Hello, and welcome to the session. This is Professor Farhad. In this session, we would look at the values of options at expiration, and by doing so, we're going to look at the profit and loss diagram, which is typically a graph that illustrates this concept. This topic is covered on the CPA, BEC section, as well as the CFA exam, also an Essentials of Investment course. As always, I'm going to remind you to connect with me on LinkedIn if you haven't done so. YouTube is where you would need to subscribe. I have 1800 plus accounting, auditing, tax, finance, as well as Excel tutorial. If you like my lectures, please like them, share them, put them in playlists. If they benefit you, it means they might benefit other people. Connect with me on Instagram. On my website, farhadlectures.com, you will find additional resources to complement and supplement this course, as well your other accounting and finance courses. So in this session, we're going to look at the graph, at the profit and loss diagram for stock options. So let's take a look at an example with the call option, the strike price of 80, and the cost of this option is $14. So when does this option pay off for the buyer? Well, obviously it will pay off when you exceed $80. But let's take a look at the graph to see how this exactly worked. So to graph this information, we're going to have a vertical line. And this vertical line, we're going to call it the profit and loss line. And this is 0.0 because we're going to have a profit and a loss. Then we're going to have the strike price, the stock price. This is the stock price, SFT. Okay. And we're going to go ahead and put right here $80. So this is the strike price. This is the strike price. When we have a strike price, it means exactly at this point, the term is we are at the money. Okay, that's the term. There's out of the money in the money and at the money. The strike price is 80. It means that in the strike price, we are at the money. Let me draw this line here. We are at the money. Now here's how it works. If you are the buyer of this, first I'm going to do the buyer. If you are the buyer of this call option, when do you make money? Well, if you're the buyer of this option, you make money when you are in the money, in the money, at 80, at 80, this is at the money. So when you are in the money as a buyer of stock option, as a call option, well, you're in the money when the stock price is 90, 100, 110. Why? Because at this point, you might think about exercising your option because it's above the strike. So here you are in the money. Okay. When are you out of the money? If the stock price at expiration is 70, 60, 50, anything below 80, you are out of the money. Okay. So we already talked about at the money, in the money, out of the money. So let me erase this because we're going to need more space for this graph. Now, remember, as the buyer of this option, as the buyer of this call option, you paid $14 up front to be able to buy the option. Therefore, when you start, when you start, you're going to have, you are at a loss immediately of negative $14 at negative $14. Now, when do you start to make money? Well, you're not going to be making money. Let me use a different color here. Maybe I'll just do dashes. So you're not going to be making money unless the stock price is 80 or above. At 80, you're at the money, but remember, you still have to cover your $14. So when are you going to make money? So as soon as the stock price goes above 80, let's assume the stock price is at 90. If the stock price is at 90, you will start to make a profit. If the stock price is at 90, now you recovered basically $10 from your premium. Now your losses are only $4. Well, if the stock price is 94, at 94, you break even. Why? Because at this point, you paid, you can buy it at 80. So at this point, you can buy it at 80 and you paid $14 at 94 and the stock price is 94. So you break even. Now what happened if the stock price goes from 94, from 94 to 100 and let's make it 94, 104, 104. At this point, you have a profit of $10. You have a profit of $10. If it goes to $114, you have a profit of $20. And notice as you go further, as the stock price goes further and further, your profit goes up. So theoretically, if you are the buyer of the option, your profit is unlimited. Your profit is unlimited because you could always buy it at 80 and sell it for $60 trillion in theory. Now what is your cost? As the buyer, your cost is $14. So for $14, you have a potential of unlimited profit. That's the buyer. Let's look at the seller of the school option. If you are selling, so the buyer, you are bullish. You think the stock goes up. Now as a seller of this stock option, let me change, let me use this color. If you are the seller, the seller, it means you are bearish. What does that mean? It means you don't think the stock price is going to go up. You think the stock price is going to be at 80 or below, and the individual that paid you $14 would never come back and want to exercise. So what happened is this. As the seller of this option, immediately you receive, profit and loss, immediately you would receive, let's assume this is $14. Immediately you received $14. So you immediately have a gain of $14. And you're going to keep this gain as long as the stock price is 80 or below, 80 or below. Now what's going to happen? Once the stock price starts to go above 80, up until 94, you start to lose some of that profit. Up until 94, basically you will have a profit of zero because you have to buy it and deliver it and you no longer have any profit. Your profit is wiped out. If the stock price keeps on rising, then you have to buy it. Let's assume it throws us to 100. If the stock price rises to 100, now you are at a loss of $6. Why? Because you have to buy it and deliver it at 100 and your break even was 94. You have to incur an additional $6 of losses because you have to buy it and deliver it. Actually not at 94, you deliver it at 80 but you broke even at 94. You have 80 plus $14 that cover your expenses. And notice if the stock price keeps on rising, your losses are unlimited. So the seller, the losses unlimited and the profit is only $14. Well, did you notice something? I hope you did that. They're the opposite of each other. They are the mirror image and even the graph itself should be the mirror image. Now, my drawing is not the best but it's the mirror image. Let me show you another drawing of this. So let me delete everything. So what I just talked about, those two images imposed on each other. This is the buyer and this is the seller of the option. They're the mirror image of each other. Now, let's take a look at the put option. Let's assume we're dealing with the put option at $70 and it cost us $10. Now, how does the put option work? Well, when you buy a put option, when you buy a put option, what are you?  What does it mean bearish? It means you fear the price is going to go down because you fear the price is going to go down. You want to protect yourself. So let's go ahead and take a look at the graph for this strike price. So there you go. We have also profit and loss, profit and loss line. We have the stock price, SFT, this is zero and here the strike price is 70. The strike price is 70. Again, at 70, if the stock price is at 70, we call this add the money. Now, as the buyer of the option, if the stock price goes up to 80, 90, 100, that's good. You don't have to do anything, but you are out of the money. So you don't exercise because, you know, why would you sell it at 70 if you can sell it at 80, 90 or 100? What's going to happen is this, when the stock price started to go down to 60, 50, 40, 60, 50, 40, on this end, you become in the money. You become in the money. Why? Because now your option worth something. Okay, your option is worth something. Your stock price is less than the exercise price, which is good. That's what you want. You want to protect yourself. So here you're in the money. Now remember, you paid $10. You paid $10. So here's what's going to happen. You're going to be out of the money, out of the money until you are $70, until you are $70. Then remember, you're basically minus 10.  