Employment V/S Self Employed – Sadhguru At BHU


sadhguru when I try to see myself as a
youth and when I try to see myself as a passengers in university then one
feeling that hurts me the most is the unemployment one and in the final this
is the most interesting you can apply so it gives me a very much interesting I am
also afraid of the ink eraser but I won’t do it
you saying you are from the town of Shiva he wore a snake always around his
neck and watch that is a good point check it out
so for me how I should become like you cool dude like that you can apply for the job we will
process the application of course see we must understand this in this country in
1990 only 7% of India was employed 93% was self-employed all kinds of small
small businesses and things because there was really no organized employment
now I do not know the exact number maybe it’s gone to 15 percent or 20 percent
maybe so still over 80 percent of the people are self-employed we are talking
this employment business already I mean lot of trouble on the social media
because of I spoke about employment in the I am Bangalore and these are all you
know business masters people they are doing MBAs and they’re asking about
employment I said in a developed in a developing country you shouldn’t be
looking for employment a developing country means there are still lot of
things to be done in this country when there are so many things to be done
instead of looking around and seeing as youth what can I do and how can I make
something out of that you are sitting and waiting for somebody to come and
give you an employment well this language of what is the employment
rate in the country comes from United States because almost everybody is
employed Excel except a small segment of entrepreneurs so that’s a different
nation this is a different nation here there is no organized employment of that
scale you cannot employ 1.3 billion people in a factory or an office or
wherever else they have to find their way and they are finding their way the
rural population is not employed it’s only the urban youth the moment they get
educated somehow they get crippled those who are not educated are finding a way
to live is did hello those who never went to the
college university they’re all finding a way to make a living but the moment you
get educated should you be more capable or less
capable you should be more capable so you should give the employment to them
and you should become the employer yes tell me if you look around in Kashi and
there are thousand things that you can see on the street that you can take up
and do and make a business out of it can you or can you not there are so I am NOT
saying there should be no employment generation yes that needs to happen on
one level but don’t ever believe 1.3 billion people can be employed in a
factory or office or some organized sector it’s just not possible
we don’t have that level of organized employment generation and it’s just not
possible at all it is just that we have to see in a developing country how we
can develop this country every one of us if you can’t do it by yourself ten of
you should get together and do it but right now the problem is general you
cannot get together two people can’t get together let’s change this one if 10 of
you students get together you think you can’t start something and run
successfully can you or not you can but you ten people can’t get
together but you want to go into a company where there are million people
working together this is unrealistic so this is going to be super unpopular
video I know a whole lot of people a whole lot of people I’m on camera a
whole lot of people are going to scream at me oh he’s this is that he doesn’t
know what the employment Oh become a guru
well trying why don’t you try you can try that also that is also useful apply
to be a mistake that you don’t have to apply anyway it happens now you didn’t
get the there is something called as mystic and a mistake you

It’s Getting Harder to Spot a Deep Fake Video


“We’re entering an era in which our enemies
can make anyone say anything at any point in time.” Jordan Peele created this fake video of President
Obama to demonstrate how easy it was to put words in someone else’s mouth- moving forward we need to be more vigilant
with what we trust from the internet. not everyone bought it, but the technology
behind it is rapidly improving, even as worries increase about its potential for harm. This is your Bloomberg QuickTake on Fake Videos. Deep fakes, or realistic-looking fake videos
and audio, gained popularity as a means of adding famous actresses into porn scenes. Despite bans on major websites, they remain
easy to make and find. They’re named for the deep-learning AI algorithms
that make them possible. Input real audio or video of a specific person-
the more, the better- and the software tries to recognize patterns in speech and movement. Introduce a new element like someone else’s
face or voice, and a deep fake is born. Jeremy Kahn: It’s actually extremely easy
to make one of these things… there was just some breakthroughs from academic researchers
who work with this particular kind of machine learning in the past few weeks, which would
drastically reduce the amount of video you need actually to create one of these. Programs like FakeApp, the most popular one
for making deep fakes, need dozens of hours of human assistance to create a video that
looks like this rather than this, but that’s changing. In September researchers at Carnegie-Mellon
revealed unsupervised software that accurately reproduced not just facial features, but changing
weather patterns and flowers in bloom as well. But with increasing capability comes increasing
concern. You know, this is kind of fake news on steroids
potentially. We do not know of a case yet where someone
has tried to use this to perpetrate a kind of fraud or an information warfare campaign,
or for that matter, to really damage someone’s reputation// but it’s the danger that everyone
is really afraid of. In a world where fakes are easy to create-
authenticity also becomes easier to deny. People caught doing genuinely objectionable
things could claim evidence against them is bogus. Fake videos are also difficult to detect,
though researchers and the US Department of Defense, in particular, have said they’re
working on ways to counter them. Deep Fakes do however have some positive potential-
take CereProc, who creates digital voices for people who lose theirs from disease… There are also applications that could be
considered more value-neutral, like the many, many deep fakes that exist solely to turn
as many movies as possible into Nicolas Cage movies.

