talking to us about building AI with Seth and OpenShift. Thank you, thanks everyone. So, Saturday morning, thanks for, you know, not watching cartoons or Netflix or anything coming out here to see us speak. Today, I'm gonna talk to you about what we've been doing in the AI Center of Excellence at Red Hat. You guys have seen a number of us talk before about our strategies with AI and machine learning. You've seen Vasek and Steven talk about Jupyter Hub and Seth and Spark as well. I'm going to expand on that and introduce a concept of OpenWisp where we have serverless actions. So you'll see a little bit about how we chain all of those technologies together to get a nice machine learning pipeline. First off to do some level setting and ground rules. Everyone is familiar about the concept of machine learning and AI. This is to just show an example of a typical workflow. It starts off with, of course, Daniel mentioned this before, the data. In this case, we have a library of data sets and from there we want to start to develop a model. That's where a lot of the brains and the intelligence comes into analyzing the data and understanding what you wanna do, trial and error. From that developing of the model, you then go into the exercise of tuning the model and using the data that you have to then train it. Once you do that, of course, the big excitement is after you've trained it and developed your model, you get to deploy it and actually see some data coming in. So for today's session, I'll walk through an example of all of those types of steps that would go through in a typical process so you can see how we can use tools in an open shift world in order to achieve that workflow. The first part of this, as we mentioned before, was the open shift framework as we start out. How do we do this in a containerized world? Well, in this case, we're using open shift. Open shift, as you all know by now, is a container platform that uses certified Kubernetes, enterprise Kubernetes, and it also allows you to do more hybrid cloud type of things. You may have some of your infrastructure in Google, AWS, Azure, you may also have it on-prem. Open shift gives you that ability to seamlessly manage all of that in one ecosystem. Once we have our containerized world, we need a place to store the data. For this example, we'll be using Ceph. You can also use other technologies. The reasoning behind Ceph is really because of the growing need to be able to separate your data from where your performance and your compute actually happens. And that was one of those architectures that came from some of the Amazon, maybe a lot of you may be familiar with Amazon's infrastructure. You had a lot of the EMR type of scenarios where you'd have elastic map reduce and a Hadoop ecosystem. And then environment allows you to spin up a Hadoop cluster, process your data really quickly, and then tear down the cluster and not have to worry about maintaining it. Obviously, if you tear down the cluster, you have to make sure the storage is still there. And object stores like S3 and Ceph came about. We use Ceph because it has S3 capabilities and we're able to leverage a lot of the technologies that are already built on top of S3. Of course, it has a RESTful gateway, which is nice to integrate with as well and it's a distributed system. Some of the other software that I'll be using in this demonstration will be Spark. You've heard a lot about Spark in a lot of the AI talks and a lot of the container talks as well. Spark is a great engine for processing data, allows you to do batch and streaming, but it also runs on Kubernetes. And in this case, we are using the ratanalytics.io, work that they've done in order to move Spark into a Kubernetes framework with their Oshinko and ratanalytics Spark engines that we'll be using. Jupyter Hub, we've seen several examples of that. That allows us to have a multi-user console to manage Jupyter notebooks. Users can have many different notebooks. You can also do many different users on there and that allows you to do your data science work. It's designed for data science and research and a great tool to do that. That'll be running on Kubernetes OpenShift as well. And then the last little piece here, some of this may be a little bit new to you guys, but once you actually do the data model work, you want somewhere to deploy it. In this case, we'll be using OpenWisk. OpenWisk is a serverless action. If you've ever used Amazon AWS Lambda, it's a similar concept where it allows you to focus more on the delivery of the real code and not worry about the architecture. So I'll show a quick example of deploying OpenWisk and then taking that model and the code that uses the model and deploying that to OpenWisk as well so that you can have a nice REST API wrapper around execution of that model. So to start off, one of the first things you want to do is make sure you're collecting your data. This is just a little bit of a diagram that shows you a typical workflow that you may have to actually ingest your data. Internally at Red Hat, we have a lot of different systems that send us data. This is just some of the examples we do. We retrieve data from Git. We also have build logs, CI logs, all that information coming into us. But we also have a warehouse that houses IT data, customer data, customer feedback, support tickets. And we leverage all of that, send that data into Seth, and then use the machine learning on top of Seth in order to process it. We have a bunch of different mechanisms for getting that data into Seth. Some of it is through Jenkins. Some of it's through other types of workflow managers, and it just seamlessly moves that data into the object store. I'll show some examples of that as well. In order to start out with Seth, the first thing you'll do is you'll actually configure it from an object storage perspective to be ready to ingest your data.  I think some of you have seen that before, but I do have a link on the slides. If you want more information about installing it, I'll just step into the part about setting up a user, and then actually after you have your user set up, then just getting your data loaded into the system. So once you have Seth object storage installed, you have to make sure the object gateway is installed. And then once you have that, you wanna set up one of your users with S3 access. And in this case, it's just a quick command that you might run where you would create your user in the Seth S3 environment. And when you do that, what you'll get back is an access key and a secret key. That is just like as if you were working in any other S3 environment, AWS or anything else, and that access key and that secret key is the important part about letting you actually write and read data from the Seth environment. So from there, what I'm going to show really quickly is I actually have, let's do a clear here, and hopefully you guys will be able to see this okay. I'll try it. Yeah, it looks pretty good. All right. So in here, what's that? Oh, whoa, that's weird. Yeah, that seriously cleared it out. Oh, that's weird. Still in all kinds of funky stuff here. All right, can you see it? Okay, that's good. So I'm gonna show really quickly as I have a bucket that I have, let's see. Oh, sorry about that. In the Massachusetts Open Cloud, in that bucket, we just called it Open Data Hub. And since I'm using SAP instead of AWS, what you'll see here is I'm actually using the AWS command line interface. And you would go through the typical steps of setting up and configuring the AWS command line interface. Actually, I'll just tell you to show your step real quick and Steven touched up on this before. You would typically do an AWS configure where you take that secret key and that access key that I showed you in the previous step and you would just populate that information. I'm not gonna actually show my secret keys here, but you'll get the idea. Yeah, I know it has awesome data in it though, trust me. So once I do that and have it all set up, then I do an AWS LS. You'll see here for my training subdirectory, I actually have no data in there. So what I wanna do really quickly is just upload some training data that I have here. And I'm going to just run this command here. What it's going to do is upload a tab separated value table called training data. This is actually some data that we're using for doing sentiment analysis. And you'll see that as I work through the example. However, there's all kinds of different formats of data. I'm just using tab separated values right here. You could use snappy compression with parquet. It can be JSON. It could be CSV files. Anything that is typically supported by a lot of the Hadoop ecosystem. Now that I've uploaded that, you'll see I actually have my training data there. Great, awesome. Yeah, uploaded data. Now what? Well, here's where you start to analyze that data. And a little bit of what Boschek and Steven has shown before, you will then start to use Jupyter Hub. Jupyter Hub is cool. It allows us to integrate with Ceph and actually query the data and use tools like Spark, TensorFlow, Scikit Learn, all of those other frameworks in order to process the data. For this example, I'm gonna stick with Spark and you'll see I'm actually accessing the data in Ceph by using the S3n libraries and jars in order to get access to it. So very simple concept there. And what I'm going to do is show you really quickly what we've done as part of the work for the MOC deployment. So here I'm logged into an OpenShift instance and this wouldn't necessarily be a data science role but it'd be more of the DevOps systems engineer type of role. We've actually created an APB that allows us to go through the service catalog and find Jupyter Hub down here. So what I'm gonna do is I'm gonna create a quick project here and I'm just gonna name it Jupyter Hub and you'll see that project there and what I'm going to do is actually click on this service broker, select my projects and it will start to deploy Jupyter Hub. Now there's a couple of options that we have here. The database memory, Jupyter Hub memory, notebook memory. I'm gonna increase the notebook memory to two gig and then start to create this. Cool. Now it's actually starting to deploy my Jupyter Hub. You'll see it's pending and then you'll start to see some really interesting things happen once the pods start kicking off here in a second. So we have the, let's see, there we go. So the pod will start to initialize. You'll see with Jupyter Hub if you saw Voshik's example earlier today, you'll see that there was a number of different images that you could have. We have a TensorFlow image, we have a Scikit learn image, we have a Spark image and so this is actually building all of those images behind the scenes, preparing Jupyter Hub for you and also creating a Spark operator. That's Spark operator. Once we actually started notebook that has Spark in it, at that point each individual user