You are at a minus 10. You are at a minus 10. And what's going to happen? Once it goes down from 60 to 70, you will start to cut down your profit until it reaches 60. Once it reaches 60, basically now, 60 is your break even. So 70 minus 10, the strike price is 70 minus $10.60. So this is your break even. So this is your break even. Now, here's what's going to happen. As the stock keeps dropping, it goes from 60 to 10 to 50, you will make a profit of $10. If it goes down from 50 to 40, you make a profit of $20. And guess what? If it goes all the way down to zero, your profit is 70 and you paid $10. So your max profit is $60. Your max profit is $60. So your cost is 10. Your cost is 10. You paid $10 in premium. And your max profit is, your max profit is $60. Simply put, if it goes down to zero, they still have it to buy it from you for 70, but you already paid 10. So your max profit is, your max profit is $60. Now, let's take a look. This is the buyer. We said the buyer is bearish. The buyer is bearish. Yes, Dada? I don't know what to do now. Just give me a couple minutes, okay? A few minutes. Okay. Now what's going to happen is we're going to look at the seller of the option, at the seller of the option. The seller of the option is bullish. The seller of the option is bullish. What does that mean? The seller of the option believes what's going to happen is the stock price, it's going to keep on rising. And as a result, if it keeps on rising, you're never going to come back.  Therefore, in their mind, in their mind, they are going to make a profit of $10 because you're going to pay them $10. Now, how does it work for them? Well, here's what's going to happen. For the seller of the option, as long as the price is above 80, as long as the price is above 80, then use a different color here. I'm sorry, above 70, not above 80. As long as the price is above 80, they will make a profit of $10. This is their profit. And here's what's going to happen. Once it drops below 70, it drops down to 60. Basically, their profit is zero because now they have to make the contract whole and they get $10, but now they basically, they have to buy it at 70 and it's at 60. Therefore, they kind of lost their $10. If the stock price keep on going down from 60 to 50, from 60 to 50, their profit is kind of the scale is not good. The profit will be negative 10 here. And again, as the price of the stock price goes down, they will have more losses. They will have more losses. So what's their max losses? Well, for the seller, what's their max profit? Their max profit is the fee that they get. The fee is $10. What's their max loss? Well, they have to buy it from you for 70, but they already get $10 in fees. So their max loss is $60. That's their max loss. Notice they are the mirror image of each other. The seller will have a max, the seller of a put option will have a max loss of 60. The buyer of the put option will have a max gain of 60. And the cost for the buyer is 10. The profit to the seller is 10. Basically, they're the mirror image of each other. Now, the graph is not the best, but hopefully you guys got the picture. In the next session, we'll look at options versus stock investments, and we'll see how options, how with a little bit of money, you can leverage your position. And it's good to see it, options versus stock investment, to see in numbers how a small amount of money can give you a lot of leverage against an investment. As always, I'm going to ask you to like this recording, share it. And always, I'm going to invite you to visit my website, farhatlectures.com, for additional resources for this course as well as other courses. Study safe, study hard, stay safe, and good luck.


Mom steps out of shower, doesn't notice seven-year-old's zoom call. She was busy on her phone so when she noticed her daughter standing there, she simply told her to go back to her seat and learn. She didn't look at her, or what she was holding. But then her daughter crept closer, showed her her phone, and whispered, How do I end this? Her eyes popped in horror as she realized what she was showing to the entire classroom. Like so many moms nowadays, Meghan Mazza-esser had to quickly adapt to a new normal when it came to her children's education amid this pandemic. With virtual learning and remote school days, she knew new challenges would arise as she navigated her six kids around this new technology and routine. But she never imagined she'd have to deal with this. At first, it was business as usual, setting the alarm for 7 AM, she cooked breakfast and woke her six kids up one by one. After breakfast, she changed the little ones and helped them set up for online school. She designated different areas in the house for each one of her kids to learn from. If only she knew that wouldn't hold them. She had just finished setting up the kids for school when she received an email. It was the school. They often sent emails now. She was a lot more involved with the school and her children's classes now that she was essentially their school supervisor.esser shook her head and giggled at the email. It was a warning. A warning to parents to dress appropriately around the house when their kids were attending school.esser had heard of reports coming in about teachers seeing parents in their drawers, bras, and everything else. It bemused her greatly and also made her wonder how unearth parents could find themselves in that position.  Finally able to relax, she poured herself a cup of coffee and ate breakfast while she watched the news.  The same pair she had been wearing for almost a week now. These days it's hard to keep up appearances, especially with a pandemic and six kids. But today, she wanted to feel refreshed. She finished her breakfast and decided to take a much deserved, long, hot shower. She treated herself to some facials and hopped in. She grabbed a heavy chunky navy towel and threw it over herself when she came out. She made her way to her bedroom. Unaware of the total mortification she was about to endure. Making her way to her room, she sat on the floor next to her phone that was charging on the wall there.  They were dancing on the trampoline outside.esser loved seeing them so free and careless. She mused over how happy they were, even while restricted within a pandemic.esser smiled at them, completely unaware of the little feet that walked into her bedroom. As those little feet got closer,esser grabbed her phone and started to text her friend.  But her struggle was just beginning. As she was composing her text message, she knew she had a runaway daughter. Without looking at her, she told her to go back to her seat and learn. But then she saw something she hoped wasn't real. Her seven-year-old daughter walked up to her with her phone and whispered, How do I end this?esser looked up to see her daughter's camera facing her. On her screen was a live Google Hangout with her daughter's teacher and entire classroom looking directly at her. A long moment passed beforeesser realized what was happening. She looked dumb-foundedly at her daughter's teacher before her eyes bulged in horror. She stood up and flipped her daughter's phone towards the ceiling. Afteresser was sitting on the ground with a heavy towel around her that had fallen down to her waist, exposing everything above to her daughter's classroom. But what's worse is that in her confused reaction to stand up and toss the phone away, she accidentally ended up showing the teacher and classroom even more than what had already been exposed. She stood up, completely forgetting about the towel that was loosely wrapped around her waist. By the time she reached the phone, it was already too late. The towel fell completely. Yes, they saw everything. Once the phone landed face down on the floor,esser, who was now well and truly humiliated, managed to discreetly end the call at long last.esser posted about her ordeal online and the hilarious post took on a life of its own. It was soon realized thatesser wasn't the only mom this happened to. Another mom, speaking of the same experience says, Parenting books teach you a lot of things. But nowhere in these books is there a chapter on how to virtual school during a pandemic. How was I supposed to handle this? A hilarious conversation then unfolded about how one should deal with this. Do they ring each child's parents one by one to apologize to them for their indecency?  Or hilariously deny it ever happened? With many funny incidents like this happening lately, perhaps a formal statement or advice should be released with a way forward for those unfortunate moms and dads who bear it all.