Google responds to Trump: We’re not working with the Chinese military


DAVID: PRESIDENT TRUMP TAKING AIM AT GOOGLE, TWEETING THIS OVER THE WEEKEND. QUOTE, GOOGLE IS HELPING CHINA AND THEIR MILITARY BUT NOT THE U.S. TERRIBLE. THE GOOD NEWS IS THAT THEY HELPED CROOKED HILLARY CLINTON AND NOT TRUMP AND HOW DID THAT TURN OUT. THE PRESIDENT RESPONDING TO THIS WARNING FROM THE NATION’S TOP GENERAL. WE FIRST PLAYED THIS FOR YOU LAST WEEK.>>THE WORK THAT GOOGLE IS DOING IN CHINA IS INDIRECTLY BENEFITING THE CHINESE MILITARY. WE WATCHED WITH GREAT CONCERN WHEN INDUSTRY PARTNERS WORK IN CHINA KNOWING THAT THERE IS THAT INDIRECT BENEFIT AND FRANKLY, INDIRECT MAY BE NOT A FULL CHARACTERIZATION OF THE WAY IT REALLY IS. IT’S MORE OF A DIRECT BENEFIT TO THE CHINESE MILITARY. DAVID: GOOGLE DENIES THESE CLAIMS, ISSUING THIS STATEMENT. QUOTE, WE ARE NOT WORKING WITH THE CHINESE MILITARY. WE ARE WORKING WITH THE U.S. GOVERNMENT, INCLUDING THE DEPARTMENT OF DEFENSE, IN MANY AREAS INCLUDING CYBERSECURITY, RECRUITING AND HEALTH CARE. END QUOTE. RETIRED FOUR STAR GENERAL AND FOX NEWS SENIOR STRATEGIC ANALYST JACK KEANE JOINS US NOW. GENERAL, CAN WE TRUST GOOGLE?>>WELL, I WOULD WANT TO THINK WE COULD. BUT I’M A LITTLE STUNNED BY WHAT’S TAKEN PLACE HERE. CERTAINLY GOOGLE’S GOT A RIGHT TO DECIDE, YOU KNOW, WHAT KIND OF BUSINESSES THEY WANT TO PURSUE AND THEY PULLED OUT OF THE COMPETITION FOR THE PENTAGON’S CLOUD OPERATION AND ALSO THEY PULLED OUT OF A CAPABILITY TO IMPROVE THE ANALYSIS OF VIDEOS FROM OUR DRONES, THE IMAGING FROM THEM. THEY’VE GOT A RIGHT TO DO THAT. BUT WHAT STUNNED ME IS WHAT FOLLOWED. THEY SAID THEY PULLED OUT OF IT BECAUSE THOSE ENDEAVORS ARE NOT IN LINE WITH THEIR CORPORATE VALUES. AND THEY WERE RESPONDING TO EMPLOYEES’ REQUESTS THAT GOOGLE NO LONGER WORK FOR THE DEFENSE DEPARTMENT OR GIVE ASSISTANCE TO THE DEFENSE DEPARTMENT TO PURSUE WAR-LIKE ACTIVITIES. THAT, I FIND QUITE REMARKABLE GIVEN THE FACT THAT IT’S AMERICA’S VALUES THAT HAVE PERMITTED GOOGLE TO THRIVE AND PROSPER. AMERICA’S VALUES THAT ARE DEFENDED BY THE UNITED STATES MILITARY, I MAY SAY. SO IT’S SORT OF A STUNNING COMMENT AND I THINK THEY ENTERED INTO A BIT OF A PUBLIC RELATIONS NIGHTMARE FOR THEMSELVES HERE.>>DO YOU FIND, THOUGH, THIS IS JUST AN EXAMPLE, WE WERE TALKING ABOUT GM EARLIER –>>WHO AM I TALKING TO?>>THIS IS KRISTINA PARTSINEVELOS. WHEN YOU TALK ABOUT GOVERNMENT INTERVENTION AND THE PRESIDENT WEIGHING IN ON GM, WASN’T THIS ALMOST A VERY SIMILAR SITUATION WHERE YOU HAVE THE PRESIDENT SPEAKING IN THIRD PERSON WHILE HE TWEETS THAT GOOGLE SHOULD HAVE BEEN INVOLVED OR SHOULD BE HELPING OUT THE U.S. MILITARY, BUT MY QUESTION FOR YOU, GENERAL, IS, DOES THIS SHOW THAT MAYBE GOOGLE DOESN’T TRUST THE GOVERNMENT TO DO RIGHT WITH ITS TECHNOLOGY?>>WELL, I DON’T KNOW WHAT THEY WOULD BASE THAT ON. I DON’T KNOW WHAT THE TRACK RECORD THAT YOU ARE ALLUDING TO HERE, THAT SOMEHOW WE DO WHAT WITH THE TECHNOLOGY?>>YEAH, BUT IF THEY DIDN’T GO –>>LET ME FINISH. YOU’RE STEPPING ON ME. IF YOU TAKE THE TECHNOLOGY THAT THE DEFENSE INDUSTRY PROVIDES TO THE UNITED STATES AND SPECIFICALLY HERE TO THE MILITARY, OBVIOUSLY WE USE THAT TECHNOLOGY TO PROTECT AMERICA’S NATIONAL INTERESTS SO WHAT’S THE MISUSE?>>THINK OF THE SITUATION — THIS IS YOUR SPECIALTY, NOT MINE, BUT IF YOU MISUSE DRONE TECHNOLOGY, THE ABUSES, AGAIN, I DON’T KNOW ALL THE DETAILS BUT I’M ASKING YOU, POSSIBLY COULD THAT BE A CONCERN FROM THE COMPANY?>>GIVE ME A SINGLE ABUSE OF DRONE TECHNOLOGY.>>LIKE I SAID, YOU ARE THE EXPERT IN IT. I AM NOT. THEREFORE, I DIDN’T –>>WHY ARE YOU MENTIONING IT, THEN?>>IF YOU ARE NOT GOING WITH THE CORPORATE VALUES AND THEY ARE SCARED THE U.S. GOVERNMENT IS GOING TO USE THEIR TECHNOLOGY FOR PURPOSES THAT MAY NOT BE IN THE BEST INTERESTS OF WHAT THEY BELIEVE IS RIGHT, IS THAT A CONCERN? THAT’S PRETTY MUCH SHOWING THAT MAYBE GOOGLE DOESN’T TRUST WHAT THE GOVERNMENT COULD DO WITH ITS TECHNOLOGY. THAT’S WHAT I’M ASKING YOU.>>I HAVE NO IDEA. I KNOW WHAT WE DO WITH DRONE TECHNOLOGY. IT PROTECTS AMERICA’S INTERESTS. I GUESS YOU ARE ASSUMING, YOU ARE ALLUDING TO THE FACT THAT ON OCCASION, DRONES HAVE MISFIRED AND HAVE KILLED INNOCENT CIVILIANS ON THE BATTLEFIELD, JUST AS SOLDIERS HAVE KILLED INNOCENT CIVILIANS ON THE BATTLEFIELD, JUST AS NORMAL KINETIC BOMBS KILLED INNOCENT CIVILIANS ON THE BATTLEFIELD. THERE IS NO COUNTRY IN THE WORLD, BY THE WAY, THAT TAKES MORE PAIN TO AVOID CIVILIAN CASUALTIES. THIS COUNTRY NEVER POINTS ITS WEAPONS INTENTIONALLY AT CIVILIANS. WE ABSOLUTELY AVOID THAT WHILE CHINA, ON THE OTHER HAND, POINTS ITS WEAPONS AT CIVILIANS ON A REGULAR BASIS.>>GENERAL –>>IT’S JONATHAN HOENIG.>>GENERAL, JOHN LAYFIELD HERE. I GOT THE PLEASURE OF YOU HOSTING ME ALONG WITH SERGEANT MAJOR IN THE PENTAGON SEVERAL YEARS AGO. BEEN A BIG ADMIRER OF YOU EVER SINCE. PROUD TO HAVE YOU ON THE SHOW. I WANT TO ASK A QUESTION ABOUT GOOGLE AS FAR AS CHINA. WHERE WOULD YOU DRAW THAT LINE, YOU HAVE A TECH COMPANY THAT OBVIOUSLY CAN BE MISUSED IF YOU HAVE TECHNOLOGY BEING STOLEN. WHERE WOULD YOU DRAW THAT LINE AS FAR AS BUSINESSES, ESPECIALLY TECH COMPANIES, DOING BUSINESS IN CHINA?>>WELL, I THINK THAT THE WHOLE CHINA AFFAIR IS ONE THAT COMES INTO QUESTION NOW. YOU KNOW, WE MADE A TERRIBLE STRATEGIC BET, MOST PEOPLE IN THIS COUNTRY 25 YEARS AGO, WHEN THEY OPENED UP CHINA ECONOMICALLY, AND AMERICA’S BUSINESS RUSHED IN THERE CERTAINLY AND OUR GOVERNMENT WAS ENCOURAGING LET’S HELP CAPITALIZE CHINA, CERTAINLY, LET’S GET THEM INTO A MARKET-BASED SOCIETY IF POSSIBLE, AND WITH THE HOPE THAT POLITICAL REFORM WOULD FOLLOW THAT. WE LOST THAT BET. THIS IS A MORE AUTHORITARIAN REGIME, MORE REPRESSIVE THAN IT’S EVER BEEN. PRESIDENT XI HAS MORE POWER THAN ANY SUCCESSOR HAS HAD. WHAT THEY HAVE DONE WITH AMERICAN BUSINESSES AND WHY THERE IS SO MUCH CONCERN WITH IT, TO DO BUSINESS WITH THEM YOU HAVE TO ENTER INTO A JOINT VENTURE WITH THEM AND IT’S AT THAT POINT THEY ARE ABLE TO UNDERMINE AND TAKE INTELLECTUAL PROPERTY. CLEARLY, THEY ARE THE MOST PROLIFIC DATA CONSUMER IN TERMS OF CYBERHACKING IN THE WORLD. THEY TAKE OUR INTELLECTUAL PROPERTY, THEY TAKE SOME OF OUR MOST GUARDED SECRETS THAT WE HAVE IN THIS COUNTRY. NUMBER TWO, THEY GET INTELLIGENCE. NUMBER THREE, THEY TAKE PERSONAL DATA. ANYBODY THAT’S INVOLVED WITH CHINA AND TRYING TO PURSUE INFORMATION TECHNOLOGY WITH THEM I THINK YOU’VE GOT TO HAVE A HUGE AMOUNT OF SKEPTICISM REGARDLESS OF WHAT CHINA SAYS THEY’RE GOING TO DO WITH IT, THEY ARE GOING TO STEAL IT. THAT’S THE TRACK RECORD.>>GENERAL, IT’S LIZ PEEK. MY UNDERSTANDING IS THAT CHINA AND THE UNITED STATES ARE NECK AND NECK IN DEVELOPING A.I., NOT JUST FOR COMMERCIAL USE BUT ALSO FOR MILITARY USE. CAN WE ACTUALLY GET TO WHERE WE NEED TO BE TO MAINTAIN OUR LEAD HERE WITHOUT GOOGLE, OR DO YOU THINK GOOGLE’S INVOLVEMENT IS ABSOLUTELY ESSENTIAL?>>I DON’T KNOW. THAT’S BEYOND MY EXPERTISE. I DON’T KNOW WHAT THEIR COMPETITORS CAN OR CAN’T DO. I WILL SAY THIS. I STRONGLY SUSPECT THAT CHINA’S AHEAD OF US IN ARTIFICIAL INTELLIGENCE PURSUIT JUST AS THEY ARE AHEAD OF US IN HYPERSONIC WEAPONS. JUST FOR OUR VIEWERS WHO MAY NOT UNDERSTAND THIS, RUSSIA AND CHINA HAVE CAUGHT THE UNITED STATES IN TERMS OF THE TECHNOLOGICAL ADVANTAGE THAT WE HAVE HAD. THEY HAVE STEALTH TECHNOLOGY, ADVANCED ELECTRONIC WARFARE. I COULD GO ON AND ON. THEY HAVE PASSED US IN CERTAIN CAPABILITIES, SO MUCH SO, PAY ATTENTION TO WHAT I’M ABOUT TO SAY, THAT OUR MILITARY LEADERS AND THE COMMISSION I HAVE BEEN ON FOR OVER A YEAR, CONGRESSIONAL COMMISSION ON THE NATIONAL DEFENSE STRATEGY HAVE SAID WE WOULD STRUGGLE TODAY TO FIGHT A WAR AGAINST RUSSIA AND CHINA AND WE COULD ACTUALLY EVEN LOSE. THAT HAS BEEN CODIFIED BY OUR SENIOR MILITARY LEADERS AS WELL. THE GOOD THING IS TRUMP DEFENSE IS BRINGING US OUT OF THIS HOLE, MUCH AS THE REAGAN DEFENSE BUDGET BROUGHT IS OUT OF A HOLE IN THE 1980s. DAVID: GENERAL, WE GOT TO LEAVE IT AT THAT. WE HAVE RUN OUT OF TIME.

