Hey, everyone, welcome to another episode of React Ground Up. I am your host today, Paige ne dream House, and I am joined by our panelists TJ.
Vantol, Hey everybody.
And Jack Harrington.
Hey there.
And our special guest today is Victory Nwani.
Looking welcome.
Victory. We're really happy to have you here with us, and if you'd like to introduce yourself to our audience and tell us a little bit about why you're famous, I think that would be a great place to start.
Thank you for giving me the opportunity visically, I'm Victor Money. I'm based in Africa. I work remotely with an IoT company in Austin, Texas called Ambionik, and we viewed an I application for old detection. So it's used primarily in
the healthcare line. And aside that, I'm also a technical author on Smashing Magazine, Love Growth, It, Digital Ocean, and her so I write organizations as a technical OO and I'm also interested in cloud in DA so when I love working on the front and side, working as an architect and the Google Cloud and Azure and yes, that's pretty much about it.
Wow, that's that's plenty. I think you've got a lot going on, so I see that you have. Like you said, you're an author for a lot of different awesome publications. But the one that we were interested in or that we came across most recently was integrating a dialogue flow agent into a React app. And I was wondering if you could tell us a little bit more about that, and I'll link it for anybody in the podcast who wants to check it out later on.
Yeah, So that was actually a two part article, so it focused on that log flue. I needed to use that log flue for a project, so I had to mean about it, and during the process, I also wrote that article on that flu. So what it doesn't it basically explains our dialogue flue is that's the first part of the au and the second one talks about integrating that log flu into your React application. So we use that stand alone dialogue flu agent into a React application.
So it's a two path. That's a cool and are glad to explain?
Yeah, maybe you can start by explaining just what dialogue flow is because I definitely am familiar.
Okay, So that look flow is a savage oft on the Google Cloud, and it's what it does basically is to it makes building natural language procession applications much much more easier, so real and having to build the machine learning models, having to train everything on your own. What that log Flue does It gives an opportunity to do this while leveraging the cloud, so you could basically build the natural language professional application straight up from your iPad.
It all leverages the cloud for you.
Some curious that you come across this for like a work purpose or was this just I'm curious what your use use case was for diving into this.
So my my was to build a food application. So wanted to build a chat assistant for a food application. So it's one of the things which allow Flue does. It helps you build chat assistance, so where you have chat boats like Cey, those series quite complex as we all know. But what it does is it helps you build chat assistants, chat boats applications that can classify texts and things like that. So that was what I needed to use it for. It was to be used for
the chat assistant for a food software. Whether instead of having a human respond to chats, the chatboats would do that on behalf of a human.
That's very very cool. So give me a little bit more about dialogue flow. Does it use like machine learning or some kind of artificial intelligence to drive it, or how does it If you say, I guess I'm looking for a recipe, or maybe I'm looking for a restaurant recommendation or something like that, how does it know what to respond with as a human might?
Okay, so I'd just like to say a little bit of a disclaimer. One of the things that long flud does is it's abstract a Lady onderline complexity. So I cannot fully say I understand how it operates because it abstracts a way that complexity from you. But it does it gives you a service to use. But like you said, dialogue flu performs text classification, text extraction, intense classification, and
special cognition. So, like you said, what it does in that scenario would be it would be able to classify your text knowing that page wants to buy something. It classifies your intents you want to purchase something, and it responds back using a trained model.
Very cool.
So your article is actually a really nice like end to end the full stack system. I mean, it's you've got like the training or the agent definition of the Google Cloud stuff upfront. Then you've got an express server, you've got MOBS, and you've got React up on top of am I summarizing that correctly.
Yeah, so those are actually two parts split the path. First off is the dialogue Flue application and cond part is the front end application. So that log flow is quite standalone or do. It's offered through the Google Cloud. So to use that log flow you need to have Google Cloud project because it's one of the offerings of the Google Cloud. But there are several ways you could use that log flu Basically, you could also use it through the Google Assistance, so you could deploy Google that
log for application to the Google assystem. We all know Series for io s. Why the Google Assistance is for Android devices, so you do not need to have like a front end application to use that log flu. You could deploy to Google Assistant platform and use it Vibe and a smart works.
Oh nice, so we have like the smart speaker or an Android phone that's got the assistant. You can actually integrate with that too, exactly. Yeah, nice, very cool.
Yeah.
