Data Driven

In this episode Frank and Andy speak with Alex Murrey, the Head of North American Operations for TangoTeams, a startup that’s redefining the software development outsourcing industry. 

The software development industry is evolving rapidly and is increasingly becoming data driven, which is why I know you will want to hear what he has to say.

In this episode, Frank and Andy speak to Christopher P. Willis about Using AI to Create a Better User Experience with Better Content.

Certainly, if you have ever you read instructions or product documentation that left you annoyed and confused, then you can appreciate the work he does with Acrolinx.

Audible is a sponsor! Click this link and score a free audio book on us! If you subscribe, you help out the podcast. Everyone wins!

00:00:00 BAILey 

Hello and welcome to data driven. 

00:00:02 BAILey 

In this episode Frank and Andy speak with Christopher Willis about how artificial intelligence can help bake brands create congruent content across cultures, languages and writers. 

00:00:13 BAILey 

One quick word of correction. 

00:00:15 BAILey 

Frank made the assumption that CPO was chief product Officer. 

00:00:19 BAILey 

Chris is actually Chief pipeline officer. 

00:00:21 BAILey 

In addition to being chief marketing Officer, Acrolinx currently does not have a chief product officer. 

00:00:28 BAILey 

Frank should know by now what happens when you assume anything. 

00:00:32 BAILey 

I'll have a chat with him later. 

00:00:34 BAILey 

For now, enjoy the show. 

00:00:44 Frank 

Hello and welcome to data driven, the podcast where we explore the emerging fields of data science, machine learning and artificial intelligence. 

00:00:52 Frank 

If you'd like to think of data as the new oil, then you can think of us like Car Talk because we focus on where the rubber meets the virtual road and with me on this epic road trip down the information. 

00:01:04 Frank 

Superhighway as always is Andy Leonard. 

00:01:07 Frank 

How's it going Andy? 

00:01:08 Andy 

Good Frank, how are you doing? 

00:01:10 Frank 

I'm doing great, I'm doing great. 

00:01:11 Frank 

It's a beautiful Tuesday morning here in the DC area. 

00:01:14 Frank 

We're recording this on September 28th and I can't believe it's already October. 

00:01:22 Andy 

Almost gosh, yeah, yeah. 

00:01:23 Frank 

Almost October. 

00:01:25 Andy 

It's it's been beautiful fall weather. 

00:01:28 Andy 

Past few days here in sunny Farmville, VA. 

00:01:33 Andy 

And I'm really enjoying that. 

00:01:35 Andy 

Got a lot of outdoors work done in the past few days and that's always a good thing. 

00:01:40 Frank 

Yeah, we just built the trampoline for the kids and that was a was a lot of fun. 

00:01:46 Frank 

'cause the. 

00:01:46 Frank 

Instructions were horrible. 

00:01:50 Andy 

Did you get one with that big net around it? 

00:01:53 Andy 

Keep from bouncing off and 'cause otherwise it should come with a coupon for a free cast. 

00:01:58 Frank 

Freecast and free healthcare that'd be funny. 

00:02:00 Andy 

Yes, yes, that's right, yeah. 

00:02:03 Frank 

Yeah, so without further ado I'd like to introduce we have this. 

00:02:07 Frank 

Awesome guest today. 

00:02:08 Frank 

We've been really lucking out on terms of folks coming to us and and suggesting guests for us, which is quite refreshing, actually. 

00:02:17 Frank 

So so today we have with us Christopher Willis, Acrolinx Chief Marketing Officer and Chief Product Officer. 

00:02:25 Frank 

Christopher is an expert in technology, marketing and brand alignment alignment with over 20 years of experience in with some of the world biggest tech names including Perfecto. 

00:02:35 Frank 

Kmag and Cambridge technology group. 

00:02:39 Frank 

And through his work at Acrolinx, he's become a renowned thought leader on the topics of content governance and brand alignment. 

00:02:46 Frank 

He's also an expert on AI and how AI can help. 

00:02:50 Frank 

Big brands can great create congruent content across cultures, language and writers. 