The Math Behind Basketball’s Wildest Moves | Rajiv Maheswaran | TED Talks


My colleagues and I are fascinated
by the science of moving dots. So what are these dots? Well, it’s all of us. And we’re moving in our homes,
in our offices, as we shop and travel throughout our cities
and around the world. And wouldn’t it be great
if we could understand all this movement? If we could find patterns and meaning
and insight in it. And luckily for us, we live in a time where we’re incredibly good
at capturing information about ourselves. So whether it’s through
sensors or videos, or apps, we can track our movement
with incredibly fine detail. So it turns out one of the places
where we have the best data about movement is sports. So whether it’s basketball or baseball,
or football or the other football, we’re instrumenting our stadiums
and our players to track their movements every fraction of a second. So what we’re doing
is turning our athletes into — you probably guessed it — moving dots. So we’ve got mountains of moving dots
and like most raw data, it’s hard to deal with
and not that interesting. But there are things that, for example,
basketball coaches want to know. And the problem is they can’t know them
because they’d have to watch every second of every game, remember it and process it. And a person can’t do that, but a machine can. The problem is a machine can’t see
the game with the eye of a coach. At least they couldn’t until now. So what have we taught the machine to see? So, we started simply. We taught it things like passes,
shots and rebounds. Things that most casual fans would know. And then we moved on to things
slightly more complicated. Events like post-ups,
and pick-and-rolls, and isolations. And if you don’t know them, that’s okay.
Most casual players probably do. Now, we’ve gotten to a point where today,
the machine understands complex events like down screens and wide pins. Basically things only professionals know. So we have taught a machine to see
with the eyes of a coach. So how have we been able to do this? If I asked a coach to describe
something like a pick-and-roll, they would give me a description, and if I encoded that as an algorithm,
it would be terrible. The pick-and-roll happens to be this dance
in basketball between four players, two on offense and two on defense. And here’s kind of how it goes. So there’s the guy on offense
without the ball the ball and he goes next to the guy
guarding the guy with the ball, and he kind of stays there and they both move and stuff happens,
and ta-da, it’s a pick-and-roll. (Laughter) So that is also an example
of a terrible algorithm. So, if the player who’s the interferer —
he’s called the screener — goes close by, but he doesn’t stop, it’s probably not a pick-and-roll. Or if he does stop,
but he doesn’t stop close enough, it’s probably not a pick-and-roll. Or, if he does go close by
and he does stop but they do it under the basket,
it’s probably not a pick-and-roll. Or I could be wrong,
they could all be pick-and-rolls. It really depends on the exact timing,
the distances, the locations, and that’s what makes it hard. So, luckily, with machine learning,
we can go beyond our own ability to describe the things we know. So how does this work?
Well, it’s by example. So we go to the machine and say,
“Good morning, machine. Here are some pick-and-rolls,
and here are some things that are not. Please find a way to tell the difference.” And the key to all of this is to find
features that enable it to separate. So if I was going
to teach it the difference between an apple and orange, I might say, “Why don’t you
use color or shape?” And the problem that we’re solving is,
what are those things? What are the key features that let a computer navigate
the world of moving dots? So figuring out all these relationships
with relative and absolute location, distance, timing, velocities — that’s really the key to the science
of moving dots, or as we like to call it, spatiotemporal pattern recognition,
in academic vernacular. Because the first thing is,
you have to make it sound hard — because it is. The key thing is, for NBA coaches,
it’s not that they want to know whether a pick-and-roll happened or not. It’s that they want to know
how it happened. And why is it so important to them?
So here’s a little insight. It turns out in modern basketball, this pick-and-roll is perhaps
the most important play. And knowing how to run it,
and knowing how to defend it, is basically a key to winning
and losing most games. So it turns out that this dance
has a great many variations and identifying the variations
is really the thing that matters, and that’s why we need this
to be really, really good. So, here’s an example. There are two offensive
and two defensive players, getting ready to do
the pick-and-roll dance. So the guy with ball
can either take, or he can reject. His teammate can either roll or pop. The guy guarding the ball
can either go over or under. His teammate can either show
or play up to touch, or play soft and together they can
either switch or blitz and I didn’t know
most of these things when I started and it would be lovely if everybody moved
according to those arrows. It would make our lives a lot easier,
but it turns out movement is very messy. People wiggle a lot and getting
these variations identified with very high accuracy, both in precision and recall, is tough because that’s what it takes to get
a professional coach to believe in you. And despite all the difficulties
with the right spatiotemporal features we have been able to do that. Coaches trust our ability of our machine
to identify these variations. We’re at the point where
almost every single contender for an NBA championship this year is using our software, which is built
on a machine that understands the moving dots of basketball. So not only that, we have given advice
that has changed strategies that have helped teams win
very important games, and it’s very exciting because you have
coaches who’ve been in the league for 30 years that are willing to take
advice from a machine. And it’s very exciting,
it’s much more than the pick-and-roll. Our computer started out
with simple things and learned more and more complex things and now it knows so many things. Frankly, I don’t understand
much of what it does, and while it’s not that special
to be smarter than me, we were wondering,
can a machine know more than a coach? Can it know more than person could know? And it turns out the answer is yes. The coaches want players
to take good shots. So if I’m standing near the basket and there’s nobody near me,
it’s a good shot. If I’m standing far away surrounded
by defenders, that’s generally a bad shot. But we never knew how good “good” was,
or how bad “bad” was quantitatively. Until now. So what we can do, again,
using spatiotemporal features, we looked at every shot. We can see: Where is the shot?
What’s the angle to the basket? Where are the defenders standing?
What are their distances? What are their angles? For multiple defenders, we can look
at how the player’s moving and predict the shot type. We can look at all their velocities
and we can build a model that predicts what is the likelihood that this shot
would go in under these circumstances? So why is this important? We can take something that was shooting, which was one thing before,
and turn it into two things: the quality of the shot
and the quality of the shooter. So here’s a bubble chart,
because what’s TED without a bubble chart? (Laughter) Those are NBA players. The size is the size of the player
and the color is the position. On the x-axis,
we have the shot probability. People on the left take difficult shots, on the right, they take easy shots. On the [y-axis] is their shooting ability. People who are good are at the top,
bad at the bottom. So for example, if there was a player who generally made
47 percent of their shots, that’s all you knew before. But today, I can tell you that player
takes shots that an average NBA player would make 49 percent of the time, and they are two percent worse. And the reason that’s important
is that there are lots of 47s out there. And so it’s really important to know if the 47 that you’re considering
giving 100 million dollars to is a good shooter who takes bad shots or a bad shooter who takes good shots. Machine understanding doesn’t just change
how we look at players, it changes how we look at the game. So there was this very exciting game
a couple of years ago, in the NBA finals. Miami was down by three,
there was 20 seconds left. They were about to lose the championship. A gentleman named LeBron James
came up and he took a three to tie. He missed. His teammate Chris Bosh got a rebound, passed it to another teammate
named Ray Allen. He sank a three. It went into overtime. They won the game.
They won the championship. It was one of the most exciting
games in basketball. And our ability to know
the shot probability for every player at every second, and the likelihood of them getting
a rebound at every second can illuminate this moment in a way
that we never could before. Now unfortunately,
I can’t show you that video. But for you, we recreated that moment at our weekly basketball game
about 3 weeks ago. (Laughter) And we recreated the tracking
that led to the insights. So, here is us.
This is Chinatown in Los Angeles, a park we play at every week, and that’s us recreating
the Ray Allen moment and all the tracking
that’s associated with it. So, here’s the shot. I’m going to show you that moment and all the insights of that moment. The only difference is, instead
of the professional players, it’s us, and instead of a professional
announcer, it’s me. So, bear with me. Miami. Down three. Twenty seconds left. Jeff brings up the ball. Josh catches, puts up a three! [Calculating shot probability] [Shot quality] [Rebound probability] Won’t go! [Rebound probability] Rebound, Noel. Back to Daria. [Shot quality] Her three-pointer — bang! Tie game with five seconds left. The crowd goes wild. (Laughter) That’s roughly how it happened. (Applause) Roughly. (Applause) That moment had about a nine percent
chance of happening in the NBA and we know that
and a great many other things. I’m not going to tell you how many times
it took us to make that happen. (Laughter) Okay, I will! It was four. (Laughter) Way to go, Daria. But the important thing about that video and the insights we have for every second
of every NBA game — it’s not that. It’s the fact you don’t have to be
a professional team to track movement. You do not have to be a professional
player to get insights about movement. In fact, it doesn’t even have to be about
sports because we’re moving everywhere. We’re moving in our homes, in our offices, as we shop and we travel throughout our cities and around our world. What will we know? What will we learn? Perhaps, instead of identifying
pick-and-rolls, a machine can identify
the moment and let me know when my daughter takes her first steps. Which could literally be happening
any second now. Perhaps we can learn to better use
our buildings, better plan our cities. I believe that with the development
of the science of moving dots, we will move better, we will move smarter,
we will move forward. Thank you very much. (Applause)

Microsoft Teams updates for mobile and firstline workers | Best of Microsoft Ignite 2018