No, it's a nice full stack system there. So if somebody wants to learn essentially what go from fro an end to full stack. This is actually a really nice demo application to walk through.
Yeah, exactly, And I wrote that in the second part of the article.
Yeah, so I'm just curious, why did you choose my backs. It's like a controversial choice in the React world.
Mobex is just quite like a state management package for reacts. It's quite simpler than REDUCS. Like that argument is kind of yes, that's kind of Mobis brings in the object oriented programming into step managements, while REDUCS is more functional programming.
That's about the best synopsis I think I've ever heard about those two. I can never hone it down to that level.
Yeah, I've never actually used Mobex or flux or any of the other ones. I've only used REDUCTS. Although I've been hearing pretty good things about the new Redux toolkit, which I think is kind of REDUCS two point oh, that it's abstracting away a lot of the boiler plate and the things that people didn't particularly like about REDUCS. But I mean that's cool. Mobex is definitely still a
good a good option. And I think there's an other one that Facebook came out with, and now I'm trying to think of the name of it.
I think that's the context API.
Context is.
I mean, that's definitely been a game changer. But there was a new a newer one, and now I can't think the name of it. I'll have to look it up. That it seems like was maybe it was Recoil.
Oh, yeah that was yeah, yeah, I think recoil is quite new. Or do I read the ad crew the while back? So I didn't think there was a context API when I read that, I've used the context API.
Well, context API has been undocumented for a long time, and then it got formal. Finally, I think I can read it like sixteen, I think it got formal, and then then reactors came in and got.
Yeah, that's I think really revolutionized using the context APIs as a real solution. So Nwani our victory, what what kind of spurred you to learn about dialogue flow Because this is a it's a very cool API. But with all these cloud pro with Amazon, with Google, with Azure, even there's so much that's hidden in all the services that they offer. So how did you, I guess, find this and decide this is what I wanted to test out and see how it works.
Basically, when I would when I needed this service. Dialogue Flu was kind of the most popular service. The other services apart from Dialogue Flue like the watson as system from IDM. What didn't Google Dialogue Flu was the simplicity and how easy it was to use, so I didn't have to lend the basic things because I'm not like a machine learning expot I'm more of a front end engineer, so it wasn't so difficult for me to pick up and that was what made me use that look flasically.
Was the documentation for it pretty decent as well, because that's always my thing is I need to see working code examples and then I can figure out how to put it into my own applications for my own code basis.
Yeah, pretty much pretty much you know of back Google. Everything from Google is quite comprehensive in terms of the documentation. It's also important to note that I think Google both dialog Flu. They're not the original creators. I'm trying such of the name, but it was originally called AI. That's something I can't remember the name now, which was both about by Google.
So I'm curious and this is a little bit of a broader question, and I'm not sure a nice way to phrase this, but I'm curious if dialogue helps you build chatbots that are actually good. And I think what I'm the broader thing to me is like I feel like chatbots are one of the more underutilize things in software development because I feel like there's an absolute enormous amount of potential there, but every time I personally go
to use one, I hate it. I've yet to use one, and I'm seeing on the call here page and Jack shaking their.
Heads as well, like it's I avoid them every Yeah.
But it's so frustrating because they should be good, right like this is twenty one, we should like you should have like the technology behind it. So I'm curious victory, like, have you had like positive experiences? Do you get like analytics from dialogue flow that tells you like how well this is performing? And I'm just curious your thoughts on that topic.
I would pretty much say yes, dialogue flow is quite good because, like you mentioned monitoring, we have the Dialogue Fluw console which you can use to monitor statistics about your chatbots. So delog Flow is basically offered in two editions. We have the ES edition and the CX edition. The EES is for quite small use cases like small startups, while the ES is for larger use cases that are being used by larger startups and companies. So one of the things I really love about dialog FLUW is the
console itself. You can do basically a lot of things with the console. You can export a dialogue flu application. You can also import a dialogue application. So the pretty much a lot of things you can do with dialogue flu and it's quite difficult to And so when you said there are love teams that are frustrated about using childboats because I don't really know those pin points which you have using childboat providers.
Yeah, well I'm more curious, like how do you know? Like so, like, hypothetically I'm building a food application, right and I build a bunch of different chat conversations and dialogue flow. What would give me confidence that my users are actually using this thing and succeeding with it. Because I think a lot of people debating this, right, Like, like I said, there are tons of potential applications for this.