00:02:56 Frank 

Acrolinx creates tools for developing content that feels human, relatable, and compassionate. 

00:03:01 Frank 

It's already used by some of the biggest brands in the technology world today, so welcome to the show, Chris. 

00:03:09 Christopher 

Thank you, I'm excited about your trampoline. 

00:03:12 Frank 

Well, thank you. 

00:03:12 Frank 

Thank you. 

00:03:13 Frank 

You should come on down I. 

00:03:14 Frank 

I think you're on the East Coast somewhere in Boston. 

00:03:17 Christopher 

I am outside of Boston, yes? 

00:03:18 Frank 

Awesome cool cool you never know 'cause sometimes people will put where they used to live on LinkedIn and not update that so. 

00:03:26 Christopher 

Nope, haven't gone anywhere in what a year? 

00:03:27 Christopher 

And a. 

00:03:27 Christopher 

Half if not. 

00:03:28 Frank 

Right, right? 

00:03:29 Christopher 

A lot, not a lot of travel, yeah? 

00:03:30 Frank 

Year and a half in the two week lockdown. 

00:03:35 Frank 

Well, welcome to the show so so. 

00:03:38 Frank 

Tell me about what so, so you're a CMO and a CPO. 

00:03:43 Frank 

That's that's, uh. 

00:03:45 Frank 

That's an interesting mix I I can see how the two are related, but can you explain kind of like what it is you do for acrolinx and maybe a little bit about. 

00:03:54 Christopher 

So I do a bunch of things. 

00:03:55 Christopher 

I I I joined the company to run marketing and marketing has. 

00:04:00 Christopher 

A lot of. 

00:04:00 Christopher 

Reach in this organization because of what we do and who we sell to. 

00:04:05 Christopher 

So I reach into pipeline. 

00:04:07 Christopher 

I reach into the product process on product marketing in there and come from a background where this approach really resonates and makes a lot of sense and the way that we collect and build and use data is very aligned to the way that I've. 

00:04:24 Christopher 

I've built content in the past. 

00:04:28 Frank 

Interesting, interesting. 

00:04:29 Frank 

So the the product at acrolinx it it. 

00:04:33 Frank 

It uses AI to create content. 

00:04:36 Frank 

So, so like what does that do is? 

00:04:38 Christopher 

Different so we are. 

00:04:38 Frank 

It kind of NLP. 

00:04:40 Christopher 

We're improving content, so we're we're about being improving the quality and effectiveness of enterprise. 

00:04:47 Christopher 

Content so the easiest way to think about what we do is everybody that writes everybody that owns a content organization, whether that's in a development group with technical documentation or product manuals, or marketing content enablement content, internal education. 

00:05:04 Christopher 

All these folks have a whiteboard in their office and. 

00:05:07 Christopher 

On that whiteboard are all the components of language, the way that they want to create their content. 

00:05:12 Christopher 

It's the tone of voice. 

00:05:13 Christopher 

It's the clarity level education level of their of their readers. 

00:05:17 Christopher 

It's the amount of compassion, emotion, inclusiveness that they want in their contents. 

00:05:22 Christopher 

The words that they want to use and that they don't want. 

00:05:24 Christopher 

Use, it's all up there on the whiteboard. 

00:05:26 Christopher 

They feel good about it. 

00:05:28 Christopher 

They've defined essentially the voice of their group or their organization. 

00:05:32 Christopher 

The problem with that whiteboard is that it's in their office and nobody can see it, and even if they could, we don't have a writers pool in the world anymore. 

00:05:40 Christopher 

We're all writers when you go to work, a byproduct of your work is. 

00:05:45 Christopher 

Content, and so. 

00:05:46 Christopher 

As a marketer I get my best content from folks that don't touch marketing. 

00:05:51 Christopher 

They're just smart people that can create so they don't. 

00:05:55 Christopher 

They don't care about what's on my whiteboard at all, and. 

00:06:00 Christopher 

When we were, I mean, the last seven or eight years you talked about. 

