When we talk about the quality of writing on the SCP Wiki, we often treat modern SCPs as somehow having more value or having a higher level of quality than the earliest of works. On any given day, you can find a dozen authors complaining that their works are being overlooked in favor of things that aren't as good. It's a bit of a problem with elitism, really, and a fundamental misunderstanding of what success really looks like. I mean, SCP-173 is one of the most popular SCPs on the site. It's not even close. The next thing is almost a thousand upvotes away. 4,914 upvotes have been cast for it, and only 283 downvotes. So now I'm going to talk to you about the lessons that we can take away from SCP-173 to make our own writing better. Now, first of all, let's talk about the confusion we have about the comparison of quality and success. It's a thing that people do pretty naturally. We just assume you have to choose between creating something of quality or creating something successful. Thought is, you know, you can be Michael Bay and make a billion dollars with another movie about giant robots fighting each other, or you can be an Oscar nominee and winner like Martin Scorsese. This is a false dichotomy for a variety of reasons. See, success does not have an inverse relationship to quality. Now, it feels like this isn't something we should need to explain, but of course we actually do. Because there are many best picture nominees which are hugely successful financially. It's not all of them. But there are plenty. People go to see good movies, believe it or not. This is true across all media. I mean, good books get read, good TV gets watched, and good SCP articles get upvotes. SCP-173 has been read for what is likely several million times. And for not an unsubstantial section of the wiki's writers and readers, it was the first thing they ever read involving the SCP Foundation and it draws them into the world like few other articles really can. And that's because of the world building. Drawing people into the SCP Foundation's world is something this article does very well. And it also builds on that world while still providing an interesting and short read. It's just 233 words long after all. And in that small space of time, it manages to convincingly build a world of secrecy and danger that hides under the surface of normalcy. Without there being an SCP Foundation wiki or anything relating to it, think about what even just SCP-173 means. I mean, it implies that there are at least 172 more of these things. And then of course, there's the containment procedures. When personnel must enter SCP-173's container, no fewer than three may enter at any time and the doors will be relocked behind them. So they have personnel. That's an organization of people who handle this thing. And they've been handling it long enough now to know how to avoid danger. They have procedures for it. And when they even have standard protocols for dealing with those issues, a line out of the description states in the event of an attack, personnel, or to observe Class 4 hazardous object containment procedures. Now, sure, that probably belongs in the containment procedures, but it doesn't change the fact that the line means something in the greater scheme of the world it's building. Because of course, having procedures like that means there are other hazardous objects that must be contained. Now I've seen a lot of newer writers treat things like this differently because there are a lot of clumsier ways to deliver this information. Something like SCP-173 is to be contained by the SCP Foundation, an organization devoted to the containment of anomalous objects. Of course, this blunter approach actually prevents much of the development that a story like this would need. Once you bluntly say what's going on, there's not much of a need to cover much else. And then already short work like this would be half as long if you could just tell the audience outright what you're going to do and why you're doing it. But beyond a subtle approach to world building, the article paints a very clear visual of what it's supposed to look like. Later, SCP articles probably do a better job of physically describing the objects at the center of their articles, but this first one simply leaves it up to your eyes because there's a picture of it on the screen. And that image is very compelling. I've talked at length before about the copyright issues inherent to that image and it's also why you're not seeing it on screen right now. But putting those concerns aside, it is a staggeringly good image to use for an article. And this is something that we've known from the very beginning. Never underestimate the bump in quality that a good image can add to the article you're writing. I think about articles like SCP-106 with that image of a rotting old man, or the face at the bottom of the staircase in SCP-087, or the image of SCP-682. These are iconic. They are compelling and they are very memorable. Now, like I said, I can't put SCP-173 on the screen right now for copyright reasons, but I'll offer a small inferior description. It shows a humanoid statue leaned against a wall with its hands outstretched. The head is huge and bulbous, and it's far too large for a body if this was a real person, but obviously it's clearly not. The head is turned slightly, looking at the camera, and the face is painted on. The room it's in is brightly lit from the outside, and the room itself is in a very, very rough state. The ground almost looks like it's covered in rust and the walls are discolored. When you see it, it imprints on your mind immediately, and a good author will reinforce that with subtle descriptors in the text that you can then use to engage other senses. Like the article says that SCP-173 is comprised of concrete and rebar. We all know what concrete feels like. Rough, and coarse. It's covered in Kryolan brand spray paint, and that reddish brown substance on the floor? That's actually blood and feces, and we can almost smell it now. Of course when it's not being observed, there's a rough scraping noise of the concrete statue moving around its containment cell, so we can almost hear it too. When you're building a monster like this, or literally any object, be sure to engage the senses as much as possible. This is true for non-SEP writing as well. Engage the senses more than one if it's at all possible. You're creating it in the mind of the audience, and your job is to make sure they not only understand what it looks like, but what it feels like, sounds like, smells like, even tastes like if you can manage it. But this