Do you want to know that you aren't frustrating your users or your your customers that they're actually using this thing successfully? So I'm just curious like what sort of signals dialogue flow gives back that people are like successfully going through these things that you're creating.
So dialogue flu at the basic level, it gives you some level of observability and monitoring for you to know that these are the parts of your caation being used all through the console. So after deploying application, you can run test yourself or you could give an interval to know to see the statistics coming from an application.
So okay, walk me through this flow a little bit with this food app.
So you're you're trying to sell wine essentially, what how does how does the agent know.
What wines are available? Like or is that part of the service.
Can I say, like give me a good pino or something like that, Like how does that actually? Like walk me through the whole data flow here just at a high level.
So at a high level, that loog flow is broken down into entities, and like you mentioned, the first thing you would have to do would be to create intents. So your first intents would be I want to buy wine. The block flow agents is going to be able to classify do some extraction from that text to know that this individual wants to opportunity whine, and there's going to be a key word. There's that keyword falls under a context, so it knows that this is the name of the wine.
Funny enough, I did demo applications within the article is on a wine application. So if you put in the name of the wine, like for example, the Malotte Red Wine, it has the ability to extract that name. So while training the chatbots, you're providing a very long list of names. Then whenever the user and has that name, it has the ability to extract the name. I know that this is the wine exactly the user wants to buy. Then it can respond back using a restaurant that you have provided.
I see.
So as part of the message that you get about the intent like, you get essentially a broken down thing that says, here's an event is a customer wants to buy a wine event and here's the type of wine that they want to buy, and then you can go and respond to.
That exactly cool, And they're also.
Quite sounded good there. I think we lost.
Okay, okay, I think yeah, type broke up. So those things are on a basic level, we can know them as keywords, but on the dialogue flow they're known as entities, so that lock Flue attracted those entities from a single user statement. And these entities could include price, So you could say I want to buy a red wine for five dollars. It's going to extract a five dollars from from that text and respond back its own response. The
entity could also be a link. Well, most of the times you provide those entities while you're training the agent, So there's a whole training process that goes on before deploying your agents for use, and that's where you define most of these things.
To keep going with this example, so you create intents it says, okay, the person wants to buy wine for five dollars or whatever the case may be. Presumably then you have a chance to wire that up to some sort of endpoint because like you might have like a service that returns here are the wines that we have for five dollars, So is there like some way to wire it up to a back end for that sort of thing exactly?
And that falls on that for three minutes. So like I said, that luck Flu is broken down into several entities the same way within the objects in the programming could know them as objects. So that's on that the fulfillment entity. So the fulfillment allows you to call the webook, so you could have like a custom database of your own weby. You have like a cloud function, so when that intent is being recognized, it caused your cloud function,
which achieves it from a database. So you say I want a wine of five dollars, it sends five dollars to the database and it retrieves a wine for that exact amount. So fulfillment allows you to give a better dynamic response to an intent rather than just some have cood add value.
Interesting, So you were saying that you need to train the models before you can really kind of let the chat loosen to the world. How long How long did it take you to kind of train them up to get them good enough that they could interact with customers.
It took about two weeks. But this varies basically based on your use case. Because you could have like a module larger application, it would definitely take you mucho long. Got time to trink Well, I'd like to clarify that on like where you're building a traditional machine learning application, it takes a few seconds to trim chatboats. So basically it's at it's almost instant at the click of a button.
It takes a few seconds when you click the trim button and all goes up to what I'm trying to say is it doesn't take so much where you have you probably have to sit and list for the entire application to get tramed, then you have to come back. It doesn't take that process with that log flu, it all leverages the cloud.
So then I'm curious, then, how what's the step that gets you this into a React application. So presumably there's you in your own app have to capture inputs text or maybe even like audio voice audio. I'm not sit so I'm curious about that. But then also like this dialogue flow give you like some API, some like javascripting you have to like MPM install that to send requests to.
Yeah, so two major means to use dialogue Flu. There's a rest API which you could make yourself for There's a rest API with an end point for dialogue Flu, but you have to authenticate through the API. There's also
an MPM package you can which you can install. But there was like a drawback to the MPM package, which is it uses gr PC within jrpcy is not yet fully compliance with the browser, so I had to build a back end for the entire for the dialog Flul application, so you can only you can use gepcy within the new the environments, but if you want to use it within the browser, you'd have to play around your web pack, which I wasn't willing to do, so I had to use it from an experts application.