will have their own Spark cluster that spins up behind the scenes. So as that's running, I'm actually gonna shoot over to a different instance of OpenShift that I have since this is still running and getting started. I wanna show you exactly what it looks like when you start to get into Jupyter Hub, so I'm gonna go back here in a second. Once Jupyter Hub actually starts up, in fact I will, actually I'm not gonna, I'm gonna just continue on my server. Once it starts up it gives you the option to select whichever image. I'm gonna skip that step because I've already selected a Spark image for the sake of time. And in this Spark image, I've created a notebook called Sentiment Analysis Training. I would love to take the credit for all the intelligence on here, but actually Subagit on our team was the data scientist that helped us create this. What this code is doing, I have no idea. All I just know is the end where it actually trains a model. So I'm gonna actually run this really quickly and just kinda step through the code and show you a little bit of magic behind the scenes here. First thing it's doing here is you do have the ability with Jupyter Hub to add a few more libraries that may not be on the image that you're using. In this case, we do have Spark and we do have Scikit Learn installed, but we do not have TensorFlow and Keras and some of the other ones. So what I've done here is I'm going through and installing those on the system and then it goes down a little bit farther and starts to import some of those libraries. Here's where a lot of the magic happens with Cep. You'll see here, I'm actually instantiating a PySpark instance and what it's doing is actually leveraging the Spark that's already on my Jupyter Hub. So if I go here to my Jupyter Hub instance, you will see that there is a Spark cluster for SH Griffey, that's me, that's me. So I've got my Spark cluster and I am submitting my job to that but you'll also see there's some other people, S Hewls, that's Stephen Hewls and then we have a couple of other people that are in the system here. So what it's done here, I've actually used the S3N, sorry, I said S3N but it's actually S3A, the newer one. I've used S3A to actually connect to Cep. In this case, I'm reading a CSV file and it's just doing some basic printing, some validation, hey, here's what the CSV file looks like. Farther down, I'm using a little bit of pandas and then shows you what some of the data looks like. That data is stored in Cep but now I'm reading it and you see some of the contents of it. And then it does all the data science-y stuff and then it shows some graphs. I like graphs so I was like, oh, that looks cool. Don't know what it tells me but it looks cool. And it continues down, we've got some more graphs here. The interesting thing is when we're doing the sentiment analysis training, we have to understand whether the accuracy of this is pretty good, is this a good model that we're working towards or are we having trouble with the model and we need to refine it. In this case, the example that I'm running through right here, we don't have much data in the system so I'm not gonna get too much into it but this will show you some of the cool things we can do with the data. We're showing a little word cloud where we're actually detecting what's being talked about in the training data. But as it goes a little bit farther down, you'll see it starts to build out the models and that happens somewhere around here where it's actually building the model, it's gonna run the model. This is where, going back to that diagram, you would do some tuning and manipulation to make sure that the model is accurate and then at the bottom here, once it's actually done, it's almost there, it's at step 83, it's finished with that. You'll see the accuracy printed out. Accuracy of 69, maybe that's good, maybe that's not, I would say it's probably not good, I'm not a data scientist. But that'll tell you, as you get more data in there, as you train the model, you can do some cool things there. So now I've got a great model and I need to do something with it. What's the next step? Well, in this environment, what we would do is, since we already have Seth, we're actually gonna store the model in Seth as well. And that allows us to get access to the model from any number of places. We can use OpenWisk, we can use any basic Python code, we can use Java code, whatever we want. And it's agnostic at that point. So storing the data in the model in Seth, what we're doing here is pickling the tokenizers and the models and storing that there. And the outcome of this, if I go back to my Amazon CLI, I'm gonna do an LS on the model folder. Oh, man, sorry about that, guys. Let's just shrink this and see if you can see a little bit better. Does that work better? Is that good? Okay, awesome. All right, now my screen's all jacked up. Oh, let's see here. You still see that? Okay, cool. All right, so what I'm gonna do here is I have a, I'll do a list on this and you'll see I've got a number of folders. I have data sets, metrics, models and training. So now I'm gonna look at my models folder and I see that I have some sentiment data there and then I'm gonna go to the sentiment folder. I'm sorry, left out a slash. And now you see, okay, great. I have my model, I have my dimensions, I have my tokenizer. Okay, so what do we do with that? So we go back to here. Now we wanna talk about how do we deploy the model and make it useful. In this use case, I'm using OpenWisk, which is a serverless action. I mentioned that earlier. But again, you can use any number of things. If you wanted to use Argo, if you wanted to use NIFI or any of those technologies, as long as you can get access to the data in SEF, that's great. Sometimes you may wanna even cache the model, maybe put it into some kind of caching layer, then you can do that as well. So the first thing I'm gonna do with the OpenWisk is I'm gonna actually show you a quick and easy way to deploy it. So I'm gonna go back to my OpenShift here and I will create a new project called SHGriffy OpenWisk. And you see that project has been created right there. So I'm gonna go back to the command line. I'm just gonna copy this command really quickly and I'll explain what it's gonna do. And I am just going to use the OpenShift command line interface to actually deploy this. Recently, the OpenWisk project that was done on top of OpenShift has moved into Incubator at Apache. So if you actually search for OpenWisk with OpenShift on Apache, then it'll come up. What I'm doing right here is I'm just taking that master template and I'm deploying OpenShift. So I'm deploying OpenWisk on top of that. And let's see, so, and what you will see here is it instantly started creating a lot of different deployments. You have Nginx, Strimsy, if you're not familiar with Strimsy, that is the Kubernetes Kafka that's also been worked on from a lot of the Redhead folks and it has CouchDB and a number of other things. What you see in the background here just starts to spin up a bunch of different pods. But again, for the sake of time, I won't focus on waiting for this to be done. I have another instance where this is already up and running. Once I have the OpenWisk environment all set up, then you actually use the OpenWisk command line interface to take a look and see exactly how to deploy the system. So what I have here is I have some code that is actually going to consume that model and actually run a sentiment analysis on top of that using the model. Up here you'll see some code where it says analyze sentiment. This is actually where it will load the model and start to feed in the text that I pass it and then I have some additional information here where it's just taking some command line arguments. Nothing fancy, just a quick example to show you. In order to deploy the OpenWisk Python code that I just showed you, you just run a couple of commands here so I'm actually going to create an action and I'll kind of step through exactly what this is doing. In OpenWisk everything is just an action. So I showed you the Python code, very simple code. I don't want to have to worry about spinning up my own engine X, my own web interface, all of the REST API that has to go along with it. So I can take that Python code and you'll see here what I'm doing is I have the name of the action called sentiment as service and then I have main.python and I actually already have a Docker image that has some of the model libraries, it has TensorFlow, it has Keras already installed on that Docker image. So I'm going to do a quick deployment of that. Boom, there you go, it's already deployed. So once I want to actually test it because OpenWisk comes with a REST API, I am going to use postman. Hopefully you guys can see that okay, man that's a really big postman. So I have two different postman commands here and all I'm doing in postman is a post with a to a REST endpoint. In this REST endpoint you see I'm now pointing to the sentiment service and I'm giving it some credentials. These are my OpenWisk credentials and the body of it is just some text that I want to pass in that I want to send them an analysis on. I'll send that along the way and down here I have an activation ID. Now if you saw it, you may not have seen it but really quickly it's starting to build up if I go over here. I'm going to go up to the OpenWisk project. It spins up a pod automatically and there's my sentiment service running in OpenWisk and it's actually doing some analysis right here. It's loading up the models, you see it loaded the model and it's actually using TensorFlow as well to start to process the data. As that's running I can then poll and see well what's going on with the action so I'm going to take that activation ID, it's basically like an execution ID and replace that with just the one that I copied here and I'm going to do a get. When I do a get to OpenWisk to see what's going on with that service it'll, well it says it's not exist until it's actually done here so I'll just keep sending it until it completes. All right we got a 200 there and now what you'll see is the result of that action. There's a little bit of metadata that OpenWisk provides but then at the end of the day you see here my results sentiment equals positive. Now the way that we've used this in Red Hat is we have a sentiment analysis service that sits out there in OpenWisk and as people are submitting their request they're actually calling to our REST API in OpenWisk to get results back. We do a lot more than just this sentiment analysis that I've shown here, we do entity detection as well so that we understand for the given text what are people talking about? Is there a good feeling about Red Hat? Great feeling about OpenShift? What do people think about DevConf? And it gives you a great way to analyze the data. But to bring it all back home now we have an entire process and where we've built the model we've