Welcome to the annual DEF CON convention. This meeting was held in exciting Las Vegas, Nevada from July 9th to the 11th, 1999. This is videotape number 52, embedded systems hacking.  Actually, a good segue was what we just saw previously with the wearable computers. This is indeed a type of embedded systems. I'm not going to get into it because to be honest, I mean, squat about video. It's basically all about video. Everyone knows what an embedded systems is. I mean, if it wasn't for embedded systems, telecommunications as we know it wouldn't exist already. But modems, the telephone switches, the routers, everything that most people go through to get into the internet and get through the internet is an embedded systems. Basically what this is is a computer that's built into a box. Usually no real accesses other than telnet, some sort of an ethernet or one port. There's no keyboard, there's no monitor, and it does a very specialized purpose. So it doesn't do three-train things just like your PC does, unfortunately. Though some people end up throwing in real fun hooks. If you know the right commands, you can suddenly play space invaders on your modem. But this is a little unusual. Most people don't bother to do embedded systems even though these could be convenient in the hacking environment. Specifically, you can build a nice little small box that's easy to avoid in detection. You can throw something in the planets box. No one knows what it is, and you can be saying there's nothing for all you want. But no one seems to do it. Partially it's because no one seems to be truly aware that they can build a nice little box, or they don't think they have the skill set to do it. It's really pretty easy nowadays. There's actual, if you go into embedded systems journal on the back, you've got demo boards. These demo boards will have everything you want on it. There's going to be a built-in processor. You'll probably have an Ethernet port, a T1 port. You'll have to do your software on it. And most manufacturers even provide software for you. So it's not very difficult anymore. Another problem that most people consider in developing embedded systems is price. Because you're actually going to have to buy all your individual components.   Or you have to get the demo board. Now one of the easiest ways to avoid the price thing is to salvage from old supports. You've got a 386 sitting around you've got no use for. How about you solder an iron and yank that chip. Find an old Ethernet card. Yank the chip there. Suddenly you're not having to pay for components.  Which is not that difficult. In addition, a lot of manufacturers still offer the demo boards for free or for very little. Because they want you to use their product and they think by offering this to you very conveniently that you are far more likely to go buy a lot of their product. Okay, so we're not going to. But they don't have to know that. Now you do have to know where to be able to get these things. If you're not going to be yanking them from your boards then you're going to have to find vendors and manufacturers. You can go directly to the person who makes the chip. You can go to Intel if you want a 960 or Motorola for a power PC. But the chances are they're not going to give you anything because they don't care about the individual person. You're going to have to find vendors. Now the good news is if you go on to a company's website they're going to list the vendors. You give one of them a call-up and most of them will end up sending you some sample chips. One or two of the cheap stuff, of the more expensive stuff, maybe 10, 12 cheaper stuff. I've sometimes gotten e-pumps this way. Call up enough vendors. You can get a couple hundred if you need them. Now there's plenty of uses for embedded systems. One is just be a sniffer. You can monitor and record traffic or any specific traffic if you want. The one problem with this would be embedded systems over a standard computer on this would be storage because you may not be able to come in and be able to yank your floppy or a flash card or whatever you're going to be using regularly and you don't want to make this a huge box. Another use for embedded systems would be denial of service. You can actually build a box who will sit on the network for a day collecting MAC addresses and IP addresses and then suddenly start spreading out garbage packets, large packets, something else. We'll be completely spoofed to IP and a spoofed MAC address so that nobody knows where it's coming from and there's no real way to trace it back because ideally with a little bit of social engineering you've plugged it directly into somebody's network. You can use this also to filter or block certain messages.   So there's plenty of uses for this. One guy I was talking to yesterday is actually building a little key strip recorder that he wants to ideally fit into a keyboard. So it'll just sit there and record every key strip type in the keyboard. Once again, this is a quick convenient and something with embedded systems is ideal for. Now there's going to be some fundamental skills if you're going to try and do embedded systems. You're going to need to be able to program and need assembly. You also probably need to see some people can do embedded systems completely in assembly but this is very rare nowadays and most everyone uses C once you get off the initial driver level. So if you want to try and do this most in assembly, most in C. Those are the two main languages if you know Java wonderful, go away. You're also going to need some hardware knowledge. You need to know which end of the soldering iron is hot. Ideally you need to know a little bit about how to wire a breadboard. What a breadboard is. How to actually solder on chips but a capacitor. It's a basic simple part about hardware. You're going to need to know how to get information on the chips you want and how to get samples. Again, most of the time you can go straight to the manufacturer's website and get information. They'll have the entire specs there. I downloaded a bunch. They'll tell you how to get an example sample code. They'll tell you distributors. You can find out how to get everything. Another good source is the embedded systems journal. That thing, if you go back the last 20 pages, it's basically how advertisements, how to get yourself chips, demo boards, anything you really want that makes it easy for embedded systems. That's the basic overview of what the heck an embedded systems is and why you would actually want to do anything with it. Let's give them actually some details because we really want to know how to actually do this. Let's start off with some processors. You can start off with... I've got a list of your firsts to add the main risk processors. There's the Intel i9-60. Now, I personally don't like this. I'm actually programming on it currently and I don't like the chip. Part of the problem is with all Intel chips you have a big ND and little ND in the issue. Now, if you actually want your members to look like the members you intend them to be, this is not the chip for you. An additional problem with the i9-60 is it's expensive and there's nothing built into it. It's just a microprocessor which means if you want to have serial ports or anything else, nothing's built into it. You have to buy it all externally and hook it all in. I don't like the i9-60. However, everybody uses it. There's compilers for it everywhere. You can find the new same compiler that'll do the i9-60. It's confirmed. Everyone knows how to do something with it generally. There's a good knowledge base behind it. There's one benefit with the i9-60. It's a Motorola PowerPC. This is actually better. There's almost as much of a common base for it. Almost as many people use the PowerPC as the i9-60. But unlike the i9-60, it actually does not have the big ND and little ND in the issue. Your members come out nice and normal. They have built-in SCCs, which are serial ports, so that you can actually hook up other pieces of equipment to this without having to do too much terrible engineering. It's got DRAM controllers built in. It's cheaper than the Intel. Again, you can usually find compilers everywhere. In fact, I use a Genesee compiler when I'm doing PowerPC compiles. If you want to go with a risk chip, my personal preference would be the Motorola PowerPC. Another common risk chip is the MIPS. Not many people use the MIPS. It's got some built-ins to it. The big problem is that it's not very common. It's not very sexy. Of course, because of that, you're actually going to be able to get lots of samples of them because the company is desperate to pawn them off on anybody. So this is the one benefit with MIPS. The MIPS is similar in construction to the PowerPC. It's got built-in DRAM controllers. It's got built-in SCCs. It does not have the big ND and little ND in issue. So if you're looking for just 13, MIPS is probably where you want to go. You can also then bow down to some of the lower-level processors. There's the Intel 8051 which you can probably pick up for about, depending on the speed of the processor, from anywhere from $1 to $10 a processor. So it's very, very cheap, even if you're not getting samples. The one problem is it doesn't have an awful lot of first power. We're talking this is an 8-bit processor. You can do some incredible things with it, but you're probably going to have to write an assembly and you're going to have to write some really clever and some really tight code. I've got friends that have been really full of 56K modems using it in 8051, and that took a year and a half of engineering to end. They were constantly having to tweak the code to keep the 8051 powerful enough to do this. I mentioned earlier 386. You can make a 386 off of winning another board and use that, and you'll probably have enough power for what you want. These actually make what they call a PC on a chip. And it's basically a 386 or a 46. I'm a small board, usually with built-in serial in the Ethernet port. You can go ahead and do that, but let's admit it. I happen to think if you're going to use a PC chip, you're cheating. We're talking embedded systems. We're not trying to make this easy. Okay? So this basically covers processors. You probably got a different process as you know of. They've got different flavors that everyone likes. Some people like the Pico. Once again, use what you like. There's plenty of them out there. I'm just covering through the basics. You can buy old devices that you've got. You've got your basic Ethernet. You've got a T1. You even have a wireless or a DSL if you want to get really exotic. If you're going Ethernet, there's a lot of different Ethernet controllers out there. My first preference is probably the Davicon chip because it's cheap. Cheap is always a good thing. You could always just jank off a familiar to Ethernet card that you don't like anymore. No one's using your old 16-bit ISA, but that doesn't mean the chip is bad. Depending on how old the card is built, the chip may not want to be made, in which case you're going to have some difficulties actually getting some specs on it. Or be aware of it. You're actually going to recover from old hardware. Just that everybody makes an Ethernet controller. This makes it easy. I went on the web and did a basic search. There's the Davicon AMV makes one. Serious Logic, National Semiconductor. You know the manufacturer of ICs. And they're probably going to make an Ethernet controller. You can get 10 megabit controllers. You can get 100 megabit. You can get ones that will switch from either way. Personally you're probably going to stick with a 10 megabit mostly because of price. Mostly because you have to need to go to 100 megabits Ethernet for whatever situation you're going to be using for it.  