Morning everybody We're at the Petro Pass in Dryden, Ontario We had to park out on the street here because last night there's a I don't know if you can see it There's a festival or like a traveling fair that's set up right beside the truck stop like way out of town just Right beside the truck stop and I went in today to talk to the managers here and say that hey We got here last night and the place was packed full of cars parked all over the place They literally blocked in all the trucks in the back. They couldn't get out if they wanted to I got into the parking lot And then you there's nowhere to go everything's blocked in so I had to back out and meanwhile there was kids Running up and down between the trucks running under the trailers running behind you even though I was backing up They would keep running behind my truck and families I guess were oblivious to what was going on They're just slowly walking behind me as I was backing up over to the fair. It was chaos Chaos and frustrating so I went inside today and talked to the people in charge.  I don't know like are they supposed to be parking here? They're like no actually they're supposed to be parking over in the assigned parking for the fair But the thing is that the fair is charging people to park over there Meanwhile right next door. There's a truck stop that isn't charging anybody or at least they didn't have anything set up Because they weren't prepared for that because they didn't think this was gonna happen I guess they didn't they didn't plan along with this business they just planned the festival as its own thing and didn't consult them and So the the fair comers and the fair goers came and Of course, they're like why would I pay for parking if I could just park for free right next door? There's a truck stop right, right? I think we can all relate to that Except that I wouldn't actually do it because I know it's a truck stop but Anyways, I like a hundred cars in here There's why And then they were using it as like I guess a playground for their kids to just like running around I thought they're gonna start jumping up on my trailer or something because like Whatever it's over I let them know what happened and then it was just chaos and they're like we're so sorry like this was not supposed to happen They're supposed to be parking over there and this was supposed to be open so drivers could fuel and not have to worry But running over a kid or anything So whoever planned this fair next door really didn't think things through And maybe they should have coordinated with petro pass here a little bit more so they could like So the festival could pay to put up signs saying hey no festival parking here at least or maybe just to let them know Hey, like you guys are supposed to park over there but we made it through and It doesn't matter. It doesn't matter anymore because guess what guess what We're going home. We're going home today. I've been gone for too long 13 days I think 13 days that I've been gone from home It's been too long It's time to go home. Let's go. We have about Three and a half hours for a yard. We're gonna leave this trailer. This trailer needs to be delivered Monday I'm gonna do that Today is a Saturday. So I want to get home as fast as I can and go home for a reset for today and tomorrow And then I'm gonna take those to their delivery point on Monday But for now like I said, I'm gonna drop it in our yard because it's a safe secure yard And then I'm gonna go to my shop Four hours of driving from here. So something like that not quite done for the month yet Just going home for a reset Getting back out here for another rounder just a short one and then It's Labor Day weekend After that so we have a long weekend In that weekend or on that weekend. I want to paint our house. Hopefully and maybe even get our Kitchen counters done or started or figured out better at least figure out how we're gonna do them Hoping that'll work out that needs to get done. We've been waiting a while. We need that counter space I've never done kitchen counters before coverage or anything. So my uncle and my dad are gonna come and Help us out Show us how it's done new coverage as well for like pantry space Instead of that stand-up one we have now by our window. I don't know if you guys remember it or not But I'll show you when we're actually doing it I want it to look good and I know if I try to do it by myself. I don't know what I'm doing It's probably gonna be be pretty obvious that Whoever didn't know what they were doing if I do it by myself Our trailer is out on another rental right now. So I was able to bring my pickup right in here But trailers been rented out every weekend since we put it on the market Pretty much straight through yeah all through August. It's a few days off We had them blocked off just so we could do the cleaning in there because we have to clean it between each guest but It's been going really good. I've actually been pleasantly surprised So tomorrow what is tomorrow? What does it say Saturday? Yeah tomorrow the trailer is coming back and We'll do the return and then I'll park it back in here and get it ready for the next people For the summertime I try to park it here in such a way where someone can easily hook up and pull it out That's probably Brit wondering why I'm not home yet. I told her I was at the shop a little while ago I got all my stuff out of the truck my laundry. I've been gone for quite a while So I wanted to wash all my bedding obviously got that all out of here Let the truck in here and I'm about to roll out and go home See Britain feel I think I've got everything. I think I do Checklists and things to do. I mean, it's not like we live far away from the shop. I have to come back to the shop It's fine. I'm grabbing it. I Just I want to be able to enjoy my time at home because this time I'm at home I'm only home for the rest of today and tomorrow and then I've got to go on another quick trip Which will only be like two days by the time you watch this already belong home, but it's I Don't want to be going back and forth between the truck and the house All day tomorrow and people enjoy my time at home tomorrow My time is very valuable when I'm at home I've said before like that's why I pay other people to do the work on my truck to To do the service on my truck stuff I could do on my own and I'd like to eventually in the future I'd really like to start doing the services on my own once Theo is old enough to be able to help me I think that'd be a nice bonding time. I mean if he's into this kind of thing I'd love to work on the truck with him together, but until then when I'm at home every minute counts every little bit counts So I don't want to spend too much time here anything. I want to get done to the truck myself. I'll do on a trip Speaking of what I'd like to get done. I want to get that front end lowered. What do you think? What do you think few inches not not like on the ground? I'd love to have air ride suspension there so I could adjust it We'll see I'll talk to the professionals and see what they suggest but definitely definitely that front end needs to come down a little bit and We'll see what we do. I'm not planning on doing it anytime soon, but I'm thinking about it Pretty much just to close up this gap right here, right? So we drop it probably with two three inches You guys remember Moses from a couple of days ago, right? His truck was just a little bit lower. Doesn't that look so much better? I got to be careful though Because if I go too low and I don't have air ride to raise it back up in winter time I should be very careful that I don't rip my bumper off in the snow And I'll say get one of those bumpers and it's fancy ones that you can push a button in the cab and the bumper lifts up You can go over the snow. I'm dreaming. I know I love dreaming. What's life without dreaming? It's boring All right Anyways, all blues all tucked in sleep good I'll be back soon. There's a door here. Just if you're wondering. Yes, I backed right into the door We know there's noise coming Hey, we just went to Boston Pizza He was flirting with the waitress Weren't you? He does really good at restaurants. You can sort of really take him anywhere Britt says that when I'm not here too, she takes him out all the time and Right? Yeah Sleeps how much has he been sleeping? Let's make all the other parents out there jealous He sleeps a minimum of eight hours a night to a Maximum of like eleven and a half I think hours and then his naps are between two and five hours, but on average three to three and a half How many naps a day? Oh, well, that's just the one big nap Okay, the rest of his naps are like cat naps like 20 minutes to half an hour But on the evening he usually takes like a good two-hour nap, too. So There's a good baby. He's really easy, baby We're just saying our next one's probably gonna be a holy terror He rarely fusses here and we can take him out in public to a restaurant He just sits there