This video is brought to you in part by TrueTechTools. Quality tools, essential support. In these cases, it traps it in, doesn't go anywhere. All right, so right here's a leak and somewhere in this right here. Yeah, look at that. This is your medium temp rack. It's a 13. We'll narrow it down. I put a leak up here that way we know. All right, so we came back to look at this case here that we had a leak from over the, I don't know, two weeks ago that I was here. I hope that we had a leak up here. Anyhow, as you can see, I've stopped the fans. I have outed off the suction pressure so it's building up and it's just going berserker. So what we're going to do, we're going to go ahead and put it into our PPM mode as usual. We'll see if we can narrow it down. The problem is my coil in that nasty back-action section there and I don't think it's going to be very easy to find it, unfortunately. This is probably not going to pull out very good. We'll see. Yeah, it says probably a big leak. Just jump down here because I'm pretty sure it's on the end because when it went off it was in the air band over here to the left. Yeah, it's definitely up here on the left. Same as what I figured when we found the leak. But in perspective, that cover comes off part of here on the top, which pulling that out is probably not going to be very easy. Yeah. Yeah, this is terrific. So what you have to do is you got to take out them screws there, there, there, and drag it out. Loving it. It definitely is in this vicinity here. It's towards the bottom as you can see. Oh yeah, she's not happy. Tell me about it. Tell me how you don't feel good. Yep, tell me where it hurts. There we go. Get down here in the bottom. Look at that. We're going to go over a thousand here probably. Yeah, it's leaking down there in the bottom somewhere on that bottom loopy doops. Hopefully not so much here because if it's in the middle of the coil, I am not going to even try. Yeah, not even going to try. What's bad is is it's right there in the middle where it's going to be the hardest to get my torch in there and fix it. And I don't think it's just one or two. That's really bad. All right, probably the best thing to do here in this case is probably why they cut it before repairing it in place, which was how I did the last one. It wasn't too bad, but this one here, because the case is at the end, there's just no way to get into it. All right, so we're going to make an end piece for that out of seven eighths. I got inch and three eighths now, inch and an eighth, so I can do pretty big size refrigeration copper. Got these both at TrueTech Tools as always, guys. Actually, I got the whole thing from TrueTech Tools. So anyhow, about 105.  Now, go right into these coils. Freaking, some of them are actually going through high gas defrost. And so they get hit with 250 area. All the band-aids are starting to come off again. Let's see here, kids. We've got got that one right there. It's got my little honeycombs. You got one right there. You got that one right there. Got one over here it was missing. Let's just go ahead and build a whole new coil while we're at it. There's one. There's one down here on bottom. Missed that one. The one I'm using here is my two tipped head here. I went through. I used brake cleaner after running the brush wheel on it. Well, I went ahead and just did all of them. And this is the side that wasn't even really, you know, leaking the worst. Still got to do that other side, but that's what we're doing. I don't, I didn't really want to run the full-blown GoPro, so I'm just using my phone. But that's what's going on. You can get it super, super clean.  So you can see I went through and completely redid all those because what's going to happen generally is you're going to have one that gets fixed and the one beside it leaks. So we ended up going through completely through the whole thing. We just ran the garden hose and melted the ice off. We just took it out the side here and we've got everything done up. So we've got these all it all pressure tested. Got our pipe undone there. And this turned out fairly well for what I had to work with. Those are the original ones there. I didn't mess with those. There's mine, look more like normal. And a couple of those had some weirdos in there, but we was able to get into it. And I just went ahead and went over all of them. As far as anything in the middle, didn't do ultrasonic, anything like that because I'm not going to fix it anyway. Got her back in there, got that little flat plate deer in there. Just got down, pulling the vacuum there. Just let some out through the liquid, stopping it here at the suction port. We got about 95 on there. We're going to go out and check that suction line. All right, so we've got that breezed back together there. Went ahead and put some nylog on all of my clear fittings, put that back together. And since it does not appear to be leaking, I'm going to go ahead and get this all detached. I've been bit in the butt where micro bubbles may not show up right away, so sometimes it's just better to double check it with your leak detector. I'm not getting anything on any of my repairs. Like I said, we've already evacuated it. I'm kind of just waiting to see, you know, is there anything leaking through the center? If there is, it's tough to look, scooby-doo. I'm not picking up anything, which is good. And over here is where everything was a disaster. I would say we are good. Or is this thing is concerned for today until it leaks again? Got all I know is that this other high quality piece of machinery has got any issues? Oh, that's always a good thing to know. Great. So we've got an older, this other coil is probably leaking too. Awesome. Problem is, whole stores like this. Unbelievable. All right, guys, so I just repaired this coil two days ago. As I put it back together, I wanted to make sure it didn't have any leaks. I was scanning around, and when I brought my wand over to here, it went off. Then it went dead. Then it went off again over here. What we ended up doing is coming back. This is a lot smaller coil than what the other one was. I cut it there, I did the TXV after we obviously pumped it down, and we got it in the back here. I didn't record actually doing the repair on that one. Let's go ahead and show you what I did. Do what we got going on here. Same coil, same setup we had before. So we got the same pipe we had the last time. Just going to slide that on a little bit. This here is Captain Hook, made by Uniweld. So is my torch handle. Now, this is Victor Torches, which belong to the company, but I bought the handle and the tips because this little tip here, which I'll have links in the bottom. You guys want to buy it through the links. It's the same price as Amazon normal, but I get a commission off of it without paying a nickel more. How do your pocket? I like this handle because the knobs are towards the front instead of the back. So we got our settling. You can leave them long, you can leave them short. I kind of do a little bit of both. This really is not necessary here on this particular, but if you are in that case and you're trying to get all the way around it like this, if you see we're kind of like all the way around it and you can just move back and forth a little bit, just about basically do one thing here and then bring it into it. Got my bucket here. You guys have seen this a million times. That's where I keep my micron gauge, which TrueTech tools blew back. Best gauge on the market period bar none. And then that's where I keep my other goodies. I've got all this stuff listed in my tool area down there. Viper wet rag, Viper supported me. I got to give them a shout out. If you wanted to, you could purge through the coil, get all the air out of it so that when we're doing the brazing, we're not corroding the inside of the pipe with carbon. Now, just so you guys understand, this is not my idea of what I wanted to do. I am not one for avoiding spending money on a new coil at all. Getting these are sometimes very hard. We're going to go ahead and go down here and we're going to squirt all these down with a nice solid stream. Chances are I'm going to go through here and redo every one of these because if you do the one beside it, guarantee the other one beside it will likely leak. Now, what I used was my wire brush wheel for most of it and what I couldn't get to with that, I used brake cleaner and then wiped it all off. That worked really well. I would have never thought it would done that good, but it did. Pretty much all of them are on the solder joints. So we're going to go around and get all those. See what we got over here on this side.  See the water beating up? That is a sure sign of oil. There's oil. There's a refrigerant leak. Right there's one leaking on the end. There's one in the middle there. There's one right there. So just plan on doing them all. We'll go ahead and open this side up, which will let the nitrogen through, pushing the oxygen out, and then we'll do our repair. Got one of our other guys over here doing a repair on the thermostat we just installed. It's a Ranko and it was off by seven degrees. So we had to come back and replace that. Okay, we're going to go through here.   I have a couple leaks on this manifold over here that I didn't have on the last one. We're going to try to get in here as best we can with the brush wheel, the cleaner the better. All you can do is do your best. I'd like to see these replaced, but unfortunately it's not in the cards. Even when they have replaced cases, they were 13 years old, bottom used from somewhere else. So I mean, it's just expensive. These cases are super, super expensive. Some of these cases, like the deli pieces, can be $45,000. It takes a lot of a lot of baloney sales to pay for that. And I get paid the same amount of money to sit here and do this as I do some of the other stuff I do. So what's it matter to get any of that last residual that we just broke loose off? Like I said, this stuff is flammable. So you want to make sure you get it all off and I'll just go bulls the wall in there and trying to get into it. See what we can do here. I've already got this set up so I can go on both sides, but we're going to basically what I did on all the other ones. And I got my top nice and warm. And once I got it ready to flow, but you know, I like to just do a little tap, kind of see. And I'll even throw a little bit on the back side just for she-dizzles. Come in here and this inside, get in there like that, pull it to the back. Same thing here. We're pulling it in there. We're not just coating it around the top. We're literally getting in there and getting it all the way to the back. Come on to this one here. It's nice and warm already. We're going to get a little bit of heat, drag it across. There we go. Starting to pull. We're moving around because we do not want to burn through this thing.  