Specifically a line interface chip which is what actually connects up to the line and talks to it. And then you have a framing chip which actually packetizes everything and sends it out. So if you're going to be looking at doing something with T1 or even E1 applications you're going to want to check to see if you're using... if you're going to be doing a single chip or multiple chip solution. I'd recommend a single chip. They tend to be cheaper than buying two separate chips. Plus let's admit it's easier if you've only got one chip to wire and then to do two chips. One of the more popular single chip solutions would be the Siemens... well it's not in Siemens but off their embedded systems group. They make it a very good T1 chip. Cirrus Logic on the other hand does a two chip solution which actually isn't bad if you want to go with a two chip solution. Wireless... there's plenty of people out there that will do wireless... Cirrus Logic actually is another one who does it. Once again you can also do DSL, Phillips and the National Semiconductors. Everyone does DSL if you're interested in doing it. But in general when we're going to be doing some sort of little embedded systems box we're probably going to do some social engineering and plug it directly into somebody's network. So you're most likely going to be interested in either Ethernet or T1 to be quite honest. Or something that's completely stand alone doesn't hook into any of that in the case of like the keyboard monitor. It doesn't actually need to know anything about T1. It doesn't need to know anything about Ethernet. It just needs to be able to hook into the keyboard. So that's actually convenient depends on what you're looking to do with your embedded program. Now when I'm talking about these things especially if we're talking about building some sort of a sniffer or recording device we've got a big memory problem because we're talking hundreds thousands of packets going through that we're going to have to record. And this is one of the big problems we've got with embedded systems is trying to get enough memory at a reasonable price that still makes your product smaller. You can go out and get a hard drive and wire it on in. But then you're talking you've got extra size you've got a larger power requirement it's not really terribly convenient. So what you're looking to do is you want to save to memory. What's the best most practical way of doing it? You've got everything basic flash chip where you can actually go write it on to a chip. And then there's not a smaller I don't know maybe about an inch long or so in average.  And you could stick a floppy end that you've got the same problem as with a hard drive. Once again you've got power requirements you've got size and you've still got to be able to go move the floppies in and out. My personal preference is probably a flash card where a PCMCIA card you can get anything from about a 2 make to about a 32 make flash card. You can hot swap them and it's fairly small so you're not talking about a lot of hardware to support it and it gives you the ability to just yank it out slap a new one in. It takes very little amount of time and you can go home stick it in your laptop and read what's actually been recorded on it. There's another way to avoid recording it all and that is if you're hooked up to the network but you can just transmit to yourself have it hard coded to send all the data or record for an hour and send all the data to a certain IP address do it over TFTP perhaps. So this is always a way to avoid resolutions too but remember if you're going to be sending over the network somebody may start wondering how come their mail server keeps sending 2 gigs of data every day to some strange IP address so try and be a little sensible about this in addition if you're going to be building up a nice little embedded box you're going to have to throw some around in it now the good news is it warm is cheap so what you want to do it depends on how good of a coding you are when it comes down to it how fast you're writing the code how fast are you doing it and how much memory do you actually need to process what you're doing depending on what you're doing I'd say anywhere from about 128k for something small which doesn't actually do an awful lot up to several makes the product I currently work on uses actually 64 makes of RAM and that's just for the main controller we're not talking the sub cards okay well you need to build up soon but I don't expect the rest of you to have to do that you've got a question? you've got a choice if it's going to be something very simple that you're doing you can probably write something from the ground up there's several companies that provide OS designed specifically for embedded systems source com does one nucleus actually makes a very good OS if you take a look more on the free slide the next even comes with an embedded version that you can use and what's nice about Linux is it's cheap and it's probably got drivers for just about any chip out there that you want to actually use depending on what you're doing you may want to decide on scaling we wrote our own wanted to know which operating system that I currently use the company I worked for we wrote our own the previous companies I've worked for we tended to buy from a nucleus and nucleus makes one of the best operating systems around that I've seen it's fairly unique similar that it's designed specifically for embedded environments and it's clean, it's nice it has great debugging features and that's another thing you guys need to keep well you're going to have to debug this thing if you imagine you're going to slap it all together and have it work first time through then you guys must be geniuses and I want you to come on up here and give this speech because obviously you're better than I am I can't even write code that compiles clean through the first time usually so imagine that I could slap together some sort of a box to do whatever I want and have all the code and all the hardware work immediately is fairly unlikely in fact if you even take a look at the first production boards of most companies you'll find that someone's been slapping on little wires here and there to make up for the accidents they discovered after they built the first batch yes? buying the little PC boards is the most practical way because you don't have to worry about having hardware failures and it gives you an easy development board I suppose the reason I call it trading is because well it seems a little easy to be honest I'm used to having to work with built-in microprocessors and having to do really engineer things from the ground up the PC boards are great actually for the little home embedded systems program because it's all there together easy to put software together on and it's really the simplest solution so really trading I just I find it a little too easy to grow and qualify as true embedded systems let's see what have I got left? I've covered most of the basics I wanted to do because I wanted to keep this kind of short check and start answering questions I don't know how many of you have actually built something or not to build something or wondering why the heck they're actually sitting here still does anybody really have any questions? okay here you can do that and there are actually some people that have built such and some of our lines in particular both of which provide more power than you actually need for the protocol you can have to be careful for most of them you build it to do to power off of them but there's enough of a variance in the actual real life views that sometimes it won't work one company I worked for built a living burden that was powered off of the phone line and it worked on about 70% of the phone lines the rest of them were bouncing around enough on the power selections that you actually had to plug in a 9 volt battery so just remember you're working in the real world and not everyone's going to actually follow the spec how long have you been doing during the systems I've been doing it for about six and a half years I started off in an industry I'm now in the telecommunications industry I specialize mostly in protocols currently for real life variations of course everyone over here seems to like me we'll just start moving back the big beard one chip solutions there are some of them out there the ones that I have played with I have played with I find them generally pretty flaky they always do strange things and give out on you at the last moment usually in this critical moment they've gotten better and I haven't played with them in a couple years now I've been totally gotten better but I've been really pretty unimpressed everyone tries to slam everything onto one chip tends to leave things out this side's obviously pretty quiet I missed you okay we'll give you we're doing some sort of a solution where everything is added on these serial cards this is actually pretty good you can do an awful lot of things with serials you can everything from HDFC just slap them on another chip it's very convenient it's very quick if you're going to do that you want to make sure that whatever your microprocessor is it has a lot of SCCs to handle it Motorola tends to slap about four of them on a chip MIPS tends to put about two on you don't want to use an Intel i9-60 they don't put SCC ports on their chips each SCC port is going to do some sort of a serial interface for you if you need a lot of serial interfaces what I've actually seen people do is they actually a slave a second Motorola PowerPC chip to the original one SCC ports depends on what you're doing when I was doing modems I was the slave programmer for the entire modem code base I then branched out I have worked on teams from any work from about two people the current team I'm on would be a little hard to describe my current chunk of it I'm the only one working on it but we've got hundreds of programmers working in the code base constantly through simple little things that you're doing especially if you're going to use something along the lines of a PC on a chip or some sort of a demo board where you've already got some software built in you can probably do it on your own in a couple months if you're a decent programmer and you know what you're doing and you can make a spec ideally if you're not that good at hardware and God knows the hardware guys don't like in their lab your best bet is to buy some sort of pre-made solution which means if a PC on a chip or a demo board there's hundreds of demo boards out there using various different chip sets with various interfaces you can very commonly find for somewhere between 20 and 70 dollars a board with a microprocessor an ethernet chip and a T1 chip on it so you've already got just about everything you could need to hook into into a network right there they'll give you power supply information usually it's something it's like a 9.4 transformer you can just plug into a wall you can gen up something independent if you actually want but you can actually get a nice little box that has everything in it and all you've got to do is slack on some code and put something around so it doesn't look like this piece of circuit board flying around which