actually uploaded the data, built the model and deployed it. So going back to what we had in the original slide it gives you the pipeline and what we've done here is for the storing of the data and the models we're using Ceph to develop, tune and train the models we're using a combination of Spark and Jupyter Hub and then to deploy the model into the rest of the environment to actually make it usable is OpenWisk. Obviously for this use case there's a number of different users that you might have in the system where your engineers, your data engineers may be more focused on the Ceph side and then your data scientists will be in the Spark and the Jupyter Hub side and then for the DevOps and the data engineers as well they'll be involved in the OpenWisk side so you'll have a number of different people involved in it but that's teamwork, right? So that's all I have. If you want more information we are starting to publish a lot of what we're doing inside the Data Hub to the Open Data Hub project and just to let you know a lot of what I walk through here is part of the Open Data Hub project so Stephen mentioned it before with the MOC and we've seen a lot of it as we've gone through the past couple of days so you'll see more and more information and more code being submitted into that repo and of course if anyone wants to contribute feel free to join us. We also have a lot of information about Spark on Kubernetes and OpenShift you can see that in the RadAnalytics.io page you can also take a look at the now incubating OpenWisk on OpenShift project and contribute in that way. At the end of the day you can always just contact me shgriffy at redhead.com. Any questions? That was awesome. Live demo on the Mass Open Cloud, that's the coolest thing ever.  So we're running Data Hub on the Mass Open Cloud Sherrard and I know many of you probably don't that the infrastructure we're using right now on Mass Open Cloud isn't necessarily ideal for machine learning, training models, that kind of thing. If you could have whatever you wanted up there within sort of reason, what kind of architecture would you like to see? Is it storage? Is it vector processing? Like where do we need to go now? Yeah, I think that's an interesting one and the reason I'm so excited about the MOC is I actually would like to see the users tell us that. I think we'll certainly be doing some performance evaluation on the workloads that are happening on the MOC. I have a feeling that we're going to explore more about Ceph and the storage on Ceph. There is going to be a knowledge sharing that has to happen where we have to understand the best way to store this data. I mentioned before you could have a tab separated value table or CSV file. But there's other technologies that will allow you to process the data better, more column there formatted data like snappy compression with parquet, things like that. But from the physical hardware perspective, we'll certainly want to move more into the GPU enablement, FPGA type of enablement of the system. So it'd be great if we start to leverage some of those technologies as well. That will allow everyone to do work faster. And I think that's going to be the nice blend of having the right storage for your data, but then also having the right compute horsepower in order to make it happen. Any other questions? My question is mostly around data acquisition. We are currently using, I mean, in your example, we are using training data. So what kind of data normalization or cleansing components can be used in the OpenShift enablement? Good question. The simplest answer to that, Spark is great for ETL. We've used that internally at Red Hat for a number of our products. And I think in this use case, it's great as well. The nice thing being, again, you've separated the storage from the compute. So you can have Spark. You can do your cleansing. You do your manipulation of the data. And then what you would want from that is more of a workflow manager to manage those Spark jobs as it's flowing through the system. Some of the other technologies that we are looking into is the ability to do Hive on Spark. So you can take a Hive job in Kubernetes, but use Spark as the framework to do that and manipulate the data from there. A lot of people are just more comfortable using Hive as opposed to Spark. And there's some other technologies that we're looking at, but it gives you a good baseline to go off of. So you mentioned OpenWISC on OpenShift as kind of an alpha project. Yes. So what's missing there? What major problems am I going to run into if I try to use it for something I depend on? The major issues I've seen, honestly, is how fast is being developed. I'm actually excited the fact that it's moved to Incubator because before then, if I deploy it today versus next week, things may break and there may be some inconsistencies there. So I think Incubator will give us a little bit of a better chance to version things off. It has a lot of support for multiple languages, Java, Python, some of the other ones, Node.js. I think the missing thing may be just putting it through the ringer of a real use case and see how it scales. And then also, we're working through the exercise of hooking up Prometheus to a lot of these as well to make sure we can monitor the system. So I think, really, it seems to be in a final, finally in more of a stable state. This has been the development on that's been going on for a year now. So I think it's starting to level off and you get a little bit more stability there. Okay, thank you, Sharad. Amazing talk. Thank you, thank you. Thank you. Mr. Reminder to everyone, the party is tonight. It is in the Ziscon Lounge. It is at 7 p.m. It is going to be the funnest party ever, full stop. So please do show up. We actually have lots of fun things. I'm not making that up. Chloe is on the fun committee. She could tell you more if you wanna ask her. Anyway, so please do turn up for that and also do not forget the keynote tomorrow morning, which is with Chris Wright and Saran, what is her last name? My mind is jelly. Anyway, it's gonna be really good. So turn up for that as well. Thanks.


Well, good morning. Thank you for coming from my presentation. My name is José Manuel Ortega. I come from Spain. This is my first time here in Fosdem. This tool is oriented for security researchers, analysis that are interested in noticing open source intelligence with FACPEN. Well, this tool is a complement that was made for the European Python last year. The link is available in my personal site. This tool that was made last year is oriented to pen testing with Python, the main tools that we have in Python, and what are the main modules that we can use for develop our own pen testing tool. Well, some of the samples that I will comment in this presentation are available in my personal jihad repository. Well, I comment some of these samples, like the Shodan, starting metadata from images and documents, and for example, the obtained information from jihad repositories for a specific user or company. Well, this is the main tool. The main points I will talk. I will make a little introduction to what is OSEAN or definition. Later, I will comment what are the main sites that provide server information, public information that is available on the internet, and services like census and so on provide and recover all the information that is servers, operating systems and so on. Later, I will comment what are the main tools that we can find in Python ecosystem for OSEAN. And later, some samples for obtained geolocation, starting metadata from documents, and other tools for footprinting. What is OSEAN? Basically, OSEAN is the acronym of Open Source Intelligent, and with OSEAN we can extract in general information from social networks and in general public sources that are available on the internet. We can obtain technical data from servers, service, software operating systems, all other information related with social media, emails, photos from social networks, IP addresses, footprinting information from services, and other information related with network and operational intelligence. Good information we can extract with OSEAN techniques. For example, the geolocation of a server or a service, the IP address, email address of a person, the telephone number of a specific company or user, user names in social network profiles. Also, we can obtain extract metadata information from images and documents, and finally, obtain in general server information and extract, obtain vulnerabilities in the service. Well, I'm starting with Censis. Censis basically provides a lot of information about Censis internally. What is that? It's crawling the web, obtaining information about IP addresses, how it serves, and so on. And save this information in other ways. Basically, it provides a decent 600 gigabytes and all information about IP addresses, certificates, location of the servers, and so on. In an easy way with Censis, Censis provides a recipe for obtaining information. For example, if we want to obtain the information from an IP address or domain, we can use this recipe. In this example, we can see that from a specific domain, we can obtain the geolocation of the domain. Information related with certificates about the site, subdomains. Also, we can obtain this kind of information. Sodan is another service like Censis. Sodan provides another database for recovering all this information that is available on the internet. All this information is fully. And Sodan also provides this. With Sodan, we can find more in Python. We have a Sodan module that we can use for searching in Sodan API with Python. We need to register in Sodan site and obtain a Sodan API key. And with this API key, we can make a search by host, by IP address, and so on. And in general, all information we can obtain if we can obtain the organization, the operating system, and in general, all partners, servers that provide this site. For example, if we try to look for the domain, we obtain the organization, the operating system, where the server is executing. And for each port, if it's open, the port detects the banner of the port. The server, the operating system, and so on. All this information about Sodan is available also if we search in Sodan.io, is that host. We can check the data, this data with passing the IP address. And the information is the same. We show that also we can detect vulnerabilities that are available in the common vulnerability and exposure that there is. Also, we can check, we can obtain this information. For example, if the server is executing an open SSL version that has vulnerabilities with this script, with this simple script, we can check this kind of vulnerability. Sodan also provides a developer API. Instead of using the Python module, we can use a classical recipe for making the request. For example, if we want to obtain the last search that users made in Sodan services, we can use that