(upbeat music) – Hello again and welcome
to Microsoft Mechanics Live! So coming up, we’re going to take a look at the latest updates to accelerate modern teamwork using Microsoft 365. Starting with the work that
we’re doing to empower different kinds of workers across
different industries. The completion of Skype
for Business capabilities coming into Microsoft Teams to deliver a complete meeting and calling solution. Deeper teamwork experiences
to transform collaboration and for IT, my favorite part, I’m going to show you new controls for security, compliance, team management, and more. Before I get started, please everybody give a warm welcome to Lori Wright. General manager-
(cheers and applause) for Microsoft 365, welcome. – Thank you, Jeremy. Great to be here. – So, we’re seeing some really big shifts in the way that people
are actually getting work done today and working together. What is your team doing
to address these shifts? – Well, we recognize
that the way that people work around the world is truly changing. People work on more
Teams than ever before. Their work is more
distributed than ever before. And, so, we built Microsoft
Teams less than two years ago as the hub for teamwork in Microsoft 365. And what we’re doing now
is we’re expanding this across a whole new set
of scenarios so that it truly is for every worker out there. – Great, so can you tell
us about some of the recent announcements that we’ve made this week? – Yes, we had a lot of announcements. Hopefully, some of you got to see the general session we did yesterday. But I’ll start with one
of the more exciting areas we announced which was
for first line workers. And, when you think
about first line workers, there are 2.5 billion of
these people in the workforce and they actually represent
80% of the global workforce. – Right. – And these are the factory
workers and the retail clerks and the people who don’t traditionally have dedicated offices or dedicated PCs. And they work in shifts and they typically just have a mobile phone and,
so, what we are doing now, is we want to give them
the same advantages that traditionally have been
given to knowledge workers where the capabilities, the
technological advantages that they can take advantage of as well. – Right, and this really
helps us, then, to customize and extend team’s
capabilities even more broadly and the other great
thing is that we’re also infusing in some AI, some intelligence. Pretty much across all
of Microsoft’s services and Teams is also doing
this but what are we doing to translate all of the
intelligence work into Teamwork? – Well, so we’re investing in AI scenarios across Microsoft 365. One example of how this comes to life is in chat translation. I’m sure many of you out there have seen and were able to translate a chat, in real time, into 40 languages. This really breaks down
communication barriers for people who are
working in different parts of the world and, you know,
speak different native tongues. and, so, this is the benefit of AI. Another strong example of
this is in our cloud meeting recording that we announced
went GA this week as well. And what this does, is
it takes meeting content, sends it up to the
Cloud, unlocks all of it, and breaks it down so that
meeting can be transcribable and searchable after the fact and it also includes facial detection. So, it’s really cool to be able to jump to different points of different
speakers in the timeline. And, so this is all
again an AI capability. Lots of other examples as
well but those are the two-. – Right, real differentiators in Teams and I know a lot of
people are probably used to using email, or
SharePoint, maybe Yammer. How do we support those
different modalities, really, as we think about introducing
new ways of working together? – Well, we’re bringing our
collaboration experiences closer together across the
Microsoft 365 portfolio. One of the examples of this
we announced this week, also, was we’re going to take Yammer
and bring that into Teams as a tab and we’re also doing
that with SharePoint Pages. So, that will also be a
tab and, so, these are ways that we’re bringing the portfolio closer. – [Jeremy] And, of course,
everything’s underpinned by security, right, the security that we get through SharePoint and everything else through Microsoft 365. – Yes, so all of this is enterprise grade, you know, security
compliance and manageability. – Okay, so let’s dive a bit deeper on the work that we’re
doing to deliver Teams to workers in different professions. – [Lori] Great.
– [Jeremy] Or industries. – [ Lori] Alright, so
since the earliest days of Microsoft Teams,
many of you, all of you raised your hands in the
audience, you’re using Teams. One of the strongest verticals that we have seen is for education. Teams is being used very,
very widely in education for classroom coordination
and for assignments. And, so, one of, as we
look to broaden now, one of the areas that we’re going into, as I mentioned, is first line workers. And so what we’re doing there is that, if you think about there’s
two different views, there’s a manager view
and an employee view. And for managers, they
often need to create shift schedules and they
need to share these schedules out with their Teams and then
these first line workers need to be able to communicate
back with their manager and to be able to say
yes or no on a shift. And, so, we’re making Teams
easily customizable where it can be worked to manage shifts both for the manager and for the employee. – Alright, so what does it look like then for the employee to start
using some of these things? – Let me show you. – Let’s do a demo. – A picture’s worth a thousand words. – Yes. – Okay, so I’m going
to pick up a phone here which is the primary device
for most first line workers. So, you see here, I have a Shifts icon. I can click this Shifts icon and I can see all of the shifts that I have been assigned to work that day. Well, the 29th is my
birthday, and so I don’t want to work on my birthday so
I am going to click that and I am going to ask to swap that shift. With the click of a button, I can say swap and see the different team members who are available to work that day. And, so I’ll go ahead here
and let me pick Adele. She looks great. Alright, so Adele, the
request has been sent off to my manager and, hopefully, Adele can pick up that shift for me. So, that’s an example of Shifts. Now, another great new first
line capability we have here, if I go back home, is that
I can see when messages have been sent to me by either
the company or by my manager and, in this case, I’m a grocery clerk and I can see that
there’s been an outbreak of E. coli in romaine lettuce
so I need to go pull this. – [Jermemy] And this is super
important that you’d have to action and really make sure that everybody gets that message. – Yeah, I mean, E. Coli
probably not a lot of fun for anyone so we’ll get
the lettuce off the shelves and we need to have it done by noon today. So, that’s an example of
being able to communicate in a very important way out to the staff. Now, one last thing I
want to show you here on first line workers is
I can go up to the clock and with a simple click of
a button, I can hold it down and I have now started my shift. So, I’m officially on the
clock and then if I wanted to I can stop my shift or I can take a break at any point of time and these are just a few of the features. – That’s good but you’re on the clock now just so you know. Well, let’s keep going. You mentioned that Teams
is now a complete meeting and calling solution
as well and we’ve been on this journey to really incorporate all of the Skype for Business
capabilities into Teams. How has that worked out then? What are the additional
capabilities that we can look forward to as we
upgrade to Microsoft Teams? – Well, last year as many
of you know, we announced our vision for intelligent communications and since that time, we have seen really, really great momentum
and, in fact, yesterday, we announced that Teams is
the fastest growing business app in the history of Microsoft. Today, we have over 300
thousand, 329,000 to be precise, organizations who are using Teams. It is used by 87 of the Fortune
100 and we had Accenture recently cross the mark
of our first customer that has over 100 thousand
monthly active users. – [Jeremy] Right and you’ve done a lot in terms of all the updates as well right? – Yes, we have. Okay, so with our
intelligent communications vision we knew first
thing we needed to do was publish a road map and say to
get from Skype for Business to Teams, we needed to do these things. And we’ve delivered all of the
features that we’ve put out on that road map, that
was over 90 features and, then we also innovated on top of that with features like blur and translation and things of that sort. Today, Teams is ready for
messaging, calling, meeting needs for customers around the world. We are helping customers,
we’re providing assistance to customers who want to upgrade now through fast track and
we’re also starting, for companies that
don’t traditionally have IT departments, pushing
out automatic migrations, if you will, to help those
companies get over to Teams. – Great, great. So, this is really impressive, in terms of all the updates, even
since our last show. We had Anne Michaels showing some things and we’ve also had Dan
Stevenson recently on. But, I know that a few months back, we’ve added a lot more since then. Can we take a look at
some the recent, recent updates that we’ve made to Teams? – Yes. Yes. Okay, so let’s do it. I’ll do another demo here. I’m going to start out,
a lot of people here are familiar with the basics of Teams but I can go up here into my Teams and see Teams and Channels. So, I’m going to start here
in the Business Review channel and scrolling here, my
colleague, Praveen, has sent me a message in a language I
don’t necessarily understand. Can you interpret that? – [Jeremy] No, I speak Mandarin and German but that’s not one of those two. – [Lori] Doesn’t look
like Mandarin or German. Okay, so what I can do,
Microsoft Teams can help and with the simple click
of a button, just like that. – [Jeremy] Wow and this
works for forty languages. – [Lori] Forty languages around the world. – [Jeremy] Not bad, very cool. – [Lori] So that is a feature. The next thing I just love to point out is across the top here, you see all of the different tabs that are built in. Well, a lot of these, like
OneNote, very commonly used application, is integrated
right here into Teams and so I can be able to
see the shared notebook of everything that’s
going on within this team. I can also go over straight into Power BI and have all the features of Power BI right here within Teams where I can drill into this content or the
data, move the data around, do what I need to
understand the analytics. I can also go over here to Stream and see all the different videos
that pertain to this team and these are just a couple of examples, tabs across the top. – Yeah, that’s one of my favorite features in Teams because all these
tabs are customizable. So, regardless of how
your team works, you can customize what people see and what the team needs, effectively. Therefore, you can have different views for any different type of team and you can just add tabs
with the plus sign there and completely customize your experience. – [Lori] That’s right and then
if you want to go shopping, we have a Microsoft Store here. You can go down to the
store and you can see the hundreds of third party applications that we have right here
that you can add in as a tab into Teams as an integration. Okay, so that’s a little
bit, everything around Tabs. So, now let me show