There we go. Going in there. There we go. Pull it into the back. And there you go. So that's how we're doing it. So we've gotten it all the way around and what we're doing is we're using just enough heat to do the job. Now what sucks is on your on this other, other loops, we're not able to go in here at an angle like I'm doing right now. Got all of these. They're all completely done. Don't look too bad. I don't have too many major issues there. Everything soaked in pretty good. We're able to come in here like this, like this, bottom and pull it all the way back into the actual, I always call it a pocket or a socket, but every one of them looks pretty good. So we're going to go ahead and go through. Every one of them sunk in like they should went ahead and went around everything on it and completely redid it all ready to do a pressure test on it. So we went ahead and went through everything here and everything worked out good. I did have one screw up down here at the bottom. I didn't pull into the pocket quite far enough. And then I had one screw up here on this one here, which was hard to get to, but I went over top of it again, just used my C shape in for that one again. And then I used my Rosebud, like I said, for the other one. So we've got it. We went ahead and repressurized it to 125.  Okay, here we go. Let's see if we can get this thing in there.  There we go. It's just like new again. There we go. Put it back in there like that. There we go. Let's see if we can get that slit on there. Look at that. Let's get a little tappy tap. Didn't tappy tap very good. It's got to go dead away. This probably helped if it wasn't in the way. There we go. Look at that. Hot diggity dogs. There we go. Maybe go up and down a couple of times. There we go. Perfect. There we go. See how that does. So I used a zoom spout oiler with some POE oil on it. We're just going to put that on our fitting so that everything kind of screws together nice and easy. We're going to put some most importantly on the back side of this flare here. Okay, now we can go ahead if we want, see if we can get this apart. We could try to do the body, but honest to goodness, I think I'm just going to see about getting a new TXV. Somebody's probably tightened it so tight that they've smashed that little miniature ring that's in there that's made to do the ceiling, but somebody probably got on there with their gorilla grip and decided to destroy it, thinking that that was going to be the best way to do it. And once it's smashed, it's pretty well screwed after that. Now adding that oil hopefully will help there. I'd really like to try to do that body. So let's go ahead and put a little oil in between there. We'll see if it leaks or anything. Let me get down there. And the screen was really clean on the other one. I don't feel like doing it, but I kind of feel like, you know what, since all eyes are going to be on this, probably should do it.  There's the screen. It's clean. Just eliminate it as a possible problem later. A little bit here.  Okay, it's not wiggling. Light on the bottom. I don't see no light coming through. So I know we've got good contact with the pipe. It's kind of on the edge, three o'clock area. Don't want it on bottom. They have different positions based on diameter of the pipe. That was where it was at. So we're putting it back that way because that's how the Superheat was set up originally. All right. So we've got her up and going. We're pulling back. We're not going to use the micron gauge. I'm just going to make sure we hold it 30 inches.  Not to mention the oil that's in there would take forever to pull up her vacuum.  So we're moving on, not to mention all of the potential leaking through the valves here and the liquid. So it's just, it's not worth it, but we'll valve off every so often to make sure it holds 30 inches and we'll move on and let some liquid back into the system.  We're still valve off on our suction there. That should be plenty to get us up to at least 80 pounds. It's leaking on the one beside it. Okay. So we had alarm and of course it's the one that I didn't even touch, but it got hot beside it and that's where it's leaking at. We're not even leaking on the one I was on. Pump her down again. Didn't pick up anything on the valve. Okay. We just repraise that. We're getting ready to recheck everything. This should all be perfectly okay because we did the nitrogen check on it. Now if there's anything leaking in the middle here, ain't going to be nothing we can do about that. We use the blower there to blow anything out that was maybe laying around in there. So we're going back through. We're on super mode still. So like I said, we just use the Milwaukee thing. Thank goodness we don't have anything back here in the coil. I don't think it's leaking on those distributors. I don't know what to tell you. Yeah, on high mode it's not leaking there, but on the distributors it's leaking. I do not want to repair that. That's brass. That can be a total disaster. Okay. Now we're in the distributor tubes. We're looking at about 290 to 300 depending on where we're at.  So we're going to take a chance here. I loosened it up so we get the tension off of it. We get the blue rod, already flux it with the other flux. We're going to do what we can do with it. Just let it naturally cool down. All right. You guys want to see when things go wrong? Here you go. So we got this fixed, which I was pretty scared that it was going to probably fall apart because you can see all the pitting in it.  But on the bottom that you can't see, some solder has came on down here to the freaking flare fitting. So hopefully it's not actually inside of my distributor tube. So we've got to pump it down one more time so we can do it again. I am having a good time. And this here, it appears it was just drizzle. I don't know where it came from. It could have been to this top piece where three-eighths comes out. That seems like I got it.  I hope for the best. Definitely got a little bit of a funky monkey juice in there.  So you just put your brush in there, knock the stuff back out. I don't see solder in the torches itself. So we'll grab some oil, put back on her. I start my camera before I know what the results are going to be. Nothing's coming out of the bottom. That's good. It's leaking from the fitting, ain't it? Yeah, it's leaking from the flare. You know, tightening this up ain't going to make a difference. But hey, let's try it anyway. Nope, still leaking. That's the way I love it. All right, guys, so we ended up taking it apart. I don't know if I recorded or not. I'll show a picture. This tube popped out. That makes your stomach just go, oh yeah, this is going to be great. I'm so glad I'm here today type thing, you know? I ended up putting it up against it, fluxed it, heated it up, pushed it in. I definitely recommend undoing this like I did originally.  I went ahead, took the flare apart, cleaned the flare out with the wire brush, cleaned it all out, wiped it out, put good old nylog, good supporter of the channel, and put it on the face and on the back of the nut or yeah, back of the flare. Put it back together and by golly, I think I finally got it. I have done this multiple times over and over. I am so beyond ready to leave. It's now almost five o'clock. So yeah, this has been going on for quite a while. We got at least 90 pounds of pressure. I left the suction stop, stop, closed. It appears we got it. Not perfect guys. I definitely have my problems. Everything else here went really good on that, but this part here just really stunk. We're in super mode. Just using my blower down there and blow this all out. We're all in the crevices there. We're getting nothing on the flare joint. Nothing bottom side of it. Nothing, nothing on any of that. None of the flares. Nothing on those distributors. Nothing on the distributors at the actual unit. Nothing in this area here. Nothing on the one that was originally leaking. Nothing on the other side of the TXV and nothing on the equalizer tube. Nothing down there and I've already scanned the other side of the coil. So as long as it feeds on that one that may have came apart, I'll be okay. All right, let's check these distributor tubes. I have turned the system on and that these are feeding. They're all going to be cold. That one's cold. That one's cold. All four of them are cold. It's feeding. Finally, something goes right today. All right, very good. All right, so let's get this thing together. So we're coming over here to the A13, which was a 20-foot lunch meat. We're at 36 to 41 already. At 41, that was the last one I just did. That was the coil. You can see we were all way up to 70s. Maybe you can't because sometimes this doesn't focus real great. Last, you know, it went 51, 46, 43, 51. So it's dropping just like it should. The other ones were already at 35. You can see that we have been holding really good now that we set the EPR. For whatever reason, they didn't have the EPR set, right? You can see these ones here cranked all the way out. It's like, why? I have no idea and I'm afraid to change stuff like that. But I set this one here at about, I think I set it at about 25 degrees, 22. Actually, it was 20 degrees originally and I'd rather set it somewhere around 25 so that we could hold maybe 35 degree areas. So usually go about 10 degrees below, just depending on the case. Sometimes it's 15, but it seems to be 10, 12, somewhere in a bulb work. You got to watch it, see where you're at. But that's what those do. But like I said, it's kind of weird that somebody has taken some of these out. Maybe they fell out. Not sure. Right now, we've got it back together, got the caps back on it. The rack seems to be still at a decent level. We're at 20%. That's assuming that it's accurate. Other cases appear to be pretty decent. You can look at set points. You got to remember too, none of these are really set. They're just whatever the EPR landed at. Probably could use a little more in it. But honestly, I don't really want to put it in there just now. We've got more stuff that we could be doing. We're waiting on approval for