specific recipe called query search that retours all the requests that users are executing in Sodan. Well, the next tool that we come in, well, this is the first tool that we come in that is developing in Python. ReconNG, ReconNG is one of the most known open source intelligence. It is very maintained. It's available in feedback repository. And internally, the architecture of this tool is based in modules. And recollect all information in database. This tool is developed in Python 2 and the main modules that it's using. We can highlight, for example, Dennis Python, LSML for passing the information. Also other tools like Metcanize, PyPathetic, for extracting metadata from PDFs, documents, and SQLite for persisting the data. Well, the architectural record of this tool is based in modules. If we type in the console showModules, it shows information what are the modules available in this tool. We have modules for discovery information, for exploit, for exploit also. Other tools, other modules that we have are, for example, contacts, obtain credentials, obtain domains, or obtain some domains for a specific target. Recollect contacts for a specific email address, for example. In this example, we can see that with the Freo J-O-E-P module, we can extract the geolocation of the forced-end.org domain. Basically what this module provides are options. They are default options. But, for example, if we want to extract information for a specific domain, we need to set the server URL parameter. Also, we can extract some domains for a specific domain. In this case, it's using the api.hacker.target.slaghost.search. The idea is to obtain all two domains that are in the main domain that we are analyzing. Also, this tool is integrated with Shodan API. With Shodan API, we can also obtain the subdomains for a specific domain. In this example, we can see that extracts subdomains, other hosts that we were in the site, IP addresses in version four and six. Another interesting tool for starting with those in tennis in Python is the Harvester. The Harvester is one of the main tools for obtaining, for example, information about email addresses, subdomains, and so on. Basically, the Harvester tool is developed in a modular way. We can find modules, we can find files for making search in Google Search, in Bing, in other social networks like LinkedIn, Twitter, Shodan. The main modules that are used for developing this tool are HTTP live, socket requests, and so on. In this example, we can see that, for example, emails for a specific domain, and other subdomains, or hosts, or other IP addresses. For example, with the v-parameter, we can specify the search engine that we want to use. In this case, we are using the Google search engine over the domain Python.org, and with the l-parameter, we can specify the limit of the results. In this example, we can see that in a nice way we can extract all information of the domain. Another tool in the rest team, well, this tool is developed by a group of people, of research people in Spain, in a group of security researchers. This tool is available in GitHub repository, and we can install this tool with PIP. It's developed in Python 2.7, and integrates with Maltego transfers for obtaining more information with the target that we are analyzing. The main modules that this tool is using are, for example, a beautiful suit for passing the data of the web, requests, mechanize, Python s, Python who is for recording information, who is information about the specific domain, Tweetpy for connecting with Twitter, Skype for Py for connecting with Skype. Another, for example, Python in my life for checking email addresses. This tool has some scripts that we can execute. These scripts can execute separately each one of them. For example, if we want to obtain, we have the search.py script. If we want to, we need to extract the information about specific user or specific domain. You can use the P-parameter with Twitter for searching all the accounts that match with the first name. And retouch all the accounts in Twitter that match with the Twitter account. We have another script related with the previous script that we find with the first name. It retouches all the other network profiles, other social network profiles that match with this name. This tool has the capacity to connect with more than 2,000 platforms in general, social networks. And it has the capacity to find all this information, to find this information in a lot of platforms. Well, this tool I'm commenting now is developed also in Python 2.7. Python 4 is oriented to tax footprinting tax for discovering subdomains. Another information related with the target that we are analyzing. Internally, it's using beautiful suit and spy tones, sockets, cherry pie for building the website. And another model, for example, NetAdress or PyPE for extracting metadata from previous documents. This tool has the capacity to connect with many data source for extracting all data. It has the capacity to connect with many data source and match relation of all results in a graphical way. For example, if we want to extract, we want to share, for example, all the repositories related with the domain that we are analyzing. We can use this tool for obtaining these kind of results. In this example, we are obtaining Jihad repositories related with the domain that we are analyzing. And also in a graphical way, we can obtain, we can see the relation between FOSDEM.org domain and other subdomains, social networks, social profile networks. For example, if we want to extract information about a specific author in a Jihad repository, we can use the api.jihad.com or slash users, and in an easy way we can obtain information like this. For example, if we want to share by FOSDEM domain, we can see the results by this. We obtain user URL, deployment URL, and other URLs related with the target way that we are analyzing. For starting Metadata, well, basically we can extract Metadata where we are analyzing or researching in obtaining Metadata. We have two modules, one PPF2 and PDFminer for starting Metadata from PDFs and for starting Metadata from Image, we have some modules. For example, we have PILO and PES6-2 in Python 2.7. And if we need to go to Python 3, we have GX6-2. In this example, we can see that we are extracting Metadata from Image and obtaining, for example, the GPS info with the latitude and longitude values and other information that is stored in the image inside. For obtaining J-location, also we have the JOP2 module. Basically with this module, we can specify the IP address and in return, all the J-location of these IP addresses. In return, city, country, a lot of information related with J-location. Internal age is needed to use a file called geolittlecity.mmdb. This is like a database that has a lot of information with the relation between IP addresses and the geolocation of these IP addresses. Well, until now, all tools that I have seen are developed in Python 2. But the question is, is it possible to develop a tool of this kind in Python 3? Yes, the question is yes, it's possible. We have a beautiful tool for passing word information. We have a request or a URL for synchronous request. We have a SYNCHIO or IHTP for asynchronous. We have a Scrappy for webcrowling or Robo-Broser. We have a BOGP for geolocation. We have another modules for connecting with social networks like P2N Twitter or Tweetpy. All these modules are compatible with Python 3. And the answer is yes. This is one of the tools that I have seen that are developed in Python 3. It's called Web of Information Gather. And it's a very simple tool that what it does is recovering all basic information about a specific website. Indec.dex, the operating system, the version of the server that is executing, subdomains of the site and struct more information related with this site. And finally, we want to extract information for Twitter. For example, we have TeamFolik. TeamFolik is developed by a Spanish security researcher. And it provides many parameters. For example, we can filter the result by star or end date. We can find information about specific user account like hashtags, mentors, metadata information from image and media. Well, for finishing, for using this tool, we need to configure this a little file for where we need to put the typical information about a consumer key as a stock end that we can find in the developer Twitter API. Also, we can extract your location. If the user is the account of the user is activated, the location of the user is activated in user accounts. We can obtain this coordination, location, latitude, longitude. And finally, the full content API provides another way of extract information about a person from an email address. In an easy way, we can, for example, obtain all the information about the specific email, the employees of this person, other social networks, other social profile networks of this person. Also, this API, we can use this API for extracting information from a specific domain. In this case, we are extracting what are the social networks that match with this domain. Well, all these tools, some of the tools that I comment are available in Kalininux, like, for example, we can find ReconNG, the harvester, are available in Kalininux. And that's all. These are the references and the books. Thank you. Some questions? No?