may actually make somebody suspicious okay we'll go with you most of them don't actually deal with the protocols at all it's going to be able to read the line or if you want to be able to read the TCTIP headers or determine what's actually within the data packet you're going to have to write that all into your own software right that's where you really want to be able to do the controlling of it anyway most ethernet chips are only going to do the basics it's going to read in the data and give it to you in a format that you can actually then read in process you can actually buy ethernet chips that'll do switching but I don't see any of you really wanting to build a box that's just going to switch the ethernet out but I suppose there's possibilities you can get switched ethernet chips you can get ones that are just going to be able to input and output single chip ethernet's a deal I'm building you can find some yeah in fact the ethernet you're far more likely to find a single chip solution than in the T1s specifically so if you're going to be doing some sort of an ethernet solution if it's not being offered in a single chip solution don't go with the company okay we'll go all the way over there black check yes you preferences for compilers and where to get un-chip samples for compilers the past couple companies I've worked at we've actually used one flavor or another of GnuC it works well you can customize it out it's pretty nice to be quite honest and you can get them to run with just about any processor that you want to use if you're going to go away from GnuC you're probably going to have to pay some money for the compiler so I recommend unless you really can't stand it stick with the GnuC as for un-chip samples I don't know off the top of my head where you can get them but I would recommend if you've got a specific vendor that you want to go through you find out who one of their distributors are and you start calling distributors one of them, at least one of them will give you samples maybe only a single one but most people are so desperate to get your business that they will send you samples there's another person from this side they're actually starting to get spunky over here why don't you go for it he wants to know about ethernet chips whether they'll give you access to the packet as it's arriving or whether they'll wait to receive the entire packet before they send it to you usually you can get access to it as it's arriving so you can start tweaking it almost instantaneously they're going to throw it in probably into some sort of a ring buffer or shared memory that you can just start reading as soon as it starts putting any information in there okay he wants to know whether I have to reload code onto my products when I'm doing debugging or if I've got some sort of an emulation and the answer is it really depends on the scope of what I'm doing the larger the project the more likely I'm going to be loading the code on it every single time because I'm probably going to have flash it's probably easier to stick something like a logic analyzer just to watch things the smaller it is the more likely I am to actually do some sort of offline emulation to be quite honest a lot of people like GDB I can't stand it if you're going to actually put some sort of emulator in it's going to cost money because to get an emulator people don't give these things away as samples unfortunately you can do a software emulator which is going to get you a certain amount of information but eventually you're going to have to run it on your actual product which means if you're trying to do it in one time when problems you're probably going to have to burn I don't know half a dozen to a dozen other minimum if you're going to be doing on something that's erasable or flashable it's not that inconvenient you might be able to get your hands on something that will actually plug in and pretend to be in which case you're talking some sort of hardware emulator applied microsystems makes a couple really good ones to be honest but you're going to be paying money these things don't come cheap we're talking about $10,000 if you want to do this make friends with some sort of a software hardware engineer and let them get them to let you into their labs on the weekends this is about debugging the efforts actually involved in debugging depending on what kind of a solution you're going with depends on how much debugging you're going to be doing if you're using a very well known microprocessor you're debugging times probably going to go down a little bit because let me warn you there are going to be bugs that you find that just aren't in the manufacturer's documents and sometimes you'll never convince them that they've actually got a problem so the more well known the process the less likely you are to run into undocumented problems in their hardware if you buy a pre-made solution some sort of a demo board there's less likely that you're going to actually have hardware problems so you can move those as another amount another time saver this leaves you just trying to figure out what your software is doing and what would be hardware actually when you actually tweak this pin does the hardware actually do what it says it's supposed to do and it doesn't always once again out the less likely you are to find out that even though they say this one pin can be floating you always have to keep it grounded if you actually want to seem over the first 32k of memory so once you've assuming that you've got all the hardware problems worked out on the software you can probably do a good chunk of software based emulation gdb once again can go with free stuff is not bad I don't like it mostly because I've used some of the really nifty hardware based debugging it and I'm spoiled but if you want a real cheap simple solution that gdb in itself will probably take care of 80% of all your problems eventually you're going to have to run this on the actual hardware real time and the problem when you start doing this is your limited amount of ways you're going to get information and access to it you can throw on the logic analyzer and actually watch how various pins are being and that is being twiddled but this is kind of difficult and with submitted logic analyzers are not cheap your best way unfortunately when you're actually running it on your when your box is like print apps it's completely backwards but the print app can be your best friend I do a good chunk of debugging actually field simple prints out of statements and assume every week of coding you do is going to take two weeks to debug it good point you did mention that you can do some logic if you're cheap and you're not too worried about speed you can throw on some sort of a logic analyzer card into your PC or slow down the processor enough to be able to actually talk to it over your parallel port this is true just remember sometimes bugs will not happen at a slower speed and they will manage speed up I've seen things where just actually plugging on an emulator pod or even a logic analyzer pod slows things down just enough that well in the order of some sort of a waveform that it'll work in the minute you unplug it everything goes flaky again in fact I've got a friend who spent three weeks trying to trace down what the hardware problem was because every time they stuck on any sort of debugging equipment the problem went away so just remember timing can be a real pain oh also on the logic analyzer front you can probably find some old ones, old used ones that you can probably buy pretty cheap they're not going to do all the nice new fancy things as the HPs do currently but if you just want some real simple, if you want to just be able to see what's going on, a good old fashioned 12, 20 year old garden basements logic analyzer is probably going to work for you either I'm a complete genius or you're very bored because I'm not getting I've got a question, go for it embedded systems websites I've got a note that most of what I do if I'm going to get information I actually read journals on it rather than going on the web for information embedded systems journal is a very good magazine if you actually want to do any research into it if you're actually looking for information just on specific chips you can go to the manufacturer's site they're going to be able to give you full data sheets put off and you can download samples of code to make this thing work it's very nice I logged on for example let's find one of these one two let's start here, professional semiconductor I got just a basic little description here in addition I could have gotten the entire spec which was a PDF file for 182 pages which went into details about how to design how to connect this what the waveforms look like clocking cycles, power, everything like that in addition I could actually find some sample code you usually can't find it as often for the T1 chips you can usually find sample code that you can just download for flash guaranteed you can find code that you can actually download and the very little changes will actually be able to get to work on your system a lot of these people will actually have hardware diagrams of how you can wire in this chip into a standard setup so you'll be able to download specs schematics, code everything the best friend is usually the manufacturer's website if you can't find it there you go back to that nice little vendor who gave you your sample chips and tell them you're having problems before you know it they'll actually have some sort of a sales engineer out there to talk you through what's wrong well actually isn't that they give you some good drawings they tell you the details of the chips I've still got a several year old issue which tells you how to build your own carburetor for 25 bucks which one of these days I'm actually not going to do so I could tell I was really good for the home hobbyist again I'm afraid sometimes being a professional you tend to look a little higher than that stuff that's why I mentioned things like embedded systems journal circuit sellers actually really good portable prom burners he was asking me if I know of anyone who manufactures some sort of a prom burner that is portable so that doesn't require great gobs of power and you can basically hook up to your laptop and be able to burn it well I don't know anyone exactly there are some companies that make prom burners that are fairly small and don't require too much power I don't know any that work off of battery or off of the PC's power you'd have to somehow or another plug in some of them will just require a little mindful transformer actually in this case circuit sellers your best bet to take a look on they'll probably list a good 20 or 30 different prom burners for you of various levels and you may actually find one that's real simple a lot of them you can actually plug into like a parallel port and burn your prom another solution has just become real friendly it's got access to a prom burner at work and it's sneaking in on the weekends this is what can be because one of the benefits of a prom burner is if you've got code from another product you can actually stick the prom in the prom burner and have it download to a binary file that you then can search through at will to find out clear text if you want or anything else twiddle a couple bits and out of the sudden it looks a little bit different like you intended so this can sometimes be really useful one is about the embedded systems in cars are there any websites