and looks around and smiles at everybody Unlike someone else we know when they were a baby couldn't take you anywhere So we we still can't take you anywhere Diesel was on the counters I was Weiner was a holy terror too. He pooped in everybody's house, but he was small so I could just pick him up He pooped everywhere And in two days day after tomorrow from when I'm filming this So it's already past when you watch this It's diesel's 12th birthday Diesel 12 years old come up here come here in the light a little bit more. Come here Come here What you gonna do for your birthday? I'm gonna heap. I mean, oh man. Oh He can you sit? Yeah Happy early birthday and for everybody watching happy belated birthday. I Got you when you were 10 weeks old. You remember that You were in the back of a pickup truck in St. Laurent, Manitoba Best 20 bucks I ever spent 12 years ago, and that's the best $30,000 I ever spent over there making all that noise 30,000 and counting because it doesn't stop. He's an IVF baby for the new people so $30,000 Doesn't matter money doesn't matter We're very excited that it worked out. We had the fertility issues for the new people Now we're so happy that you're here now We were waiting for you for so long We tried for five years Yeah, not more five and a half. Yeah, five and a half unexplained infertility doctors couldn't explain it So we went through IUI Went through IUI four times didn't work didn't work Yeah, and we went IVF and The doctors helped us first time was the charm. You were hand-picked by the doctor That's why you're so perfect, right? Right Yeah, and the first time worked what a journey now look at you. That's you handsome man Stealing hearts everywhere. It's getting all shy because the camera's on them. It's like diesel shuts down when the camera comes on You can see himself in the front of this one, too The other GoPro is either wasn't a screen on the front of the camera like this. This is the 10 So you can see you can see himself right That's you


We willingly give our blood, sweat, and tears to fight and win our nation's wars. But what about when it's time to pack away our rucks and put down our weapons for the last time? You once asked yourself, do you have what it takes to serve? It may be time to ask yourself that again. If when I was in the Army they said, and then one day you'll be a teacher, No, absolutely not. I wasn't somebody that anyone would say, oh, she loves children. She'll be great at it. I don't think that's what someone would describe me as. As long as it's working in your mind, that's all that matters. I was at Fort Bragg. I was a military police officer and I just adopted my daughter and we had been together not even quite a year. And so I was like, okay, I'm getting out. Don't carry that with you. Believe in the past and when you certify again, you're going to be good. So my friend told me about teaching and I hadn't even ever really considered teaching. That wasn't on the short list by any means. I was lost. I knew I wanted to be a teacher because of the hours and the availability. I just didn't know. Frankly, I didn't know anything. And so I Googled like every smart person does and I kept coming up with troops to teachers and that started my journey. You drive me bonkers. Troops to teachers has been a very successful program. We placed over 21,000 teachers into the classroom on a daily basis. We process applications. We follow up with those people that are seeking employment as teachers and we also reach out to states that have job openings, opening up the opportunity for them to be hired as teachers. If you need to speak to anyone or contact me, just shoot an email. Give us a call. Okay. They explained everything. They sent me an email that was super long but super informative.  They asked me for my email and boom. I had all the information in my fingertips. What? That's impressive. Right? Teaching is a very rewarding career. Just like being a service member and knowing that you're a part of making a change and a difference in the world, teaching is like that as well. You're making a difference. If you make a difference in one child's life, you're making a huge difference in society. Good morning, one of the kids. I'm that person when I was in uniform and they would thank me for my service. It just seemed like no way. I'm so grateful to the military for the service they gave me and it's kind of the same with the teaching. They're the ones that really keep teaching and growing me. So if you look at your time in the military as what it's brought to you then teaching is going to be the same way. Jack, believe it or not, you have learned a lot from me. Yes.  And I think I relate to that and I don't want them to feel like that. And so if I can give them that belief that I picked up in the Army and build them and encourage them I think that's what I'm supposed to do with that military career. I don't know for sure, but I'm going to give it a try for as long as I believe in it.


So welcome everyone come to my talk and I'm Wilson Wang I'm from by dance. I'm a research engineer in the infrab lab and today I'm going to talk about the web assembly in by fast. So by fast is or internal like fast platform like for for like by dance environment but I mean they are like it's very similar to other like the you know like the fast platform but today I'm going to talk about something like details that we implement that is different from like the other fast platform and especially about the the places where we use web assembly. So the talk it will be three parts for the first we will talk about our legacy like the fast environment and then after that we will talk about the how we use web assembly in our current fast environment and finally we will talk about or in progress research about or like next generation web assembly based fast system. Okay and finally I will give some demo so yeah let's start and first I will talk about the fast like the past like what we what was there before we start using web assembly. Okay so there are like it you know our legacy by fast architecture we have two kinds of like the functions like one is native function another one is event function so for the native function it's container based you know like use their customized images and in order to like run their function like the when the container start they need to have like have their start.sdc script to start all the the services and then after that their code needs to listen to like on a particular port for example like for HTTP services they need to listen on the port 80 for incoming requests and the second about event function so the event function is a little bit different from the native function we have a bunch of common like like shared common images for example for like Python, JavaScript or many other different runtimes and the users just need to provide their business logic code and then like we will use these common images to start their like the event function and in this case like the user code will be like much like their code will be much smaller than the like the native function so the ports with these two different kinds of functions that they are flexible because they we can provide like a user with different types of workloads and it's easier to migrate their container based microservices workload to fast because we have a lot like a lot of like the container based microservices they are either using Go or different other like languages and then when they want to migrate they are like the workload to or fast system then they we need to give them away so that they can you know so this will this process can be more smooth like more smooth okay the current ways these two functions that well for the container costar it's well known it's very slow right so you need some time with some time to for it to get started and another one is that the container images are usually are very usually are large and for the next slide I'm going to talk about the optimizations we did to the legacy workload so there are three you know like there are three major container costar optimizations that we can find in the industry or in the academic area and the first thing that we change the Kubernetes like part creation from declarative to imperative so you can think of like so in this way we can avoid a lot of like the you know like the backend force the data update and then observation all these observations that are happening in between so that we can save time that's the first one and so second one is using like one pool using one portals speed up like the initialization and this is also very common use and the last one it's not very common but many companies are starting using it so it's like you can snapshot your port like container processes and later we like at a particular like initial stage and then later recover from the snapshot so in this way like the for large containers so like it can like it can start up faster okay and next slide okay so for the for these