you, one of the things, let me go back into this team and I’m going to show
you a meeting recording. This is the feature that we
have called meeting recording and I can start here and
I’ve missed this meeting but I want to catch up on
it and understand everything I need to know that
happened in the meeting but I really don’t have time
to watch the whole thing. So what I can do here
by starting it is, one, for accessibility reasons,
as well as if I’m just in a noisy place, I can turn
on closed captioning and have- – [Jeremy] Very cool. – [Lori] Yeah. – [Jeremy] Voice to text? – [Lori] Correct, so voice-to-text cognitive services happening here. I can also go and search
and say, what’s important, what did I miss, where did
I get action items assigned? So, I can type my name
and looks like here’s the two points where my name
was mentioned in the meeting and so I can go and check
that out and see what I need to go do. – Very cool, imagine all
the hours we would save just by fast forwarding to those
action items with our names on them in a captioned meeting
like this. That’s awesome. – (laughs) That’s right, that’s right. So, that’s a little bit
about meeting recording. Now, let’s go down and look at a a meeting that’s already been scheduled. This is a meeting that
my colleague, Farren, has scheduled with me
and so let me go ahead and join this meeting
directly within Teams. I hit the join button
and what I have here now is the pre-join screen
and so I can turn my video on or off, I can turn
my mic on or off, I can choose different devices
but this is the new feature that we just made generally
available this week, where you see two of me in the background here. – [Jeremy] A little inception there. – Yeah, alright let me get rid of that. So, I’ve now turned on background blur and with that my background disappears. (light applause and cheers) – [Jeremy] Very cool. – [Lori] And so this is about
eliminating distractions. – [Jeremy] Yeah, all the
distractions, all the mess that we might have
behind us in our offices. This will make it much better. – [Lori] Gone, the cat that
does acrobatics behind you. – [Jeremy] Or all the machines that were maybe re-imaging behind us. – Okay, that and there’s the
one and only Farren Roper. Alright, so Farren can do the same thing. He can blur on his end as well and you see how blur works. – [Jeremy] Very good stuff. – [Lori] Yeah so that’s blur, and then one other thing that’s worth a brief mention here is calling. So, full calling
capabilities are now built into Teams as well. You see all of my contacts
here that I could call any of these individuals
but I also just have the standard dial pad that we all know. I can go out here, I can
dial any phone number in the world and I do this through either a Microsoft calling plan
or through direct routing. And direct routing let’s
you basically bring your own calling plan with your existing TelCo and connect things up. Now, I see I can click
over to voicemail, as well, and you see I have a
voicemail from Angela Donohue. Well, instead of playing
it out loud right now, all I can do is take a quick look and see that it’s been transcribed for me. I know what Angela wants,
I don’t have to play it. Transcription is there now, as well. – Very cool and I know that
Angela is a real device buff so, one of the other things
I love about using Teams is using Who. – Ah, Who. Who is truly one of my
favorite parts of Teams. I use it all the time. So, I go up here and I do a slash command and you see all the slash
commands that are available. It’s a short way to
navigate around in the app if you just do slash,
you can see everything that’s there so I’m
going to say Who and then I’m going to say who knows about devices? Because I need to find the devices expert in the organization. Well, it comes back and it looks at all the different activity that’s happening and it tells me that Angela and Christian are the two people who are having the most conversation around
devices and so I’m going to pick Angela and go
ahead and send her a chat. And when I do that, here I
see Angela’s very proficient and has already read my
mind and knows that I need – [Jeremy] She’s using that
predictive chat technology. – [Lori] (laughs) Coming next. – [Jeremy] It’s an alpha. – [Lori] And so, here I can open up and see this presentation
that Angela has sent me on on our new device’s partners. And these are now, we announced
a new certification program for third party devices
where each of these partners are building so that Teams,
you can run great reliable Teams experiences across all
of these different partners. – Right, and I know a lot
of people are maybe, they’ve outfitted their meeting
rooms with custom hardware from their providers,
they’ve designed their rooms around them. How are we supporting
those types of devices? – Well, one way we’re doing
this is by helping connect the existing video
endpoints that are out there and we’re doing this
through a set of Cloud Video interop partners. Polycom is the first, they
announced their GA in market with their CBI solution
this week and then BlueJeans and Pexip will also be announcing GA here in the next couple of weeks. – And where would I go then
to find more information about this if I’ve got one of these rooms? – Well, we just launched
a new website, also. Another exciting step forward this week. You can go to office.com/Teams
and you’ll be able to see all of the devices
that are available across our third parties
and you can even buy these devices directly from the store as well. – Great stuff. So, Lori, let’s switch gears here. I think that there are a few system admins and Microsoft 365 admins
among us so let me talk about some of the security
compliance capabilities and for that, I’m gonna take over and I’m gonna show a
couple of things here. First, one of my favorite
capabilities across SharePoint and Office 365 or Microsoft
365 is data loss prevention. So, here we’re seeing an early look at DLP working inside of Teams. You know, I’ve got some information here that I probably shouldn’t be sharing like social security number,
credit card information and when I do that what’s
gonna happen is it’s gonna block the message and I can click in and see why it’s been
blocked and here I can see. Obviously, you shouldn’t
be sharing credit cards or social security numbers
and the nice thing is, beyond that, the person
that’s receiving that message is gonna see that it was blocked because it has the
sensitive information in it. So, all of this is really using DLP and that labeling and
classification engine behind the scenes to be able to make sure that sensitive information
doesn’t leak out. One of my favorite things here or a lot of my favorite things here
with Teams are all the updates to the admin center so let me show you a couple of things there. So, this is the new Microsoft Teams and Skype for Business admin center. Bit of a mouthful but a
very powerful admin center. Just to show you a couple of things here. So, there’s a new manage Teams note here that you can use but I’m
going to click into users cause what I want to show
you is something you can do around user management that’s brand new. First, we can see all the different users that we have in our team. If I click on Adele Vance,
for example, I can use this to see what team she’s on
and I can also use the edit command here in the Teams upgrade and I’ll expose a brand
new set of options here. So, typically, as you make the transition from Skype for Business
to Microsoft Teams, you have an Islands mode that lets users kind of use either one but now you’ve got the Teams only option so
you can upgrade to Teams and you can also, we’ll
be producing group policy settings that will also
allow the client side of configurations to work there as well. Now, let me show you a
couple of other things here that are pretty cool. So, if I go into Manage Teams, you’ll see that I have all of my
Teams here enumerated. Nice list of all the Teams,
the membership, everything in there and I can go and edit the Teams. I can also do some things, in terms of going directly into the team itself and what I want to do
is, maybe somebody leaves the company, I wanna
assign different ownership to the team, go from member to owner maybe if the previous owner
of the team has left. I can do all that right
here from this console so very, very powerful stuff in terms of managing the Teams experience and one of my favorite things cause I’m a real (applause) – Oh, feel free to clap.
I mean this is good stuff. We’ve got some other, if
you’re using dynamic groups in Azure AD, and hopefully everybody is and you can use it for devices or users but let me show you what that looks like on the user side. The nice thing, let’s say
I’m operating a hospital. You never know what can
happen when you’re filming Microsoft Mechanics so you
have to operate hospitals and do some side gigs sometimes. So, here I’m going to click
into the Portland Hospital and you’ll see that I’ve
got this dynamic group and it’s got dynamic membership roles and I wanna click into
those dynamic roles. What I’ll see here is
that any department that starts with Portland,
anybody that’s got that in their Azure AD attribute is going to be joined to this team. That means that as I hire
people, as people leave my organization, that team
is gonna dynamically grow and contract with those
new hires into the team. So, everybody’s provisioned
directly into the Teams they should actually be in
and, one last thing, is, I know this is a request we
get from a lot of people, is templating and kind of
doing work to make sure that we can provision
Teams in automated ways using scripting, maybe calling
APIs through PowerShell, whatever you want to do and
we’ve done a lot of work here in terms of building Teams
using scripted automations. So, for example, if you
want to hook into HR systems or do other work, you can
actually templatize Teams, put in content, personalize those Teams. This is all brand new
stuff, you can see it’s in preview that we’re
adding to Microsoft Teams. So, those are a few of
my favorite Teams things but, you know, we’ve done a
lot more than this, right? – We have. I think, you know,
one, it was a great demo. We might wanna hire you on
the demo team if you have some spare time but otherwise,
we’re barely scratching the surface here, in terms
of all these great features. You know, for both our
users and for our admins, it’s really awesome to see all that’s happening here with Teams. – Very cool, so lots of
really good updates, really, to hopefully help bring Teams together. Thank you, Lori, for the
tour of all the different additions to Teamwork but
what’s next on the horizon? – Well, you know we’re always
working on the next thing and I look forward to coming
back for the next show and telling you all about it but for now, I’ll tell you that the things that we’re really, really focused
on are continuing with the extensibility of Teams
and also making sure that across Microsoft 365, it
gets smarter and smarter and is really helping
Teams around the world work better together. – Right, and I think I’ve
answered the question but for those of us who are
looking to get started with Teams, where do
they go to learn more? – I think the easiest
place is office.com/Teams. Here, you can find anything
that you need related to Teams. We have a free version where you can get started or you can go ahead and start in the full featured paid versions as well so lots of options out
there on office.com/Teams. – Thank you and also be sure to check out our recent shows on Microsoft Teams as well as stream on Microsoft Mechanics. Thanks for watching. Subscribe to our channel. We’ll see you next time
and goodbye for now. (upbeat music)
(applause)