And we are actually one minute before schedule, right? This never happens. So the organizers are doing a great job. And I think they've also scheduled the talks well, because you heard Dr. Anand's talk in the morning, where he did a deep dive into how speech recognition happens and really sort of went deep into that. And I just spoke a little bit more about some algorithms about image and video and audio processing. And I'm sort of continuing that conversation, right? Where I'll talk a little bit about audio processing, but also how we sort of understand what the user's saying and what the intention is. So I think it's a nice sort of flow between those three talks. So before that, and just to quickly set context, again, I spoke a little bit about how humans have evolved from the last millions of years. But let's talk a little bit about how our interactions with tech has evolved. So if you really look at it, this is how we have interacted with personal tech. Personal tech sort of started in the mid-70s, where you had small, I don't know if you can really call it personal computers, but small terminals, right? Black and white monitors with just a keyboard and you interacted via character mode, right? Not unlike the terminal that we use now while coding, but that was all there was. Sometime 10 years later in the mid-80s, things changed. We moved to a sort of graphical user interface. Companies like Microsoft and Apple and Xerox came up with visual operating systems, right? So you actually had, you could actually see a file, you could click on a file, you could move this piece of hardware that would translate onto the screen, your computer mouse, which didn't exist before. Sometime in the mid-90s, things changed again. We moved to the web paradigm. Again, how we sort of interacted with tech, I think changed that time, right? Because you had early versions of browsers. It's fairly young crowd, but I'm sure a lot of you all remember early versions of Netscape Navigator and Internet Explorer, where it took forever to load the static website, but there was a thrill in actually seeing that. And how we interacted with tech changed. You had radio buttons, drop-down menus, browser components that came into the picture. So things changed then. In the mid-2000s was the era of mobile and this is something that I think we are all familiar with. And even in the 15, 20 years or so that we have had the mobile phone, things have changed so much, right? We have gone from really clunky, basic phones with small keypads and black and white screens to the advanced smartphones that we have right now. And just think of the sort of interactions you have with your smartphone right now, like how do you zoom in on a webpage, right? You do that, you pinch to zoom, or you swipe right, or you pull down to refresh. These interactions didn't exist before. So as tech sort of evolves, so does how we interact with tech changes. So if you can see, almost every 10 years or so, there's a change in how we interact with tech. So as if on time, sometime in the mid-2010s, things changed again, right? And the paradigm sort of shifted to voice user interfaces. And now, we as humans, we've been using voice as a means of communication for a really long time, about 100,000 years. It is an integral part to how we communicate. But surprisingly, our tech hadn't reflected that up until then, right? People had tried, but it was simply not technologically possible. Now, we finally have access to the computing power, we have access to the networking power, and we finally have access to the data that sort of allows us to be able to talk to machines via voice, right? So we at Amazon, we truly believe that voice represents the next major disruption in computing. And you guys probably hear this word a lot, disruption, when something changes the status quo, or a new platform, or a new product, really changes how we operate something, or changes how we behave. And we believe in computing, voice is the next major disruption. We, of course, saw this disruption happen, and we came up with this beautiful device here, it's called the Amazon Echo, right? Essentially, there's a line of hardware products called the Echo, there's Echo Dot, Echo Plus, et cetera. There are also third party devices, and all these devices are really powered by the Alexa cloud, right?  So everything from switching on your smart light to getting the news to playing music, to hearing a song, all these things that you typically do on your phone, now you can do just via your voice, right? They're completely voice controlled. The great thing about these devices is most of them come with either a five microphone or a seven microphone array, so it enables something called far field recognition. So I don't have to have the device right next to me when I talk, I can stand across the room with ambient noise and still interact with these devices, right? So similar to how on your phone, when you buy a phone, it can do a few things out of the box, like make calls and SMSs, take photos. What's the first thing that you do, right? You download apps. Similarly, you can enable skills. A skill on Alexa is like an app on your phone which sort of enhance the capabilities of Alexa. So a lot of things you can do with an Alexa device, but you can really enhance the capabilities via skills. So you can order an Uber cab, for instance. You can play a song via seven. You can get a restaurant recommendation via Zomato and so on. And similar to the mobile app ecosystem, the skill ecosystem is completely open. So third party developers can, in fact, build skills on their own, right? And there's a skill store. You can publish your skills there and anyone else can actually use it. So, and by the way, I'm doing a workshop on how to build skills this Sunday as part of ODSE. So if anyone's interested, please sign quick plug there. But so that was just a set context. Today, though, we're going to talk a little bit about how Alexa actually works, how machine learning and data science plays a huge role. It is so vital to how Alexa actually works. And I'm going to talk a little bit about the sort of customization that we had to do with an Indian context, right? Alexa launched earlier this year and there are so many things unique about India and how we speak that we had to do a few customizations for the Indian market. Before that, though, like I said, machine learning plays a huge role in how Alexa works, right? Recently, like I said, I do a lot of these events and someone asked me this question saying, if I buy this device now, when will it get outdated? When do I have to buy the next version? And without the risk of sounding too like markety, you don't because all these devices are cloud based, so as long as you're happy with the quality of the speaker, all the enhancements are happening on the cloud, right? So soon Alexa will be able to understand more and more, more accents, more words, more context, more languages, while the device sort of just serves as the conduit for like an input output. So the cloud really is getting smarter thanks to all the machine learning and the sort of breakthroughs that are happening with speech recognition and natural language understanding. Cool, so let's sort of dive deep into how some of these things work and you will see this slide quite a bit today, right? So essentially, this is how we use data in machine learning. It's highly simplified of course, but we sort of split it into two phases, right? There is a training phase and an inference phase. In the training phase, what we do is, and this is like say before the Alexa device was launched, we didn't put a lot of training data for speech recognition, for natural language understanding, whatever, and we'd have a ground truth, right? A ground truth is basically something empirical that we know to be the truth and we'd put all of those through a trainer and have certain models, right? And then in the inference phase of course, when like a user comes and interacts with Alexa, that's the input, the decoder sort of infers the output, right? And if your training data is very good, obviously your decoder is going to be good and you're gonna get like really good results with the speech recognition and the natural language understanding. So I'll get back to this slide a little later with some specifics. Typically though, this is how Alexa actually works, right? If you have to really break it down, excuse me. So on the left, right, is a device right there and those are all the components on the right that you see. So you have ASR, which is automatic speech recognition. You have NLU, which is natural language understanding. You have skills, I just told you what the skill was and you have the text to speech component. Now each of these four components have like a lot of machine learning and data science that go into it, they're actually, you know, sort of ensures that they work well. So suppose a user says something like Alexa play music, right? Very generic statement. First is the device listens for something called the wake word, right? And here's where I really stress that most of the magic, most, all of this happens in the cloud, right? The hardware device in itself doesn't do too much. It just listens for something called the wake word, right? And the wake word in most cases is the word Alexa and you'd be surprised as to how much like, you know, data science and machine learning goes just into the wake word engine, right? Because it has to be, it has to accurately, you know, sort of pick up Alexa and someone in India versus someone in the US is going to say the word Alexa differently, right? So it's something I didn't expect but there's actually a lot of science that just goes into that one small thing. So there is a wake word engine that listens to the word Alexa and once the user says Alexa followed by an utterance, whatever the user said is pushed to the cloud, yeah? In the cloud, there are a few things that happen. First is, you know, you obviously need your speech to be converted to text, which is where ASR comes in. That's the first step right there. Once that's done, you sort of need to understand the intent behind what the user said, which is basically what natural language understanding is. So that happens, you get the intent. Then you need to push that to a skill. It could be an inbuilt skill or a third party skill, right? For you to actually complete or execute the command or to respond to the user. And then finally, that text has to be converted back to speech, you know, for text to speech because again, we are in a voice first world so the user needs to hear the answer or you know, maybe the song. In this case, when they say play music, they need to hear a certain song. So let's take each of these steps and let me tell you how data science and machine learning sort of plays an important role. I'll be largely concentrating on the NLU and the skills part of it today though. With ASR, again, I spoke a little bit about automatic speech recognition. I mean, there are two phases to it. One is before launching the device, how do you really sort of make it accurate given that there are so many different accents, so many different dialects and so many different ways of saying things. So we did something called active learning for spoken language understanding, which is a sort of semi-supervised way of learning, right? So essentially, we had some existing speech-to-text models and again, before the device was launched, we put a lot of data into it, right? So and it was semi-supervised. So the model essentially looked at confidence scores and it did, if the confidence score was below a certain number, it would send it for some human intervention, right? And then humans would listen to it and actually transcribe the text, do speech-to-text for a large amount of data, right? And this was, of course, when we launched, before we launched the device in the US, that was like few years ago, but before we launched