to be able to go to to find out information about the actual chips the chips that are running inside your cars the answer is I'm sure there are I'm not aware of any off the top of my head I know of a lot of companies that offer to sell you modified versions of various chips for your car one of the most common is to get rid of the speed limiters I don't know too much more about that I had a friend who somehow had a connection back in GM who was actually able to get modified code for his car and he just came into work and burned himself a new bomb swapped it out and suddenly was able to get much better gas not a whole lot of his track but I don't know if I need websites specifically I'm sorry FPGAs do I ever use them I personally don't use them a lot of people do that I consider them more along the lines of a hardware engineering or software engineering and the hardware engineers don't particularly like me in their domain they're simply without me tending to destroy just about anything I put my hands on they're nice they're a little expensive they tend to be they tend to do very customized things much like ASICS they can do some stuff that you're still going to have to throw a microprocessor in it and for the general little home hobbyist you're probably just going to want to do a microprocessor and give up the electric speed that you get who wants to know about mailing lists or news groups to be able to find out about this I haven't done a lot of research into it I know there's a couple of news groups we out cop area I don't remember the exact addresses but they talk about some of that I've popped in once or twice when I've had to ask a very specific question and generally gotten one or two good responses followed with a lot of crap that I don't want to have to deal with so I don't pay attention to them very much he wants to know if there's any groups that are talking about what people are working on currently talking about nice new cool stuff and things like that the answer is I'm not sure I've seen one or two that report to be so on the internet but I find most of them start off with someone presenting something they develop very quickly into flame wars or well you must be a complete idiot because of blah blah blah blah blah and so it's very hard to actually get very useful information out of them if you're actually afraid of them it's like wild I'd be very interested see I best buy a hotel whether there's any back doors and have half that I don't hear too much about it the first way to go around finding out if there's any back doors is to get all the information on it see about getting a spec see if you can get a schematic or a drop on it see most of these companies are going to show you how the thing works and to some degree or another once you have an idea how it's actually going to work you can start finding tools and figuring out how to hack it but first you need to find out how it works so I'd recommend going out and getting every single piece of information possibly can get on the I bus and spending the next couple weeks being totally immersed in it I haven't found anything where it isn't a bug in it somewhere you're talking basically about the PC on a stick I was mentioning earlier here studying this at convex and we saw a little PC just on a small board there's a company that makes and calls them PC on a stick they do a little PC on a cube which is like so big or so which has everything built this makes it really convenient easy to develop and let's admit it there's three trillion pieces of software out there that actually run on the PC which takes your development time and minimizes it extremely there's probably good ideas for the home hobbyist however if you're going to get serious and you want something that's going to work in a very narrow field you're probably going to find that this is a little bit too broad for what you want however for a starter it's probably ideal I see another question hold on one sec oh boy he's asking about testing cycles there's these wonderful great little design plans that come out that never actually work usually what's happening is you end up writing your code probably two months before there's actually any hardware for you to stick it on you're hoping and praying that the hardware will actually get done before you get to the point where I cannot write any more code when that happens you stop your code on and you spend the next three months hand in hand with the hardware engineer one in the morning tearing your hair out trying to figure out whose problem is going on it's really painful if you don't have already well developed hardware because you're trying to figure out whose problem you're trying to be bad whether it's software, whether it's hardware and whether it's easier to fix in software or hardware usually if it can be fixed in software that's where to go because let's admit it's software's cheaper it's easier to chain hardware's a royal pain to have to go wiring stuff up to so there quite often be knocked down dried out fights screaming at each other because the software guy doesn't want to have to fix it in his code and the hardware guy refuses to fix it in his code and yes, blood will sometimes occasionally flow but in general it's going to probably take two to three months not for a large board for a small board it's probably not going to take a couple weeks to debug the hardware the software usually is going to take longer unfortunately sometimes there will be a hardware bug that will not show up until many months actually into the development and debugging cycles sometimes will not even show up until you actually change software enough run into problems where it works perfectly fine on one version of software and the next version it breaks and everyone brings the software until you discover it's actually suddenly exploiting a hardware bug that no one knew existed that's one of the benefits about buying vanilla boards or a low PC stick solution is you're avoiding a lot of the hardware pains and on connections first thing you're going to have to do is you're going to have to have some sort of access to the line that the modems either coming in or out on so you're going to have to plug in some sort of a box that's going to take either a phone line or a T1 in and out secondly you're going to have to know well the easiest way would be to know what type of modem the person is running you have an idea of what protocols you're going to you're going to want to be running also basically to be able to talk to a modem connection you're going to need a modem data pump to be able to translate this into something you can read so you're almost going to have to have a modem to begin with and then just modify it somewhat this is not terribly convenient you can have something that's going to just collect the data and spit it out to you but to translate that data into actual useful terms you're going to need a modem data pump and depending on what type of modem you're talking to you're going to need the appropriate data pump because everyone knows that not everything with data pumps is quite as compatible as they claim it to be is everyone happy? again, thank you


Hello and welcome to News Brief, a production of the Government Information Service. I am Nivalu East. 150 travel advisors have said yes to Saint Lucia at the Saint Lucia Tourism Authority hosted Global Romance Summit. The say yes to Saint Lucia Global Summit, organized by the Saint Lucia Tourism Authority, SLTA, brought together travel advisors from the USA, UK, Canada and the Caribbean. Professionals versed in transformation, design and adventure presented on the best ways to sell Saint Lucia as the ideal destination for love and leisure. At the event, Minister for Tourism, Investment, Creative Industries, Culture and Information, Honorable Dr Ernesto Le, committed to improving Saint Lucia's tourism product even as the country continues to receive accolades. The say yes to Saint Lucia Global Summit was held from 13th to 17th October 2022. Saint Lucia joined the rest of the world in recognizing World Standards Day on Friday 14th October 2022, in an address to the nation given by the Honorable Emma Hipaldit, Minister for Commerce, Manufacturing, Business Development, Cooperatives and Consumer Affairs. She called for Saint Lucia to meet the set industry and manufacturing standards recognized globally. She stated, quote, as a small island developing state, which wants to affirm its presence and participation on the global stage, we must place emphasis on standards and our national quality infrastructure. The government of Saint Lucia has placed the implementation of a national quality policy as priority on the agenda of our national development strategy. We recognize that while the administrative structure of government can create and implement policy to realize this, our culture must also be reflective of a people who embrace and engender the concept of standards to improve constantly our quality of life, end quote. The minister went on to elaborate on the importance of the national quality policy infrastructure and lauded Saint Lucia's Bureau of Standards for the successful role they have played in its implementation. This yes, international theme for World Standards Day is shared vision for a better world. The Department of Home Affairs and the Honorable Dr. Virginia Albert-Poyert, Minister for the Public Service, Home Affairs, Labor and Gender Affairs, last week joined in the commemoration of the International Day of the Girl Child, which took place on Tuesday, October 11, 2022. The theme, Our Time is Now, Our Rights, Our Future, is deemed to be a fitting one as it brings into focus the right of girls to have access to the opportunities that will position and prepare them to fulfill their potential and to have a successful productive future. The year 2022 commemorates the 10th anniversary of the International Day of the Girl. According to the United Nations quote, women and girls represent half of the world's population and therefore also half of its potential. Gender equality, besides being a fundamental human right, is essential to achieve peaceful societies with full human potential and sustainable development. Moreover, it has been shown that empowering women spurs productivity and economic growth, end quote. In 1995 at the World Conference on Women in Beijing, countries unanimously adopted the Beijing Declaration and Platform for Action, the most progressive blueprint ever for advancing the rights of not only women but girls. The public is nearby notified that in keeping with changes in international oil prices and governments' application of the modified market pass-through petroleum pricing mechanism, the retail price of LPG 100 pound cylinder has changed. The retail price of gasoline, kerosene, diesel, LPG 20 and 22 pound cylinders remains unchanged. The price change takes effect from Monday, October 17, 2022. Gasoline remains unchanged at $3.89 per litre. Kerosene remains unchanged at $3.91 per litre. Diesel remains unchanged at $3.89 per litre. 20 pound cylinder remains unchanged at $45.27 per cylinder. 22 pound cylinder remains unchanged at $49.79 per cylinder. 100 pound cylinder decreased from $318.64 to $313.07 per cylinder. The 20 pound cylinder is being subsidized at $17.35 per cylinder and the 22 pound cylinder is being subsidized at $19.08 per cylinder. The public is informed that the next adjustment of the retail price of fewer products will be on Monday, November 7, 2022.