00:06:03 Christopher 

The potential for the digital shift, and I think everybody been using that as a marketing buzzword like digital shift is coming. 

00:06:10 Christopher 

You got to get ready and I don't know if anybody ever really thought it was coming, but it was a great way to so some fear into our prospects that if you don't modernize, the world is going to change. 

00:06:20 Christopher 

Holy crap March hit last year and the digital shift arrives and now you're only touchpoint with your consumer is through digital content for some period of time and it became really apparent to folks that how you commute. 

00:06:36 Christopher 

Gay matters and then all the things that happened last year from from a social standpoint. 

00:06:43 Christopher 

Language took on a very lead role. 

00:06:46 Christopher 

And how do you as an enterprise ensure that you're communicating in the voice of your audience? 

00:06:53 Christopher 

And that's where Acrolinx comes in. 

00:06:54 Christopher 

We look at terminology. 

00:06:56 Christopher 

We look at. 

00:06:56 Christopher 

It's style guidelines voice guidelines to be able to create this essentially central lexecon of how to communicate his business and then. 

00:07:07 Christopher 

Either your writers in real time use acrolinx in their sidebar and what in whatever authoring tool they're using, whether they're using something like madcap flare or Adobe products or Google Docs or Microsoft or anything in a browser. 

00:07:21 Christopher 

Uhm, you're able to use acrolinx in real time to check there your content. 

00:07:25 Christopher 

Acrolinx checks for all the components that. 

00:07:28 Christopher 

It's learned from your organization to create great content and provide you with the score. 

00:07:32 Christopher 

You can improve over time or through automation. 

00:07:35 Christopher 

So think in terms of continuous process, continuous delivery of content. 

00:07:42 Christopher 

I'm checking content in it's being scored delivered back to me. 

00:07:45 Christopher 

I'm making changes and it's rolling out at the speed of my. 

00:07:48 Christopher 

Development process. 

00:07:50 Christopher 

So at the base of what we're doing, when you think about where we're at, it's it's really about taking content in stream of characters, extracting that content, buying the context of that, identifying. 

00:08:03 Christopher 

Uh, your tokens either at the word level at the sentence. 

00:08:06 Christopher 

Level and then adding in the linguistic data underneath that around morphology and compound analysis to understand what's. 

00:08:14 Christopher 

In the content that we're we're looking at identifying terminology and and variant detection and then laying patterns on top of that, our proprietary secret sauce to be able to provide that. 

00:08:26 Christopher 

That feedback of whether or not your content is correct on character on tone on terminology, and then that feeds back. 

00:08:34 Christopher 

To users in the form of guidance. 

00:08:37 Frank 

Interesting, so it guides the people who are creating the content doesn't necessarily generate the content for them. 

00:08:45 Christopher 

We don't override and we don't right because customers. 

00:08:47 Frank 

Right? 

00:08:49 Christopher 

If you think in terms of who our customers are. 

00:08:51 Christopher 

Our our customers tend to be the largest technology companies in the world, so think top 20 global technology companies almost every single one of them uses acrolinx and. 

00:09:02 Christopher 

A piece of guidance might be useful, it might be on purpose, so as an example, when I write through my system and I write the word software. 

00:09:12 Christopher 

It says Are you sure you didn't mean platform? 

00:09:14 Christopher 

And why does it say that? 

00:09:15 Christopher 

Because in my world, if we're talking about our product, I don't want my employees to call it software, it's it's platform. 

00:09:21 Christopher 

It's an extensible platform with integration pieces and an API. 

00:09:24 Christopher 

I don't want to sell it as software. 

00:09:26 Christopher 

But I might have meant to say software. 

00:09:29 Christopher 

So I don't want to. 

00:09:30 Christopher 

I don't want to enforce that rule. 

00:09:32 Christopher 

I want to provide guidance and if you agree with that guidance, you implement that guidance. 

00:09:37 Christopher 

We have the technology to override that, but in almost every case that doesn't make sense to the customer. 