optimizations there are limitations and the first thing that the costar optimization you know like there's always a guy between different isolations so for the VM like when we started like a VM there are like you know we have a VM inter VM exit and this cost the cost are more than 10 times higher the cost of usually like a system call which is commonly used by Lin's container and the second one is that the system for system call is the cost is also more than 10 times higher of the simple user space like call or jump instructions and so this this is gab like it's we cannot avoid and because of this and then there's always a gap between you know like the VM and container and then you know a different other isolation so how do we start like fast functions with latency that's like the millisecond level or some millisecond level and so we are thinking here like probably we need a sandbox environment that I can mainly use like a call or jump instructions and there are like we have two choices one is unicolonial another one is a web assembly and then we've been like thinking about unicolonial for like quite some time but still like there are many you know like the limitation with the unicolonial that we you know we make us like hesitate to adopt the unicolonial solution and finally we found like the web assembly and we believe that it will be much like convenient for us in our environment then finally we chose we chose web assembly and for okay now we are talking about the present what the what we have like right now in the as a lightweight web assembly worker so we introduced the web assembly worker for our by fast system so what is that it's a new like fast worker based on what's in time so like other components in the fast system like gateway or like all other agents they are very similar to you know the common the common fast systems but in our case we actually added like a fast worker based on what's in time so what's the difference it's raw space we use tokyo async framework to make a better use make a better use of the micro core multi core environment and also for async common request the web assembly sandbox is either created or reused from the cache and we use like the user web assembly functions pre-compiled ahead of time so that we can you know like that it can run faster and also we can start it faster and also like we have another service provider framework which gives the advanced features and the core capabilities to the user code so in the next slide I'm going to talk about what is service provider framework okay the service provider framework you can think of it as like a micro kernel design or message passing in design so why do we need to when do we need to implement it so there are like you know many features like our u-ring or even fd like these are like you know used by many of our legacy workloads but uh in web assembly actually it's they are not they are not directly provided so we need to use them then we need to find a way to you know to provide these features so what a way did we add the service provider framework it provides the host calls with back-end support to user web assembly functions and the current implementation that we have for this for this like back-ends are like kv-store service discovery, HTTP request and response and also message queue and definitely we also provide something like our u-ring through this interface but I'm not going to cover these details in like in my top because there are so many I can't cover them in like in a single top and there are a few things working progress because this service provider framework it came way before the component model and then you know in the community then they proposed the component model and also other like other new features to wasting time then we decided finally you know we might need to investigate like the new design how we can adapt like the component model and to improve our service provider framework and also we are thinking you know integrate the dapper you know or implementation so that they will be something like from the community like we can directly include it you know okay so to improve or like improve or like the service provider framework yeah and but there are pain points with all Wesson worker so there are two main pain points that we we need to like resolve you know or Wesson like you know Wesson worker so the first thing is that we have like increasing number of like small web assembly modules and they are small they are divided and they have dependency between each other so and also like for the different Wesson modules they have different versions and all these messing up together and then we get some we get an enterprise a hairball so they they they you know they have dependency then they are the develop for the developer they are productivity greatly greatly affected and also the second thing is that it's hard to identify and resolve scalability and performance issues we need to speed up the cascade request for example service a called service to be and then how do you know like then how do we make a speed up these requests and also we need to find the you know application bonus like for for example like application a called application b and then you know like if the application b like running slow then it will slow down the whole request okay so how do we solve these two problems and we have a partial solution and this is what we currently have but they didn't solve the didn't solve totally solve the problem like there are two solutions one is to work service another one is combine deployments i'm going to talk about this i'm going to talk about these two like the improvements that we have okay so the first thing about plug it okay so the for the worker service it manage and deploy function in groups with like the manifest files describing the functions backs and so the the work service we support mixing web assembly function and other like language runtime like functions and for the different like the functions that they when they communicate with each other we use the idl or you know you can use JSON to describe the worker function interface for a request the idl you can think of like a port above or something equivalent and we use kubernetes similar concept to organize the functions you know like we so the developer they write they are like the yaml files the yaml files contain something like deployment service group snapshot and then use these to describe the relationship between the functions and how they get deployed so the they are also like ports and cones with these worker service so like it's a poor high level of like solution to manage the group of functions but like but still it needs a lot of extra like efforts to manage the you know like manage these application deployments people need to write their yaml files and then they need to organize somewhere so that the platform can retrieve these yaml files okay and second the improvement that we did is combined combined deployments you can see from the the graph here so when the request comes then it will first come to function a if function a needs to you know talk to function b then it will in the original design function a will follow the request of gateway and gateway will do a reverse board c and send the request to another worker which will bring up the function b and return result and this is you know this the two and three is totally necessary if we can bring up the you know the the destination function on the same host so that what we did is that for the combined deployments we actually when the function a needs to call another function and this function can be bring up can bring up like on the same host then we will simply just bring up the function b on the same host and process the request and return the result so that like in this case the original remote request become like local requests then then we improve the performance and we can see the result here in this case it's where you were testing using javascript runtime on top of web like using on top of web assembly and with runtime that using where using is actually spider monkey so spider monkey generally the performance is like higher than quick j s and the results show that the average and long little tail latency are greatly reduced for small size traffic you can see here the for the remote request usually you know average around like 10 to 20 millisecond and then finally we will review the two like two or three millisecond but as the size of the request like increase then you know we couldn't get a lot of improvement for it but still we for the long tail latency we can see you know the difference okay now the last part we are talking about the upcoming feature the next generation fast system investigation so like we discussed about the solution that we have but they are not told they are not like for the combined performance and also for the worker service they are not solving the problem not totally solving the problem so what we can do to you