is it stir up that's on live, live hello, hi, we're live, good, good to know hello everybody, CES crew here, reporting for duty good role in MB you can, does that pop up on your screen Tom, if I if I click on the white shot of the floor right now I see you, yeah if you click on the white shot of the floor holy crap yeah, you're gonna have to look at the live stream because I get a different present oh, I see what you're saying oh, for me, uh nope but, uh, yeah, the details on the shot ah, no, I don't usually look at the shot oh, uh, I received that chat wrong button about 10 minutes away from the show so, yeah, that does not pop up on the live stream if I select, oh, wait a minute, you know what, no, I can't present to everyone that's what I have to do got it, got it oh, look at that, we can see this show floor when Roger does that why isn't it switching to me when I talk? oh, because you're overriding me, that's why yes so if you mention the white shot, I'll yeah, yeah that way it won't make any confusion let's make sure it actually goes back to me when I talk to yeah, there we go nice, I'm gonna lie perfect, oh, it's looking good so, Tom except for the cable management do you want me to order the CES quick hits just in terms of what's written? uh, okay so DJI for sure has to be there Paul, if you had a favorite down there in those CES hits let us know I think TCL and Sony need to be in there I'd paint you that other one about the shoes I don't know if you saw that I did not see that but they might not be room for it yeah all right, so uh, JBL I don't care about the JBL it's just more that the Google Bank shoved into things okay, the signal, yeah and we gotta have Moen up there, right? okay, so yes up to my hip air you can order up after that okay what's the X mean? oh, that's just don't move, those are definitely in no it marks the spot AT&T reportedly won't sell Huawei phones after all oh, they won't wow there's been big noises coming out of Huawei that there was what was gonna happen all right, cool so there are no time queues, Tom so yeah, you should come up with some I meant to ask you about that earlier sorry, yeah, it was um, DTMS I received that chat room oh, the chat room is a pound chat it gives you 10 minutes on the news a good time for quick hits are we leaving any gap for anything from Samsung or it's gonna be a bit hard we'll be wrapped by the time they finish saying hello I was just thinking they might have an embargo, Lyft keep an eye out for it Roger's gonna keep an eye out for that yeah, I'll get the email at the second wait, what am I doing? keeping an eye out for HTC and Samsung they've got the 146th TV that was yesterday um okay I'm trying to put it in um, swap I'll get the email from Samsung they always email me like 1 minute into there I just gave that I pinged on our quick hits perfect, thank you you don't have to worry about the HTC step till it'll happen I thought it was more public when I just said HTC and it was blank okay to the HTC for Hater no I'm gonna give you 3 minutes on NVIDIA and 3 minutes on LG and I'll set up NVIDIA Sarah, you set up LG sure, cool all right and Peter it's thing Q AI, right? because he made that joke like he came for coming yeah, no it's thing so that was just a joke so DeepThink was their own AI platform sorry, their own AI service and Think was actually, maybe it was Anyway, Think was the platform itself which is allowing Alexa and Hone to be on which is way easier to say yeah all right, um we can start early I'm not gonna know where my no 93 members, wow yeah, we're not even early nope I know, this is the way it goes yes, please we don't have a live link at DailyTechNewShow.com yeah, but if you go to DailyTechNewShow.com where's the live link we'll do that another day year 5 yeah all right, Sarah can you do the powered by you let me know I'm ready okay, here we go 3, 2, DailyTechNewShow is powered by you to find out more, head to DailyTechNewShow.com slash support this is the DailyTech news for Monday, January 8, 2018 from Las Vegas Convention Center in Las Vegas, Nevada I'm Tom Merritt Sarah Lane, nice and cozy in our little broadcast tower everybody on the show today is from the same place we're actually in unincorporated Clark County that's cracks, we're not in Las Vegas Peter Wells is here as well from Sydney Morning Herald, how's it going, Peter I'm very well, Thomas, how are you and how are your feet wait, I'm not supposed to ask that we have an email about that we're actually gonna get to that later on the show Paul Spain, how are you a host of the New Zealand tech podcast in Z, in Z depends where you're from yep, that's good to be here, always fun being at CES excellent, our producer Roger Chang is making all this happen over there in the corner thank you Roger hello I'm behind them all right, let's start with a view tech things you should know Google announced it will combine Android Pay and Google Wallet into a single service called Google Pay, payment info saved to your Google account will be available in any Google services including YouTube and Android Apple released iOS 11.2.2 and a supplemental update to macOS high Sierra 10.13.2 with Safari and WebKit mitigations for the specter chip vulnerability, so now they have mitigations for Meltdown and Spectre GoPro expects lower fourth quarter revenue due to weaker demand for its cameras and drones over the holidays and actually plans to exit the drone business all together and cut more than 250 jobs GoPro plans to sell the existing Karma drone inventory as part of a restructure the company also cut the price of its latest hero 6 camera from $400 from $500 rather to $400 GoPro founder and CEO Nick Woodman told CNBC Monday he was open to selling the company and CNBC reports that GoPro has hired JP Morgan to explore some options former Google employees James Daymore and David Gudeman are suing Google for unfairly discriminating against them based on their race and political views Daymore was fired in August after posting women in engineering to an internal message board Apple shareholders Jane Pajana partners rather and California state teachers retirement system sent a letter to Apple January 6th asking the company to create ways for parents to restrict children's access to their mobile phones iPhones in particular and study the effects of heavy phone usage on mental health sources tell TechCrunch the Telegram plans to launch its own blockchain platform and native cryptocurrency for payments within the Telegram Open Network. Telegram users could bypass remittance fees with sending funds across international borders move sums of money privately and deliver micro payments that bypass credit card fees. Facebook has reached a deal with Sony for music streaming. The company previously reached a deal with Universal leaving Warner as the only remaining of the three major music labels to sign on. Facebook is also shutting down M its messenger based virtual assistant that combined human operators with AI. The last day of service for M is January 19th. Goodbye M. Bye M. And PowerMAT has joined the wireless power consortium which developed the Qi standard. PowerMAT developed the PMA air fuel standard the major alternative to Qi. PowerMAT will contribute technology to the standard and maintain backwards compatibility with Qi. Apple signed on to Qi last year and PowerMAT cited this in its statement on the matter. And that all is the non-CES news. How about that? Kind of a big day for non-CES news. Here are even more CES news. Some more top stories. AMD and Intel announced the 8th generation Intel core processor with Radeon RX Vega-M graphics. It's the Kaby Lake R chip with a Radeon RX Vega-MGH or RX Vega-MGL GPU that's GH non-GH. Connected to 4GB of HBM-2 VRAM. Intel is launching 5 versions with the inclusion of AMD graphics noted by G at the end of the year. R-CPUs will have the Intel HD graphics 630 integrated chip still in there even though they have the Vega which can be used for low power needs. A new NUC with the chip should be available this spring. Now we've got some other AMD announcements I want to let people know about but this was the big one. Everybody's been waiting for this discreet AMD Intel combo here. What do you guys think of it? I think this is a pretty cool tie up. I mean we see more and more of these across the tech industry especially with the bigger players that have got their fingers in lots of different pies and they seem reasonably comfortable to partner up and work together. And look you know in terms of getting a more powerful machine that doesn't use too much battery and it's all incorporated and this makes a lot of sense and I think probably going to be good value as well. I think it's also just the perfect chip for Apple's suite of laptop computers. They've generally used Radeon chips for graphics processors with Intel chips as well so this is the first time I don't know it looks like a chip that could very easily slip into one of these MacBook Pros because of course MacBook Pros have never had the greatest graphics capabilities in terms of gaming which is what people want. It is what that is meant for I don't get my gut feeling this is not based on anything in particular that Apple will go for this for some reason I don't know why. I guess only in the 15 inches do they tend to have that option of the better graphics. HP, Asus and Acer all plan to bring Amazon voice services to their Windows PCs this year. Acer will roll out to select Aspire notebooks and all-in-wanners. HP will add it to the Pavilion Waves desktop which doubles as an audio speaker and Asus will bring it to select 2018 ZenBook and VivoBook laptops as well as the Lyra Voice Wi-Fi system and Voice Assistant. Amazon and Microsoft have been working together to integrate AVS and Cortana. So maybe Microsoft won't like this maybe they will like this. I can't really tell because they are cooperating but this is Amazon moving even farther like on Windows laptops here just use Amazon instead. Yeah I think it's certainly going to make things harder for Cortana when we see Amazon just becoming so dominant with Alexa. The idea is that Cortana is good for things that she is not she who shall not be named is not and so maybe this is the ideal situation. Is this one of those the enemy of my enemy is my friend things where they don't want Google to be sneaking into laptops so yeah partner up with Amazon that seems to be the biggest competitor right now. Yeah and if you already have an Echo or something like that you know that could be good for you. Let's start off its e-Pallet autonomous concept electric car resembling a small shuttle not a space shuttle like you know bus shuttle. It has a modular interior that can be used for ride hailing cargo transport on-demand delivery even mobile hotel rooms was one of the use cases they suggested that it might be used for I'm not sure that I would use it for that the e-Pallet comes in different sizes as well so you could have a smaller one for something like pizza delivery a larger one for your luxury hotel room for the early 2020s and they also up to show it off the Tokyo Olympic Games which is also in 2020. Well I'm trying to understand how the mobile hotel room would work where would it be it still has to physically be somewhere I guess it just drives around town and you just sort of soothe to sleep maybe if you don't use it instead of you know jumping on a plane or you know a short short journey that is like a you know sleeper and a train so you just you know it picks you up at your door in San Francisco you wake up in the morning or the next hours later and you're in Los Angeles that's cool you know it's like Amtrak for the rest of us well is it for the rest of us it might not be cheap we're getting to the point where there's like these solutions where I go like what's the problem what is this for I'm really believed to the weirdest one of these you know the more mundane cargo transport ride hailing etc I think this is interesting the Toyota is starting to show off like hey here's some enterprise level stuff here's some transport problem stuff not just personal use cases this is the kind of thing that sometimes feels like it might be the first self-driving cars a lot of people ride in because companies that operate tours or shuttle systems might jump on this when they can't develop their own well it wouldn't be CES without a really big television that will never fit in any of our houses but hey I can't speak for you out there at home Samsung has a 146 inch 4k micro LED wall