Welcome to a new episode of the ITU Journal webinar series, where you can find insights and forward-looking research on future and evolving technologies. The ITU Journal is an international journal providing complete coverage of all communications and networking paradigms, free of charge for both readers and authors. This publication considers yet to be published papers addressing fundamental and applied research, building bridges between disciplines, connecting theory with application, and stimulating international dialogue. Its interdisciplinary approach reflects ITU's comprehensive field of interest and explores the convergence of ICT with other disciplines. We count on your support to make this webinar an interesting experience. Please submit your questions via the Q&A channel at the bottom of your screen. All questions from the audience will be taken during the Q&A session after the talk. The meeting is being recorded and the recording will be made available on the webinar website. Closed captioning is also available for this event. You can enable this by clicking on the closed caption icon at the bottom of your screen. We hope that you will enjoy the talk and we encourage you to stay connected until the end for the Wisdom Corner live life lessons. I will now give the floor to our master of ceremonies. Hello, and welcome to the new webinar series with CDOs of the IT Journal on Future Inevolving Technologies. My name is Alessa Magalditti from ITU, the International Telecommunication Union, the United Nations Specialized Agency for Information and Communication Technologies. It is my pleasure to open today the webinar with Dr. Alex Jinsson-Choi from Chairman of Iran Alliance Germany. After the Q&A session is just announced by our avatar, I will moderate the Wisdom Corner live life lessons. So please stay online. Dr. Choy agreed to a personal chat, so he will share with us some lessons learned over the years that might perhaps be useful for some of you. It is now my honor to give the floor to Mr. Seizo Onoe, Director of the ITU Telecommunications Standardization Bureau for his welcome remarks. Onoe-san, the floor is yours. Thank you. Thank you, and colleagues and friends. It is my great pleasure to welcome you all to this second talk on our new series of IT webinars with CDOs. Let me begin by thanking our great guest speaker, Alex Jinsson-Choi. He is my old friend, and I first met him. He worked for LG Electronics, and he became a CTO at SK Telecom and CTO at Deutsche Telecom. Now he is a Senior Vice President at Deutsche Telecom and Chairman of Iran Alliance. ITU, highly appreciate your support. The first talks in this new webinar series are sharing CTO insight on industry ambitions for 5G, 6G, and associated innovations to boost network intelligence. Our talk from MTD talk of earlier this month took us through the company's research and development to advance 5G as well as prospects for 6G to drive new improvements to our quality of life. I will encourage you to review that talk online. Recordings of all IT webinars and workshops are available on our website, great in the archive, very rich in expert-oriented content. Today, Dr. Choi, Alex Choi-sang, will speak from his experience at Deutsche Telecom and Aura Alliance to detail how machine learning contributes to the intelligent control of 5G RAID access networks and how this automation and automation could evolve for 6G. These talks from CTOs are presented by the ITU journal on future and evolving technologies. Our journal embodies ITU's commitment to the public interest. It is unique in publishing papers from world-renowned researchers at no charge to authors and readers. Our journal welcomes research on all topics all year around. And I have no doubt that this CTO webinar series will inspire yet more contributions. These talks will highlight the growing synergy between academia and industry in developing and applying new technologies. Academia and industry stimulate one another's work as partners in research and development as well as in sandbox initiatives to prove the market inviability of new solutions. These CTO talks are certain to uncover new opportunities to expand this collaboration and that are exactly why we have arranged them. I would also like to encourage you to take advantage of the ITU platform. In addition to regular issues, our journal is currently welcoming contributions to five special issues on AI for accessibility, the metaverse intelligent technologies for future networks and distributed systems, satellite constellations and connectivity from space and next generation computer communications and networks. ITU Academia membership is another key avenue for academia to engage in ITU's work. Academia and industry are reinforcing their growing collaboration by working together in ITU experts groups responsible for the radio communication, sanitization and development. Contributions from academia bring greater strengths to the work of ITU and greater impact on research to the mutual benefit of academia and industry. We also supplement our membership-driven work with open frameworks such as ITU focus groups and initiatives like AI for Good, Digital Currency Global Initiative and United for Smart Sustainable Cities Initiative. These frameworks, as well as our open workshops, aim to give everyone the opportunity to influence our work. I welcome you to join us. Thank you. Thank you very much, Noyesan, for your welcome remarks. Now I'm very pleased to give the floor to Professor Iyana Kildiz, Editor-in-Chief of the ITU Journal of Future and Evolving Technologies. Iyana, the floor is yours for your opening remarks. Thank you. Thank you, Alessia. Good morning, good afternoon and good evening, worldwide. I welcome you all to the third season of our ITU Journal for Future and Evolving Technologies webinar series. The objective of our journal was to bring the academic and industrial worlds together in order to minimize the bridge between the academia and industry. Our journal ideas were incubated back in December 2019 and the inaugural issue came out in December 2020. It is an open access journal, no fees for the readers, no fees for the authors. The papers go through a review process and we try to cover all forefront research activities in the world, both in the academia and industry. I would encourage you all to submit your papers and also if you have ideas for special issues, please do not hesitate to contact us. The first two seasons of our webinar series were dedicated to the leading academicians worldwide, where this season has the industrial leaders present their visions. Let me express my sincere thanks to our today's speaker, Alex Jinsong Choi, Deutsche Telekom for accepting our invitation and giving this webinar. I wish you an enjoyable and productive time. Alessia. Thank you so much, Ian, for your welcome remarks. And now I'm very pleased to give the floor to Dr. Bilal Jamusi, Chief of ITU Study Groups Department, who will briefly introduce our speaker and will moderate the Q&A session. Bilal, the floor is yours. Thank you very much, Alessia, and a very warm welcome to Dr. Alex Jinsong Choi, who is the Chairman of the Oran Alliance and Senior Vice President Group Technology and Head of T-Labs, which is the Central Research and Development Division of Deutsche Telekom. In addition, he's a member of the Technology and Innovation Management Board, where he has responsibility for several strategic topics. Dr. Choi has been a thought leader for over 20 years in the mobile telecommunication industry and the consumer electronics by driving forward key strategic and research topics in telco and AI. Dr. Choi was the first Chairman of the Telekom Infra Project, TIP, and previously served as the CTO of SK Telekom in South Korea. With the introduction of Nougu, the first AI-based virtual assistant in Korea, Dr. Choi, was influential in the development of AI solutions. Dr. Choi, the floor is yours. And for our participants, we will use the Q&A to queue in your questions as we go. Thank you very much. Over to you. Thank you, Bilal, for your kind introductions. Let me try to share my screen. Can you see the screen? Yes, I can see your slide. Okay, wonderful, wonderful. First of all, thank you, Ono Esang, for your kind invitations. And also, I'd like to thank Professor Ian and also Alessia. So, hello, everyone. It's really a great pleasure to join you today and speak about the exciting future of wireless communication technologies and the transformative potential of AI native 6G network. So today, I'm going to talk about AI machine learning, RAN Intelligent Controller, or RIC for 5G and 6G. And O-RAN Alliance that I'm chairing now, we have been promoting the introduction of open architecture in mobile networks, particularly in the radio access network. And in O-RAN Alliance, the RAN Intelligent Controller, or RIC, has been developed for RAN automation and optimization with cutting-edge AI ML technologies. Furthermore, an ecosystem around the RIC application, known as XS and RFS, is also being developed not only by incumbents, but also by startups academia. So in this webinar, I will talk about how AI machine learning based on RAN RIC will support the key requirements of 6G. So my first slide is all about the AI native 6G and the role of AI ML. So the terminologies AI native here, it means that the artificial intelligence is integrated into the core functionalities of a system from the beginning of its life cycle, meaning design, developments and operationalization and maintenance. This ground-breaking approach will shape the future of wireless networks as AI native 6G network will leverage AI technologies such as machine learning, deep learning, and now even chat GPT for the design deployment management that I just described. So what is the AI native 6G and what are the key requirements which is shown in this slide? First, we are talking about wireless AI ML, AI and data-driven communication and network design will enable joint training, model sharing, and distributed inference across networks and devices. Second, scalable network architectures. So this aggregation and virtualizations from cloud to edge along with the use of advanced relay mesh and even 3D topologies, if you include the satellite, will address the growing demand for wireless communications. And third is a new radio designs. It means new wave-of-form and new coding for centimeter and also subterrahertz and intelligent surfaces and joined communication sensing and large-scale distributed by more advanced duplexing like a full duplexing and energy-efficient RF will revolutionize the way we transmit and receive the data. Next is the communication resiliency and to end the configurable security, post-quantum security, general trust, and robust networks, tolerant to failure and attacks will ensure the reliability and the safety of wireless communication. The next is coordinated spectrum sharing. So a new paradigm for more dynamic use of a spectrum will leverage location information, environmental awareness for dynamic and adaptive coordinations. Lastly, merging of different words. So the integration of physical, digital, virtual words will be facilitated by ubiquitous low-power sensing and monitoring, as well as immersive interactions that take human augmentation to the next level. So here next slide is the AI native maturity model. So it is important to have a common maturity level framework in this context. We have already seen something very similar in other industries like autonomous driving industries. So here we can think of something similar for our telco industry. So Ericsson has introduced a multi-dimensional AI native maturity model as shown on the right-hand side in this chart. It consists of metrics of five different levels, each representing a step forward from non-AI native at level zero, all the way to highly autonomous at level five. The left column in the table shows different dimensions, such