is all pretty basic. So why did SCP-173 take off? Well, let's take a look at the era it was created in. The idea of secret forces working behind the scenes have always existed, but deeper fundamental government conspiracies as understood by the wider public, at least in the west, have their roots in the mid to late 2000s. I'm gonna explain why. See, SCP-173 was originally written in 2007. When we think about what that means to the culture that was present at the time, we can sort of see the idea of why a widespread secret like this took hold instead of the standard personalized or specific conspiracies that existed before. In 2007, George Bush was still president, if that doesn't make you feel old, I don't know what will. But his popularity had plummeted among the American public at the time, and the origins of the Iraqi war were, more and more, being understood to be a lie. True or false? That narrative ran through fiction at the time strongly, and that mistrust of government, reticence in fiction of the idea that those in power were hiding things from the rest of us on a grand scale. And it's really continued ever since. While movies in 2007 didn't generally reflect this, mostly there was some stuff. The stuff that was written then, and filmed then, and then released in 2008 certainly did. A small selection for memory would be movies like Cloverfield, where the government is all but understood to if not be behind the monsters attacks by making a mistake. They're at least aware it was going to happen. This is also the year that Iron Man and the Incredible Hulk came out for the Marvel Cinematic Universe. And hopefully I don't have to explain how SHIELD and the SCP Foundation have a strong similarity. Heck, even the comedies of the time had this theme of conspiracy running through them, even if it wasn't treated particularly seriously. Harold and Kumar, a skate from Guantanamo Bay, is a thing that happened that year after all, though the less said about it the better. But the biggest movie of 2008 was The Dark Knight, which is a political thriller about corruption, and it's a movie that ends with a grand lie being told to the populace to keep them happy and subservient. In a more limited fashion, even television got on on the action. With the adaptation of an older work for television in the Dresden files about a secret world with supernatural that's hiding from the public. Though because that was actually adapted from a book from 2000, that's actually a good way to demonstrate that the underlying concepts are not entirely exclusive to that era. They just became more popular then. You know, the first Indiana Jones movie had the US government keeping magical relics and artifacts and storage somewhere hidden away, and that came out in 1981. The X-Files covered a lot of the ground involving grand conspiracies well before the SCP Foundation was ever conceived. Buffy the Vampire Slayer and its spin-off angel also had a heavy dose of secret conspiracies hiding the supernatural from the rest of the world, and Buffy even included the initiative, a fictional group associated with the US military, that literally kept sentient supernatural entities in boxes for experimentation. And we could think of these earlier works as setting the stage. By 2007, the world of fiction was clearly primed for something like the SCP Foundation. And even if the creator of SCP 173 was not cognizant of the trends in fiction at the time, you don't have to be aware of it to be swept up in it. But you, as a writer, knowing this can actually observe the trends in fiction and run with them. Like the last couple of years I've seen a huge trend in horror, both on television and in film and in books. If you understand that and you work in that genre, you can increase your chances of success. And that goes double for the wiki. People are going to read the things they're interested in, at the time. Following greater societal trends will help you create something that is lasting, and which feels a niche that maybe no one else has thought of yet. Let's talk a little bit about the lessons that SCP 173 teaches us in summary. 1. Stop thinking about success and quality as somehow mutually exclusive. Do something good and success will follow you. There's no problem with chasing trends if you can create something good along the way. Treating quality and success as separate means you might end up willing to sacrifice quality for success, and that's the one bad option you have. Do both. 2. You don't need to launch world building with some grand creed that explains everything. Give us a subtle story, understated, that takes place in the world you imagine, and that can be much more interesting to readers, and it will genuinely help you in building the world in the first place. 3. When you're writing in SCP or frankly anything, your descriptions should be compelling. One easy tip is to make sure that you use one sense beyond sight in the description. Sight and sound are the most passive options. Smell and touch are the most visceral, obviously, outside of taste, which is a lot harder to do. But choose something that helps the reader understand what you're trying to describe outside of just sight. And it might be cliche, but that doesn't mean it's not true. A picture is worth a thousand words, so pick something memorable and evocative. And 4. Understand the underlying themes of what you're writing and how they fit into the grander desires and trends of society and culture at the time. What people want to read or watch is constantly changing and evolving. Your writing should change with it. And finally, have fun. I'd like to thank my subscribers for May, especially Dr. North, who just became a $20 patron. Thank you. I appreciate that more than I think you can imagine. It's donations like yours that help make sure I can keep making this kind of content. And also a thank you to everyone else on the screen right now. Every single one of these people has pledged on Patreon at patreon.com forward slash decimarian. If you want to support my content, head on over and pledge at any level. If you do, you'll get a shout out in the next video. And also, I know I've got a lot of new subscribers today. I just want to say thank you. It's been a while, last few days, watching the increased interest in traffic. If you haven't subscribed already, please do that. And definitely, if you're already subscribed, hit the notification bell next to that so you're always informed when I post a new video. You wouldn't want to miss something I made, right? Anyway, I'll see you guys on Thursday. And thanks for being here.


