data to the service. Don't do the inference and reduce it on the device.
Bring it up to the service if you can.
Interest.
record vast amounts of it.
And then let
Lecnology
Some of which has not been developed yet, but
The promise is to use some of that technology.
With huge context windows.
To learn
What an anomaly actually looks like.
But there's also exciting technology.
In the human interface.
Some of the stuff that we're doing.
haven't released yet, but we're experimenting with the concept of
Dashboard
Bye.
Weary.
If you have a lot of data
There are many things that you can do to help.
operations tech uh personnel or even the people in the business unit.
who are looking at IoT data.
To say oh
Which ones
have a higher frequency of X happening, or which ones haven't reported.
You can create these dashboards. That's the classic way.
of getting value from data large data sets.
Another way of getting value.
is using analytics tools to do queries.
An interesting thing that we're
Experimenting with is
What if you could use
LMs
To describe the query.
That you would like to do.
And then
generate queries and then
Generate charts.
Based on
The problem that you're trying to solve
As opposed to being so hyper explicit.
I think there are gonna be many possibilities in that realm.
As people do more and more experimentation.
Is there any other enabling technology we haven't talked about that you wish existed?
You helped create Azure and that was a whole set of internet services.
Box to streaming to use your language.
Now you're creating the ability to pump data from anything and do lots with that data.
LLMs are creating reasoning capability with big context windows and the reasoning engines themselves.
Is there anything else that you wish you could snap into existence as an enabling technology that you've thought about?
Or that you think might be coming that's relevant for this big picture.
There's so much that's in flight right now.
Concurrently.
I want to be super honest with you that I'm just trying to absorb
All of the same we haven't even talked about.
radio access technologies, but
There's as much
Innovation going out on the radio access technology space.
As there has been in the semiconductor space and as there is
In the AI realm.
Satellite has the potential of delivering
One hundred percent ubiquitous coverage.
Where we didn't have that before. We've had
Cellular systems
out there that handle where there's
population.
But now with companies like Skylo or AST.
There are possibilities that
cellular based backend technologies.
Will be able to be used.
with new radio access technologies

Ubiquitous connectivity.
What?
solutions will
happen with that.
With some of the technologies that have happened with five G and have not yet been absorbed.
Into solutions.
And are coming with future generations.
There's mind boggling bandwidths that are possible.
On a point to point basis.
On a line of sight basis.
And so on.
There's just so much
Innovation.
In the area that I'm closest to right now.
Where I want to see innovation.
Is the easy button for
physical products for hardware design.
Right now.
There is a shortage of really strong talent who understands
How to design and build
Harbor devices.
It's not a black art, it's a skill.
And
I really have tremendous respect.
For people who have
Learn that skill.
Through apprenticeship.
And
Formally
To build low power devices, to build very energy
Efficient devices.
But there is still a number of
spins that must happen. You must
Conceptualize the solution.
Prototype it.
spin it into an initial hardware prototype.
Put it into use.
Refine it.
Go through that same process again.
When I
started in this industry, that's what software was like.
We had card decks.
And you had to
I mean, I know this I'm showing my age here, but
You had to go type out the card deck. You had to go give it to the
operator with JCL, you know, uh cards on the
Run back, run the job, get it.
Go see if it's a little bit.
Did the solution.
We're still in that era with regard to physical devices.
Over time
I believe
AI
And LMs
They hold some promise in that realm.
It's very difficult to see today.
Especially if you're one of those people with those skills.
But shortening the cycle time.
For
creation of physical products, I think is
Really exciting.
And we're not there yet.
One of the things we're seeing is
the world of hardware usually plus software the two are pretty inextricably linked now.
is attracting some of the most
Ambitious talent.
In the world.
Software is so mature.
There's so many resources for how to develop software. There's so many playbooks. It's so well understood. There's software for everything. It'll keep going, but it feels like a pretty well worn path. Whereas
There's no similar set of books, playbooks, ideas, classes, et cetera, for developing hardware.
What do you think is the most significant difference between
Those two things. What do the best
hardware development people.
You said it's too small of a sample.
But the ones that are good at it.
What do they do especially well that's most distinct from the great software developers?
'Cause I would love there to be just more of these people out there and so I'm curious about them.
I actually believe the core skill
Is
similar in some ways. It's just that they're different disciplines.
The thing that I
Grew to respect.
very early in career, we don't talk about
A lot these days.
On the software side.
Which is systems
Thinking.
Let's take it into a completely different discipline architecture.
You can have architects
and others in that discipline who understand very
Small
Units.
Of
Design.
Then
There are the few
systems people who can build an entire skyscraper.
They understand how it all fits together.
And it's a fractal problem.
There are some people who may understand
some little part of a valve, and there are others who understand how to build a rocket and others who understand how to go to the moon.
In software systems.
There are people who write device drivers.
And who understand how to do unit testing.
on device drivers or on a piece of a user interface.