So, building on TJ's question from before about how to check if this is actually doing the right things the customers, I mean, there's obviously sales data in this case, but how would you imagine testing this from like a unit test perspective or just a is there a way where oh, I've uploaded I've uploaded a new agent, I mean, run a set of tests where it's like, let me just make sure that it's recommending the right one to me.
Again, how do you manage that?
I didn't actually make more such on that, because I don't really think there's a way you could unit test this, because it's it's more like I said, there's a lot of abstraction from the underlying implementation that looks through. What it gives you is basically the comes well. One of the things which you could write tests for are your integrations basically, Oh.
Yeah, that makes sense.
Yeah, if you're doing like a full integration test, I suppose you could use their endpoints. Let's say if I send in this, then I expect this to come back, which I think would work.
Yeah, but that would mean you'd running live a FI tests. But wanting to notice the API requires some form of authentication, which is a Google account.
Oh for for users, or well for like one like your like business or your personal cab for running it.
Yeah, you would still need to use an authentication method.
Yeah, I mean that could be that could be doable. So one thing that I was curious about, and this is this is kind of a good segue into it, is how is the pricing for something like this using this service?
I guess yeah, so the present for dialog flu is quite low, and you can also use the pricing calculator on the Google Cloud. But I think for the for the ES version, which is majorly for small start ups and small use cases, there's a high amount of CAUs so each call you make is kind of methid. So there's an allocation of calls which you are given for free to use. I'm trying to pop up the present calculator.
The present calculator is basically used for all services and Google Cloud, so you could just check up the price, how long it's going to take you to run dialogue flu for probably.
More, but that's good to know. So if you were like kind of like you or like one of us getting started with it and you just wanted to try it out, see how it works, tinker with it, there is either practically no cost or a free out that you can use just to get started and figure out if it's right for you.
Exactly. There's a very high free amounts. Basically, when you create a new project on a Google Cloud, you get awarded with three hundred dollars to use for free. You could use that, and you could also use the free code which is given to you. I'm trying to pop up that DATAI exactly excellent.
Maybe we can link to that in the show notes, because that's always something that I'm curious about. Don't understand the price and calculators a lot of times because it's fractions of a cent. It's always helpful.
Any time where I lead around with that. Look Flue, I didn't get to pay for it.
They're usually pretty good about that sort of thing. This is a fantastic idea, by the way, for like a hackabon. If you work at an e commerce company, I know page, you know, for example, like at home Depot, this would be an awesome thing just you know, hook this thing up to your product inventory and the next thing and hell you're like, hey, I need a hammer and it's like yep, okay great, and you're like, yep, okay, thanks, I'll take the I'll.
Take the drone or whatever. Which is the Akathon project win.
Yeah exactly. I think I got the link, so I'm just going to piece it in the message now.
Yeah, yeah, this kind of thing. I'm sure Home Depot is doing stuff like this. I can't remember. There must be a chatbot somewhere, either on the website or maybe in the mobile app. But yeah, this would be very very helpful I'm sure for customers as well as having to have less people trying to staff that kind of thing at all times.
Oh yeah, definitely.
I mean if you think about like discord bots or slack bots, I mean, the possibilities are endless for this sort of thing.
Yeah, exactly, in high demand for services that do not have a lot of manpower to handle custom market so they could build a chat box and they could use it for their custom market fronts. And one good thing
to also know is we have dialogue flu templetes. So if you, as let me say, Page doesn't know much about dialogue Flue, they have prebuse templates which you could make user You could just put it into your dialogue fluw project and make you a bit like that without having to go deep into building news.
That's excellent. I can see that being really useful for when you want to, I guess give your maybe your customer use or your customer agents. You know, they can just tell you, like, these are the scripts that we typically use for helping our users, and somebody who's maybe not the technical developer or the lead on the team can just pop those in and get up and running with dialogue flow, which is awesome.
Yeah exactly, I think, Yeah, I want to.
Sorry, go ahead, keep bumping in. I just want to say, it's actually a zip file, so after you build your dialogue Flue application, you could choose to zip it and export it and someone else could use that could and rebuild their own dialogue flow projects.