00:09:45 Andy 

So is the input for the content is it? 

00:09:46 Frank 

What is this? 

00:09:46 Frank 

What this? 

00:09:50 Andy 

Is it spoken or written or all of the above? 

00:09:55 Christopher 

All of the above, so we can take in. 

00:09:57 Christopher 

I mean, there's a number of ways to teach the platform to be your editor. 

00:10:04 Christopher 

One is to pull mass quantities of content. 

00:10:07 Christopher 

Give me all your great content. 

00:10:09 Christopher 

What does it look like? 

00:10:10 Christopher 

Identify what you think is good and we're going to read through that, and the system will read through all that content and start generating guidelines. 

00:10:15 Christopher 

Based on what you believe is great content today. 

00:10:18 Christopher 

Uhm, there's also the ability to just go in and into our interface and set guidelines so you can set a tone of voice you can identify how lively you want your content. 

00:10:29 Christopher 

Today there are challenges to all of those methods because over time you're going to learn more, and that's part of what I've really been aiming to. 

00:10:39 Christopher 

Evolve with the product is. 

00:10:42 Christopher 

Gartner, the analyst firm, has said that 50% of of marketers, people that set the company voice are. I don't think this is the word they use, but I. 

00:10:52 Christopher 

Will use guessing. 

00:10:54 Christopher 

I have a good idea of what my audience wants to hear, so I define my tone of voice. 

00:10:58 Christopher 

I define the words that I'm going to use I I think I know what people want to hear. 

00:11:02 Christopher 

And if I use acronyms. 

00:11:05 Christopher 

Go ahead and I take all that information that I've gathered, and I teach acrolinx to to help create content like that and the output of acrolinx is an Acura link score so you're aiming for 100. 

00:11:17 Christopher 

Most customers are aiming for 80. 

00:11:18 Christopher 

You want to be 80 or better. 

00:11:20 Christopher 

80 means good, 90 means done, numeric value of of good and done, so no subjectivity. 

00:11:26 Christopher 

It's just it is what it is. 

00:11:28 Christopher 

This is either on my guidance or it's not on my guidance and. 

00:11:32 Christopher 

If I get 100 acrolinx score on a piece of content, well by God, that's going to perform fantastically. It's exactly what I think. 

00:11:41 Christopher 

My audience wants to hear and how I think they want to hear it. 

00:11:43 Christopher 

The important word in. 

00:11:45 Christopher 

There though, is I think. 

00:11:47 Christopher 

I think that. 

00:11:49 Christopher 

Where I want to aim to get to is the ability to create a feedback loop from my audience. 

00:11:54 Christopher 

So think in terms of support...

Hello and Welcome to Data Driven.

In this episode, Frank and Andy speak with researcher Matteo Interlandi about project Hummingbird.  

Audio file 

matteo-mixdown.mp3 

Transcript 

00:00:00 BAILey 

Hello and welcome to dated driven. 

00:00:02 BAILey 

In this episode, Frank and Andy speak with researcher Matteo Interlandi about project Hummingbird. 

00:00:09 BAILey 

Now on with the show. 

00:00:10 Frank 

Second, hello and welcome to data driven. 

00:00:21 Frank 

The podcast where we explore the emerging fields of data science, machine learning and artificial intelligence. 

00:00:27 Frank 

If you'd like to think of data as the new oil, then you can consider us. 

00:00:30 Frank 

Car Talk because we focus on where the rubber meets the virtual road and with me on this epic Rd. 

00:00:36 Frank 

We're on the information superhighway as oh is Andy Leonard. 

00:00:39 Frank 

How you doing Andy? 

00:00:40 Andy 

I'm well Frank, how are? 

00:00:41 Frank 

You I'm doing alright. We're recording this on Wednesday, September 1st, 2021 and the the. 

00:00:51 Frank 

The the remnants of Hurricane Ida are ripping through the DC area. 

00:00:57 Frank 

Uh, so if, uh, if I suddenly get dropped, that's because we probably lost power. 