Trump: Apple’s Tim Cook made ‘very compelling’ case against tariffs


TIM COOK MADE A COMPELLING CASE AGAINST TARIFFS ON CHINA. LISTEN TO THIS.>>TIM WAS TALKING TO ME ABOUT TARIFFS, ONE OF THE THINGS HE MADE A GOOD CASE, SAMSUNG IS THEIR NUMBER ONE COMPETITOR, SAMSUNG IS NOT PAYING TARIFFS BECAUSE THEY’RE BASED IN SOUTH KOREA, IT IS TOUGH FOR APPLE TO PAY TARIFFS COMPETING WITH A GOOD COMPANY THAT IS NOT. HOW GOOD AFTER COMPETITOR? THEY ARE A VERY GOOD COMPETITOR. SO SAMSUNG IS NOT PAYING TARIFFS BECAUSE THEY’RE BASED IN A DIFFERENT LOCATION, MOSTLY IN SOUTH KOREA, BUT THEY’RE BASED IN SOUTH KOREA, I THINK HE MADE A VERY COMPELLING ARGUMENT SO I’M THINKING ABOUT IT. DAVID: REBECCA FAN NONE, TECH TITANS AUTHOR. WHAT DO YOU THINK ABOUT IT? DOES APPLE HAVE A CASE THAT TARIFFS SHOULDN’T APPLY WHAT THEY DO IN CHINA?>>APPLE IS COMPETING WITH SAMSUNG WHICH IS THE LEADING MOBILE APP COMPANY, I THINK THEY DO HAVE A CASE. WE NEED TO HAVE MORE OPEN ECONOMY, MORE FREE TRADE, BUT ON THE OTHER HAND, APPLE IS PRODUCING IN CHINA AND SAMSUNG IS PRODUCING IN SOUTH KOREA. SO THIS GIVES SAMSUNG A LEG UP OVER APPLE AND, SO TIM COOK DOES HAVE A CASE IN HIS SPECIFIC INCIDENT BUT OVERALL I THINK THAT, WE DO NEED THIS OPEN ECONOMY. WE NEED FREE TRADE. I THINK IT IS GOOD FOR THE GLOBAL INNOVATION ECONOMY OVERALL. I THINK IT HELPS CONSUMERS AND BUSINESSES. DAVID: BUT, THE QUESTION IS, CHINA MADE THIS HUGE, GREAT LEAP FORWARD. I THINK HE USED THAT PHRASE, BORROWING FROM MAO ZEDONG’S PHRASE, BUT HIGH-TECH THEY MADE A BIG LEAP. HOW MUCH OF THEIR BIG LEAP WAS BASED ON TECHNOLOGY THEY STOLE FROM US?>>I DON’T THINK THEY STOLE TECHNOLOGY FROM US. DAVID: YOU DON’T THINK THEY STOLE ANY TECHNOLOGY FROM US? I THINK EVEN CHINESE TECHNOLOGY WIZARDS ADMIT THERE WAS SOME OF THAT GOING ON.>>WHAT WAS HAPPEN, CHINA WAS COMING IN, INVESTING IN U.S. TECH COMPANIES. THEY INVESTED IN MANY LEADING COMPANIES IN THE U.S. INCLUDING UBER, LYFT, MAGIC LEAP, TESLA AND THEY WERE LEARNING. ALSO — DAVID: THEY WERE DOING MORE THAN LEARNING. THERE WERE SOME MEMBERS THE CHINESE GOVERNMENT THAT WERE SENT IN TO LITERALLY SPY ON TECH COMPANIES, STEAL SOME OF THAT HARDWARE OR SOMEHOW TRY TO DEVOLVE IT AND FIGURE OUT THE WAY THAT AMERICAN COMPANIES WERE EVOLVING WITH THAT TECHNOLOGY AND BRING IT TO CHINA. SO I MEAN, THERE REALLY WAS A CONCERTED EFFORT ON THE PART OF THE GOVERNMENT TO STEAL FROM THE UNITED STATES.>>I THINK THE FBI IS LOOKING AT 1000 INVESTIGATIONS RIGHT NOW. THEY’RE INVESTIGATING THESE CYBERSECURITY INCIDENTS, AND I THINK THE JURY IS STILL OUT. WE NEED TO SEE WHAT THE OUTCOME OF THAT INVESTIGATION IS. I DO THINK CHINA HAS COME IN TO THE U.S. THEY HAVE INVESTED IN OUR LEADING U.S. TECHNOLOGY COMPANIES. THEY HAVE GONE TO SCHOOL AT OUR FINEST SCHOOLS AND THEY HAVE WORKED IN OUR FINEST TECH COMPANIES IN SILICON VALLEY AND ELSEWHERE. THEY HAVE GONE BACK TO CHINA AND TAKEN A LOT OF KNOW HOW AND COPIED WHAT WE HAVE DONE IN THE U.S. AND MADE THE FACEBOOK OF CHINA, THE GOOGLE OF CHINA AND SO FORTH. BUT NOW TODAY, WHAT CHINA IS DOING IS THEY’RE ACTUALLY INNOVATING IN THEIR OWN RIGHT AND THESE — DAVID: FORGIVE ME FOR INTERRUPTING BUT DO YOU THINK THAT IS WHY THEY’RE MAKING PROGRESS ON 5G, IS THEIR OWN INNOVATION? CLEARLY THEY HAVE A TENFOLD GAIN ON US IN TERMS OF PLATFORMS FOR 5G THEY HAVE OVER THERE?>>THEY’RE DEFINITELY OUTSPENDING US IN 5G INFRASTRUCTURE. THEY’RE GETTING AHEAD IN OTHER VERY IMPORTANT TECH SECTORS SUCH AS A.I. CHINA IS, HAS A NATIONAL GOVERNMENT PRIORITY TO GET AHEAD IN AT LEAST 10 TECHNOLOGY SECTORS THAT REALLY MATTER. DAVID: LET’S TALK ABOUT A.I. FOR A SECOND. THIS IS SOMETHING THAT I’M SURE YOU KNOW, PETER THIEL, ONE OF THE GREAT MINE IN HIGH-TECH IS A PROBLEM. WHEN COMPANIES LIKE GOOGLE ARE TRADING INFORMATION ON A.I. IN THEIR DEALINGS WITH CHINESE COMPANIES, THE GOVERNMENT GETS INVOLVED AND SOME OF THAT A.I. FINDS ITS WAY TO THE MILITARY, THE CHINESE MILITARY, WHICH IS NOT OUR FRIEND. IS THAT A PROBLEM?>>WE DO HAVE COMPANIES, THE LEADING A.I. COMPANY IN THE WORLD, THE MOST VALUABLE A.I. COMPANY IN THE WORLD FROM CHINA. A COMPANY CALLED SINCE TIME. THEY ARE USING, VERY BIG IN FACIAL RECOGNITION WHICH CAN BE USED BY POLICE TO TRACK CRIMINALS. IT CAN BE USED TO TRACK JAYWALKERS. DAVID: WE’VE SEEN IT WITH THE HONG KONG PROTEST.>>EXACTLY, WE’VE SEEN IT BEING EMPLOYED IN THIS CASE.>>THEY ARE ACTUALLY WORKING WITH HONDA ON AUTONOMOUS VEHICLES, WORKING WITH QUALCOMM. QUALCOMM IS AN INVESTOR IN SENSE TIME. THEY ARE WORKING WITH QUALCOMM ON NEXT GENERATION DEVICES. IT IS NOT ALL SUCH A BAD, BAD SCENARIO. DAVID: IT DOES CORN ME. I HAVE TO ASK ONE FINAL QUESTION. WHO WINS WITH 5G. WHO GETS THEIR WHOLE SYSTEM TIED INTO 5G FIRST, CHINA OR THE UNITED STATES.>>WHAT IS HAPPENING NOW, YOU HAVE A RACE. CHINA HAS ITS OWN STANDARDS, DEVELOPING ITS OWN STANDARDS. IT IS BEING ACCEPTED IN MANY COUNTRIES AROUND THE WORLD. THE U.S. IS FIGHTING BACK. WE’RE NOT ALLOWING CHINA 5G TO BE IN THIS MARKET. SAME THING WITH AUSTRALIA. DAVID: BUT THE ANSWER TO THE QUESTION IS?>>WHO IS GOING TO WIN? I THINK THE JURY IS STILL OUT. I THINK WHAT IS HAPPENING IS THAT CHINA IS, CHINA WILL HAVE ITS OWN STANDARDS. THOSE STANDARDS WILL GO INTO ASIA. I THINK THE U.S. AND THE WESTERN WORLD WILL HAVE ITS OWN STANDARD. DAVID: WOW, TWO SYSTEMS?

Biggest wins for AI will be in health care: Former Google CEO


CASES THEM TO WORK HARDER. MARIA: I LIKE THE IDEA OF REALLY LOOKING AT THE PEOPLE BRINGING OUT AS MUCH AS YOU CAN FROM PEOPLE GIVING PEOPLE, THAT LEADERSHIP, AND THAT COMPOSUREMENT PEOPLE REPRESENT IDEAS AT GOING IS THERE A WAY YOU NEED TO HARNESS THAT STRENGTH, BUT NOT FOLLOW ALL THE DECISIONS OF THE PEOPLE BECAUSE A LOT OF PEOPLE QUESTION WHETHER OR NOT IT ITSELF TOO MUCH NOW THERE HAVE BEEN BIG DECISIONS, IN A MANAGEMENT HAS MADE AT GOOGLE BECAUSE THE PEOPLE WERE UPSET ABOUT WHETHER, PENTAGON CONTRACT OR WHETHER A.I., ETHICAL UNIT, IS IT TOO MUCH?>>IN THE GOOGLE CONTEXT ONE OF OUR VALUES IS THIS KIND OF INTERNAL CONVERSATION. WHERE BILL WOULD SAY I’M SORRY STICKING TO VALUES STAY VERY FOCUSED WHAT YOU WANT AS A BUSINESS THE REALITY IS TODAY, THESE MANAGEMENT JOBS ARE HARDER AND HARDER AND HARDER BECAUSE OF SOCIAL MEDIA AND SO FORTH YOU’VE GOT TO LISTEN, EVEN MORE CAREFULLY TO YOUR EMPLOYEES. BUT AT THE END OF THE DAY, THE OLD PLAYBOOK WHICH IS LEADERSHIP, COACHING, GETTING PEOPLE WHO ARE AVEN YOUNG AND RELATIVELY EXPERIENCED HUGE POTENTIAL TO ACHIEVE THEIR GREATNESS WHATEVER IT IS, THAT IS A UNIVERSAL HUMAN VALUE OUR ARGUMENT IN THE BOOK IS THAT THESE ARE APPLICABLE TODAY IN THE FUTURE THESE ARE UNIVERSAL VALUES OF MANAGEMENT ON LEADERSHIP.>>SOME POINT THE LEADERSHIP HAS TO SAY OKAY. I HEAR YOU, BUT WHAT DO I STAND FOR WHAT DO WE STAND FOR.>>THAT IS THE VALUES.>>IN BOOK YOU GO THROUGH MANY LESSONS BILL TAUGHT INCLUDING PEOPLE BILLED TRUST CREATING A WORKPLACE BASED ON LOVE, WHAT DOES THAT MEAN? GIVE ME A PRACTICAL IDEA BASED ON LOVE.>>YOU SHOW LOVE SHOW UP A MANAGER, COACH SHOW UP FOR YOUR PEOPLE, BREATHE CONFIDENCE INTO THEM, WHEN TIME GETS UP SHOW UP.>>ALSO MEANS CHEER. BILL WOULD CLAP LIKE THAT IN BOARD MEETINGS.>>IN THE MIDDLE OF THE MEETING NO GOOD REASON, MARIA I LOVE YOUR SHOW, [CLAPPING], FEELS GOOD.>>IN A MEETING, BY AUDIBLY CLAPPING LET YOU YOU KNOW WHAT A GREAT JOB YOU HAVE DONE.>>FANTASTIC.>>MOMENTUM TOWARDS THE DECISION.>>GETS EVERYBODY BUYING IN.>>HAVEN’T YOU SAID SAT IN MEETINGS AIRFARE KIND OF BORED OKAY. LET’S GET GOING IT IS THE SAME THING AS WINNING IN THE GAME.>>FUNNY HOW LITTLE THINGS MAKE A BIG DIFFERENCE LET ME ASK YOU ABOUT A.I. GOOGLE AMONG SENIOR COMPANIES OUT THERE WORKING ON ARTIFICIAL INTELLIGENCE WE HAVE BEEN LOOKING AT IT HERE AS WELL. IT IS EVERYWHERE IS IT JUST GOING TO GET BIGGER MORE PREVALENT.>>A LOT AHEAD GETTING EXERCISERS TO ABOUT SMARTER I THINK BIGGEST WINS IN HEALTH CARE I THINK THIS IS LARGELY UNDER REPORTED.>>YOU SAID A LONG TIME.>>I AM CONVINCED HERE IS WHY, AS MUCH AS WE THINK OF OURSELVES AS INDIVIDUALS BIOLOGICALLY WE ARE SIMILAR TO EACH OTHER COMPUTERS CAN WATCH WHAT HAPPENS NOW THE ALGORITHMS ARE SO GOOD WHEN YOU GO INTO A HOSPITAL IF WE KNOW ROUGHLY, YOU GIVE US YOUR PERMISSION ABOUT INFORMATION THIS IS THE HOSPITAL NOW NOT GOOGLE, THE HOSPITAL CAN SAY, HEY WE THINK THIS IS THE NEXT AILMENT THAT IS GOING TO HAPPEN, THAT IS HOW GOOD THE ALGORITHMS ARE GETTING THE WHOLE YEAR OF PRECISION MEDICINE THE ABILITY TO HAVE MEDICINE DIRECTED DIRECTLY AT YOU DIRECTLY REVOLTED TO ALGORITHMS, DIAGNOSTIC THE COMPUTER THE MAKE A RECOMMENDATION MORE ACCURATE THAN DOCTOR’S ICE.>>A LOT OF BABE DEBATE IN A LOT OF DEBATE IN TERMS OF EMPLOYMENT SOME JOBS WILL GO AWAY ARE YOU ON LARRY PAGE THEY ARE THEORY OF THINGS ORELONLON WHERE THIS COULD BE DESTRUCTIVE CAN YOU EXECUTE ARTIFICIAL INTELLIGENCE IN AN ETHICAL WAY NOT TO HARM TOO MANY PEOPLE.>>ABSOLUTELY IN ETHICAL WAY WHOLE INDUSTRY IS FOCUSED ON THAT I AM CONVINCED THERE IS HE GOING TO BE A HUGE JOB SHORTAGE BY THAT I MEAN, NOT ENOUGH PEOPLE TO FILL THE JOBS THAT ARE OPEN BECAUSE OF THIS. AND THE REASON IS, THAT THE A.I. SYSTEMS WILL MAKE THINGS SO MUCH MORE EFFICIENT SUCH ECONOMIC GROWTH WE LITERALLY ARE GOING TO NEED MORE PEOPLE MORE EDUCATION, TO FILL THESE JOBS, THERE IS NO QUESTION THAT DESTRUCTIVE THAT DISTRUCTIVE THAT DISRUUCTIVE THAT DISRUPTTIVE THAT DISRUPTIVVE THAT DISRUPTIVE.>>SOMEBODY SAID WHEN WE LEARNED NUCLEAR TECHNOLOGY WE DID NOT GIVE NEVER BEEN NUKE NUCLEAR BOMBS THIS IS NOT NUCLEAR THIS IS CAPABLE OF MAKING EVERYTHING WE DO MORE EFFICIENT, CLEARER, BETTER GRIMZ MORE PRODUCTIVE IN THE SAME WAY THE PERSONAL CPR DID THIS IS TAKEN OVER OUR WE’LL INDUSTRY IN TERMS OF MACHINE LEARNING, BETTER BUSINESS ALGORITHMS IF YOU ARE RUNNING A BUSINESS NOT USING A.I. MACHINE LEARNING YOU ARE COMPETITOR CAN BEAT YOU –>>I AGREE WITH THAT THAT IS WHERE WE ARE SEEING IT IN EVERY SINGLE INDUSTRY FASCINATING ABOUT DATA RIGHT DATA, INSERTED INTO THE COMPUTER MAKING THE COMPUTER SMARTER.>>TODAY, THE SYSTEMS ARE COMPLETELY DEPENDENT UPON LARGE SOURCES OF DATA SO COMPANIES THAT HAVE MOST DATA WHETHER IN MAPS BUSINESS OR WHAT HAVE YOU TYPICALLY ARE WINNING. IN THE FUTURE WE THINK ACTUALLY POSSIBLE FOR KRRZ TO GENERATE THEIR OWN TRAINING DATA SO THERE IS A HUGE NEW FIELD COMING OUT, WILL MAKE THAT EVEN MORE EFFICIENTLY.>>BILL CAMPBELL WOULD SAY?>>THAT’S TERRIFIC AS YOU CHEER] CLAPPING].>>THANK YOU FOR WONDERFUL

