Rick Rutter, Director, The Feed, Juniper Networks

Get AI on Par with Your Network Domain Experts

Networking for ChangeLeadership Voices AI & ML
Rick Rutter Headshot
Get AI on Par with Your Network Domain Experts

Here’s why you need AI on your IT team.

How can your IT team deal with the ever-increasing complexity and growth of networks? The answer: AI. Watch as Juniper’s Bob Friday and Sudheer Matta discuss how AI is changing the way we work and live by performing tasks on par with network domain experts.

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You’ll learn

  • Some of the challenges IT teams are facing today (more everything!) and how AIOps can help

  • How a virtual assistant can help you manage network complexities and benefit your business

  • The differences between AI and machine learning (ML) and how businesses can use  them

Who is this for?

Network Professionals Business Leaders


Rick Rutter Headshot
Rick Rutter
Director, The Feed, Juniper Networks 

Guest speakers

Bob Friday Headshot
Bob Friday
GVP, Chief AI Officer, Juniper Networks 
Sudheer Matta Headshot
Sudheer Matta
GVP, AI-Driven Enterprise, Juniper Networks 


0:01 [Music]

0:07 artificial intelligence is improving

0:09 user experiences across the spectrum

0:11 from it teams to consumers the ability

0:13 of our networks to access large amounts

0:15 of data quickly analyze it and make

0:18 decisions is changing the way we work

0:20 and live i'm rick rutter from juniper

0:23 i've assembled a couple of my colleagues

0:25 to help me in a discussion around ai and

0:28 how it's improving our world in

0:30 delivering positive change gentlemen

0:32 thanks for coming if you could quickly

0:34 introduce yourselves yeah rick bob

0:35 friday cto of juniper's enterprise

0:37 business

0:39 and thank you rick uh sudhir mata uh vp

0:41 of products here at the juniper's ai

0:43 driven enterprise

0:44 right on well to kick things off what

0:46 are some of the challenges that

0:47 companies are facing today and how do

0:49 you think ai ops can help

0:51 one of the things that's happening in

0:53 customers around the world big and small

0:56 is more users more devices more

0:59 applications more bandwidth every single

1:02 day right but the scale of the it team

1:05 isn't growing at the size of the

1:06 exponential growth we're seeing in these

1:08 other vectors so how does the same says

1:12 i.t team deal with more and more and

1:14 more and more of this you can't throw

1:16 people at the problem it is time for ai

1:20 to bring that cost of operations down so

1:23 the same size it team can handle more of

1:27 the scope on the same network right

1:29 that's the power of ai makes sense yeah

1:31 and for me personally i think we talked

1:32 about you know when i was at cisco it

1:34 was clear what i heard from these

1:36 customers was hey they were tired of

1:38 controllers crashing you know they were

1:40 tired waiting for a year to actually get

1:42 new code and they really wanted to know

1:44 visibility it wasn't good enough to know

1:46 whether or not the ap was up and running

1:47 they wanted to know if the user was

1:48 having a great experience and so that

1:50 was really for me what i saw the need

1:52 for mist and relate this cloud ai

1:54 architecture

1:56 that makes sense i mean like so let's

1:57 dive into the virtual assistant because

1:59 i think that's amazing like why

2:02 help help me understand a little bit

2:04 like why a virtual assistant and how it

2:06 can really help my business

2:08 you want to start yeah so so

2:11 one of the things that we talked about

2:13 at the very beginning right why do we

2:14 need ai there's more more users more

2:16 data more applications more trouble

2:18 tickets every day

2:20 the

2:21 simplest reason for a virtual assistant

2:24 is we want problem solving to be pushed

2:27 down to the lowest tier level tier one

2:29 when a call comes into university and on

2:32 the other side is a zoology major taking

2:33 a trouble ticket in the help desk they

2:36 could just ask marvis hey what's wrong

2:38 with this user's experience right and

2:40 marvis comes back with a curated answer

2:42 with a factual actual answer right and

2:44 so pushing the the amount of the

2:48 knowledge graph needed to solve these

2:50 problems we went from ccies and jncies

2:54 to level one to be able to solve that

2:56 problem that's one of the reasons we

2:57 went down this marvelous path yeah i

2:59 mean i think the fundamentally the other

3:00 thing is you look at the poor i.t teams

3:02 in the future these networks are getting

3:04 much more complex than 20 years ago 20