know like to further improve it and also like give the developer a better like the developing experience okay now let's talk about the service of weaver so service weaver like for cloud like in their paper this suggests like three things that are part probably can be used to improve the cloud application development the first is monolithic application development is important so like for the developer they can develop a single like the application binary and later you know this will this will be more convenient for the developers and the second thing is that the new need to distinguish between application like physical and logical boundary so like people write a component but this component like they are they are logical boundary but they are not necessary the physical boundary when in the actual like the running environment and the third thing that are distributed like smart runtime is needed for auto optimization auto scaling and also for debugging well this service of weaver actually for only for go but so for our case we want different languages that you can work together so that we need like force item the course language interoperability so how do we do this like how do we like achieve goal and you know and do all these four items so our answer is like west among ray okay so how many how many of you guys know like ray or use ray before okay so i'll give a short introduction about ray so on ray's official website they say that ray is an open source or unified compute framework that makes it easy to skill ai and python workload from reinforcement learning to deep learning to tuning and model serving it's very long right and actually from like young stovica he said that ray is a distributed computing ecosystem at the service so here is one example of how you write ray code so you you know in the using python you can write a function and here the function square actually returns the square of the the the input value right and you use the decorator to like read our remote to decorate this function then later when you call square dot remote it actually actually this execution is like distributed by it's distributed by the ray framework so to somewhere else inside the cluster so that you get you just get the the return the return value of the futures and later when you call rega you actually you get the actual value for these like executions so that's how like ray looks like okay so next one i will talk about the ray architecture so the ray it has one like usually one hand node and multiple worker nodes say the handle and worker node they form like a ray cluster and so that you later can submit your job to the uh ray cluster and uh and like and run the your like the your logic your logic and the there are two things one is like or two important concept in ray one is task another one is actual so the task it's still is and the actual is staple in the case of python so like the ray support you know python and also java and in the case of python you can single like function as like uh uh stateless and the class actually is staple so when you execute a function it's uh when during the execution inside the recluster it actually still is so each time when you call it it actually you know the result does not depend on the previous previous call and for the you know java for the python classes when you have like an instance then later when you call its method it actually uh it's actually an actual it's staple so each time when you call like a class uh method uh in ray as then it actually depends on the previous states okay so now i'm going to talk about or vestimony architecture so there are two parts uh one is execution and scheduling for execution we add a new ray vestim worker uh so what is so what it does is it's different from the fast worker so the here the worker actually the ray worker so the for the ray worker it handles what by somebody specific task actual execution request so that when uh when you uh so that when you submit your call it actually as your code actually execute on these ray vestim workers and uh the runtime we use actually it is uh vestim match so the reason we are using vestim match is that uh or call uh actually like it's the projects actually uh using the basal to build and then we have some really hard time integrating with vestim time because like with you know like when you are building them like the for the uh for the cargo then you know there are a lot of uh problem with it for example like the when the cargo when you build the vestim time there are some scripts that you're running during the compile time which is very hard to integrate with uh with the beta project so that's why we choose the vestim match and also for the vestim match it provides more featured plugins and which will be very helpful for us and later I will show one example of yc and n like how do we do the inference actually we need to use we need to use it using the vestim match and the second ray host calls so for the ray we actually explore them uh like as ray host calls so that later different languages when they compile to web assembly they can use this ray host calls to uh execute like the uh execute task or actors and uh for the scheduling the the vestim runtime actually depends on ray to schedule the task uh and actor executions and also we will uh we use like ray to profile its execution uh like result and improve the like the function scheduling strategies and we can also uh depends on the scheduling result we can scale uh the task actors to improve the throughput okay here I'm going to show one example of vestim on ray uh you can see the the code on the right side so we have a function called task func which is basically doing some calculation and we return the result so the uh from line uh 18 to 20 we actually calling it locally so it's just we uh so we call the function and get a result and in order to use vestim on ray what we need to make some changes so from line 27 to line 32 we this is actually uh how to use uh vestim on ray to execute a function so the line 28 in line 28 we call ray we give a function pointer and also we also give a buffer which will return the future and later uh it's line 30 which we will do we'll call we'll wait for the uh like the future result and then uh populate the result the actual result then print it out so yeah and uh next thing I will go I'm going to show a demo like the the the like previous call uh demo and also uh mobile net uh inference demo okay uh here is uh because I I have like formal access in my uh like the environment inside our in enterprise environment so I'm going to show like a recording so why did uh to run like to run the example code and this uh the first thing is actually we need to compile the uh the ray so this command is it is just used to compile the ray and including all vestimon ray yeah it will you know like for the ray if you want to build it uh from the scratch then it will take a long time but this is since we already have some uh compiled before so it would uh be it would be very short okay then after this uh what we do is actually we need to uh run the example here uh we'll compile the code it's here we actually uh let me see oh yeah so in the under the example directory we actually build the example web assembly code and finally it is the uh let me see the execution yeah here here's just a command it'll be a long so later we you know we will improve it but right now you can see that here like it's called warrior so that's something that we uh used to uh like to load the web assembly code and execute it uh inside the ray environment yeah this is it's trying to connect to the ray cluster which is already uh running okay you can see here so this one it's actually calling locally uh directly like uh here and then we get uh we bring the result then later when we call it remotely actually uh like the call the ray uh I mean call the ray to execute the function then we also get get the same result yeah this is uh the call we shown here that's exactly like we are exactly executing the uh exactly the same code okay then after that it will uh like say determine the code and also terminate the ray cluster okay and for the uh second demo I'm going to show uh like western match mobile net inference demo and this thing uh this protocol is not actually executing the western like executing ray code but uh we are here to demo you know like the how it is uh how easy to uh actually like to run inference using west match and you know future we are we want to do some further uh improvement today so that we can actually run the inference distributionally but uh right now I'm just going to show the how we run the or inference here's this example so you can get it from western match and see the western example and uh what it does is just you give like an image and then later it will identify what is there inside the image okay here in this case we are running uh the let me see if I can yeah these are the commands that we use to um run