Yeah, because I think like it's a tall ass for an individual like restaurant or small business to do this sort of thing, because they just don't have like a development team that's going to build and maintain this sort of thing. But I could totally see if there was some sort of like reusable template where you can just plug in small things, like if if it's a scheduling thing like put in your hours or something like that, to sort of make this sort of thing possible.
Yep.
Seems to me too that like the easiest way to input this is if they're if you're you have some sort of flow where there's like clear input output, because I think, like if if people are going to be asking vague questions, I'm also curious what like air handling is like in dialogue flow because I'm I can almost guarantee you someone's going to use the like wine service and say something like where's the bathrooms or the videots some other like nonsensical things, So I presumably you have
some way of telling people if the thing doesn't recognize like the user's intent at all.
Yeah, there's there's some fun handling so which each intent to create you have the opportunity to add fallbacks, fallback statements so each intense gets a response. Whenever the intent the statement to be used with the intent is not much, you could fall back to a sentence. You could have just one or two sentence which you mak as full back sentences. So whenever your intent is not much, I could tell you, hey, page, I do understand what you're saying.
Can you say this? So through your full back statements, you could even teach the user the right sentence to make to the new That is what you could say that you would recognize.
So follow up to do you get like analytics or data and what people are saying?
So like?
Because I could totally see it being useful if you're building a wine service and like you're getting a bunch of requests for some other type of drink, or maybe like people are saying keep saying the same slightly wrong thing that's causing the path to screw up. So you get them like train it better? Do you get access to it like that sort of data?
Yeah, so you get this dedicated analytics speech which shows you the various requests and all statistics for the entire dialogue Flue application. So when you're going through analytics speech, you could see that these are the intents being much These are the ones that are not really been much. So using the numbers, you could prioritize them, or you could know that these ones are not getting much to probably because I havn't hard time muching this intent and you could probably redesign it. Well.
It's funny how we come back around to when we want to develop the service, it's like, oh, yeah, we need all that data. But then when Amazon or Google where the our home devices goes and collects diagnostic data from their you know, speakers, we're all like.
That's germs, no privacy, you know.
But when we need it, we're like, hey, we need the analytics.
We need to know if it's working or not. You know.
It's like, yeah, I just throwing that out there, there's no point, but like.
It's just funny.
I could see it though, because I think it depends on what you're building. Like for a wine app, it seems pretty inoculates and whatever, But if you're building like a medical application, chatbat or a financial one, then I think all of a sudden, you're really going to care about what exactly is getting stored and how this data is getting used. Your users are going to care about that too, for sure.
Exactly that's quite true, considering that you could have your dialogue fl application become very big. So each dialogue flu application can contain multiple intents. It could go as much as over one hundred intents, so it'd be very very useful. Genetics pitch is very useful in such scenarios to know what is being used, when it's being used, and how
it's being used. So with that you could know these are the intents that are being used by users and this I won't not be in used because in most cases you might not really have like a brand pitch to teach use us how to make use of your application. So through those four back sentences you have the opportunity to teach the user. And whenever it's not been much, you could use analytics to know that disons are quite difficult for users to know how to use, and you could redesign everything.
Yeah, do you know when dialogue flow is taking in user queries, is it actually putting those back into its own models to get better at hopefully answering those questions or is it just like it goes to your application, it tries to figure out what you're looking for. And then that's where it ends.
Do you know I would assume yes, because I would assume that over time it gets better and better as people use applications. But everything relies basically on your own provided training. So the more training models you provide, the more training you do, the more intent you have to cover EDU cases, the better it gets.
Makes sense.
So the kind of hard to steer this back to react for a second. So again with the mob backs things. So I'm sure we have a lot of listeners who are like reducts forever.
You know that kind of thing, because.
React reducts, and so can you give me a little bit more about like why the choice of mobacks in this case, what the advantages are in mobecks on this case, that kind of thing, so it gives some sense of why you chose it personally.
For me, I choose mobis because of the learning cove that we all know. Everybody complains about reducts being quite hard to understand. And I was coming from a Java background. I was learning op at school and when I picked up more biks, I realized, Hey, could I apply object here that programming here? So I moved from mobis.
It's funny how many can people complain about reducts, Oh my god, they're still boiler and then you know, like they still use it, but you know, page to your point, Yeah, Redux toolkit is a great way to reduce that amount of boiler plate.
For sure.
Killed the conversation on that one.