They've discounted you. They've overlooked you. They've snubbed you. They've denied you access. Why? Because they're judging from the exterior. But remember this, man's rejection can never stop God's appointment. It can feel like nothing's ever gonna come to fruition in terms of your calling. It can feel like you're constantly being overlooked. You're constantly being denied opportunities. But so long as you keep your heart right, so long as you tend to what God has given to you to do in this season, so long as you keep your focus on Jesus, God is ultimately the one who appoints an anoints. It is not man who anoints. It is not man who chooses who gets what ministry. That's the Lord.


I would like to welcome to the stage to kick this off, the Honorable Mayor Reed. Good morning. Thank you all for being here today. This is a great opportunity for leaders like yourself to get to Montgomery, Alabama and learn a little bit about what we've been doing here. But I know most importantly, we're just glad to offer our presence and our thanks for you for your service and for your leadership, not only to this community and the communities that you reside in, but also to this country and this world. So we appreciate everything that you do. We're glad to have you here in Montgomery, Alabama. This has always been a place of change. This has always been a place that challenged and pushed the envelope, so to speak. And we've always been a place where people believe in strong leadership, strong Air Force leadership like former retired general, Bernard Randolph, who is my wife's uncle who's a retired four-star general in the Air Force. Leaders like that have always created change all the way through civil rights leaders such as Edie Nixon, Ralph Abernathy, Joe N. Robinson. Why am I bringing up these leaders? Because these are leaders that you don't probably know, but you wouldn't know this last one. That's Reverend Dr. Martin Luther King, Jr. Those were the leaders that helped spur him as a 26-year-old pastor right here in Montgomery, Alabama to lead civil protests for 382 days. Something that was supposed to be a one-day protest lasted 382 days. That changed this entire nation and the world. But the leaders that I mentioned to you are probably people that you never heard of because they weren't out front. So leadership we know starts not just with the people who are out front like me, but often with the people who are beside you and sometimes behind the scenes that are pushing for that change. One of the reasons why I ran to be mayor of Montgomery, Alabama, which I have done now for a robust 115 days is because I want to be the thermostat and not the thermometer. We wanted to set the temperature as opposed to take the temperature.  What does that leadership look like? Often we confuse management with leadership. I was told a long time ago management is maintaining the status quo and leadership is changing it. And so as leaders we expect you all to do that within your own capacity. And what we want to do here in Montgomery, Alabama is be a partner with you and be a continued partner with the Air Force. But leadership isn't easy. You can't lead with an end to the ground and a finger to the wind. It's an undignified position. So you're going to lead, you have to be willing to step out there on faith and you have to be willing to trust your moral judgment about what it is you're doing. And I believe that's important whether you're in the military or whether you're someone like me that's in an elected office because not all elected officials are leaders. I would say most of them are not. Most are managers. But those that are leaders actually look to influence and impact change in a positive way. That's what we're doing in Montgomery, Alabama. We look forward to continue to do that with you and we're glad to have you here and we hope you enjoy your stay. Thank you so much.