3:07 years ago everything lived inside their

3:09 little data center and their firewalls

3:10 nowadays we have everything distributed

3:12 to the cloud you know zoom microsoft all

3:15 this stuff is outside of their control

3:17 you know so we're moving to a much more

3:19 mobile world you know if you look where

3:21 we are with mobility you know we're at

3:23 60 percent of everyone in the world is

3:25 connected to the internet through some

3:26 wireless mobile link that by itself has

3:29 another layer of complexity and they're

3:31 going everywhere on the internet and so

3:33 that's where ai ops is he is helping

3:35 these deal with complexity right and

3:38 that's what aiml is really designed to

3:39 do is help deal with complexity and deal

3:42 with these more complex networks it

3:44 makes a lot of sense and sometimes i i

3:46 feel like people get confused the

3:47 difference between like ai and ml and

3:50 some of these you know other topics like

3:52 can you help me understand the

3:54 difference between ai and ml and and how

3:56 businesses can use those you know so you

3:58 know this is a great question what i

4:00 tell people right we have been working

4:02 on automation ever since networking

4:04 started ai is this ultimate taking

4:07 automation to the ultimate level right

4:09 ultimately ai is a concept of building

4:11 something on par with a human you know

4:14 when i started in this i was really

4:16 inspired by jeopardy right when i saw

4:18 watson playing jeopardy i was like if

4:20 they can build something that can play

4:21 jeopardy

4:22 we should be able to build something

4:24 that can answer questions on par with

4:25 network domain experts right and so that

4:28 is ai and most people confuse ai with ml

4:31 aim is doing something on par of the

4:33 human and it takes a lot of different

4:35 algorithms ml is actually math and

4:38 algorithms that actually helps us get

4:39 that implemented now that's important

4:41 because

4:42 of late in 2014 is when ml really took

4:45 off that's when we saw

4:47 google and

4:49 all these neural network stuff we got to

4:51 enough computing power and data to

4:53 actually train these models so there was

4:55 an inflection point in 2014 that really

4:57 saw the birth of ai and ml across all

4:59 types of industries

5:01 that's amazing right on this is very

5:03 cool by the way bob's phd is in this

5:05 field so i didn't know that

5:07 but it makes sense yeah that's awesome

5:10 one other thing that seems to be coming

5:11 up more and more is like sustainability

5:13 and i think we were talking a little bit

5:15 like how can we help like a lot of our

5:17 customers like hit their sustainability

5:19 goals i mean climate is something that's

5:21 on everybody's mind can something like

5:23 this help

5:24 with that actually it can and let me

5:26 step back and say we as juniper we have

5:28 pledged that we are going to we're going

5:30 we're going green and we're where we'll

5:32 be at 100 carbon carbon neutral by 2025

5:36 it's is as a company great goal for us

5:39 but let's talk about the impact of ai on

5:41 sustainability not too many in it think

5:44 of it this way

5:45 so if i can eliminate a truck roll to a

5:48 site by virtue of having ai to solve a

5:51 problem either i've self-remediated it

5:54 or we've we've created the

5:56 the data needed in the cloud so that

5:58 somebody doesn't have to go

5:59 and real example the gap eliminated 85

6:03 percent of the truck rolls going to gap

6:05 retail stores around the world 85 truck

6:08 rolls are down

6:10 that's sustainability ai can have a very

6:13 real impact in terms of operations and

6:15 efficiencies we drive including

6:18 the green initiative that's amazing

6:20 really really cool um so let me look i

6:23 think we've gone through a lot of these

6:24 but i mean one of the things uh

6:27 that that i keep like struggling with is

6:29 i i hear that like people are still

6:32 skeptical of ai like why is that

6:36 so so so let me tell you i would say you

6:38 know the hardest thing for for people to

6:41 walk away from is if i'm a cli uh you

6:45 know expert on on cisco if i've mastered

6:48 and carefully hand chiseled a network of

6:51 aruba it's hard for me to walk away from

6:53 that and that's that's the challenge and

6:55 so there's a lot of skepticism in ai in

6:57 terms of mostly

6:59 knowing what they know and the

7:00 incumbency and the legacy architectures

7:03 but

7:03 if you're going to prove a concept with

7:05 us if you see a proof of value there is

7:08 no more skepticism once you try it once