that's actually called the wall micro LED is similar to OLED it doesn't need a backlight so it's similar to how video billboards are made but with smaller LEDs so you can't see the pixels unless you're within a foot or so of the display Samsung says the wall is a consumer product and available for purchase sometime this year with more detail coming in the spring it's somehow modular which allows you to start with a few panels and then add them as you need a bigger and bigger television that's pretty cool no details released on how this actually works though so in concept it's cool anyway Samsung also has two 8k proof of concept models the Q9S which can upscale any video including standard f to look crisp in 8k okay I mean big TVs obviously always a standard right like you said but modular modular screens like that I've seen a couple of ideas like this along along the way but this is the the I don't know if it's the highest profile one but this is the one where it feels like okay I'd like some details on how you're really going to make this work but if they're doing it over there in their booth well and the idea that and I know we there's some question about how the modular interface is actually working but depending on hey I'm not even necessarily always going bigger with a TV maybe the TV for whatever reason you moved to a new place you've got wall space that's not quite right take a little bit off of that eBay those extra panels put them in storage or whatever you need to do could you make them into a separate TV in the other room well break it down and sort of spread them around when you can't all agree on what to watch it's like a worm and then it's two worms and they come over and you give them one panel there you go snap one off take it to holidays little one you can squeeze in your pocket it is fascinating though and the micro LED thing is you know that I don't know that that will become the next wave it seems like quantum dot and Samsung has quantum dot TVs that they're showing off as well is probably the bigger deal but this that is interesting D-Link ASUS are all showing off 802.11 AX Wi-Fi routers 802.11 AX is in early development it's not set for a standard release until 2019 from IEEE but when it comes it can do about 3.2 gigabits per second or even depending on how it's implemented theoretically go up from 10 to 10 to 14 gigabits per second all on wireless it can support more devices at once and it has uploaded download parity, helps with congestion anyway 802.11 AX is supposed to solve all your wireless ills the D-Link AX 11000 Ultra promises to get you those speeds up to 11 gigabits per second over Wi-Fi it sort of looks like a stealth bomber with 8 antennas ASUS has the RTAX 88U that promises 6 gigabits per second there are no devices that work with 802.11 AX yet so hence they're not saying they're going to ship these routers until the second half of 2018 after maybe a phone or two come out with support I think this is great it's good to see this next generation of Wi-Fi coming along I've done a bit of reading behind the scenes on how it works and it really seems to be a bit of a rethinking on the Wi-Fi that we have today and of course we're used to new generations coming out sort of ahead of them being ratified and that helps bring the prices down just people a chance to test them and get early access so any announcements like this I'm looking forward to because Wi-Fi is still not the best today right? What do you think Peter? I just kind of wish that they would get a marketing team to come up with some better names for this stuff than 802.11 AX AX is all of your problems AX is to do anything AX is to do anything see you just need to work right there just start flashing the move on thing No you're right I mean it's not a fancy name but hey it's like all of these things whenever you're like 802.11 was the same way at 1.802.11 AC was the same play it's more than you need probably more than your internet service can deliver eventually it will come The drill of the CES booth being put together is telling us that we are done to get all tech headlines each day in about 5 minutes subscribe to dailytechheadlines.com We should have mentioned this the day before the show floor officially opened so people are literally putting together booths right around us so that's just how it goes Now we got a couple of the big press conferences already happening HTC is happening right now Samsung is going to happen right after we're done Sony's tonight but Nvidia had theirs yesterday and announced a couple of things of interest that we're going to talk about here one is a hardware initiative with Acer, ASUS and HP called the BFGD which I'm sure they're hoping people will misinterpret what it stands for but it actually stands for big format gaming displays it uses Nvidia G-Sync on a 65 inch 4K screen with 120Hz to give you HDR gaming terra-free. It's got shield platform built in Google assistant built in full direct day backlight 1000 nit peak luminance and DCI p3 color gamut to go on sale this summer so it's it could theoretically be a stand alone with shield built in because you can do some gaming right from the actual television but the idea is you could also pair it up with your computer and get the best of both worlds does this capture anyone's imagination here? I definitely want one. I don't think I could afford one or even fit one into the house so yeah it does look very very cool. I love saying I think gaming PCs are going to be pretty huge at CES this year I think just because it seems to be the last profitable area of PC gaming the PC market it's one of those areas where you've got your alienwares and companies like that that can actually charge a premium and people will pay that premium because there are a lot of nerds our age now who used to build their own systems don't have time for it anymore but do have a lot of money that they can throw on one of those gaming PCs and feels like a new product category to have not just a smart TV which is what this is with the shield built in but a smart capable gaming PC because paired with the GeForce streaming service or the shield version of the GeForce streaming service you can just play games within the television and of course they also expanded the beta test of the GeForce now streaming service that was the one they announced last year CES so starting this week beta users of the Mac client will be able to install and run the Windows app so you can have that on your PC and hook it up to the BFGD and do all kinds of crazy things What's interesting is that for the longest time real quick is that display technology has either been driven solely on a PC platform or consumer electronics with HDTV you kind of see kind of it slowly melding together I mean with HDTV it was supposed to do that already but no PC settled on the 16 by 10 aspect ratio while HDTV settled on the 16 by 9 and so there were some similarities you could use both but they weren't quite the exact same display well and I sorry I thought you were finished oh no no good because all I was going to add was we used to think well I don't know if I want my smart TV built into the TV I want a separate one and a lot of people still think that but smart TVs starting to sell well I don't know yeah I mean I was certainly one of those that thought the idea of smarts in the TV was not very smart but look I've got a smart TV now that's probably three years or so old and we still you know utilize that interface as well as the other things that applied into it and if you offload a lot of this stuff to the internet like with the GeForce Now or the Shield Service you don't need all the the guts in the TV to be all that it's like a thin bunch and NVIDIA also announced the autonomous driving Xavier system on a chip shipping to select customers there are two new Pegasus software platforms running on Xavier Drive IX interpret sensor data for users so like facial recognition, gaze tracking to change the environment so if you're actually driving you can tell if you're nodding off to sleep and wake you up stuff like that know where you're paying attention on the road also it could provide certain benefits to you even if you're just a passenger in a self-driving car Drive AR is where it really gets fun that's the augmented reality interface you can put up road conditions of interest on the windshield on the screen for you and it can provide entertainment if you're a passenger as well the Pegasus motherboard now packs two Xavier socks and two GPUs and a package the size of a license plate used to have to fit in the trunk so it's getting smaller they've got about 320 partners, VW is going to build on Drive IX, VW ID Buzz Electric Car will feature that Baidu and CarMaker ZF will use NVIDIA for Baidu's Apollo project that's their self-driving car and Uber has been using NVIDIA hardware in its AI systems NVIDIA is also collaborating with Aurora which is the former Google self-driving guy Chris Ermson's company on the self-driving platform so NVIDIA is certainly leading the way empowering autonomous cars yeah yeah this was actually the story of the year for me last year just because I know nothing about cars so I found it very fascinating to really deep dive into that car hall I think it's the north hall and really find out kind of the brains behind these new services and yeah NVIDIA just seems to have really grabbed that market and kind of by mistake but by accident that they didn't really understand that their GPUs were the ones being used in all of these manufacturing these car manufacturers and once they discovered that they went hard on it they seized the opportunity I love the idea of the Drive AR concept you imagine turning all of the glass within your car into augmented reality screens that could be kind of cool I mean if you've got a level 5 self-driving car taking care of the driving you can turn all those windows into video screens yeah I think Mercedes showed off a demo of that concept in the past but this is obviously the bits and pieces to make that work LG had its press conference bright and early this morning at 8am pacific time and speaking of smart LG's new branding for all of its smart products and services is called Think AI Think with a Q at the end of it and says there's three things that are great about it learn habits over time like a heating device or a cleaning device or car technology as it knows you its owner bringing AI to everyday products and then openness and working with other platforms one of the big other platforms being Google Assistant which is now going to be integrated into the new OLED displays I know Peter you were actually at the conference this morning what stuck out to you because we've got now a 65 inch LG rollable OLED display that was pretty cool just sort of a bigger version of what we had already seen a couple of years ago you impressed well actually the LG rollable display was from a company called LG