the device here, we had to follow like a similar sort of exercise as well. The thing is the model itself figured out the important labels to get the human utterances for, right? If the confidence score, if it was slightly below a number, it wasn't able to accurately do it. It wasn't able to accurately get that speech-to-text. Human would listen to it and transcribe it, right? This way, remember I said there's a training and an inference phase. You were able to train a large set of data without having to do too much manual work. Once that was done though, and everything was set, we have to sort of rely on ASR to get accurate speech-to-text, right? Speech-to-text is solved, is a sort of solved problem, but there are times when a phony might look like this, right? When someone says 40 times, right? So what could it mean? Now, how do you accurately get what the user said? Mainly because of this, right? It could mean that the user said 40 times, like doing something the number 40 times. There's a chance the user meant for T times, right? The phonemes are the same, and this is a reference to Chai. Maybe the user meant for T times to T off as into play golf, right? Or there's a chance that the user meant for T times, yeah? Something like this. So there are so many cases like this, especially in spoken language, when people are trying to be conversational, where like a phrase or a word might sound very similar. So how do you sort of differentiate what the user said? What happens in this case is Alexa actually looks at the training data that a developer provides in reference to a skill, right? So for example, if I'm a developer and I've built something to do with T and coffee ordering and a user says, you know, Alexa opened the skill and then says 40 times, there's a good chance that they meant this for T times, yeah? So that is that one extra step that we do to sort of accurately match, especially in cases like this when, you know, a set of phonemes could mean like two, three different things. Once that's done though, you need to, once that's done, you need to, you know, actually do the natural language understanding before that. But let's talk a little bit about how we had like to do some certain things for the Indian market, right? So there are so many words and phrases and things that are so local to India. Like for instance, back in the US, not too many people actually say who is the prime minister because that designation doesn't exist, right? So we had to sort of feed in the data and there is a tendency with like an Indian user to say the word prime minister instead of prime minister, right? So all these sort of variations actually had to be fed into the system. Also things like food names and festival names as well, you know, locality names like Malaysia was very difficult, right? But thanks to all the machine learning that we have actually fed into, it's now able to recognize things like Malaysia. There are a few more complicated things. People say things like, remind me to go to Mukambika Devasthanam, right? It's not going to get 100% matched just yet, but luckily with some of the algorithms that are there and with repeated usage with users saying things like this, we're going to get to a place where, you know, we can actually accurately say that. Cool, so that's done. The speech is converted to text, but now how do you really sort of understand what the user is saying, right? Yeah, so his question was to the truth can be sort of expressed via not just voice but gestures and things like that. So for this talk, I'm going to be talking only about voice. Amazon does have something called the echo look, which is a camera that sort of helps you with what to wear and gives you things which is basically sort of going towards the whole multimodal ambient computing thing. So in the future, it'll definitely be a part of it. For this talk, I'm just going to stick to the whole voice aspect of it, yeah? Cool, so I'm going to use one specific example. Does anyone know where this is from? Trilla, yes, thank you. So this is Michael Jackson-Silla and I'm going to use this specific example for like the next few slides, right? One of the greatest music videos ever. So suppose someone says something like Alexa, play thriller by Michael Jackson, right? The ASR does its work fairly easy, you know, it picks up what the user said and now it's gone to the NLU, the natural language understanding. So what actually happens? So right now how it actually works is this, right? Where if someone says something like Alexa, play thriller by Michael Jackson from my 1980s playlist. There are a few things that are happening. So Alexa basically picks out three types of things, right? The first one it picks out is the domain, right? This is clearly to do with music, so it has like the domain as music. The second thing it picks out is an intent, right? For those of you all who might not be familiar, think of intent as a sort of meaning or the intention behind what the user said, right? The intention here is to play a certain track. So Alexa picks out that, which is the play music intent and then it picks out the third thing, which is a slot, right? A slot is like an entity, think of it as a certain variable in an utterance, right? Because this could easily be something like play, I don't know, parachutes by Coldplay from my 2000s playlist, right? So there are three variables in this, in this case, one is the name of the song, which is music recording, the other is the musician's name and the third is the playlist, yeah? So essentially you need your domain, your intent and your slot, which is picked up by the Alexa Cloud. So this is a flat intent or a flat slot schema. It's fairly easy to represent and it's worked well for us right now, right? So right now I'm guessing few of you all have Alexa devices for statements like this, it works very well and it's also easy to represent but there are certain problems with it. For instance, the exact same utterance, right? Could mean something else because there is a video of that same song, right? So if someone says play thriller by Michael Jackson from my 1980s playlist, there's also a video intent that could possibly be, you know, be activated. So how do you sort of, and of course the slot values also change accordingly because thriller now goes from music recording to music video and Michael Jackson goes from musician to actor, right? You have also from music playlist, 80s playlist goes to videos playlist. So it might be easy in terms when you have like very few domains, like maybe you just have like say music, smart home, weather, games, whatever, like say eight, nine domains. But eventually we want to be able to scale up to a lot more domains where users don't have to, you know, users can speak naturally to Alexa and Alexa can actually respond. So there are a few more challenges as well and again, few of you all who have actually used Alexa a lot might see this. One is something like this, doesn't share any shared semantics, right? There are no shared semantics between play music intent and play video intent, right? Which can be a problem once you're really scaling up. Also from a usability point of view, there are a lot of problems, right? For instance, if someone says something like, find me restaurants near the IPL game, right? The intent here is to find restaurants but it's two levels of intense, right? First you need to find where the IPL game is which is like a location sort of intent, get that, push it to find me restaurants and whatever. So it's two intents right there. The second one is a little more straightforward. It's find, play Harry Potter and turn the lights to dim. It's straight up two intents that are not related but the user has said it in one line. Now if someone comes and says something like, Alexa dim the lights, the lights are dimmed, Alexa play Harry Potter, the Harry Potter movie is played but if someone says something like play Harry Potter and turn the lights to dim, it kind of gets little complicated. The third one is a sort of holy grail I think in conversational interfaces which is negation, right? If someone says find me running shoes, not by Nike, it's a little tricky for a conversational interface for machine learning to sort of, you know, look for like say Reebok, Adidas and Puma because what it's going to do is it's going to say find me running shoes so that's a shopping intent and it's going to look for a slot value which is Nike and then show you Nike shoes, right? So it's very difficult and maybe with this example you can define utterances which sort of pick it up but as a human you can really sort of fool a system by using negation and things like that. And lastly just something as simple as play thriller, right? Because thriller can be a song, thriller can be a video, maybe it's the name of a book, an audio book. So so many different things and then you're sort of hoping that the system disambigates for you instead of smartly trying to figure out what happens. So to change that, we came up with something called the Alexa meaning representation language. This was just presented I think couple of months ago at NAACL 2018, I think that was the end of July, August. So it's a paper that's just been presented, you can see the link down there. The big difference in this is it doesn't really represent in terms of straight intents. It's more about actions and creating a factored graph between all these things. So let me show you how it works. So when someone says play thriller by Michael Jackson from my 80s playlist, the first step is to pull out the slot values. That still remains the same, right? This pulling out the slot values still remains the same. So you're going to pull out a music recording, a musician and a music playlist from the slot values. Here you're replacing your intent with something called an action, like a playback action. Note that we haven't defined it's a playback music, playback video, et cetera. We've just defined playback action. Now each action sort of can take an argument, right? Each action can take an argument. In this case, the music recording is the argument that the action is taking. And similarly, the slot values can associate itself with properties as well, right? So the music recording slot value is associating with the musician and music playlist by a properties called by artist and in playlist. So as you can see, a sort of drawing like a factored graph, there is a graph that's sort of related. And you're going to use this factored graph representation as a representation of what the user said, as opposed to like a flat intent schema. The difference between this and the earlier one was in the earlier one, we use very sort of fine grained types, right? Where it was music intent specifically, like play music intent. Here you're using very coarse grained types, right? It's just playback action. We don't know if it's audio or video just yet. The thing is this is rooted in, it's called the Alexa schema ontology. It