When researching for my video on the history of airplane wings, I came across a lot of cool experimental planes. I didn't want them to go to waste, so here are three of the coolest ones I found. Don't forget to subscribe and hit that notification bell so you don't miss out on any future uploads, and let's jump in. First up, the Rutan Voyager. The initial idea for the plane was first sketched out on the back of a napkin before being built in the Mojave Desert over the course of five years, mainly by a group of volunteers. The airframe, largely made of fiberglass, carbon fiber, and Kevlar, weighed 2,200 pounds before more than 7,000 pounds of fuel were loaded on board. That meant that a takeoff, more than 75% of the aircraft's weight, was the insane amount of fuel that would be required to circumnavigate the globe. Voyager came equipped with two propellers, one in the front and one in the back, powered by two separate engines, although the rear propeller was only used during takeoff. Voyager's world record flight took place on the longest runway in the world at Edwards Air Force Base at 801 a.m. on December 14th, 1986, with 3,500 of the world's press and attendance. As the plane accelerated down the runway, the tips of the wings, which were heavily loaded with fuel, were damaged when they unexpectedly flipped downwards and scraped against the runway. You might wonder why the designers didn't realize this would happen in advance, but in the 67 test flights that led up to this flight, the plane had never been fully loaded to capacitate. Contact with the ground caused parts of the wingtips on both sides to be ripped off, exposing the blue foam core, but the pilots determined that the aircraft was still within its performance specifications, despite the damage, and decided to continue west. During the flight, the two pilots had to deal with extremely cramped quarters. To reduce stress, they had originally intended to fly the plane in three-hour shifts, but the plane was so difficult to control while heavily loaded with fuel that it prevented routine changeovers, and so Dick Rutan stayed at the controls without relief for nearly all of the first three days of the flight, not three hours, three days, and that was only about a third of the way into the plane's journey around the globe. Along the way, the pilots had to maneuver around bad weather numerous times, most perilously around the 600-mile wide Typhoon Marge, and Libya when they were denied access to the country's airspace in response to the American bombing of Libya earlier that year. With that in mind, I'm not sure why they hadn't planned to fly around Libya in the first place. In front of 55,000 spectators and a large press contingent, including 23 live feeds breaking into scheduled broadcasting across Europe and North America, the plane safely came back to Earth, touching down at 8.06 am at the same airfield almost exactly nine days after takeoff. The average speed of the flight was 116 miles per hour, about a fifth the speed of modern commercial airliners. At touchdown, there were only 106 pounds of fuel remaining in the tanks, less than 2% the fuel they had to take off. The flight was the first successful aerial non-stop, non-refueled circumnavigation of the Earth that included two passes over the equator, as opposed to just circling the North or South Pole in a few minutes. In the 36 years since, this feat has only been accomplished one more time by Steve Fawcett in the Global Flyer, designed by the same man as the Voyager. Number 2 – The LTV-XC-142 Kind of a mouthful. Planes are great because they can go far and fast while carrying a lot of cargo, and helicopters are great because they can take off and land with very little space and without having a dedicated airstrip. But what if you could combine all of these traits into one plane? Well, meet the XC-142. The 142 was a tilt-wing experimental aircraft designed to investigate short takeoff and landing transports. Its wings could turn up to 90 degrees relative to the ground, so it could take off and land vertically while being able to achieve the faster speeds and larger cargo holes of a traditional plane. In service, it would carry 32 equipped troops or 8,000 pounds of cargo at a max speed of 400 miles per hour. The 142 first flew in September of 1964, and a few months later it crossed the Atlantic in normal flight while taking off and landing vertically. But while initial testing proved promising, problems would start piling up. During continued testing, the aircraft's crosslink drive shaft, the mechanism that allowed the plane wings to tilt, proved to be its Achilles' heel. The shaft resulted in excessive vibration, wing flexing, and difficulty operating the plane. And one major problem found in the aircraft was an instability between wing angles of 35 and 80 degrees, usually encountered during takeoff and landing. And new propellers designed especially for the XC142 proved to generate less thrust than expected. And as these problems piled up, the Air Force continually requested changes to the plane's design until the program was cancelled altogether. After that, the one surviving aircraft of the five originally built was handed over to NASA for testing and now sits on display at the U.S. Air Force's National Museum at Wright Patterson Air Force Base near Dayton, Ohio. Although this wouldn't be the death of VTOL aircraft, the first widely successful one came just a few years later in 1969 with the introduction of the British Harrier Jumbo Jet, which saw extensive use in the Falkland Wars and is still in service to this day, making it one of the most successful and most famous VTOL planes ever developed. And the U.S. didn't abandon the idea of VTOL aircraft altogether. Both the V-22 Osprey, first introduced in 2007, and the new