as architecture, collaborations between AI agents, data ingestion, storage and processing, and AI machine learning, model lifecycle management, and security, and last but not least, is a self-ex capabilities. For example, if you look at the bottom part of the table, you see the difference between different AI nativeness levels in terms of self-ex capabilities. To be specific, look at it. Level one, this bottom layer. Layer one has a self-awareness capabilities. And next, level two has a self-diagonesis and configuring and monitoring capabilities. And level three has a self-healing capabilities, which is quite advanced. And level four has a self-augmenting capabilities, nice, which is nice. And lastly, level five has the self-designing and AI driven AI capabilities. So if you ask me this question, so from which level, we can actually call it AI native. So my answer to that question is, you know, we can call it the network AI native from level three. So each of these dimensions evolve across these AI maturity levels, allowing us to have a comprehensive nuanced understanding of our native network journey. So this AI maturity model serves two purposes. First, it provides a baseline assessment of where a telco network currently stands in in its AI journey. Second, it shows us the target milestones for the next levels across the various dimensions. However, it is not, it cannot be the one size fits all. So the target level for implementation is decided based on individual business needs. So what works for one organization, one telco may not work for other telcos. But the model itself is very flexible and designed to guide us toward what's best for our unique business circumstances. Next is AI machine learning driven 6G intelligent communication ecosystems. As I said, AI machine learning will be seamlessly integrated into all network layers and devices. So this integration will encompass the entire 6G architectures, including every protocol layers and also AI interface resources such as radios. For example, if you look at the table on the right hand side, it shows four layers from fiscal data link and applications. It also shows what AI ML use cases make sense in each layers. For example, for network layer in the middle, they are there are energy optimization for recovery and scheduling my AI ML use cases, just as an as a reference. And also the use cases can further include other virtual functions, network slicing, etzy cloud and network orchestrations. So AI ML will be essential in optimizing all these resources and protocols. This holistic approach will pave the way for unprecedented level of efficiency, adaptability and performance in each layers in the telecommunication systems. Factors for considerations in integrating AI ML into your network to fully leverage the benefit of AI, certain there are certain other network environmental capabilities that must be considered. And one is the network interoperability. When we talk about interoperability, we are actually talking about the ability of different systems or components to work together seamlessly. The better level of this interoperability, the easier it is to integrate AI into the system. To give you an example, consider the introduction of multi-agent collaborations of distributed AI into the network management systems. So distributed AI can take data from various points in the network, analyze it and make decisions. So these distributed AI agents don't just analyze the data, they can also work with the network managers at every level enhancing efficiency, solving problems and optimizing performance. So as we move forward, it is important to remember that implementing AI is not a trivial task and nor is not a standalone task. Intelligent and virtualized open-rand. So the RAN Intelligent Controller, or RIG, is a vital component in the implementation of AI native 6G ecosystems. It's a primary goal is to provide a standardized framework for both non-realtime and near-realtime RAN control and optimization with AI ML that can be used across different vendor equipments and various network deployment scenarios. By offering a programmable and modular interface, RIG RAN Intelligent Controller allows for a variety of its AI ML applications, not as accept RAPs. The modules that have AI ML capabilities along with the flexibility to be used in a different ways can redefine how we innovate the resource management features in our radio access network. Lastly, securing a large and reliable set of data is absolutely, absolutely necessary for training AI model training and also integrating into the RIG platform. So that brings us to this slide over architecture of RAN Intelligent Controller, where RIG, as I said, or RIG is like an intelligent manager for radio resources in the network that connects your mobile device to your service providers. Its job is to make sure these resources are used efficiently. What's good about it is it can work with the network equipments from different vendors, thanks to the standardized open interfaces defined by the RAN Alliance like A1 interface and E2 interfaces shown in the diagram, this BG diagram. And it can be used in various kinds of network deployment scenarios. So this RIG is basically comprised of software tools that sit between different part of the network that connect RIG and other part of the networks and that handle different functions. It has a flexible and programmable interface that lets different RAPs accept and access and manage the resources. Central innovation enabler RIG, unlocking the RAN potential with the AI ML both 5G and 6G. So once again, RIG lets AI models or accept RF developers to provide a specific AI machine learning model for a specific use cases. For example, it can help us distribute radio resources and manage transitions between different cells and dealing with the interferences and balancing the workload traffic between different cells and managing 5G, 6G network can be really complicated because we are bringing a lot of network points, new radio frequencies and multiple types of radio technologies including massive MIMO and diverse network deployment scenarios. So the RAN Intelligent Controller is going to be extremely helpful at handling all of this complexity. So getting into more detail about RIG, two different RIG. One is a non-real-time RIG and the other one is a near-real-time RIG. So while the near-real-time RIG focus on the time-critical and latency-sensitive operations below one second, the non-real-time RIG handles a non-real-time task that can tolerate the higher latency here, I mean greater than one second latency. This separation allows the scalability and flexibility in the ORAN architectures. Once again, the near-real-time RIG interacts with RAN elements through the standardised interfaces known as E2 interfaces and also collect gather information and make the decisions based on the network conditions, traffic patterns and even user demand. And you can transmit a comment to the RAN equipment so that they can actually execute such comment. Alright, so the next slide is AI ML model training and learning approaches for non-real-time RIG. So here I'm introducing the deep learning as a specific example. So deep learning is also known as a neural network. It's a type of AI, which is a very powerful for many reasons. First, it has a great feature extraction capabilities. So deep learning is like an auto detective. So it can pick out important information from data automatically. So it means you don't have to spend so much time and effort to do it manually. And second, deep learning will use lots of data. And unlike traditional tools, deep learning performs much better with more data. And this is great because it means we can make the most of the best amount of data available in your mobile network. Thirdly, the learning without labours. So deep learning can work well with the data that's not laboured. So we should let the learning its own. So this is crucial when dealing with lots of unlaboured data. So deep learning can do much, much better job than any other machine learning models. And lastly, multitasking learnings. The information that neural network deep learning learns can be also applied to different tasks. This means less computing power memories will be needed when the system has to do multiple tasks at once. Next is a near real-time rig, deep dive. So as said previously, near real-time rig works in near real-time operating in timescale between 10 milliseconds and less than one second. And the work is based on measurement from individual network brand equipments like radio unit and DU and CU. And it communicates with other part of the systems through the A1 and E2 interfaces. And this is how it gets from the policies from the non-real, sorry, non-real-time rig through the A1 interfaces. And that policy will be used to make a decision in near real-time rig. And it manages network equipments in a very specific areas, again through E2 interfaces. Also, it has a functionalities like a database. I mean, REN, Radio Access Network Database, where it stores important information about different part of the radio access network like nodes, cells, bearers, flows, devices, etc. All related to each other. It's also capable of keeping logs tracing operations and collecting measurement. And also it can communicate with the upper layer orchestration and management system, known as SMO. So, except R-apps. R-apps is for the non-real-time, whereas X-app is for the near real-time. So R-apps in the non-real-time rig framework make rules that can influence how certain things functions. Think of it like, I mean, it's an analogies. Think of it like a backseat drivers. For a backseat driver, they are not directly controlling the car, but backseat driver can provide directions. Whereas the X-app, which is for the near real-time AI machine learning model, can actually do the direct control functions within the network elements. So it's actually an actual driver sitting in a car. So these X-apps and R-apps work at different speeds once again, except work on between the 10 millisecond and one second. So, for example, the non-real-time AI machine learning model, or R-apps, it does the following task. It gives police-based advice to the near real-time rig via A1 interfaces. It analyzes the data, it trains AI machine learning models, it makes inference, influencing for network optimizations, and it provides recommendation also on configurations. So the next slide is an interesting survey results. This is an operator survey. So this survey shows where, you know, the operator priorities. So it tells us the top, for example, you know, on the right-hand side, there is a chart. So these are the operator's priorities for the near real-time use cases. So if I look at the top three operator priorities, and they are optimizing video and video optimization, and the second one is a quality of service-based radio resource optimization, and third one is a dynamic spectrum sharing. So about 80% of the operators who participate in this survey picked these three top three use cases as their priority. So if you look at it, all these three top use cases, all about making sure high-quality best experience are delivered for those killer applications, especially the video. Today's, you know, according to the market research, the video comprises more than 70%, 70% of the whole mobile traffic. So on the other hand, there are use cases that didn't rank the high, but doesn't mean that they are not important. Still, my opinion, as the market, all-in market, or 5G market, further grow, the all-in and also the all-in technology grow, mature, and the other use cases shown here, like a MIMO optimization and traffic balancing and become also very relevant to the operator priorities. So then what is the business rationale behind these three top three use cases of RIC? So the reason why the business telco wants to use this RIC for the top three use cases are as follows. First, when