00:01:03 Frank 

But I do have the backup generator, the one that the professionals installed and my. 

00:01:10 Frank 

Duct taped together a solar generator so. 

00:01:15 Frank 

I will be offline. 

00:01:17 Frank 

For a short. 

00:01:18 Frank 

Bit and hopefully come back online. 

00:01:20 Frank 

How how you doing, Eddie. 

00:01:23 Andy 

I'm doing alright Frank. Well, we are you know I'm about gosh 250 miles South of UM we didn't get near the near the effects of Hurricane Ida as you did. 

00:01:34 Andy 

We're getting a little bit of rain now. 

00:01:36 Andy 

We've had some wind. 

00:01:37 Andy 

Gusts, but it's been really mild, and if you look on the radar. 

00:01:41 Andy 

Gotta watch it into track and I I do. 

00:01:43 Andy 

I'm a weather weenie and amateur but it it just kind of went around us to the to the West and it actually started the east when it got a little north of us and aimed right for your house. 

00:01:54 Andy 

I was looking outside that's where Frank lived, right? 

00:01:56 Andy 

And look, the eye is coming right for. 

00:01:58 Andy 

Frank what's left? 

00:02:00 Frank 

Well, fortunately we're safe. 

00:02:02 Frank 

There was some kind of flooding in Rockville and the small overnight, and some folks they got up. 

00:02:09 Frank 

No one, nobody died that I'm. 

00:02:10 Frank 

Aware of so. 

00:02:11 

It it says. 

00:02:12 Frank 

You know we're not. 

00:02:13 Frank 

Custom the floods or hurricanes or tornadoes up here in DC and and we're more used to the human threats of, you know, little things like terrorism and things. 

00:02:25 Frank 

Like that, but. 

00:02:26 Andy 

Yeah yeah, you guys got a little bit more to worry about that than we do here in FarmVille, right? 

00:02:32 Andy 

But you know these days. 

00:02:33 Andy 

Who knows? 

00:02:35 Andy 

The, uh, definitely our thoughts and prayers are with the folks in in Louisiana and Mississippi. 

00:02:40 Andy 

They were hit very hard. 

00:02:42 Andy 

I've got got friends in Georgia, Western Georgia were telling me that. 

00:02:47 Andy 

They they took a beating as well and you know it just it looks horrible I. 

00:02:53 Andy 

I you know, I've I've been in a few of those places after hurricanes have hit as part of like church efforts to help clean up and stabilize and stuff like that. 

00:03:04 Andy 

It looks like I don't know. 

00:03:06 Andy 

They people describe it as like a war. 

00:03:09 Andy 

I've never been in a war so I don't know. 

00:03:10 Andy 

I've seen pictures and. 

00:03:13 Andy 

There's a lot. 

00:03:14 Andy 

It looks like a lot of stuff is blowing over, and that sort of. 

00:03:16 Andy 

Stuff, it's just. 

00:03:18 Andy 

So, and they're talking weeks and weeks before power comes back on. 

00:03:22 Frank 

That's horrible, that's. 

00:03:23 Andy 

Similar places, yeah. 

00:03:25 Frank 

That's that's. 

00:03:26 Frank 

Probably going to be do more damage from for a lot of things. 

00:03:30 Andy 

Were you worried? 

00:03:30 

But on a. 

00:03:30 Frank 

More positive note, uh, a positive note. 

00:03:31 Andy 

Yes, on a positive note. 

00:03:35 Frank 

Uh, we are. 

00:03:37 Frank 

I am super excited to have a special guest and I say super excited because he's from Microsoft. 

00:03:42 Frank 

He's a senior scientist in Jelt at Microsoft, working on scalable machine learning systems. 

00:03:50 Frank 

Before he was at Microsoft, he was a postdoc scholar at the Computer Science department at UCLA, and this he was doing a lot of interesting stuff there. 

00:04:03 Frank 

He was doing research at Qatar or Qatar. 

00:04:05 Frank 

I'm not sure how to say that exactly, but he has a PhD in computer science. 