essentially extends the schema.org. So the great thing is it's compatible with all the other websites and other things that use schema.org. And this is the sort of representation of how it looks, right? You have a thing which, and this is just a small representation. It can be an action, a person, or a place, or a creative work. Under creative work, you can have a movie, music recording, book, comic, whatever. So this is a sort of ontology that is followed. And it sort of takes care of a lot of things, including type ambiguity. Remember earlier when I said play thriller was a little, it could have been problematic given that, you know, thriller can be like a video or a book or a song. So if someone says something like play thriller, the first thing is the action, which is a playback action, which is associated with a creative work whose name is thriller, right? So there could be an ambiguity there in terms of whether the creative work is either a movie or a music recording. That's fine. So I'll show you later how that's actually handled. The good thing about this AMRL, Alexa meaning representation language, is the fact that you can reuse it across domains as well, right? So this example is another tricky example in the current scenario where a user says something like turn on the song thriller by Michael Jackson, versus the user saying turn on the living room lights. So as you can see, the sort of action associated with both because you've used the words started with turn on the, is an activate action. It's just that they take arguments that are different objects, right? So in the first example in the thriller by Michael Jackson, the object is music recording, right? And of course it gets, you know, the name of the song, the name of the artist, et cetera. In the second case, the object is lighting, right? So then you get the room and what type of lights and so on. Cool. So that's been done, right? So now we have a way to represent what the user said. How do you actually accurately execute what the user said? So we do something, and again, this was just presented at NACL very recently. Excuse me. It's called Hyprank or Hypothesis Reranker, right? So assuming someone said the phrase just play Michael Jackson, since we said play, it's a playback action. That's the action. And it's going to, I've drawn a dotted line there after playback action because it creates the rest of the ontology. Once it's done that though, you sort of need to get the best skill to actually respond to this, right? So how do you actually do that? So we have something called a Hypothesis Reranker, which does two things, right? It does, the first one is called short listing where it essentially in the most efficient way finds the K best number of skills that can actually execute this, right? So there are probably a lot of skills that will be able to execute this command, play Michael Jackson. So it finds the K best skills that can execute this. And then what the Hypothesis Reranker does is it accurately with a lot of precision using some contextual signals, which I'll talk about, using those contextual signals. It finds the most precise one that will actually execute this command, right? So how the Hypothesis Reranker works is pretty, is quite cool. It's also a neural net, it's an RNN. So Dr. Anand earlier spoke about LSTMs, right? Which is long short-term memory. So that's what it does. Essentially there's a hypothesis of the user utterance. And with users utterances, you need bidirectional LSTMs because you need to know what came before, right? If a sentence is six words, just knowing what the fifth word is doesn't make sense. It has to be with the context of the four words before and the one word later, right? And with bidirectional LSTMs, you can actually do that. So the Hypothesis Reranker sort of uses these LSTMs and it is a hypothesis to sort of say, hey, this skill is the best one to execute what the user said. So for instance, when someone says play Michael Jackson, there could be three skills that could execute this, right? We know Michael Jackson as a pop music star, so maybe it's that. There are a bunch of Michael Jackson videos as well. There's also a classical musician, not related to the famous person we know, but a classical musician named Michael Jackson, right? So using these contextual signals, which could be everything from your usage to the last seven days usage, to domain, to popularity, to the device you own, it'll actually pick up the skill that will best serve what the user said. So for instance, if I have an echo without the screen, it's that simple smart speaker, it'll probably pick the pop music one based on all these contextual signals. There are a lot of Amazon echo devices with the screen, like the EchoSpot and the couple of others as well. So given that your device is the one with the video, it'll probably pick up the video one because that is the contextual signal there. But essentially what the Hypothesis Reranker does is use all these contextual signals to pick out the best skill for you at that moment of time. Of course, with India, we had to make some of these customizations to the NLU as well, and I think this was very tricky, right? For instance, typically like in the US, a typical user would say something like Alexa play songs by Coldplay, right? Or they would say something like Alexa play songs from parachutes by Coldplay, where you know an album name and you know a band name. But here in India, there's more people will tend to use movie name and actor actresses name to listen to songs, right? You typically won't hear American users saying play Tom Cruise songs, for instance, right? Because it just doesn't happen that way. It's just how we listen to music. So then we have to change the sort of contextual signals to sort of prioritize, like say when someone says Alexa play Amerkan songs, to look for data associated with Amerkan songs to actually play out, right? There are a few other pretty cool examples, I think. For instance, I think India is the only country where we'd multiply or ask for multiplication by saying two twos are, yeah? So a lot of this data actually had to go into the systems, you know, so that when Indian kids actually ask questions like Alexa what are two twos are, it should, you know, accurately be able to answer. Few other things that we have to do. So for instance, in India, when someone says Alexa, what's the score? It's very, very, very high probability that they mean cricket, right? So again, you're sort of improving the contextual signals there to sort of give the cricket score so that it picks up the skill that can actually give the cricket score instantly. Or you know, during the IPL, we should get a lot of questions like Alexa, how much should Koli score in the IPL or what's Mumbai Indian score right now and things like that which basically we had to customize a sort of NLU to really understand this and you know, give with context. So, so far I've spoken a little bit about how, you know, the NLU works when a user says something, but what about a skill developer, right? If a lot of you here are developers, you probably want to develop or have already developed for Alexa, how does the data that you provide actually sort of accurately help with what the user is saying? Right, so I'm going back to this diagram, right? Where we have two phases, the training phase and the inference phase. So let's look at how you as a developer can actually provide some training data that gets used when the user is saying something, right? And again, we're going back to intense because that's the system we're using right now. AMRL, like I said, is something new that we'll be looking to implement going forward, yeah? So the training data that you provide as a skill developer is few things, you know, utterances, few sample utterances like how a user would typically interact with your skill, right? So suppose you're building, say, a weather skill, you'd say something like, you would, you have to predict what the user will say. So a user might typically say, Alexa, what's the weather? Alexa, how's the weather? Or even something like, Alexa, is it cold outside? Is it hot outside? Or maybe even something like, Alexa, do I need an umbrella today? All these things are essentially different ways of asking for the weather, right? So you need to give those utterances and match what the intents are and what the slots are. So here's some ways you can do it. So we're taking an example of a skill that gets you to do different activities, right? So you can say something like, and I'm looking at the bottom right there. You can say something like, Alexa, ask travel buddy. That's the name of my skill, right? Travel buddy is the name of my skill. Alexa, ask travel buddy about surfing in Sydney. Or someone can say, Alexa, open travel buddy and then say, is there good surfing in Sydney, right? So the intent here is to find information about an activity. So we're going to call it activity info intent. And there are two slots. Remember, I said a slot is a variable. So a slot here is surfing and Sydney, right? Which is the type of activity and the city in which you want to find the activity, right? Because that sentence can easily be, Alexa, ask travel buddy about bungee jumping in Bangalore, for instance, right? So you have an activity and a city. Now, typically as a developer, you want to provide some training data like this, right? And wherever there are curly braces, that means it's a slot value. So you would provide like say five to seven different utterances that a user might say to your skill, right? So they might say something like activity in city or activity is in city, good activity in city, how is activity in city and is there activity in city, right? So you're just typically giving, okay, these are the ways my users will talk to the skill, right? What happens is when a user says something, there's sort of statistical match that actually happens. So suppose you don't give enough data, right? You're being lazy. You say I have one intent which is activity info intent where I say activity in city as one utterance. And you give another intent where you give the exact same utterance. Basically one utterance is matching to two different intents here, as you can see on the top left. So if a user comes and says something like Alexa asked travel buddy about surfing in Sydney, it'll probably match to the wrong intent, right? Because there's a 50% chance it could match to either intent because the training data that you provided is too less. But if you've done a good job, if you've actually provided this, just take a look at the examples. There's the third one says good activity in city. The fourth one says how is activity in city? And the fifth one says is there activity in city? But the user has come and said is there good surfing in Sydney? Now we haven't actually, as a skilled developer, have not actually given that example in my user's utterances. But because it's not just a deterministic match, it's also a statistical match where it looks for the same meaning or some sort of statistic match there, it'll accurately pick up what the intent is and what the slots are, right? So as a skilled developer, this is how the data that you provide helps with how the users really react or interact with your skill. So we've spoken a little bit about how the ASR works, how the NLU works and how a skill uses data. I'll briefly touch upon the text to speech. Again, it's a little more hardware and not really my domain and not a little bit out of the scope of maybe this conference. But essentially even the text to speech uses some amount of machine learning and data. So during the text to speech as well, there is some speaker adaptation that actually happens. Remember I said it's not just the echo devices that use Alexa, the Alexa is a cloud service, right? So there can be third party devices that use Alexa as well. Like I know Sonos has a speaker that use Alexa or I think Harmon has one.  