it comes to the video optimizations, about half of the businesses see it as a way to provide the best experience for their customer, and other half see it a way to earn or create a new revenue stream. Second, when it comes to the quality of service-based network services, nearly all business or operators answer is to provide the best customer experience once again. Whereas for the spectrum sharing, dynamic spectrum sharing use cases is mostly about the savings, I mean operating cost, TCO or operating cost savings. Okay, so, so far, I only talk about the bright side of the RIC, but there is challenges for a RIC, AI ML-based open-run. And so, despite all this immense positive potential of AI ML, we must also recognize and address the challenges that lie ahead. So, first, in the area of AI-based run management, the challenges are shown on the right-hand side. First, developing a reliable conflict mitigation function for RIC to reserve overlapping or conflicting requests from different AI machine learning models or accept RFs. Second, challenge is managing the complexity of maintaining inference models, different inference models for thousands of mobile cells in near real time. Third, challenge is creating flexible AI models that can dynamically adapt to different metadata for SLA and KPIs from various operators and vendors. In the area of security, challenges are as follows. First, how to protect against malicious activities that may arise from continuous and seamless updates of models. Second, addressing deployment-specific security challenges attributed to virtualization and software-defined network approaches such as authentication authorization issues. Lastly, in the area of energy efficiency, the challenges are first, ensuring that all end compliance software achieve similar or better results compared to the traditional solutions. So, next slide, 3GPP run working group and AI ML focus. As you know, 3GPP is known as the primary standardization bodies for the 3G, 5G, you know, since 3G and 4G, now 5G and 5G advance and most likely they will continue their job for the next generation, which is a 6G. So, what are they doing in this context? The 3GPP run working group has already identified three pilot projects in this AI machine learning applications. Number one is a general state information. I don't want to talk too much details in the interest of time. So, number two is beam management for the, for example, massive MIMO, you know, beam management. And the lastly, positioning. So, they identified the three items that they will explore and to come up with what would be the, how the AI ML best support these three identified use cases. So, the goal in 3GPP is to evaluate the possibility of AI native layer one, which is a physical layer to enable the deployments and interoperation of AI machine learning based technologies in 3GPP specifications. So, continuing what the 3GPP is pursuing is this. By utilizing AI and data driven configurations, we can achieve end to end optimizations across the entire mobile network. The dynamic parameter adaptations powered by machine learning algorithm allows for real time adjustment to meet the ever changing demands of the wireless environments. The neural network system design can customize and tailor network performance to a specific wireless environment, ensuring optimal performance under various conditions. So overall, with the AI native physical layer or air interface design, we can achieve, we can enable continuous system improvements. In between major, two major 3GPP releases. So this is a very interesting notions. So meaning, once a one certain release is implemented in your system with a strong support from the AI machine learning engine inside, that implementation will further evolve automatically. So without, you know, waiting for the next release come out from the 3GPP. This is a new notion of standardization strategy. So switching a gear a little bit and talk about the chat GPT. And here I picked this use cases because this use case seems to be the most suitable use cases. And when we talk about the potential use cases of chat GPT in mobile network. So it's an intended ribbon closed loop AI network management. So it's a busy slide. Sorry about that. I borrowed it from the Ericsson article. Now let's deep dive into this specific use cases. Which is a network automations. It is once again, intent driven closed loop network automations. So the diagram here illustrates how it works on the left hand side. It includes a process of collecting various types of network status information and comparing with the operators network management policies. If there is any discrepancy. The AI agent identify the problems cause and determine the solution and fix this discrepancy problem by executing a series of comments. So this closed loop system typically operates automatically without human interventions. As shown on the right hand side tasks like network control, adjusting priorities in ongoing network sessions can also be performed using natural languages. Here is the chat GPT come into play. So in the context of intent driven networking GPT or trust GPT can be used as a component within the system, which play as a translator's of the high level intents into the machine readable and machine actionable network configuration common and policies. Let me give you an example how to help in this translation. Let's say so the, let's say one intent description says, it says, this is an example, ensure low latency communication between the finance department and the data center to support real time data analysis. It's like a high level natural language based intent, given to the systems. Then the chat GPT it translated to it read it and translated to a machine readable machine executable statement description. In this case, for example, it can translate to like this create a quality of service policy that prioritize traffic between the IP address range of the finance department and the data center with a target latency below 100 milliseconds. So this translated statement is machine readable machine understandable. Although the chat GPT can provide a more technical translations of intent. It is essential to have a specialized intent driven networking system in place to convert the translated into the machine readable SDN based actual configuration and put command and policies. One more use cases chat GPT chat GPT generated the software for network automations. So let's take this use cases demonstrating how to GPT holding programming capabilities can be used for network automations. You know, chat GPT has a programming capabilities, although, you know, as of today is not perfect, but it's a good enough. And it can greatly assist human engineers in boosting their productivity tasks like automatically generating script for a softwares, as well as AI machine machine especially the machine learning models. This simulation can be achieved using chat GPT's programming capabilities. Furthermore, it could open up future possibilities for developing functionalities such as on the fly testing and even simulation code generations on the fly generations, which is today extremely challenging task. So when we tried in adapt to the chat GPT. So there is a part of possibility, but it's not proven yet. So it's still too early to say any concrete evidence. So that brings me the almost the final slide. It's a chat GPT blessing or curse for mankind. I have to mention this. There have been warnings raised regarding the potential risk associated with the chat GPT technology for human kind. So these concerns highlight the need for careful consideration and responsible deployments of AI, like a chat GPT. And one of the primary concern is the issue of bias and misinformation and also hallucination issues. So chat GPT learns from various amounts of data, including online sources, which can contain toxic or biased, or even inaccurate informations. So if not properly addressed, this issue, it could lead to a perpetuation or amplification of existing bias and spread of false, fake information or false informations. So safeguarding user privacy and ensuring data security also crucial aspect. Finally, by last slide takeaways. So number one takeaway. AI machine learning will be the key technology vector for the true AI native 6G and its intelligent communication ecosystem enabling seamless and immersive integration across all aspects of our connected lives. Second, native AI at all network layers, protocols, computational layers and devices will ensure that AI ML is integrated throughout the entire mobile architectures 5G and 6G and driving efficiency performance, adaptability like never before. Third, a virtual open RAN with Rick will be the essential starting starting point and components towards realizing the AI native visions. Next is a RAN Rick allows for flexible vendor choices and architecture options promoting open and competitive market that encourage innovation and collaborations. And next is the accepts RF ecosystem will provide continuous and rapid implementation. AI driven features innovations for operators. Lastly, while several AI machine learning challenges must be considered and reserved for all and Rick. AI powered network automation intelligence will continue to mature and develop paving the way for a truly artificial intelligence and adaptive future wireless networks such as a 6G. So as we looking forward to the emergence of 6G and the wide spread, you know, adoption of AI ML in our communication system. It is crucial. We continue to evolve, innovate, collaborate and push the boundaries of what's possible. Thank you for your attention. Thank you very much, Dr. Troy. This is excellent. We have many questions as you've been presenting. So we'll try to address some of them. Perhaps I will start with the first question in terms of the state of open data sets to enable this AI machine learning in the current mobile networks. Yeah, I mean, it's a very good question. I mean, historically, there was, what can I say, all the generations solutions known as a song self organizing networks and there they also have the same issues how to access and collect the live data from the live networks. And so you have to negotiate with your business partners. In this case, it's operators and get their grant to be able to access such live data because the network operational data is extremely confidential. But anyhow, how operators willing to, you know, share those data because this is for their operational excellence. The other possibility is you can develop called the simulators will vary realistic simulators and use those simulators to generate artificial data sets, which can be used for the train your models. And that's also possible, because in that case, you can avoid the such kind of restrictions, kind of, you know, sensitive sensitivity of the live network data access. Okay, well, thank you. Related to data sets. There is another question on the privacy aspects. When one personal data is used in the Rick. How, how can we deal with that and ensure the privacy and the protection of people's data. Again, there are many, many tricks. You can all know anonymize the data's and so they are anonymized agents. That's probably most straightforward solutions for them. And of course, and all the, you know, data collection and storing and accessing, we have to comply with the regulations called GDPR. So as far as you comply with the GDPR, you most likely be safe. Very good. Thank you. On the following slide on slide 18, following question on slide 18, in terms of air native air interface design. How would we handle the impact and updates to the UI implementations and what would be the role of standard bodies in the context of self learning between three GBP releases. Yeah, that. Yeah. So, I mean, the idea is a simple. If you develop and integrate, it's called the AI engine, AI engine. And you ingest all these life data's in operations. And then