the uh run the like uh inference and we need to give the argument like we also like argument is like uh it's shown here so with uh the model like the like the model file and also the input image so the because it's because it's running on like the cpo so generally like it is a little bit slow here I will probably speed up a little bit yeah here you can see it's executing it's a loaded model and start executing okay you can see the result here it identified the banana inside the image you can uh you can get it from the west match west in an example you can run it locally so this uh yeah it is very easy to execute you can just run it using west match okay now uh I will talk about the the in progress and future work so while we're planning to we're planning to run lama 2 uh inference based on like lama 2.c and uh because it's pure like it's purely written in c so later we we are we are like working progress to uh make it running on west mount ray so later you know when you run uh this uh inference it actually can run uh digitally so you can have data uh inside the inside the cluster on different nodes and the second thing we are doing is that we are because you can see the code it's still it's not three four yet so later we want to see if there any uh way we can further improve the uh the west mount ray so that it will be easier for the developer to take advantage of the ray underneath and also later we are planning to like uh do uh like rise decays for different languages to support like uh to support west mount ray and right now it's we mainly support c and c c plop us and later we want to add like the gel script support and also the like rust support and the repo is here and also we have like the proposal is already accepted by the ray uh like by the like the re-community yeah okay thank you for attending my talk and uh any other uh any questions yes please this one so this uh okay that's a good question so like how many of our services are running on uh like wasm so uh right now it's it's like the most of our like workers still like a legacy workload they are like either go or some other like for example java and we see a portion of force like the users like switching to web assembly these people are mainly you know like they they need to process some like the message queues usually you know message queue users and all some of the uh like they found in you know like the services they want to use web assembly because the web assembly uh it can stop very very quickly and compare to container that's the like the first advantage that people you know all the first reason the top top first reason the people switch to web assembly yeah so these are different uh you know these are different sides of the request so first one is one k uh one k uh data size and then you know this uh is the request from uh function a to function uh you can see here like function a to function b and that's the like size of data so the like the top left one is actually with the one k size data and if we go to the bottom that will be like a set uh like a larger size data you can see here with the maximum we have like four megabytes and we have some data missing there but uh yeah so right now uh you can see that when we have like smaller data uh because we are running the destination function on the same host it is very quick and because we have no like network latencies and it will be a few few like millisecond to for data for for the to get a result and but if we you need to like uh use a gateway for the request to gateway and then uh bring up the destination function somewhere else then you can see that the generally it's much the latency is much longer and also for the long tail latency it can reach more than like 200 200 milliseconds yeah uh we have like I mentioned the uh there are two like we we uh let me see if I have it here so okay so uh let me uh we have like the uh for the web assembly function we have co-star and also have the uh you reuse the the cache ones right for the co-star it's a few I think for us we it's only like uh less than 10 uh millisecond and then for the like if we use the one from the cache it will be like less than five millisecond compared to we like a container or something right yeah the container like the like when I say the millisecond it's the actual data that we get we like you know bring up the all these things that are happening like we see in like a few uh millisecond but for container it's usually uh like more than uh you know more than uh 10 millisecond it's definitely way uh longer than the web assembly functions yeah any other yes please yeah rust yes yes and the west match actually actually it is uh using c++ but they have like the uh the like rust SDK so that you can use the rust code to call uh west match oh I see okay so the you can see that for the west time it's something that we have right now because they are using uh you know they are using rust everywhere almost every component they're using rust but in our case it's west mount ray so the re project it actually compile using basil and uh if you want to compile like the rust project using basil then there are a lot of you know like headaches for you to uh so for example like for when you use the cargo to build rust code then there are like some like build rs which basically execute it uh like at the compile time but for basil you know it's uh like it's hard basically it's hard to integrate these two concepts and it will be not very easy so that's why we choose west match that's the one main reason another reason that uh for west match is they have the plug-in support so you can have different plugins and then it will be easy to have your own plug-in and it's extended yeah okay any other questions that's true that's true yeah that's uh that's uh the the thing that between different teams so like something they are actually yeah they actually the team that are using you know like the proposing the different framework they actually we are trying it out but there are a few small issues that we need to resolve but our future goal will probably you know make it a plug goal we can make it either using uh Tokyo or using our internal like the uh different like the frameworks yeah okay okay great thank you everyone for coming have a good day


Item No. 66-62 Level 2 Restricted Containment Class Keter Disruption Class Ecce Risk Class Caution SCP-6662 Intelligence Sapient Exo-Normative Tangibility Solid Displacable Threat Physical On-Hon-Style Magnificent Cautionary Points Likely to escape is confined. Physical containment and restriction of movement are ineffective and risk unnecessary provocation. Emphasis should instead be placed on diversionary tactics, such as manipulating SCP-6662 into searching remote and unpopulated areas. Highly distrustful of adults and adolescents, SCP-6662 will presume it is a threat to any given adult to be in a state of either anger or boredom. Avoid approaching SCP-6662 in a belligerent or confrontational manner and instead employ a blight or indifferent demeanor. By contrast, SCP-6662 is excessively trustful of prepubescent and may be effortlessly manipulated by them. Male age 12 and under are to be utilized for direct communications with SCP-6662. Description SCP-6662 is a quasi-candidate humanoid entity with limited ontokinetic properties. At will, SCP-6662 may bring into existence almost any variety of tool it needs, typically, though not necessarily, producing it from the backpack it carries. SCP-6662 has occasionally used its ability to manifest devices and gadgetry capable of novel or scientifically improbable functions, such as a handheld instrument which unfolds into an operational and fully-sized armored tank at the push of a button. All technology produced by SCP-6662 is operated via simplistic and brightly colored analog controls. The reconstruction of recovered components has consistently revealed a near-total lack of coherent internal mechanisms, indicating that these devices operate largely, if not solely, by SCP-6662's subconscious alteration of reality. The range of objects SCP-6662 is capable of producing appears to be limited to tools which fulfill its immediate physical needs, often at the expense of its emotional needs and desires. Several characteristics, SCP-6662's head, hands, feet, tail, and fur resemble that of a Eurasian wolf, Canis lupus lupus, albeit with more human-like traits, such as longer fingers, larger eyes, and complex facial muscles capable of a wide range of expressions. Its build is grossly top-heavy, to the extent of appearing unbalanced. This visual impression is amplified by an abnormal composition of musculature which appears at once lean and pronounced, yet rounded and undefined. Despite the exaggerately masculine proportions of its physique, SCP-6662 bears no other features indicating a biological sex. Extensive medical analysis has found no indication that SCP-6662 is capable of reproduction, sexual, or otherwise. Nor has this body been found