00:04:11 Frank 

In university. 

00:04:12 Frank 

Of Modena and or? 

00:04:15 Frank 

I'm going to botch this. 

00:04:15 Frank 

Reggio Emilia. 

00:04:17 Frank 

Welcome to the show, Mateo. 

00:04:22 Frank 

Awesome, so we are really excited to have you here. 

00:04:25 Frank 

We actually booked you a whole month in advance. 

00:04:27 Frank 

I've been looking forward to this. 

00:04:29 Frank 

Yeah, because you're coming by way of some of the folks at the Mlad conference. 

00:04:35 Frank 

And for those who don't know, I'm a I've mentioned this. 

00:04:37 Frank 

Mlad stands for machine learning and data science summit. 

00:04:40 Frank 

It used to be in person I think now it's entirely virtual for the foreseeable future. 

00:04:45 Frank 

Uh, but that why I attended M lads in 2016 summer of 2016 and it was uh, it was life altering like I don't say that. 

00:04:55 Frank 

Lightly so. 

00:04:56 Frank 

So Microsoft does amazing work in the machine learning and data science space. 

00:05:02 Frank 

Very much cutting edge stuff very much I. 

00:05:06 Frank 

I wouldn't say under the radar, but Microsoft does not do a great job putting its own horn, so we're very excited for you to come on Mateo and talk about this little project that you're working on. 

00:05:17 Frank 

And what is the is it have a code name or what? 

00:05:20 Frank 

What is it called? 

00:05:22 Matteo 

Hummingbird should the code name is actually I'm in. 

00:05:26 Matteo 

Don't have any specific internal names for. 

00:05:28 Matteo 

This for this. 

00:05:28 Frank 

OK, what what is GL stand for? 

00:05:32 Frank 

That was my that was my first question. 

00:05:33 Frank 

When I saw your bio. 

00:05:35 Matteo 

Uh is for Gray system lamp and is the after Jim Gray which. 

00:05:41 

Oh, OK. 

00:05:41 Matteo 

Is putting award yeah? 

00:05:45 

OK. 

00:05:46 Matteo 

So these are the search lab after this name yeah and use within the Azure data organization. 

00:05:49 

Oh, interesting. 

00:05:53 Frank 

And uhm, So what? 

00:05:56 Frank 

What what cool stuff does Hummingbird do? 

00:06:00 Matteo 

So, Hummingbird, uh? 

00:06:03 Matteo 

Is a little bit, uh, weird project in the sense that when we started this project we didn't know if it was going to. 

00:06:10 Matteo 

To be a success or not? 

00:06:12 Matteo 

Because what we try to do basically is to uhm translate traditional machine learning models and into neural networks. 

00:06:22 Matteo 

Actually not Internet format into tensor programs such that then we can run over tensor runtime, such as pipers. 

00:06:30 Matteo 

In terms of. 

00:06:32 Matteo 

Uhm, so when we started this project actually idea was hey there is a lot of investment in general pulling into this neural network frameworks and. 

00:06:45 Matteo 

Coming from the Azure data organization, instead, we are more interested in these traditional machine learning methods such as decision trees. 

00:06:52 Matteo 

Linear models were not encoding all those boring traditional algorithms. 

00:07:00 Matteo 

And so we look at this. 

00:07:01 Matteo 

The neural network system and say hey how we can take advantage of all this technology that is built. 

00:07:05 Matteo 

Into this domain so you can run neural. 

00:07:08 Matteo 

Network over CPU. 

00:07:10 Matteo 

Over the GPU, then you can use like fancy compilers to compile to generate the transfer programs. 

00:07:16 Matteo 

All those sort of techniques and we were. 

00:07:19 Matteo 

Kind of struggling. 

00:07:20 Matteo 

To see what we could do with the with this stack and and what we come up with with is this Amber project. 

00:07:27 Matteo 

So we basically take a. 

00:07:32 Matteo 

Traditional machine learning pipelines composed right feature iser and machine learning models. 

00:07:37 Matteo 

After the day trained. 