And there are those people who really
through their skills have learned to build
an operating system and a very, very large
Application.
In hardware.
There are analog engineers.
Who really understand
Certain aspects of it. There are
People who
design secure elements and understand hardware side channel attacks.
It's very difficult.
Right now.
To find
Semiconductor people
Who bridge up into firmware. The firmware people who get cloud.
And yet it's all holistic now. An intelligent machine.
has to be
From
The chip level.
Maybe using an application specific
Inference engine.
All the way up.
through that cloud service, the more
You can have a systems
Understanding
The more valuable.
you will become and the fewer people there are.
I don't know.
How LMs
Which are the accumulation of the knowledge.
Of the really deep specialist.
And the writings.
Whether it's
Code.
Or
Writings or schematics.
of people operating at the systems level.
I don't really know yet the capabilities that are gonna happen at that level.
It's gonna be an exciting time.
Going back to those two big themes that I see throughout all your thinking of
Connectivity and collaboration.
If one of those two themes is at the thrust or at the center of a product
or service that someone is building.
I'm curious to know what advice you would give. Let let's say I'm building a workplace collaboration tool, of which there are now many, but there's probably lots of places where we're still doing single player work when we should be doing multiplayer work or something.
Вот you learned about what matters.
In products where the core
Job to be done is collaboration between
Teams.
If you were teaching a seminar class or something of a group full of YC startups or something that were all doing collaboration tools.
What would you tell them, look, I've done this a bunch. Here's what matters, here's what matters less. Don't make these mistakes, focus on these things.
Well
Technologists like to focus on
technologies and platforms and they tend to intuitively get excited.
by those problems. But
fairly early in career, this was in the notes era.
I learned that
Business rises
Non linearly.
In proportion to
Domain specificity.
That is
You couldn't have an e mail system.
Or a sharum where people swap information.
And ultimately that platform will become a commodity.
It's
Just a matter of time.
Whereas
A Salesforce automation system or
A legal document management system.
because of its domain specificity
Is built on the same underlying technologies.
There is a
Chat window to the right, there's a document.
management system underneath. There is a
query mechanism to f help you find
Everything.
There's an access control sub system.
If you really want to make a difference.
To the world.
Focus on a domain.
The more you can focus on the domain.
the more value you will be creating.
You can make a lot of money both ways.
But
You will make a lot of money as a
Platform provider.
Over the long term only if you're a big player.
If you're one of the few big players
Everybody makes money on
Picks and troubles.
Early on.
In a domain, but
Over time the only ones who make a good living
Who earn good money on
Commodity technologies.
Are the few biggest
Players.
Whereas there will
Always.
B
Immense value.
In
Domain specificity.
If you think about
the explosion of technologies happening today that you're in the midst of.
And compare it to other explosions that you've personally been a part of across your very storied career.
How would you stack this one up against
the others.
This versus early days of the Internet or Cloud or Mobile or
P C or pick your era.
And paradigm shift. What does this one feel like to you versus the others?
I have to say, number one, that
I'm just super
Fortunate.
To have been born when I was
And
be able to
Be alive.
During
This velocity of
Interesting problems to be solved and interesting
technologies to solve them.
There has never been an era
Like there is right now, and as far as I can see, there will never be an era.
Like tomorrow.
Meaning
They're all stacking.
On each other.
We still have not internalized.
The innovations of the past
Today
And we're still building them.
On top of each other, every one of the things that I mentioned.
Is still growing.
Computation
Is still growing.
But not growing
In one CPU.
It's growing in parallel and in application specific.
Processors.
Storage.
Is still growing.
Networking is growing from
The
Wireless realm with all these different
Radio access.
Technologies.
Semiconductor technology itself is still
Growing. We've got chiplets now. We've got
A clean separation between the
parts of the stack in that ecosystem.
AI
Different types of databases.
We haven't even scratched the surface of LMs.
I just couldn't be more excited. And the reason I'm in this industry and
Engaged to the degree that I'm at.
Is that
You can imagine and then re imagine.
Different domains based on new mixtures.
New compositions.
Of technologies that are appearing
Every day. And what is the new technology
That's gonna happen five years from now.
It's fun.
How would you encourage people to think about
business strategy.
M and A
Putting your business hat on here as one of these
paradigm shifts as unfolding. Sounds like we're just in for a permanent paradigm shift all the time in all directions, based on that answer.
But the creation of enterprise value.
Not just product value for the customer, but enterprise value for the business.
You've done this a lot of times. You've built companies, you've sold them very successfully to
Places like Microsoft.
You've then gone and worked at these places and tried to disrupt yourself. You've seen the full life cycle here.
A lot of people listening are in technology entrepreneurship. That's what they do. They're building technology based businesses.
Any word of advice on
The
enterprise value side of the ledger. We've talked a lot about product and technology.
But you've also done the thing that I think lots of people are trying to, which is build enterprise value.
Anything
Notable there that you would leave us with?