So there is some sort of unsupervised speaker adaptation that actually happens. So given some data like my characteristics, device characteristics, speaker accents and stuff like that, it automatically sort of learns and adapts to be able to do the text to speech as well. So just to sort of recap, when a user says something like Alexa, is it hot outside? Like I said, the device does few things. Signal is processed, it listens to the wake word, all this happens on the device. And then it pushes this to the cloud where first ASR happens, automatic speech recognition that once that speech is converted to text, there is some natural language understanding that takes place. Once you sort of get the intent and the intention behind what the user said, it goes to the skill where you actually maybe hit like an open weather API, get the weather, figure out location, et cetera. And then it goes back to the text to speech and Alexa reads out whatever the answer is. So that was in a nutshell. I'd like to cover one more thing. I have 10 moments, okay. One more thing, I wasn't sure if I'd had enough time so I didn't add it in my deck, but I do. There is something pretty cool that we're trying though, it's not in production, but how do you really learn customers' preferences? Let's take the music example. How do you really learn customers' preferences via voice, right? So on like say Amazon.com, you can learn customer preferences by a variety of ways, by what they buy, what they click on, what they add to their cart, what they've reviewed and you know, you can weight them very differently, but this is not a visual medium, it's voice first. Typically you're presented with one option or you ask for one option. So how do you really learn what the customer's like? So there's a very cool paper again about sort of trying to learn customers' preferences by song duration, right? So suppose a customer says play hello. There are two famous songs with that name. There's one famous song by Adele recently and for the older people in the crowd, there's like a Lionel Richie song from the 80s. I can see a few people nodding cool. Yeah, which also has the same title. So how do you know which one the customer really wants? So basically again, this was presented recently with really good data to back up, but essentially you try and learn the customer's preferences using the song duration. So what happens is take this really long, huge matrix where every row represents a customer and every column represents a song. So each element in that matrix would represent the customer's affinity to that song. Excuse me. So essentially what you're doing is you're saying, if the customer listens to the full song, that means that was probably the song that they have liked. So you make that hypothesis right there and you can do some sort of weightage. So you say if a customer's listened to, say beyond 30 seconds of the song, you add like a plus one. If it's less than 30 seconds, if they've said Alexa, stop, that's probably not what they meant, right? That's not the song they wanted to listen to at that point of time. So you add a minus one. Now even from the 30 second till the end of the song, also you can't have like a straight line because maybe someone said stop after 50 seconds, but if someone's listened to the song all the way to the end, that probably meant you got it right. So you have a sort of weighted graph to do that. So essentially you have hypothesis for like every song and customer, but that makes your matrix really, really big, right? It's like a theoretically and infinitely big matrix. So what happens is you essentially just factorize the matrix, bring out like maybe get like a 50 by 50 matrix. So when a customer actually asks for a song and if they listen to it, you sort of add that to that part of the matrix. And then that's how you actually learn the customer's preferences based on the song durations of what they've been listening to. So this was something presented very recently. I thought it was very interesting because there is no way for a customer to actually say, yes, this is a song or rate that song at that point of time. I mean, there are different ways of looking into your library and things, but when you've actually not done any of it and you have zero data points, how do you infer like everything like this? So again, this was presented recently and I just thought I'll share it with you all. Cool, so almost to the end of the talk, if you want to learn building for Alexa, how you can build skills for Alexa, I have a workshop on Sunday, but if you want to learn online, there's a great course on Code Academy. So just go to alexa.design slash code academy and you can learn it. We do a lot of events and meetups and we have meetup groups. So just go to alexa.design slash India. We have a dev days coming up in Delhi and the last link is a link to a blog where a lot of these things are explained, right? The alexa science blog specifically. So take a look for the ones maybe who want like little more depth.


Good afternoon, I'm Dr Bonnie Henry, the provincial health officer for British Columbia and this is our COVID-19 report for June 9th. I'm very grateful to be speaking to you from the traditional territories of the Locungun speaking peoples of the Songhis and Esquimalt First Nations and we're very happy that we can have these important updates on these traditional lands. So today we have nine new people who have tested positive for COVID-19 and one additional epidemiologically linked case bringing our total new cases to 10 in the province and our total to 2,669 people in BC with COVID-19. That includes 908 people in the Vancouver coastal health region, 1,370 people in the Fraser health region, 130 people in the Vancouver coastal health region, 195 people in into your health region and 66 people in the northern health region. There are no new health care outbreaks. We continue to have four active outbreaks in our health care system in long-term care and we've also gone a day with no new cases in our long-term care. So we continue to have 340 residents of long-term care who have been affected and 218 staff. We have no new community outbreaks and we continue to monitor and support at the six remaining outbreaks that we are managing. So that leaves us with 183 active cases across the province of whom 16 are hospitalised, four of whom are in critical care or ICU. Another day, a very positive note, we have had no new deaths in the last 24 hours. So that leaves us 2,319 fully recovered from COVID-19 in BC. I'm very grateful that in recent weeks our numbers of new cases here in British Columbia continue to trend down and to be low. We have had, as we are aware, a number of small community outbreaks but we are at that point where we are able to find these quickly and that speaks to the work that we are all doing to follow the safe distancing rules but also to stay away from the virus and to get tested if we get sick. But I want everyone to understand that the COVID-19 pandemic around us is far from over. In British Columbia we continue to have small numbers of cases but across Canada and around the world it is still a major problem and is going to be in our communities around the world for some time now. The global case count continues and many regions are facing a resurgence in cases as they've taken measures to open up including regions that are very close to us in the United States and just yesterday was the highest single day for new cases globally since this pandemic started with over 136,000 people being affected and we know that there are new regions of the world that are being affected and when this is happening in one country we are all connected. We know from several months ago that it matters to us when something like this happens in China. It matters to us when something happens in Italy in Spain. It matters to us when it happens in the United States and here in Canada. And now we're looking at the challenges that are being faced by countries such as India and Brazil. There are no borders and it recognizes none of our geopolitical barriers that we put in place. Very early this morning I was on a call talking with my colleagues around the world with the WHO looking at how we are managing these cases and how we are supporting each other how we're doing public health activities what are the things that worked how can we become more efficient and more effective at case management at contact tracing and learning from each other and we'll be having a series of these over the next two days. But here in Canada we know that international flights are increasing and US border restrictions are going to be eased to allow for families who have been separated for these last few months to be able to reunite. These changes are not unexpected and they are important in helping us get our social fabric back together. We also know that many businesses and schools here in BC and across the country have reopened so our goal needs to be to learn to live safely with this virus to protect ourselves as much as possible as we do that. To do this we need to be watching closely what is happening globally what is happening in our own continent and what is happening here in the province and we need to take our measures that we have learned that we continue to need to protect communities, our families and our province and our path forward is to minimize, manage and modify as we need and that means we all need to continue to take the actions that we have been doing to minimize our numbers of close contacts and reduce the number of cases that we see in our community. We need to manage those clusters and outbreaks with rapid contact tracing with making sure that we in public health have the resources to stop expanding rapidly and we need to modify the measures we are all following as we need to given the situation that we are facing here in BC. What all of us can do today and every day is to continue to assess our own risks our own risks in our family our