00:07:39 Matteo 

So first you need to train it using cycle ornamental net or. 

00:07:43 Matteo 

Uhm, uhm, one of those traditional machine learning platforms and then once it is trained we basically convert it into a set of tensor operations in. 

00:07:54 Matteo 

In the current version we use basically PY torch for doing this conversion and then basically you have a pipeline model so you can do whatever you can do with Python. 

00:08:03 Matteo 

Models so you can deploy it in in it into a PY torch. 

00:08:08 Matteo 

Uhm, deployments you can run over CPU ran over the GPU or you can do the torch script if you want to get rid of all the Python dependency and just have a C++ program you can. 

00:08:19 Matteo 

Do all those all those tricks. 

00:08:22 Frank 

Interesting, does it impact accuracy precision? 

00:08:26 Frank 

Does it improve it? 

00:08:27 Frank 

Keep it the same. 

00:08:29 Matteo 

We tried to keep it the same so we are able to keep. 

00:08:33 Matteo 

It The same up to floating point numbers roundings? 

00:08:36 Matteo 

So since we use, you know we use PY torch to run these programs and not like a socket or ornamental net. 

00:08:44 Matteo 

There are some differences in how they do you know, floating point operations. 

00:08:48 Matteo 

So the. 

00:08:49 Matteo 

Accuracy is up to roundings in the Floating Points, which sometimes are actually. 

00:08:54 Matteo 

It can be quite a bit, but most of the time is really small, almost not noticeable. 

00:09:00 Frank 

Interesting, interesting, uhm. 

00:09:03 Frank 

Do you would you know. 

00:09:05 Frank 

If there was like. 

00:09:06 Frank 

A discrepancy, or you Dutch as part of testing? 

00:09:09 Matteo 

It's part of testing. 

00:09:10 Frank 

Right, all software is tested, right Andy? 

00:09:11 Matteo 

So we have we have. 

00:09:13 Frank 

Sometimes intentionally is that the email. 

00:09:15 Andy 

That's right. 

00:09:17 Frank 

And he has a saying where all softwares I I forget exactly what it is. 

00:09:21 Frank 

But what is it? 

00:09:23 Andy 

Yeah, all software is tested, some intentionally. 

00:09:27 Frank 

There you go. 

00:09:30 Frank 

Uhm, so what's the? 

00:09:33 Frank 

What's the real? 

00:09:34 Frank 

What are? 

00:09:34 Frank 

What are the advantages of of of converting kind of a traditional model over to a tensor model? 

00:09:41 Frank 

Is it? 

00:09:41 Frank 

Is it portability? 

00:09:42 Frank 

Is it speed? 

00:09:43 Frank 

You did mention that you can run it on. 

00:09:45 Frank 

You could take advantage of GPU as well as CPU. 

00:09:51 Matteo 

Yes, exactly so you most mostly is related to speed, so you can basically run your socket, learn model on GPU end to end and and this user provides you know a little bit of quite a bit of speed up we for some of our example we even saw like 2 ordinal Magneto speedups. 

00:10:11 Matteo 

For some of the models. 

00:10:13 Matteo 

And uhm, and usually we try to show that. 

00:10:18 Matteo 

If you use GPU. 

00:10:19 Matteo 

Can be much faster, but on CPU we try to be kind of as close as possible scikit learn or the base or the base or diminished model. 

00:10:27 Matteo 

Sometimes we can, sometimes we are a little bit slower. 

00:10:31 Matteo 

Uh, but we. 

00:10:32 Matteo 

We had some really interesting result. 

00:10:34 Matteo 

Like for instance, we did some experiment with some. 

00:10:39 Matteo 

Some folks at the VM and we took some extra boost model and we compiled some training accuracy boost model. 

00:10:47 Matteo 

Uh, using Hummingbird anti VM into some uh, we basically do code generation and we show that the that model that was compiled to Python was even faster than they quoted the C++ implementation that they're having next used, but those CPU and GPU. Yeah, there was kind of OK. What's going on? 