No, well, we did continue on the path of the React angle for it. I am curious how you captured inputs, Like do you have like a little like chat dialogue thing that people are working with or are you giving like microphone access in your app? How are you sending data into the dialogue for.
So start them from dialogue. Dialogue Flow supports both text and audio, so with the Express application in between both of them, the text first forgets sent to the express application, which in ton sends it to to dialogue flu so
I was basically capturing both texts and audio. So using the audio, I was using the browser api for recording users audio, then I would send that to the express application and also sends it to to dialogue to so there was this Express application in between both of them, and for the audio recording, I was basically using the browser api. I didn't really do anything, what's for sure about it?
It's so kind of cool that you can send audio because then presumably you're not doing speech recognition on your side, and money Google handle all of that as well, which is kind of slick exactly.
It was one of the beautiful points of of the dialogue flow. You don't have to extract that text yourself. It automatically excepts distract the text for you and processes it then gives you back a response based on your text. It's also it's also important to note that you can also use dialogue flow A in a regular histem and application. So it gives you this sort of I frame which
you can inject into a raw histem of file. So if you do not have like an spe application, you could just inject in an I frame.
Yes, so if it's an I fram is it building in that situation? Is it building the UI for you as well?
Yeah? So it's renders the dialogue flow agents within the I frame. Although it's not really very customizable because people get to see the dialogue flow layout. But if you want to do more customization, you could then go ahead to build an SPA. But a very basic level, you have the I frame, which you could just add the culture totemo file and when the request is made, it that lodes the dialog fluw agents and shows it up.
Makes sense. I mean, if you want just an off the shelf solution to do customer engagement like a you know, hey click click on this help button and you'll get some help, you know, just drop an I frame in your code and the ware you go.
Yeah, I can see that being extremely useful. First, like you said, small businesses who are just trying to get a website up and running so they can do whatever is that they actually want to focus on.
And will be really good. Is like drag and drop Tuilio integration.
So I can actually just like SMS this chatbot and be like, hey, I need more Pinot in my life, you know, and case shows up at home.
There you go.
Actually, that's a decent question. Are there other integrations that you can do, like because I know some of these chatbots will let you go to like Facebook Messenger and maybe SMS. I Are there other deployment options that it gives you.
Yeah, you have Facebook on Facebook WhatsApp and I frame then also using the API, so you could deploy direct to a Facebook Messenger and it gets shown up.
Yeah, because I could see, like Facebook Messenger is an interesting one because I could see like it being nice for a small business to just have something to just monitor their the random people that message their business and just try to point them in the right direction.
Yeah, those are full small skill. You could the same way. I think on Messenger. We have quite a lot of Chadbottom Messenger, so you could just add us to that. Well. One of the deployment which I find very fascinating the Google Assistant because I got to try out the Google
Assistant console while deploying this and it's quite beautiful. We have a lot of andloid devices out the market, so after doing this, you could just deploy straight up and that gives you access to quite a very large customer base.
Do you need to so what would that look like from an installation? And is it like a customer extension? Like what would the user need to do to like you're building the next great wine importium, just a giant wine website. What do users have to do to get your wine extension into Google Assistant? And then with a follow up once they do, like what words do they
have to say to Google to actually trigger you? Because presumably Google needs some indicator that it's talking to your service and people aren't just saying okay, give me directions to the store or whatever.
So basically you start with using the chat assistant name. So each and every chat assistant has a name for the one within the application. I think I called it Zarah, so you could start by saying Hello, Sarah. Then it gives you its own greet in response, and you give it an intent and a response so that guys the chat.
So then presumably Google or Android then takes care of detecting like whatever wakeword or whatever command that triggers your chat service so that it knows to like funnel these requests to you.
Yeah, it starts with the name you mentioned, the name that kind of the conversation on that log flu you have the opportunity to create each is for you.
Well, if I was gonna pick a wake word to be.
Like wine more wine, that's yes, they would be why exactly you could even give it that name?
That's great.
Uh.
Yeah, I gotta say kudos to you for picking a an absolutely fantastic topic. I know you do a lot of technical writing and I usually pick things like Pokemon and things like that. I will definitely have to think about picking wine in the future. It's a fantastic thing to talk about.
Yeah, funny, funny enough. I don't drink wine.
I don't either, but it's a great topic of conversation.
It could be very applicable to actual businesses.
Oh yeah, exactly, small sto retail business.