risks in our small communities particularly if we are going back to school, particularly if we have people who are more vulnerable to getting severe disease particularly if we have loved ones who are in different settings like care homes. We need to take precautions to protect ourselves and those around us whether we are at work, at home whether we are traveling, whether that is essential travel that we are doing as part of our work or whether it is being with our family over the summer and going to communities or traveling within BC. We need to continue without exception to stay away from others stay home if we are feeling well and anywhere in BC you can get tested if you have symptoms that are related to COVID-19 and no matter where you are we need to continue to follow our rules for safe social interactions so that smaller numbers, bigger spaces safe distances washing our hands regularly cleaning our environment and the added layer of wearing a mask if we are in those situations where we might not be able to maintain our safe distances. We have said all along that we are experiencing our pandemic here in BC and nation to nation province to province state to state our circumstances are unique but our efforts to keep our loved ones and our communities safe are shared amongst us all. We can protect our families our communities and our province by protecting each other and doing this by being thoughtful and understanding our words and in our actions and continuing to do it as we have been doing it here in BC by being kind to each other by being calm and by staying safe. Thank you I'm happy to take questions. Thank you as a reminder to everybody on the star one to enter the queue you are limited to one question I would also ask you please take your phones off mute you will not be audible until I call your name first question is from von Palmer Vancouver Sun Dr. Henry thanks for taking the question a statement from you and health minister Dick last Wednesday urged the organizers of peaceful protests to quote follow the provincial health officers order to limit gatherings to no more than 50 people are you disappointed that that order wasn't respected and do you know why it wasn't enforced yeah so we have always taken the approach of support and education for all of our orders and this is no different I am disappointed because I know there are very effective ways for small groups of people to demonstrate these important issues and to do it peacefully and to do it safely and I encourage people to find those ways there's lots of examples in the world and here at home so smaller groups keeping a distance from each other these are the things that we need to do to protect our communities and I was talking about that today talking about it with colleagues around the world and my colleagues in some states in the US are very concerned that the protests that are happening down there particularly when there's attempts to shut them down and use of things like gas to disperse crowds those are things that can provide an environment that would allow this virus to transmit and we are starting to see increases in some states that are very worrisome we have not yet seen anything like that here in Canada but certainly not in BC but we are watching carefully and I will say again find small impactful ways where you can stay separate from each other where you can have your voice heard in a way that's safe particularly for those people who are more likely to be disadvantaged by this pandemic and that includes some of the people for whom we are standing up and having our voices heard Next question is from Mary Griffin, check news Hi, thank you very much for taking my call Dr. Henry I've just been looking at a long-term care facility here at Victoria Mount St. Mary's which as of today sorry, yesterday they updated their protocol that now allows family members who meet their guidelines to go in to see some of their family members for the first time in three months but it just seems that this information about that there is a loosening on restrictions for family members is not very well known and the senior advocates indicated that the guidelines were loosened at the end of May on who can go in to the facilities and I just think some family members would be interested in knowing that they may be able to see their loved ones coming up particularly here on the island where we haven't had a new case in weeks So I would be cautious we've always said that there are some essential family members who need to provide care to people in long-term care and that has been decided on a local basis by the Regional Health Authority the MHOs we will have a provincial policy for general visiting with the appropriate caveats in place to protect that community and to protect the workers and to protect the people coming in as you know many people who visit a loved one in long-term care are potentially at risk themselves either because of age or because of issues of health and that will be coming on a provincial basis and we will be doing this in a coordinated way that supports all families and all long-term care homes so I think that is important to know and we have to be careful not to become complacent we know people move this virus is spread by people giving it to others most often the people that we are close to and we need to be able to be sure that we are not going to introduce it in an environment where others will be at risk and we have not seen a case thankfully on Vancouver Island for some time but that doesn't mean that we are free of risk because we know there needs to be movement back and forth to this island to support essential services for a variety of reasons and that as I mentioned when there is virus anywhere virus, risk everywhere Ethan Sawyer, CBC Hi Dr. Henry yesterday you mentioned a cluster of cases in the Fraser Health region associated with family gathering as more of us consider expanding our bubbles it might be helpful to know a few more details about that event such as how many people attended was it held outside or inside and how many people tested positive for COVID-19 after attending Yes, so I can't tell you all of the details but I know it was a family gathering that was a combination of inside and outside and that there was approximately 30 people and at least 15 of them have tested positive so that is a warning sign to us all and it's not that somebody intentionally brings that into their community to their loved ones to their family this is something that we have been seeing around the world that that is one of the most common ways that it gets transmitted it's the people that we are closest to and spend time with so these are the things that we have been talking about about the importance of outside but still maintaining distance not sharing food in terms of having buffets because that's a way where we pass things on to each other potentially but the most important thing is the time that we spend in close proximity to somebody even if it is outside if you're spending time in close contact talking to somebody it is still risky and that of course is our concern right now so we go back to the basics that we need to remember maintaining our safe distances keeping our bubble small right now and this will be something that we'll need to continue so that we don't get these explosive outbreaks that can potentially happen we know that people in our homes people in our families many of them are essential workers whether it's healthcare workers whether they're truckers coming back from the US with essential goods whether they're people back and forth to Alberta for example so there are many reasons why people need to travel and we need to be aware of the risks in our communities and the risks in our family and it is why I've been so fussed about about the limits on gatherings or environments where we inadvertently spread it to the people that we are closest to Richard Sisman Global News Dr. Henry Workfake BC I'll thank you for taking the question Workfake BC has issued some guidelines around television and film do you have an expectation of when we could potentially start seeing that sector back up and is there anything that stands out for you as concerning about the operation of the television and film sector in Bruce Columbia? Yes, so I actually haven't seen the details yet of the guidance, I know they were working on them that is the plan for our next phase, so phase 3 we're not there yet we're still in our second incubation period but as we see the numbers are looking relatively good so that's a possibility we still however have challenges with we are not having non-essential workers or family reunification the restrictions we have on our borders right now, so that is an area that will need to be addressed as well we need to consider where people are coming from, so if there are people coming from a variety of places into our into our province whether it's from the US or from countries in Europe or China they bring their risk with them so we need to ensure that we continue and right now there's still a quarantine order federally and there's a provincial order that people need to self-isolate for 14 days after coming so all of those provisions need to be taken into account as well Next question is from Marcella Bernardo News 1130 Dr. Henry, I was hoping to ask you today a little bit more about what you just talked about with the film industry but other industries like restaurants theaters and businesses that depend on numbers being higher to survive will there come a time that large facilities with enough space to accommodate the 2 meter distance rule will be allowed to have more than 50 people You know those are things that we're looking at and currently right now there are provisions for some restaurants depending on the size that they have right now the restriction is on 50% of occupancy plus the distancing and the small numbers of people so the whole idea behind this is looking at risk and every time that we allow more people to be in a closed space together in particular allow more people to have those important visits in long-term care homes we are running the risk of more cases and more outbreaks and so it becomes a balancing of that it's not about trying to punish businesses or it's trying to find ways that we can safely enjoy those businesses enjoy restaurants safely go to retail stores safely visit our loved ones in care homes as best we possibly can but we must recognize that every time we do that there is a potential risk of transmission even though we have low numbers that we found here in BC that doesn't mean that we're out of danger with that so we will be continuously reviewing these things and we've been at as I've said when we started this we're making it up in a sense as we go based on best evidence that we have from around the world and what others are doing and how it's working and these early morning calls that I had with my colleagues around the world is ways that we help exchange