the AI engine. Use these life data's and to further to train the existing, you know, train the models so that it can evolve or enhance the overall system performance and optimizations. So by doing so, I mean, why are you waiting for the next release. It's a two force one is a new new feature. So when it comes to the new features in the new next release. Yes, you have to wait for that and then implemented once that release is available. Honestly, you know, since the today's three GBP release release a 17 or 18. I think it's a feature wise. It's a good enough. I mean, of course, still there's some backlogs, especially for the, for the new features for the vertical industry vertical market but once it's done. Then I don't concern about the, the, you know, the features set off the existing release. So the remaining issue will be the optimization and performance, how to maximize all kinds of efficiencies, like operational efficiency, energy efficiency, spectral efficiency. So when it comes to the efficiency metrics. I mean, this additional continuous training the model can can fulfill those tasks. What I mean by, you know, your AI machine learning engine and models will continuously evolve as long as you continuously feed the live data. Okay, thank you perhaps related to the AI models Marco Carugias on the flexibility. And if there is any guidelines or common understanding on the choice of which models on machine learning approaches based on the application requirements. No, there is no one size fits all solutions, because the good news is that you have so many different machine learning models available to you, including the traditional one like very basic, you know, supporting back come machine as 3M and even the one for Easter and those are the basic machine learnings. And then we have a, you know, more sophisticated one like a deep learning convolutional or nowadays it's an LLM model transformer model. You have a variety of machine learning. So then, you know, it may not be too easy to figure out which model best fit for a certain use cases so I forecast that there will be a tools, which automate that task for you. So before one hyperscaler came up with this tool called auto ML. So auto ML, all you need to do is to provide the training data. That's it. And it generally automatically give you, give you the models for that, for that, you know, based on those training data. So same thing will happen eventually for more advanced machine learning as well. So I'm, you know, I'm not so I know that doesn't mean that I'm really a positive on that. But because there is a demand growing demand for such task, figuring out automatically figuring out the models based on the training data. So I'm so definitely it told those two will come out in the market and be available hopefully as an open source. So you can make it make some modifications and customizations. Okay, maybe one or two final questions, one related to the implications on the size and the number of antennas needed for 6G with AI, especially given the spectrum sharing. I mean, when it comes to, yeah, when it comes to the, you know, next generation, in this case, 6G, you know, it's all about, it always boils down to the spectrum. So which spectrum band, you know, depending on this, which spectrum band you able to use for 6G, you know, all other parameters, dimensions and scale of scalability and efficiency will be will be determined based on the spectrum band. So today, there is a lot of speculation and discussions around the centimeter wave, or I don't know, you know, this might be a right suitable spectrum for 6G, but I don't want to make any speculations because they just began the discussion so we will have to wait and see what this 6G spectrum discussion goes. Okay, final question, is the RIC capable of playing an active role in brownfield deployment of networks or says only for ORAN greenfield networks? That's also good questions. Yes. Initially, we aimed for the greenfield scenarios, but then why not, you know, why not trying to make the ORAN RIC interoperable with the traditional RAN. It could be via the EMS with a certain gateway functionalities, so between the traditional EMS and the ORAN RIC, we add a gateway. So still, this is just an idea. So the details, the debilits are on the details. So there is an interest. I recognize this interest from the brownfield operators. They want to adapt the RIC for not only for the new ORAN RAN deployment, but also for their existing network infrastructure RAN. And also, as I said in the beginning, you know, there is an older generation, previous generation solution called SON. So why don't we just let traditional SON directly talk to RIC. So this is also a possible approach. Fantastic. Dr. Choi, I'd like to thank you very much for the presentation, the excellent presentation and the excellent answers to the questions. And I turn it over back to Alicia. Thank you so much, Bilal, for inviting this session. And thank you, Dr. Choi, for your very interesting presentation. So now we will quickly move for the last minutes of this webinar to the wisdom corner live life lessons. So Dr. Choi at Mason agreed to guide students and young scholars in the field of current ICT research, and also he will share with us some impactful life lessons. So I would start with my first question. So Dr. Choi, which is your hard-earned life lessons that you would like to share with us today? Okay, so, yeah. Every project, every project begins with the customer expectation. And I was usually confident about the success of my projects that I led. You know, I tend to believe my project result could meet the needs of customers and bring the significant impact to the market. However, my lesson, here's my lesson learned. In many cases, the reality was the reality is very different from my expectations. So it was as if I was thrown a stone into the sea expecting a big splashy, but instead only cause a very little ripple. The market response is truly harsh. The customer interest in our product was made in many cases, very temporary. So this experience gave me a very valuable lessons. I realized that the market response is more uncertain than I thought.   So it's only after you launch the product or services, you are actually better understand the real demand and needs on many and from your customers. So this kind of a feedback after a lot launching is absolutely crucial. And lastly, the technology alone is not enough. You know, you need to understand the whole customer journey and focusing and addressing the real customer problems. Excellent. Very useful. Thank you for sharing these lessons with us. One more question in which field and in which topics you would recommend students to study today. You could perhaps share with us some, some emerging technologies or trends in the ICT field that you find particularly promising for future research, because we believe that your advice could definitely guide students but also the young researchers who are just starting their careers in ICT. Yeah, yeah. I mean the good news is that there are so many different emerging technologies or trend in this area in ICT domain. So, but then if I, if I pick some of it, I strongly recommend this interdisciplinary area, like a convergence technologies relating to the digital transformations. And so here you need the, you know, component technology like AI machine learning, cloud, big data, wireless communication, industry 4.0, robot and drone. You don't need to master all of it. You have, but you have to understand what those technologies capabilities. And then you focus on the certain business case, not just the use cases, business cases in area of digital convergence or digital transformations. So that's, that's my recommendations. Thank you. I'm sure everybody took note of that. So my, my third question, how you spoke about the chat GPT in your presentation so we are wondering how will in your opinion, chat the GPT impact the future of research and let's say everyone's life in general. Okay, so my general level. And it's a usefulness is to Ford. One is, you know, it can give you a very good enough insight for any new domains. Yes, they, their outcome is based on the training data's existing data's, but somehow chat GPT is smart enough to give you some good insight on on any new topics as well, I was very surprised. And, of course, it could be a fake or hallucinate the result of the whole hallucination. But anyway, it's quite inspiring. And yeah, so that's one use usefulness. And even if the answer is not so accurate. I mean good enough answer. It's okay. It's acceptable.  So, yeah, so you can save a lot of time. Once again, check GPT it's a best usefulness is all about the productivity enhancement for you. And second, it could be a very good sparring partner throughout your journeys. Once again, you know, check GPT. For daily life. It's like a AI agent. So we can continue to give you the timely information and inspire you. And in many cases, I mean, it's always good to have some real time on the spot. So that case, it's for daily life, AI agent, check GPT, because it's it's use natural languages and also multi-modal GPT can also use the non text textorial communication like pictures, videos, or even other sensor data based information locations. And so on so on. So that that's the those are the things. May I ask you how do you use it? How do you use chat GPT? Can you, can you give us some example? For instance, have you used it today? Yeah, I'm a paid subscriber. And I use it daily basis. And mostly, yeah, mostly, I'm using it to get some insight and more detailed information about some of the topics that I am not so familiar with yet. All right. Okay. Thanks for sharing that. I have last question from my side. How do you stay up to date with the latest advancements in the research in the ICT field and is there any specific resources, journals, books that you probably have recently or communities that you recommend young researchers to engage with? Yeah. Personally, I, I, I'm a big fan of both chat GPT and YouTube and Wikipedia. Oh, yeah. And the important thing is that, you know, you, you have this mindset. It's like a problem solving mindset. So you always think about what could be the good customer problems you can, you can tackle. So, and then continuously think about how to solve that problem. So, you know, why, you know, if you have a such problem solving mindset and being more curious, and then you always, you know, a desire, have a desire to search for all different types of knowledge, information, insights, and best practice, etc. So, I mean, there are so many information sources, but the most important thing is that you have to have a such desire to explore such informations and knowledge. Thanks. So these are first. Thank you very much. I would like to invite Dr. Oh Noe San, my director, Dr. Bilal Jamusi and Professor Yana Kildiz, if they would like to join me for the closing, and please feel free to take the floor before we close. Thank you also, Alex. Very nice presentation. Thank you. My pleasure. Yeah, Bilal Oh Noe San, if you would like to say a few words, feel free. I think Oh Noe San is on mute. Maybe Oh Noe San, you can unmute. I mute it. Thank you very much, Alex. Okay. You know, you are my mentor. You are my mentor. Long time ago. Yeah, very great. Nice to hear that, Bilal. Yes, thank you very much, Dr. Choi, very good insights also for the young scholars. And very pleased to also see Ian, Professor Ian on the screen today. Good to see you. So you're here. Excellent. So thank you very much, everybody. Thank you very much to our speaker, Dr. Choi. And I would like to say that we look forward to seeing you all online again next week, next Tuesday at 4pm for our third webinar with Dr. Alex Sinclair, CTO of GSMA from UK. So thank you very much, everybody. I'll see you online next week. Thank you. Thank you again. Bye bye.


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