display which is a technically a separate company to LG which is so strange but they always make that point it's part of the cable I think absolutely so they didn't have that on display this morning but they did talk I guess it was incredible how often they went back to Google Assistant and talking about how their platform is different to any of the other TV manufacturers out there because they are opening up their platform for everyone and they did mention Amazon Alexa once throughout the presentation and then not one of the examples they gave was about Amazon so it was interesting it was like yeah they're going to be there but look how awesome Google is and Google also had their own representative on stage as well so it was a decision that they made beforehand to just kind of put Google Assistant front and center new OLEDs also supporting also going to sport rather LG's new Elphin 9 processor the company says it's 35% faster in terms of both CPU and GPU and features 50% more memory and then of course support for 120 frames per second video and something they call 4K Cinema HDR which is optimized HDR for dynamic tone mapping and rollable, they showed the one that rolls up like a shade yes, I know do you want a rollable display that looks great, dynamic HDR why not do I have to pay for it though our car windows are videos now there's a slight challenge with all of these cool things they're a little bit pricey to start with but of course if we can find good relevant uses and they can go mass market then we can all have one a lot of emphasis too on robots at the LG press conference one was called Chloe it didn't do very well in the stage presentation our first big CES demo fail I was you know lots of jokes about this robot doesn't seem to like me very much but the idea is that people hopefully are more comfortable giving orders and getting information from something that resembles a robot that thinks and feels and is cute yeah, it was up on stage last year as well no information on this shipping I asked LG after the conference was over they still haven't mentioned it with shipping maybe they changed their mind after it played up on stage, who knows the InstaView ThinkQ it's hard because the queue is at the end it's hard to say if you thought smart refrigerators were a thing of the past Think No More has a 29 inch touch screen display that works as a hub for a lot of your other smart products at home and then the AI technology LG says we'll have proactive service meaning that instead of you having to call a technician if something's wrong that you don't know how to fix for an unknown issue in theory ThinkQ can detect the issue before it occurs and then send that info to a service center ahead of time and do your work for you now of course this would assume that it's always broken when the software says it is but assuming that it works properly I guess I could save you a few phone calls tell me what stands out to you the most I mean LG is underwhelming this year and part of the reason is they announced a lot of their coolest stuff last week and that's been a thing that they do at CES so I'm not surprised that people are looking at this and saying yeah no I heard about the robot but it's not really shipping you're rollable OLED TV can I buy one, when can I buy that that's kind of the feeling from LG right now we've got HTC doing their announcement right now HTC showcased the Vive Pro an updated PC powered virtual reality headset that adds a high res display 2880 by 1600 so that's a little bit better than previous 2160 by 1200 in fact a 74% increase in pixel density over the regular Vive which is now at 615 PPI and we also showcased a wireless adapter which will let user stream content wirelessly using Y-Gig so the headset would become truly untethered it'll have integrated headphones and dual mics HTC currently sells an add-on that brings the headphones to the current gen 5 but the Vive Pro will use Valve's updated Steam VR 2.0 tracking system as well which allows for more active tracking Vive Pro takes premium VR to a new level do you agree I guess no details on pricing or anything like that but yeah this is HTC's most successful product so of course they're going to lead with the new version of it but it seems like a spec update which is good adding the wireless capability is important because this is higher end than mostly what we see in terms of light VR type wearables so unless you want something big and chunky that idea of being able to have your PC drive it but not have to be carrying around a lead weight on your head makes a bit of sense that wireless adapter won't be releasing until this summer and there's no price on that either but again it's coming from HTC there have been third party adapters this one's coming out of HTC's own house rather than it's Vivex accelerator program so there you go with HTC let's finish with a lightning round of other CES stuff that we found interesting starting Peter with your favorite so far yeah I think so I mean it's a very small update but Osmo released a smartphone stabilizer the Osmo 2 which will be exclusively sold in Apple stores for $129 which is a very big price drop from the original Osmo which sold for $299 I love this little device and I've been meaning to buy one for a very long time so I'm going to run over to their booth straight away and play with it they've also released a Ronin S which is designed for mirrorless cameras as well so they're really getting into that whole space and yeah I just think it's some really really cool stuff nothing groundbreaking but very cool stuff as promised I promised this last week TCL announced its 6 series Roku TVs with the Roku TVs with the new Roku TV voice remote they have an AC Wi-Fi Ethernet and 3 HDMI 2.08 ports there's also the 5 series without the metal styling of the 6 TCL also announced the Roku Smart Sound Bar which can be paired to a TV or just be used as a standalone speaker so the Roku Smart devices from OEMs officially rolling out TCL had announced that they would have something at CES I haven't seen anything else yet and they weren't lying Sony announced 3 Xperia phones these were highly anticipated by a lot of folks the Xperia 5.2 inch 1080p XA2 with a 23 megapixel sensor 4K video and 120 frame per second slow-mo capability as well as the ability to shoot at an ISO of up to 1280 the XA2 Ultra has a 6 inch screen and 4 gigabytes of RAM has 2 front facing cameras for better selfies and the 5.5 inch but 720p Xperia L2 so it's a little bigger but a little less resolution is also coming out. All 3 phones have a rear-mounted fingerprint sensor which Sony had not done a fingerprint sensor before none of them have price or release actually they have done fingerprint raters but they've normally been on the side of the phone oh that's right they did do the side ones which I love the side ones well okay I love to get your opinion on this next one. Signal company with no vowels is a wristband slash watch strap product anyway from InnoModel lab which was actually spun out of Samsung's incubator South Korean startup allows you to use your finger as a phone receiver and the way it works is if I'm wearing this strap I pair it to a phone and I put my finger up to my ear I can hear callers just because the vibrations are traveling from my wrist down my finger and supposedly early reports say the audio wasn't like amazing but it's fun but it works so let's say Aya's actor and I were actually kind of laughing about this because I was like I don't want to do that that just seems like that's gonna hurt my hand and he said what if you're on a subway your phone somewhere in a bag you got your you know your strap on it's crowded you kind of do this because you really need to talk to somebody in a pinch kind of cool. Did you play with it last night at Unveiled? I did not get a chance to now. Yeah it kind of worked I mean I mean well it did work it sounded okay I felt very strange doing it though I want something wireless and my finger becomes a wire. Right yeah I mean at that point you're really just holding that strap up to your I mean it's maybe slightly more comfortable but it's not totally different right I think it's more comfortable than the wearables that we have today in terms of our ability to you know hold your watch up to speak into to unsolved. Alright. Hip air from Helite is an $800 belt with two airbags over the hips that auto-inflate within 0.2 seconds if it detects a fall to absorb 90% of the impact the problem is the people who need to wear this don't wear the current hip pads that you can get they're certainly not going to pay $800 to wear a belt that's going to turn into a big tire. I don't know BIM is a pretty rich I can say the selling price. It's very expensive it's a very expensive belt now hip replacement is also expensive. Well the biggest problem is that Helite isn't working with insurance companies yet so you've got to pay for this all out of pocket. Cosmetic. If you're on a fixed income then you're resided. Sure. Ring announced two versions of a stick up cam and ring beams LED lights for pathway stairway and spotlights they work with other ring devices to light up when triggered and then the ring alarm home security system will ship this spring. And Garmin announced the 4Runner 645 music which lets you save music to the smartwatch to play back 3.5 gigabytes of music they say it's about 500 songs over bluetooth you don't have to have your smartphone present you can play them right from the watch starts at $449 though but it is available now I'll give them credit for having a price and not even just a release date but you can buy it today. There's a bit of competition that's already doing something similar so I think they're probably a little bit behind the eight ball on this one. Yeah. GE is showing off a smart home hub with a 27 inch screen with two cameras and one no price yet but it's expected to be available in the second half of this year runs the Haller U Plus smartlight platform and works with other GE smart appliances. There's a little bit of a lock into an ecosystem there but I guess if you love everything GE makes a smart thing. I'll say it to replace your vent with it. So you have to really kind of rethink how you do everything in your kitchen because it's sort of in the hood replacement situation. Well thanks everybody who participates in our subreddit you can submit stories and vote on them at dailytechnewshow.reddit.com and facebook.com slash groups slash daily tech news show we got time for one email before we're out of here. So this one comes from James Smith he lives in Irvine, California hello James and he says I'm wearing my grand field man hat today. People talk a lot about how much better it is to cover CES from home rather than actually going there. The people who go complain about the crowds ain't got to walk everywhere seems like I don't know a topic for a journalism podcast but I just want to hear about the gadgets themselves. I don't care as much about how much walking all you journalists are doing to get to all the gadgets and I mean I kind of had to laugh when I first read this because I'm like well try to be here sometime and you're going to do a lot of walking but it's true when you're not here the whole spectacle is completely lost on you. And you want to know what the stuff is. That's the point of other people going. I know your feet hurt. Right. Now I get it James I get it. Yeah we can we get it so thanks for the reminder we will try to stick to the facts as much as possible. And I've got to say as someone who just a couple of years ago was sitting at home in Sydney Australia listening to people complain about CES and walking around as terrible as it gets sometimes I love every second of this ridiculous conference I love it today. There you go. Perfect. I will say as someone who's attended this event more than 13 times in their lifespan five is enough.  