Oracle CEO: AI is integrated into our autonomous database


SLOWING IN THE U.S. AND WE ARE RIGHT ON THE DOORSTEP OF EARNINGS. I SPOKE WITH ORACLE’S CEO, MARK HURD EARLIER, I SAT DOWN WITH HIM YESTERDAY TO DISCUSS THE U.S. AND EUROPEAN ECONOMIES, WHY ORACLE IS BUYING BACK SO MUCH STOCK AND WHERE HE SEES GROWTH NOW BECAUSE WE ARE ON THE DOORSTEP OF EARNINGS. I’M WANTED TO GET A SENSE FROM HIM ABOUT THE INTERNATIONAL SLOWDOWN THAT WE’RE TALKING ABOUT. BUT WE BEGAN WITH NET SUITE, ORACLE’S INVESTMENT IN THE APPLICATIONS MARKET AS WELL. TELL US WHAT YOU’RE GETTING FROM YOUR CUSTOMERS THIS WEEK THERE IN LAS VEGAS AND ABOUT NET SUITE.>>SURE. THANKS, MARIA. YOU’RE RIGHT, WE’VE INVESTED A LOT IN THE APPLICATIONS MARKET. WE’VE INVESTED IN BIG AND SMALL SEGMENTS OF THE MARKET, BIG CUSTOMERS AND SMALL CUSTOMERS. WE ACQUIRED NET SUITE, GOSH, I DON’T KNOW, PROBABLY TWO AND-A-HALF YEARS AGO NOW AND IT’S REALLY BEEN AN AMAZING SUCCESS, TO YOUR POINT. THERE’S, I DON’T KNOW, LESS THAN 10,000 BUT ROUGHLY THAT NUMBER OF CUSTOMERS HERE FOR OUR EVENT. IT IS VERY EXCITING. WHEN WE BOUGHT NET SUITE, MARIA, THE COMPANY WAS GROWING ABOUT 15, 16% IN REVENUE. WE’VE INVESTED A LOT IN R&D. WE’VE INVESTED A LOT IN TAILORS THE TAE TAILORING THE APPLICATION FOR MORE INDUSTRIES. WE’VE ADDED SALESPEOPLE AND IT’S RESULTED IN JUST INCREDIBLE GROWTH. STARTING REALLY ABOUT A YEAR AGO. SO ABOUT A YEAR INTO THE ACQUISITION WE BEGAN TO REALLY GROW OUR BOOKINGS AND THAT’S TRANSLATED TO REVENUE. SO LAST QUARTER WE REPORTED REVENUE THAT WAS ALMOST DOUBLE THE REVENUE GROWTH WE HAD COMING INTO THE ACQUISITION. MARIA: YOU’RE SEEING IT IN THE NUMBERS. THE APPLICATIONS BUSINESS IS SOARING RIGHT NOW AT ORACLE, AS YOUR CUSTOMERS MOVE FROM ON-PREMISE TO CLOUD. TAKE US BEHIND THE CURTAIN THERE. WHAT KIND OF COMPANIES ARE MOVING FROM ON-PREMISE TO CLOUD? HOW DO YOU CONTINUE GETTING THEM TO SWITCH OVER INTO THE ORACLE CLOUD? AND HOW SIGNIFICANT IS THIS IN TERMS OF THE APPLICATIONS BUSINESS AT ORACLE?>>THERE’S A COUPLE HE’LL THINGS>>THERE’S A COUPLE HE’LL THINGG>>THERE’S A COUPLE HE’LL THINGI>>THERE’S A COUPLE HE’LL THINGG ON. THE A APPLICATIONS MARKET IS $25 BILLION, SPENT PRIMARILY ON APPLICATIONS. MOST OF IT TODAY IS SPENT ON ON ON-PREMISE APPLICATIONS. THE MARKET CHANGES SIGNIFICANTLY AS IT MOVES TO CLOUD. AS IT MOVES TO CLOUD, THE SUBSCRIPTION YOU PAY FOR THE CLOUD INCLUDES NOT ONLY THE APPLICATION BUT INCLUDES ALL THE HARDWARE, IF YOU WILL, THE SERVERS, THE STORAGE AND SO IT BECOMES A BIGGER MARKET JUST BY THE VERY NATURE OF THE MIGRATION OF THE APPLICATION TO SAAS. INSIDE THE INSIDE THAT, $75 BILLION IS BACK OFFICE, THAT WOULD BE DESCRIBED AS THINGS LIKE GENERAL LEDGER ACCOUNTING, SUPPLY CHAIN AND PROCUREMENT AND H.R. AND THE OTHER 2 A 5 OTHER 25A 5 OTHER 25 T5 OTHER 25 TO 30% IS FRONT OFFICE, SALES AND MARKETING AUTOMATION. NET SUITE IS IN THE MID-MARKET, SMALLER CUSTOMER SIZE OF THE BACK OFFICE MARKET AND IT’S HAD EXPLOSIVE GROWTH. WHEN YOU ASK WHO IS MOVING, IT’S EVERYBODY FROM THE BIGGEST GUYS, WHETHER THOSE BE AS BIG AS AN AT&T, ON AN EXTREME, I COULD GO THROUGH MANY OTHERS, TO YOUR SMALLEST STARTUP. MARIA: ARE YOU TRYING TO GET THIS APPLICATIONS OF COMPANIES TO MOVE JUST TO THE ORACLE CLOUD OR ARE YOU TRYING TO GET ALL APPLICATIONS TO MOVE TO THE CLOUD OR ARE YOU JUST LOOKING AT THE ORACLE PORTIONS OF THE BUSINESS? HOW DO YOU GROW THIS EVEN MORE IS REALLY THE BOTTOM LINE?>>SO IF YOU LOOK TODAY, HALF OF THE CLOUD APPLICATION CUSTOMERS WE HAVE WERE ROUGHLY OR HALF OF OUR REVENUE, THAT’S A BETTER WAY

Practical A.I. applications for business | Deep-dive with Richard Boyd (Part 3)