to produce any recognizable hormones other than extreme amounts of insulin. SCP-6662's choice of dress has consisted of the same articles and clothing since its first sighting, wide-brimped fedora, zipper jacket, and a backpack with a simple button flap, all heavily weathered and made of brown leather. SCP-6662 has expressed neither an interest in leg wear nor an understanding of the purpose they're of, presumably owing to its lack of genitalia. Behavior and Psychology Although classified as sapient, it is proven difficult to compare the level of intelligence displayed by SCP-6662 within an analogous stage in the process of human intellectual development due to its profound unfamiliarity with and mis-comprehension of many fundamental aspects of baseline reality. SCP-6662 has directly alleged itself to be a foreign presence in this reality, though it is otherwise spelled to acknowledge a distinction between the human species and its own, expressing a presumption that the two share enough similarities that any physiological differences are too negligible to warrant its attention. Furthermore, SCP-6662 has continually struggled to grasp concepts related to human development and family structures, frequently falling back on the misassumption that all post-pubescent humans function in the role of parents to all pre-pubescent children, with no other delineations in relationships or social groupings. Somewhat paradoxically, SCP-6662 did not identify with either role or parent or child. Rather, it described itself as part of an entirely separate social binary of keepers and seekers, with SCP-6662 claiming to belong to the latter. To date, SCP-6662 has not identified any other being from her own reality as belonging to either of these social groups, and has been unwilling to elaborate on its native society and culture. As SCP-6662 is able to fulfill its physical needs by way of its anomalous capabilities with virtually no effort, it instead directs its time and energy almost exclusively towards its fixation with the acquisition and consumption of a variety of edible substances it collectively refers to as Treasure Treats, SCP-6662-1. While SCP-6662 has provided extensive descriptions of SCP-6662-1 and has repeated and treaties for assistance in acquiring it, it has not been found to match any known food product, and attempts to recreate it have been met with vehement rejection by SCP-6662. Despite these setbacks, researchers have observed that descriptions of SCP-6662-1 consistently fit the general characteristics of breakfast cereal, particularly sugar cereal. SCP-6662 has not displayed any inclination towards socialization or interaction with other sapient beings outside the context of acquiring SCP-6662-1. Attempts to engage with SCP-6662 in a social or intellectual capacity have invariably resulted in SCP-6662 making a token display of attention before quickly shifting its efforts towards coercion, deceiving, or otherwise manipulating the other party into helping it acquire SCP-6662-1. However, SCP-6662 is a parent inability to understand the thought processes of other intelligent creatures, as rendered virtually incapable of concealing its intentions from any human being old enough to speak. SCP-6662 avoids non-human mammals and exhibits confusion and discomfort in their presence. Addendum- Mobile Task Force agents successfully planted a covert listening device in SCP-6662's backpack during an October operation in their Prague. Researchers have since discovered that SCP-6662 habitually narrated its dots, feelings, and actions aloud, and at great length when it believes itself to be alone. The following transcript is taken from a small selection of these recordings. Revision is the documentation or underway, pending further research. The sun sets to the horizon's edge, threatening to plunge the sky in the darkness. I retreat to the quietude of a nearby cave. I do not wish to see the stars tonight. I cannot bear to look upon them, nor for them to look upon me. Night is when the questions come. Night is when I doubt. How long has it been now? How many years? If a year can even be called a year. The sun rises and sets so slowly in this world. Everything beneath it has staggered to match its tempo, even myself. More so as my spirit continues to falter, and my memories of the old world grow dimmer. Perhaps it is a blessing to forget the past. Every time my mind begins to drift towards reminiscence, my psyche instinctively seizes up in self-defense at the mere anticipation of it. It is as though heartache radiates off of my memories, like heat from a flame, like the sting you feel before you're burnt. When I push too far, when my thoughts are close enough to brush the surface of those memories, our ears are traveled together, your knowing smile piercing through my burrata, the gentle tartness of a raspberry ruby marshmallow. I recoil from the searing pain and draw myself back to the present. My instinct of the seeker is to press ever forward. Each fresh dawn is a call to a new day, a new adventure, a new breakfast, just as no day can be relived. No breakfast can be reamed, no matter how balanced it may be. There was a time when I wouldn't have said that life has been a journey from one breakfast to the next, but now I have explored the darkest jungles and braved the deepest tombs this world has to offer, but the only frosted oak doubloons that can be found are the pictures which yet ache in the back of my head. What good is a journey when the destination no longer exists? Why should I keep my eyes to the present when everything I see can only be found in the past?  That is why I retreat deeper into the depths of the earth, afraid to even glimpse the moonlight. The stars mustn't seem to live this miserable parody of the life I once knew. You mustn't see. But time has worn down my walls. Even in the darkness I can feel the approaching heat of the questions which most scorches my soul. When one's purpose for living has been stolen, is it possible a new one may be found? It cannot be. It mustn't be. Because if it is, if I am presently able to determine my role in life, then it has always been a possibility. A second question naturally follows, unbidden, before I can stop myself. If the focus of my life was mine to choose, what would my heart desire above infinite possibilities? And I am burnt to senders. Within the answer lies an inferno. One whiff has raged long before the question would ever ask, and it consumes me entirely. The memories come unbidden, they cannot be restrained. There stands Samuel, his once colorful beak cracked and faded, his old bent back stooped even further in grief over three small dead lightnesses of himself, albeit only for a fleeting moment before he turns his back and resumes his solemn journey.  And now I see you descended from the treetops with terrifying ease, snatching a bowl of treasure from the claws of an unsuspecting child, your eyes lighting up in anticipation of the grin I gladly grant you. Then we lay here peacefully on the arctic slope, gazing up at the stars, dreaming of the future predestined for you since birth. What may it have meant then, that I was gazing at you all the while? My mind is overtaken entirely by images of you and us, our trials and triumphs, our laughter and our tears, how much we face together, the great tiger, the sly elves, the undead noble in his high castle. None who dared oppose us could match our combined strength. The final scene, I'm unprepared, you smile at me for the final time, taking your bag from my arms as you walk to the launch pad. I'm genuinely happy for you, so proud to see the years of training and struggle pay off. This version of me doesn't understand Losia. He doesn't recognize the heavy void in the pit of his heart. He doesn't even realize that he wants to cry. For all the pain in this world has made me suffer. For all the ugly truths of the universe it has laid bare.  Moms and dads and the children they call their own. Moms tied together by blood and bond, forcefully at times, but also by choice. Had I known all that back then, had I known of the endless potential offered by the gift of life, untethered from the artificial limits imposed on us by the roles we were assigned without consent, free from the oppressive idolatry of the so-called most important meal of the day. I would have gladly forfeit my final days of pineapple pearls, choco-tastic treasure chests, and fruity fiesta gemstones. I would have made my destination the warmth of your gaze, and my purpose to pursue your smile. I would have followed you to the stars. I emerged from my cave. My burning heartache now tempered to a strange warmth. Questions of shame turn to those of hope. If there are many worlds, could they share the same sky?  Whatever boundaries of space and time were broken for me to learn these lessons, I will break them again. I will snap every joint in the skeleton of reality between my bloody jaws until I am at your side in the cosmos.