I'm loving being back after a bright because I love you guys and I want to support you. Actually I have to say I was a little skeptical about coming back last year but I had a lot of fun doing it and then this year CEA has been great giving us this little booth here on the floor. Which has been fantastic so. You know and also real quick it also depends on how you approach it. I really like the way we're doing it this year and it's allowed us to do a lot more things that we wouldn't have been able to do like if we were attached to a larger media organization where you know we're set on specific beats. Well that's it. Time to say thanks to our folks. Paul Spain thank you for being here. Always fun. Let folks know where they can find what you're doing. PaulSpain.com that's where my updates are and the new project that I'm working on which is Disruption Playbook. It's all about innovation and disruption and how people and companies achieve it. Still a work in progress but there's a bit of information online there at disruptionplaybook.com. And Peter Wells my friend where can folks find what you're doing? Just head to the Twitters and search for Peter Wells that's the easiest way to follow me. Excellent. Thank you both for being here. Thanks everybody for watching and Sarah we will be able to meet some people in person tomorrow if they're in Las Vegas or unincorporated Clark County. That's correct. We're going to be at the level up Arcade and Bar which is inside the MGM Grand. Tuesday January 9th tomorrow 8 p.m. Pacific time. We'd love to see you there. Come say hi. Have a drink or non-alcoholic one whatever it's fine but yeah we want to meet as many of you as possible and get to know y'all so thanks in advance for coming to our little meetup. Yeah hope everybody is enjoying the coverage. We'll be back here tomorrow right? Yeah in fact same time same place we are like Monday through Friday at 4 30 p.m. Eastern 2130 UTC whether we're at CES or wherever we are in the world do this every day weekdays anyway at elvigigradio.com and diamondclub.tv. If you want to email us our website is feedback at dailytechnewshow.com see if I go out of order everything pulls apart and our website is dailytechnewshow.com back tomorrow with Allison Sharon and Patrick Norton is our guest talk to you then. This show is part of the Frog Pants Network get more at frogpants.com Diamond Club hopes you have enjoyed this program oh that's such a weird experience without the music yeah that's why I held my hand up yeah yeah yeah since like a few tech things you should know where I'm like in my mind I'm like and girl right oh yeah alright that was great loved it we got there more than I thought we would it did not feel as rushed as it could have we had time to talk but then every time I go we've been chatting for a while but we're on time you guys did a really good job like going through each one I know we had to skip a few things but it didn't feel like you cut any of the information short in order to get to move on so it was great I kind of got confused with some of the tabs because there are so many I have a small screen oh yeah yeah I'm going to leave the extra stuff we didn't get to in the show notes too so if anybody's curious what else did you lead for time and of course Rich may be using some of this in daily tech advice oh yeah and just one thing for the LG what was it the HDR one of the big announcements about that was up until now the OLED TVs have only ever supported Dolby HDR by adding HDR10 they will now support HDR from Xbox and PlayStation so yeah like the OLED was never a great gaming TV for that reason it is now not only the best TV to watch movies but also games so there you go well there you go yeah I'm just levelating up show titles yeah what do we call this so if you guys want to see this go to showbot.chatrealm.net top of the list we got just another pixel in the wall the uncanny X-Van another pixel in the wall stands for format that's what you were saying it's hip to be safe Samsung builds the wall tech in XS and CES is in XS LG is ready to roll LG rolling rolling rolling a Vive and well get it and alive and well get it daily format news show fingers on the pulse of new wearables um I've got too much distracting me here to really pick so I'll let you guys figure it out I'm gonna put CES 2018 colon and then whatever you decide um I like just another pixel in the wall gotta love this ridiculous conference I've always I've always been curious to know that someone who's like been at CES like since it was a much smaller trade show back in Chicago and earlier way back so tiny IOT internet of teases five more pixels for your face signal finger phone um and what do you think um I always like Pink Floyd references another pixel in the wall that's good I like it I like it that was wonderful they were all wonderful though wonderful they're all our favorites they're all our favorite but that one is just my special favorite fair enough alright I'll throw it in another part just to push it up so another pixel in the wall yes and I'm capitalizing crazy out here anyone who's never been to a trade show while they're still putting it up like a like a big like industry wide one there's so much activity outside there's a forklift people running around in their little go cart I'm I'm curious to listen later and see how much because it sounded so loud to me but maybe maybe not in the headphones it was not so bad yeah yeah me can hear it but it's not it's not yeah it wasn't like the forklift was right behind this which it was which is what are we who is a social media guy for recode posted a picture on Twitter just now in some casino that is not named that features the world's greatest hot sandwich something I need to discover I was really disappointed so the hill became the West Westgate there used to be a great lake kind of like a Jersey Mike sandwich place in there but it's not there anymore I need to know where it is Peter and Paul Ethan Kane in our chat room wanted to point out that you guys can use show about the TV if you're doing a live show if that's up that is very cool thank you yeah Roger I was at IFA I think you were there maybe I don't know but yeah they're set up there is nuts the day that they're setting up I think their occupational health and safety laws are slightly different than they are out here they have them oh no we have them but somehow mysteriously don't matter when something happens oh but so this oh I shouldn't talk I might get some of the trouble yeah I want to hear that story I'll tell it after the stream stops maybe I'll save it for the patrons save it for the live made up I think I might blow off what I'm supposed to be going to and come to that so we're not going to talk about our feet no we are going to talk about we have talked about forklifts I think that's fair forklifts are it might be something that's you know you wonder what that was sadly and Vegas has amazing food or unincorporated Clark County has amazing food I never remember enjoying eating here I never get excited about oh I want to go eat somewhere because everything's such a it's either really expensive or it's really hard to get into or it's faster well the problem that I have is that I don't I've never been to CES and like really had a lot of free time just because you're working and when you do that it's like you wait until you're half dead and you're like I'll eat anything so then you just eat garbage that's my problem I will say having been to a SEMA show which is the automotive like aftermarket parts guys in the same location the LVCC our editor who came with us actually went to school here and so she pointed out all the places to eat which is great because it was like track it wasn't wildly expensive it was still very good and it wasn't packed full of people well if you follow Mitzula on Twitter Mitzula is a Vegas native and he pointed out for people going to the DTS meet up tomorrow there's a bow place that's not far from the convention center that's because it's a bow place it's a bow it's a bow it's Chinese food you probably haven't heard oh you got a bun it's the way it's pronounced oh yeah no I wasn't claiming it you're saying bow I thought you were saying bowels that's why I said that's not what's up we're not trying to send you to a toilet I know one of the funny things called bow bow it just sounds like someone with a southern accent saying oil wheel you got the press release yeah I just got Samsung's press release oh yeah so what's up with Samsung we'll go into depth on tomorrow's show too but what are they saying there's just one press release so far they normally send out three or four and it's just all about their internet of the things being open LG did the same thing today they talked about how open they're I think LG's openness is a lot more open than Samsung's openness which is all about fixity hmm yeah but who knows maybe maybe they're getting smart things yeah smart things being in the platform he doesn't mean that they're finally getting smart it's about time they got smart yeah don't know about not including home or Amazon in their stuff LG's move is much smarter personally well they should at least give the options right so you can use Samsung's platform or you can use the others it's important to be agnostic I remember speaking to a Samsung person about two years ago who was talking about how they were going to stop reinventing things that Android gave them for free and so they were shutting down their photo service and they were shutting down their music service and now they heavily promote google music and google photos and I don't understand why it feels like that part of the organization wasn't talking to the big speed part of the organization the joy of the big multinationals indeed speaking of though I'm supposed to write an article about that very topic so I should probably bugger off I'll shut down the alright thanks everybody for watching we'll be back tomorrow bye