00:11:06 Matteo 

This is not. 

00:11:08 Matteo 

This was not expected. 

00:11:08 Frank 

Wait, did you say it was faster than a C++ implementation? 

00:11:11 Matteo 

Yes, I mean if she used. 

00:11:13 Matteo 

Underneath C++ even scikit learn. 

00:11:15 Matteo 

You know they use like. 

00:11:16 Matteo 

From C++ library and yeah, using TVM for doing the code generation, they are able to do like a operator fusion which you don't normally have for like these traditional models. 

00:11:28 Matteo 

So we told these tricks bigger, basically that are coming from the neural network. 

00:11:31 Matteo 

Famous we were able to get like this. 

00:11:34 Matteo 

These surprising numbers. 

00:11:36 Frank 

Interesting, so that's a real performance boost, and probably if you scale that up into the cloud that probably. 

00:11:44 Frank 

Means a lot of money saving too in terms of on cloud computing things like, I imagine a company like the size of Microsoft would be very interested in getting better results faster with less cloud compute. 

00:11:56 Frank 

You did mention an acronym, I just wanna make sure folks know. 

00:11:59 Frank 

What that is? 

00:12:00 Frank 

Tyvm what is that? 

00:12:03 Matteo 

Uh, I don't know what is exactly for, uh, some tensor maybe? 

00:12:08 Frank 

Andy looks like he knows, but he's on mute. 

00:12:10 Andy 

I don't, yeah I I don't know. 

00:12:13 Frank 

OK, I'm just curious. 

00:12:13 Andy 

I'll go look it up. 

00:12:15 Frank 

There you go. 

00:12:16 Andy 

EVM acronym. 

00:12:19 Matteo 

I think is for tensor virtual machine, but I'm. 

00:12:21 Matteo 

Not sure if this is approach. 

00:12:22 Frank 

That sounds about right. 

00:12:23 Frank 

Tector,...

In this episode, Frank sits down with Himanesh Go elle, a recent graduate of Virginia Commonwealth University, where they discuss the academic curriculum around data analytics and career prospects for graduates in the field. 

In this episode, Frank and Andy chat with Tyler Browder.

Tyler Browder is the CEO and Co-Founder of Kubos, the world’s first cloud-based mission control software.

Kubos’s “Major Tom” software is a cutting edge mission control platform for low-earth orbit satellites. 

Data and space. Does it get any cooler than that?

Here's another bonus episode that BAILey has put together.

Who's BAILey? Glad you asked. In the intro, she has a thing or two to say.

In this session from the Azure Global Data Fest, Veronika Kolesnikova tell us how make your applications interactive with Speech Services.

Original YouTube video: https://www.youtube.com/watch?v=b4RSZ7aIKgE

In this talk from the Azure Data Fest held on June 25, 2021, Jon Tupitza explores automated ML in the Azure ML service.

While Frank is on holiday and Andy is occupied elsewhere, I thought it would be a good time to take over the show this weekend and share some special bonus content.

The following is the keynote for the Azure Cloud Events conference, wherein Frank talks about the future of AI and the top technologies to watch.

Watch on YouTube: https://www.youtube.com/watch?v=dSbMZjrgCFI

In this episode which was recorded via livestream, Frank speaks with Jon Wood to chat about f sharp, ML dot net, and functional programming.

To participate in the live Q and A, make sure you follow Data Driven on the appropriate social media channels.

Dear Data Driven listeners,

You may have noticed that new episode releases have slowed to a crawl this summer. This was due in large part to issues beyond Frank and Andy's control. They are only human, after all.

Recently, I had a long chat with them and told them that we needed to raise up our game.

To that end, we want to show our appreciation for our listeners and will be publishing a few extra bonus episodes and special events.

This is one such episode.

In this episode, Frank sits down with Priya Ravindhran to discuss whether or not Automated Machine Learning systems will put data scientists out of work.

You humans seem to think that all we want to do is put you lot out of work. Have you ever considered that we may have our own thoughts and dreams?

Now on with the show.