I'll say one thing which
I think it's a little
Different than
What
certain people, particularly leaving college, might hear, but I
Believe that
You can't develop for the enterprise.
Unless you
understand the enterprise and you can't understand it unless you
Live in it.
For a while.
I strongly encourage
People who are leaving college to
Go do a tour of duty.
Of several years.
Within a big company.
You could say the same thing about government.
You're not really gonna understand.
The organizational dynamics or bureaucratic dynamics.
Unless you actually live in one. You're never gonna understand what a nonprofit is like.
Unless you
Do a tour of duty a nonprofit because hurting volunteers.
Is different.
than hierarchical decision making and
Command and control.
Within an enterprise, I think.
There is
Just immense value to be delivered to society.
Biden.
Applying technology skills
to the problems at scale.
In enterprise.
Because of the nature of enterprise right now.
You can have huge impact.
to large enterprises at scale, even by working for a small to medium sized enterprise.
I know this is a little counterintuitive, but
If anybody really wants an education go all the way back
to the thirties and read.
The nature of the firm
By Ron Coase.
In those days.
The big company was all there was, and minimizing transaction costs.
Was the only purpose of the firm.
We are in a completely different era now where
The firm is actually
A very
Complex.
network.
Of small
Entities bound by common
Економікс анпер.
And the organizational form.
for many industries is no longer one big enterprise. It's lots of little companies that
Work together.
To develop.
An ultimate end product, I'll bet you if you look at somebody like SpaceX.
They didn't develop
Everything themselves, they have a network of subcontractors.
Who specialize in machining this part or
Doing this and that. They probably use their capital.
and ability to hire skills only on certain skill sets. But anyway, my
recommendation is
If you're a young entrepreneur
And you don't have a lot of experience.
Don't trust gravitate.
Two
Building
A consumer app.
Or a consumer
device or something like that.
You can learn by building anything, but
They're not teaching you what are the things that are gonna make
The most impact on society and probably
They're not giving you the things that will be most valuable
For your entire career, you learn immense things.
by working with people in teams.
By working on units
of larger
Products and larger entities.
And
You will learn
How these enterprises buy things.
Why it's important to understand.
The management of complex systems.
Not just the creation of
Complex systems.
Incredibly m unique and powerful way of thinking about one's early career for sure. Right, you're
career has been so fun to study.
Your business obviously we're investors in your business and so it's been
even more fun to study this particular one up close. But if you just think about the overall arc
And uh
Way that
these technologies are stacking and your role in creating some of the steps that we all get to climb is so cool and so fun. I always ask everyone that I interview the same traditional closing question.
What is the kindest thing that anyone's ever done for you?
The kindest thing that has ever been done was
On the career side.
was done by a man named Mitch Capor, who
Was
Part of the hacker hustler duo of Mitch Caper and John Sachs.
Who did Lotus One Two Three?
And Mitch could see that I had a passion.
In a certain realm.
This was in
prototyping the product that eventually would become Lotus Notes.
I was only a small number of years out of college.
I was a pretty decent engineer.
I worked on spreadsheets.
had personal software for Dan Brooklyn and Bob Frankson, very fortunate with that.
And then I went to work on a little spreadsheet work for Mitch and John.
But
Those guys saw that that isn't what was exciting me. What was exciting me was this
Concept of people collaborating.
Using the computer as a communication device.
And it was
early in the industry it was too early.
But he could see that was my passion.
And after I did some work for him, I built a product with a few guys, of course, called Symphony.
The date that
That product ships.
He came down to my office.
Unprompted.
And Set Ray, I know you've been on the side trying to get venture capital.
I know that nobody will listen to you. I know that you've been striking out.
You told me, John's told me.
Let's figure out a way that you can do
What you wanna do. I don't understand what you're trying to do.
I don't get it.
But
You clearly are good at what you do and you have a passion about it.
So let's figure it out. So for the next six to nine months.
We negotiated and we found a way to structure a relationship.
And it was a very unique relationship and
I spun off and did a start up. It was a very unusual way of
Being funded.
But he gave me that opportunity.
And
Like I said, he didn't understand it.
A career is the connection.
The sequencing of
Many relationships and much learning.
And that was probably the biggest single
Leverage point.
It's so cool to think back on
Lotus notes, groove networks, Azure, Safecast, now blues, wireless.
so many interesting things that you've been a part of building and that it started
These path dependencies are so interesting. The fact that it started that way is so
Cool. And hopefully it makes others like it's making me think about who could we do that for?
Whose passion could we go encourage and support?
Even if we don't fully understand it ourselves.
A wonderful closing thought. Ray. Thank you so much for your time. My pleasure. Thank you so much, Patrick.
Um
If you enjoyed this episode, check out Join Colossus.com. There you'll find every episode of this podcast complete with transcripts, show notes, and resources to keep learning.
You can also sign up for our newsletter, Colossus Weekly, where we condense episodes to the big ideas, quotations, and more, as well as share the best content we find on the internet every week.