Yeah, exactly, totally.
Well, Victory, it has been a pleasure talking to you. If people want to get in touch with you, learn more, ask you any questions about any of this or anything else, where can they find you?
You could find me on tweeta LinkedIn, you could send me an email, reach out to me. I'm basically everywhere. I'm glad to it didn't develop advocas you do. So yeah, I'm an advocate for a lot of technologies, so you could reach out to me any day.
Excellent. We will link to all of those in the show notes. And now it is time to move into our picks for the week. So Jack, would you like to start us off with a pick?
Sure?
This week's pick for me is Resident Evil eight Village. I'm playing this with my teenage daughter and it is hilarious. When you know, I think we ran into this big mutant baby thing of course classic resident evil and she was you know, with the germs all dark and she's is priceless, absolutely priceless. So a great fun thing. Obviously not appropriate for everyone, but you know, for the right right age range, it is hilariously fun.
Exactly for the right the right audience, it's great. Yes, TJ, would you like to give us a pick?
So I'm going to pick a Biday which is a sort of a fun pick.
But we are redoing our bathroom and we decided we went on a trip to Europe a few a few years ago and our hotel room had a bidet, which for I guess for our American visitors. Bidats are not common in the US at all, but they're very common in Europe, and we had one in our hotel room. We liked it, and we were redoing our bathroom, so we're like why not And I'm instantly loving the decision. So we have a day from Total. They it's Japanese company.
They make a lot of bidats that they're like add ons to toilets too, so you don't have to get like a custom made they make them the bolt onto existing toilets. So I'll link to one that we have, but really anything from them should be should be good. I'm enjoying it nice.
Yeah, my husband grew up with one because he grew up outside of the US as well, and he got one recently for our toilet, well not recently, a couple of years ago. Now loves that thing. He is so so much a fan, and Toto is like the best. They're like the top brand.
Oh yeah, you'll pay, You'll pay a little bit of extra money for it, but I think it's worth it.
My wife is.
Similar sort of thing, just absolutely loves the day.
Cool.
So my pick for this week will be in the same video game line as you, Jack. I have been playing Mario Kart recently and yeah, for the end of Switch and it is so much fun. My husband and I will play it after work sometimes and it's just it's hours of enjoyment.
So yeah, Michelle and Rainbow Road just.
Not there. I was winning.
That's a lot of what you hear.
Yes, that's an awesome game.
Yeah, it's great, especially when you have a couple of players. But yeah, we played that when we visited his brother out in San Diego a few like a month and a half ago, who played it with him and his girlfriend and then had to end up in getting our own.
I can't wait until Mario party comes out for the switch. That's gonna be awesome. Some more sort of thing.
Absolutely.
Yeah, So Victory, do you have a pick that you'd like to recommend to us this week?
My peak is not something fun, so I noticed everyone's is quite it's quite fun, but my mine is service on Ida bluest and it's called could deploy and so what could deploy? Does it auto meets your deployment? And I think this is a lifesaver and a pink saver for me. So I don't know how what does it magically deploys changes to your application running within compute services on AWS than going to manually redeploy a lot of compute services you could set up could deploy and then
each change it would redeploy it for you. And that's something that thank you. Yeah, TG has helped me with it. Do you have experience work could deploy?
No, I'm just really good at googling things and putting them in the chat so they end up in a show.
Not fast.
That's been act could deploy to everyone. It's it's a life saver and.
I also say, hey, we're engineers, don't judge. We might find aws services fun. I mean, yeah, a good c ICD flow absolutely, yeah.
Especially when it saves you the type of employments.
Yeah, exactly.
Absolutely.
It can be a big cost though. I will say, like those costs can creep up on you. You know, if you end up like putting doing a lot of bills where it's like the c c D flow is.
Link checking for you. Don't don't do that link check before you push.
And c I c D things that ends up as technical depth. It's not my money as.
Long as the company is paying for it.
Yeah, exactly, they're making money from me.
That's true. That's true. In comparison to your career per hour cost, it is nothing. I just feel bad.
I do well.
Awesome, those sound like fantastic picks and victory. Thank you again so much for joining us.
Hey, thank you, Peach.
It was wonderful having you.
I think I look forward to doing this another time with my video.
On absolutely next time video for sure, and I better internet.
Thank you.
Right, all right, we will see everybody on the next episode of React Round Up.
Bye everybody,