– Welcome to UpTech Report series on AI. I’m Alexander Ferguson. This video is part of
our deep-dive interviews, where we share the wealth of knowledge given by one of our panel of experts. In this episode, we continue our conversation
with Richard Boyd, founder of Tanjo in Carrboro. Richard is a successful
entrepreneur, author and speaker, so we wanted to know how has his thinking on technology and AI evolved. How does he use it in his own business? And how could other business
leaders use it in theirs? – Early on, our team is
working in computer gaming. It started when I met David
Smith here in North Carolina. When I met him, he was beginning, he had just done a game called The Colony, which was the first
real-time 3D adventure game that attracted a lot of attention from people like Tom Clancy and guys like James Cameron, who at the time was working
on a movie called The Abyss down in South Carolina. So just this idea of taking technology and applying it to
problems to solve them like what we saw, we helped James Cameron solve
some visualization problems around the movie The Abyss, early on, and that was a fascinating process. But I guess today, so I guess it was a
natural evolution, right? Like applying technologies to problems and we ended up getting really interested in Artificial Intelligence as a way to build deeper meaning
into the virtual worlds we were building and like I said, with
computer environments, building more convincing
characters that you can believe in more convincing environments, and it sort of just evolved from there. I mentioned 2009 as the
time when we got religion, so to speak, on machine learning. And that’s when David and I went out to Microsoft Research Labs where Alex Kitman was working on the Microsoft Kinect. If you remember that, it was
called Natal at the time. They were just trying to teach, so they were kind of this, I understand that they
don’t sell it anymore, but there was a piece of hardware you could attach to your Microsoft Xbox that would watch you in your living room, and you could use your
body as the controller. That was the central idea. But in order for that to work well, the sensors had to be amazing. So they called Lockheed Martin, and Lockheed bought my last company, so David and I were there, we went out to Microsoft Research Labs, and it would happen to be during the Game Developers’ Conference, we were out there anyway. Walked in and saw Alex and there’s a guy named Jaron Lanier there who
I’ve known for a long time. He’s a guy who came up with
the term virtual reality. He’s this kind of dreadlock guy. You see some pictures of me online with, and initially we were looking at how can we help you with the sensors, should it time of flight, should it be structured light, whatever. But we found out pretty
quickly they had that nailed. And what they’d built was like the optimal solution to that problem in the form factor that
they had to fit it in. But the other thing
that they showed us was, oh yeah we’re trying to teach this system what a living room is. And that is a difficult
computational problem. And so, again, there were two approaches. The approach at that
time still coulda been, let me just program in and tell them what a chair is, what a table is, what a plant is, a whatever. Or the other way, which they thankfully used, was machine learning. Which is, let me just have
examples of living rooms from all over the world, Asian, European, South American, U.S., rural versus urban, whatever. Everything you might encounter in that, and give them all the, give the system all those examples. Millions of millions of examples. And whatever they did
had to fit within about less than 100 megabytes of space. The whole brain for the system. And they were able to achieve that. So that just blew us away, and that changed our thinking completely. – [Alexander] How did that revelation change the course and
direction of your business? – Secretary of Education at the time, Arne Duncan, and his Deputy, Jim Shelton came to Lockheed and said, hey, we in the government have
lots and lots of information at the Smithsonian and all over the place, in the Library of Congress. How do we make it available to teachers in an easy way? Like we’re trying to scan
and digitize this stuff in, but how do I make it
discoverable by tagging it? Right now we’ve got armies
of human beings in there trying to put tags on stuff. And I usually use a picture
of that last scene in the Raiders of the Lost Ark, where you’ve got a clerk with this crate, and it says Ark Thingy on it, and it’s the Ark of the Covenant, that can destroy or save the planet, you know and it’s inside this box. He’s putting in this massive warehouse with a tag that says Ark. It’s like, that’s undiscoverable. It’s a potent thing that’s
valuable, but undiscoverable. And most of the information we have, is what we call dark data. Right, it’s whirled away somewhere, inaccessible and undiscoverable because it’s not digitized or not tagged. Even if it’s digitized, it’s not tagged. Well, what’s amazing with, what we did for the, what’s
called the learning registry for the Department of Education, was built a system that can
go and look at that stuff, you could read the
Declaration of Independence, or the Magna Carta or any other document, or look at images of things, and if it had something similar to it in it’s massive
multi-dimensional lookup table, it would go ahead and tag it, right? And if it didn’t recognize the thing, then it would say I need a human expert, and it would call for help, right? Phone a friend. In this case, it’s a human, to come in and say, oh that’s actually an ancient Cluniac drinking
vessel from 100 B.C., and go ahead and tag it. But of course, once it’s been tagged once, the great thing about
machines is they never forget. – [Alexander] How can
businesses and organization implement practical A.I. applications? – So whether you’re practicing law, or you’re practicing
architecture or whatever, what you want now is a
machine learning brain like I’ve just described, that goes through
everything that you have. All the assets that you have, and reads everything. Every document created, every, ideally, to be honest, every email written by all of your people, and it understands like
what do people know? What is our organizational knowledge? And it maps it all, and by the way locates
where everything is. Which is something that’s
incredibly important for digital transformation. And then once it’s mapped, now you can track things like how does new information
enter organization? Who’s championing it?
Who’s challenging it? How do decisions get made? Why did we choose this
vendor over that vendor? And why did we choose this
strategy over that strategy? And we’d be able to tell you forensically, what decisions are made and why, and maybe help you make better
decisions in the future. What made Red Hat really successful, here again here in the triangle, was this idea that
implementing Unix based servers within your organization
is a complex activity. It’s also very intimate activity, because it’s where all your
people are connecting, right? So do you wanna just outsource
that to someone else, or do you wanna buy turnkey
on premise tested solution that works extremely well that you can shepherd
and manage going forward? And that was that decision that led to how much should they just get bought for 34 billion or whatever it was, right? From free software. So I think that same
principle applies here. Is that again whether you’re
a government organization or you’re a company, you’re
an architecture firm whatever, get your own machine learning
system inside your firewall under your control, and make sure you know where your data is and where it’s going. If you wanna get people fluent and comfortable with this idea that hey I want this asset here, I want this machine learning companion that’s gonna help me do my job better, but also it becomes an
enduring sort of map of how decisions and how work is
done within the organization, so we’re doing that for all of North Carolina Community
Colleges in North Carolina, so there’s 58 of them, right? And when this is fully implemented, one of the things that I, ’cause I’m on the board of
trustees of White Tech, right? So I understand how turnover happens, and the sort of complexity of
some of these organizations. At White Tech we have like
70,000 students a year. It’s a 250 million dollar enterprise, that’s underway that does a
lot of good in the community. But we just, our president just, like presidents do, they retire. So now we gotta put a new person in place. And there’s lots of other
turnover that happens at a various levels
throughout the organization. What if when that new person steps in, they could see right away, like they have a little companion A.I., that assistant we talked about earlier, that says, well it looks
like you’re approaching your first board meeting. Well the last person,
here’s when they approached this kind of problem, here’s the resources they went to, here’s the people they went to, and here’s how they did that job. It’s also really good for
the organization to have that have a map of that intelligence
within the organization when people leave your company, and you’ve invested a lot
of money in those people. And time, you’d like to
have some model of that that stays behind after they leave. – [Alexander] What kinds of success have you found with using A.I.? – Our entire solution set is around something you can implement
in less than six months that will have a 10X return on investment. And that’s our kind of guiding algorithm for everything that we do. So that means that we’re looking
at the low hanging fruit, things like accounting, so we work with a local accounting firm, found out that there’s
some new rules around revenue recognition and lease recognition that were coming out. We looked at that and said that’s perfect. Because all I need to do is get a bunch of sales contracts, feed it to a system and don’t let it see what Kanye West or anybody else is doing, nothing else on the internet. Just focus on this very
tightly bound realm of what kind of language will you encounter in a sales agreement? Whether you’re selling
software, hardware, services, consumer goods, whatever it happens to be. And become familiar with all
of the terms and everything, and not just like 10,000. Not 100,000, but millions of contracts. Let it read all that, create its own sort of
inferred understanding of how to process that, and then just do the
basic job of bin sorting, like yeah this is a
really standard contract. This one, these have a
few non-standard elements that a human being needs to look at. These are on fire. Like this is all non-standard. Whoever’s doing this is
probably trying to cheat you, and this needs a lot of human attention, or you probably should not
do business with that person. Whatever the rules are, right? And so applying it to things
that are easy to digest, and get that 10X return
in a short amount of time, that’s where we find our success. – This was just a taste. Stay tuned as we share the
full deep-dive interviews we had with each one of
our panel of experts, and our upcoming episodes, focused on specific topics that will transform the way you think about Artificial Intelligence. All this on UpTech
Report’s new series on A.I. (soft instrumental music)

How Motorsport Is Advancing The Autonomous Industry | Roborace



everything that moves will be autonomous from cars to trucks tour buses deliveries and motorsport is now the pioneer in this regard being able to take this technology put it into action and do it at the extreme level we can accomplish what we need to at high speed that we can definitely bring it our roads and make our roads much safer and more efficiently my grandfather built this famous circuit I was the Battle of Britain airfield I was just asked what he would think of these cars being here I think you think this was absolutely fabulous and exactly what we should be doing he was always looking forward that for me the most emotional of course are the real car seeing so later on I'm really looking forward to see them on the track going up the hill this Center is very much about the future we are very interested in these kind of topics when it's down to how the life and the world will change and what technology you need in order to improve people lives improve how where the planet is having to it's the first time that I've seen the cars on track it's quite amazing to sort of see the future of motorsport here at a very traditional venue great legacy so about the history of motorsport often here at Goodwood but it's either the future of motorsport and how radical that future's going to be it's quite incredible animated inserting the interested in future events I hope they would be like their sons beautiful sunshine lots of technology to play with and explore and I guess something aspirations let us look forward to the future