7:11 there is no ai skeptics on the juniper

7:13 missed customer side yeah i mean i think

7:16 you know if you look at people it's like

7:17 you know you're driving your tesla

7:19 right i don't think most people are

7:21 ready to take their hands off the wheel

7:23 yet you know so gaining that trust

7:25 inside your virtual ai system is

7:27 combination trying to understand what's

7:29 going on and that's probably one issue

7:31 with aiml right because the math is a

7:32 little bit more complicated than most

7:34 networking it guys used to right they're

7:36 used to automating things with scripts

7:37 or something they can logically

7:38 understand this is a model where you're

7:40 basically training it so there is a

7:42 level of trust you have to learn to

7:43 trust it and that's where we worked at

7:45 marvis is around this conversational

7:47 interface right you know how do you make

7:49 a virtual assistant really a part of

7:50 your team you know so that is a key part

7:53 that you know we are working on right

7:54 now is making it easy for people to

7:56 interact with marvis and actually get

7:59 them to see that you know

8:00 when you actually start using it you

8:02 know it's poc right when you get this

8:03 thing up and running you know when

8:05 marvis says there's a bad cable

8:07 well it's like well let me see you know

8:09 i don't know if i trust you the first 10

8:11 times but after the 10th time okay i'll

8:13 trust you so now customers are starting

8:15 to actually let marvis issue those

8:17 support tickets right okay i trust you

8:19 that you found a bad cable i'm not going

8:21 to ask you anymore this saves an

8:23 incredible amount of time resources

8:25 money yeah i'll give you the biggest

8:28 skeptic that uh that i've actually

8:30 worked with uh most recently is someone

8:33 is a about a 4000 ap higher education

8:36 university a top 10 university in the in

8:38 the country and the it manager there a

8:40 long time friend and he said hey

8:44 i built this network sort of hand

8:46 chiseled the entire network for high

8:48 performance

8:49 i don't believe that

8:52 marvis can actually really just out of

8:55 the box work in a high density

8:57 environment like

8:58 300 people a person auditorium

9:01 previously

9:02 people didn't trust ai for that they

9:04 used to manually channel plan and hand

9:06 plan this but now with marvis we see

9:09 data better than humans can see it's

9:11 really that simple

9:13 for the first time he said sudhir

9:15 i called on your powerpoint

9:17 right but i went into the proof of

9:19 concept i let the system figure it out

9:22 and it came up with a better answer than

9:23 i could on that network and i would say

9:25 i think you find you know people are not

9:27 so much skeptic about ai i think

9:29 everyone realizes that ai you know we

9:31 are going to see a self-driving car in

9:33 our lifetime right you know we are

9:35 seeing doctors being able to diagnose

9:36 cancer better with ai so i don't think

9:39 anyone is skeptical about ai working i

9:41 think it's more skeptical when

9:43 you know when are you going to be in the

9:44 back seat of your tesla pressing it to

9:47 drive well there was a guy the other day

9:49 you told me that's what i told you there

9:50 was a guy you know and the scary thing

9:52 it is happening right there was a guy in

9:54 oakland who got arrested for being in

9:56 the backseat of his tesla so it's not

9:58 like as possible it's like when is it

9:59 going to become mainstream and if he can

10:02 do that we can definitely put on the

10:03 network and help businesses improve

10:05 their lives if someone can ride in the

10:06 back of their tesla across the bay

10:08 bridge and someone in jeopardy watson

10:09 can play jeopardy yes we can build

10:11 something that can answer questions i'm

10:12 part of network domain expert the good

10:14 news rick though is we've actually

10:16 proven it now right every single network

10:19 we're going into has fewer tickets

10:22 faster deployments fast resolution it's

10:24 happening now you don't have to wait

10:26 with some of our like with some of our

10:28 competitors who are saying oh yeah i'm

10:30 building this it's coming please wait no

10:34 go into a poc with them right now and

10:36 see the difference

10:38 well listen sadeer thank you so much bob

10:40 thank you as well uh if anybody is still

10:43 skeptical about a i challenge you let's

10:45 give these gentlemen a call get that poc

10:48 working

10:49 thank you all very much and see you soon

10:52 [Music]

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