information and understand what are the things that make a difference so we will be absolutely revisiting the guidance around restaurants we'll be revisiting all of the guidance that we have we're doing a review nationally about numbers in terms of mass gatherings and is there a cutoff that has some science behind it now, now that we've seen what's happened in other countries but then if I you know we go back to where we need to stay the course we will not be changing the fact that we need to maintain those safe distances we need to maintain the hand hygiene we need to be fastidious about staying away from any place if we're feeling unwell we won't be changing those and we won't be changing those anywhere in the world in the near term and I've told some stories some of them are events that happened here but very recently in Germany there was a church gathering where they were supposedly maintaining their safe distances and 107 of the congregants and 3 people died so you know these are the things that we're learning from that there are certain things that we do in a faith based setting where singing and singing together chanting can increase our risk of spreading this over larger distances so we need to be mindful of those concerns as we move forward but for now we will be absolutely reviewing things as we go Bob Macken break your news Good afternoon you talked yesterday about consistency in doing things and reducing chains of contact but thousands of people as you've seen across Canada are not following the orders against mass gatherings the Prime Minister attended one and here in BC the MP for Richmond Centre and a Vice President of the VGH and UBC hospital foundation were in a group shoulder to shoulder with no masks for a photo op I don't see much resistance to health authorities to this or are you content to let this happen so as to eventually achieve herd immunity No our aim is not to achieve herd immunity through infecting people we've seen that that can be deadly to young people as well as to those who are more vulnerable more at risk I can only say that our approach in BC has always been to support, to educate to make sure people have the means they need to do and to know what they need to do and ask them to do that and to remind people of the importance of it and I continue to do that and I would continue to talk to leaders in our communities about the best ways that we can fight the important causes like anti-racism causes in a way that does not add to any risk in our communities Next question is from Lisa Cordesco CHLY Thank you Good afternoon Dr Henry If I understand it correctly there has never been a provincial health order banning film production or really visits to care homes since your just policies individually taken on so in reality those sectors can resume activities without your approval am I correct Not entirely no we have had an order around both local orders and provincial orders around protection of long-term care homes and part of that is restriction on visitors so that is as well we've had restrictions on essential working but it's a slightly grey area in terms of things like TV and film production but that has been under our direction not, it's a too risky a venture for the way it was in the past and they need to come up with ways of doing it that meet the criteria that we have in place to protect people and the other part of course of the film industry is there are restrictions that are law if you will around international travel around people coming into BC and to Canada and there's requirements around quarantine that need to be put in place around those as well Binder Sajjan, CTV Hi Dr. Henry there have been increasing calls for disaggregated data as it pertains to racialized communities and how they are impacted by COVID-19 I know you've talked about this before I'm just wondering if you can just let us know where BC is at and how you respond to critics who say that it's a disservice not to have that information we absolutely agree with that and that's why we have been putting in place a number of things and we initially started collecting information, case information on this virus our case report forms did not include race-based information or disaggregated information by race or ethnicity or socioeconomic status or job in many cases so that is something that is important and we recognize that we have from the very beginning collected information on indigeneity and we continue to do that in partnership with Métis Nation BC and the First Nations Health Authority and that has been really important in helping us understand the impact in those communities but we have two initiatives that I mentioned yesterday but we'll talk about again one is the survey that we did that we had started planning for this from very early on and that is understanding the impact that both COVID has had and the measures we've put in place because we know both of those have impacts on different communities and we are collecting some very important disaggregated information by race, by ethnicity by community, by socioeconomic status because that does help us understand the impacts that it's had on various different communities across the province in addition we are doing a lot of work actually with my team with the VCCDC looking at what we're calling the unintended consequences both positive and negative because we want to be able to highlight going forward what are the positive things that we can do more of and what are the negative things that we need to address and who is differentially affected by those so we are doing that and in addition we're looking at proxies for certain communities by being able to report at a smaller geographic level and we talked a little bit about that last week and we'll be presenting data at a smaller level to get a better understanding of that in the coming days as well Keith Baldrick, Global News Hi Dr. Henry, thanks for taking my question the closure of the Canada-U.S. border is set to expire on June 21 Reuters news agency today is reporting both governments have agreed to extend that until at least late July just like what your take is on that I assume that's something you would support and given what's going on in the states right now with 14 states reporting record high 7 day averages of COVID-19 cases what's when you talk to your counterparts in the states and public health what are they telling you what's going on there they're asking you for advice given how well we're doing here that's a good question so yes we are very concerned obviously about the border I think it is important I've said this before about family reunification and making sure we're putting provisions in place that allow families to come together again and that has started as a I guess midnight tonight so we'll see what is important about our borders and what we see from our data is and the genomic epidemiology we presented last week is that we need to be able to manage people who come across their borders whether it's international from Brazil or from Europe or from China or from the United States and we will continue to do that and work with our federal counterparts on that so I wasn't aware of the extension yet but I think we need to be very cautious about allowing people who are here as tourists coming across the border and I think that's the last thing we need right now we need to focus on families we need to focus on essential workers and being able to support them and in terms of talking with my colleagues across the US and I talk regularly with my colleagues in the Pacific Northwest in Alaska we have weekly calls and we all exchange information and we're learning from each other and it has been very concerning Washington State, Oregon and Alaska starting to see upticks more concerning is some of the states where they have had early openings and I think thinking about the states like Georgia where they've had a dramatic increase and their numbers are as high as they were when they put their lockdown measures in place in March and it is concerning part of that is related to increased testing and so that is what we're seeing in a number of states as well but much of it is a true increase though particularly my colleagues in Washington State are dealing with some of the same things we are in terms of outbreaks in food processing facilities so the numbers I have a better idea of they are getting a handle as we are thankfully on some of the issues around our long-term care homes and the population that's affected in states like Georgia and Arizona is a new population they are not seeing as many hospitalizations but it may just be that that's what we call a leg indicator maybe sometime before that shows up I will say as well one of the biggest concerning areas in the United States is some of the American Indian communities both in the Navajo and the Hopi Nation in Arizona and I know they are spending a lot of time trying to support those communities we are learning a lot about this virus as we go and discussions with my colleagues around the world there is still much we don't know and I know there has been a bit of controversy about how much is spread asymptomatically et cetera but we are learning a lot about what are the things that work to help manage it and there has been some great studies that have come out that have shown that the distancing that we put in place does work it saves lives and those are the things that we are trying to titrate and put in place in ways that are more strategic so that we don't have to go back to some of those broad stroke measures that we took in March and we have lots of discussions about trying to support each other in doing that we have time for one more question this afternoon for any reporters to ask a question there will be a statement released later today for recommendations on protecting families and communities from COVID-19 visit bccdc.ca for non-medical questions about the province's COVID-19 response visit gov.bc.ca forward slash COVID-19 and for a full listing of the provincial health officers orders visit gov.bc.ca forward slash PHO guidance last question is from Liza Euston News 1130 Hi Henry, I know you've mentioned in the past that work is being done on sports teams and when sports teams can work or get on the field again and how that's going to work wondering about swimming pools is there any chance the swimming pools will be able to be open this summer yeah absolutely I know they're working on that too that is some of the things that we've learned that this virus doesn't transmit in especially chlorinated or ozonated water so yes the risk of course is people coming together around the pool in the locker room and those things so there will need to be measures in place to reduce numbers to make sure that we're not having close contact with people in the locker rooms and I know that's being worked on but I absolutely I think that's something we can look forward to in the coming weeks that's all the time we have for today