F-35B stealth fighter have VTOL capabilities. Lastly, the Grumian X-29. The Grumian X-29 was an American experimental aircraft that tested a forward swept wing for NASA and the U.S. Air Force from 1984 to 1991. It was part of a quest to build the ultimate fighter jet by taking advantage of its inherent instability that would allow it to outmaneuver any enemy fighter. The aerodynamic instability of the X-29's airframe required the use of computerized fly-by-wire, which made corrections to the flight path 40 times a second to control the plane. The engineers concluded that if all the flight computers failed, aerodynamic forces would have destroyed the plane before the pilot even had a chance to eject. Planes with forward swept wings, which are angled in the opposite direction of conventional wings, are rare, but the X-29 wasn't the first to employ them. The German Junker Bombers from the Second World War were the first successful prototypes with this design, and the man who designed them would later create the Hansa HBF-320, a small business jet with forward swept wings that took to the skies in 1964. To this day, they're the only commercial aircraft to have ever employed forward swept wings, and a few still fly to this day. In the Hansa Jet, the wings were swept forward to allow them to be mounted further back along the plane's body, creating more space for passengers and an otherwise cramped aircraft. But whereas the Hansa Jet's wings were swept forward by just a few degrees, the X-29's were swept forward by 33. This put such immense forces on the wings, a new advanced composite had to be specially designed for them to keep the wings from being ripped off by the aerodynamic forces. The X-29's unique design led to another interesting effect. Have you ever seen those small flaps that go up and down on the wings of a plane, often around takeoff and landing? Well, those are called ailerons, and they're a crucial component to controlling a plane. When a normal plane goes into a stall, a loss of lift that can lead to a crash, the ailerons are usually the first thing to stop working, because stalls tend to start at the wing tip and move inward, due to the way the air flows over a wing. This loss of use of the ailerons leads to a loss of control in an already dangerous situation. But with forward swept wings like the ones on the X-29, air flow is forced in the opposite direction, moving inwards towards the fuselage. This causes stalls to start closer to the main body of the plane, leaving the ailerons functional for longer and giving pilots much needed control. While the plane was being developed, this maneuverability was believed to be essential for fighter superiority, because if you're playing stalls before enemies, you can easily be shot out of the sky. The X-29s were flown in 422 research missions between 1984 and 1992, but in the end, as stealth became more important than maneuverability, the X-29 was resigned to history. And since then, forward swept wings have also been made obsolete by thrust vectoring, or the ability to physically move an engine to control the direction of its thrust, ensuring maneuverability even in case of a stall. Well, I hope you liked learning a bit more about these unusual planes. If you liked the video, be sure to subscribe. And remember, there's always more to learn.


What's up, good people and welcome to 20 Updates Hapa SPM Bars. Ngao pale kwam tandao the Pluto, yani Mr Sanitizer amekasirika vibaya sana. And the reason as to why Pluto is mad is because a lady went on social media, did an interview and said, ya kumbalimza liya the Plutom totoms chana, na the Pluto does not take care of the child. Hindo baya mi fanya the Plutom kakasirika sana nili bidi tumempigia kumbalimza, what is going on, an adjo oms chana, hamjui, and what is the plan, skiza conversation. Miss B. Hapa, sasa? Ako live kwenye SPM Bars? Yes. Tumiona, this is a story ambei me kwa kumtandao leo. Ambei, amstiana a lienda kafanya a certain interview on a certain YouTube channel a katema akonam toto wako. Lakin itumiona, nikama kidogo unamjo, amstiana hamjui, do you know this lady? No, that's Jemuona. Ay, ahu Jemuona? Ayu simtina jiyu, ayu akawana jiyu, kana kudiyo mbora nikukana, ayu anim bidi jiyu, that's just someone, I don't know.  Amal, jiyuri na konga veri siresa niti kama suzatimata zi. Yes. Mi only have one child. Dikonamto to nani to skaisa viya. Ya. And you know people are now confused in that wiyu deyu muhnyame pustizo vitu. Ni ulems chala.  Yes.  Mm-hmm. Zami na nga liye pa liye po, because the moment mizia kwa nzeli niye mei po, atu lile na nikihenda, I thought niyo, niyo mei mama mei ame, ame ni nizeli, vitu sundun li kwa naku wangali anase mani, kuna na nga liye, nimkuna sijui bana. Nia. Eh, so for me, miitu kwa maizumina konga veri siresa, and my friends will tell you. For such cases, mi mi is takangi wijingamto. Nia. Okay. Ame, vitu kwa na kujua, are you planning to su the owner of the channel, ama the lady? I have already contacted my lair. So your lairs will handle the case? Nia. Kwebo wezu katumbea kama umeyamua ni chanela mani ni the lady herself. Eh, you know now, investigation done is that you are saying that you are the lady herself and when you are on the channel, you know, then piyakunam tu ame ni takes Instagram a kinemi, apparently she knows the girl. Mm-hmm. Wana pana sumana hez, jini kese university, tena li kwa jinkua takadifaji a fees. Nia. Nia li kwa mavi ati she's going to do anything for, for man, something of this sort, eh. Ah, jamani. Naka ni, naka ni amia, lati yote imenyo, yo demo na sema telekona egiria. Yes. Yo demo kanembeni wongo, junim siana, yua inenda utunona. Yeah. But aga ni amia, then ni kwa mo detail sum, waiting for more details, eh. Yeah. Eh, last my lair takes the case from there. Ha, jamani. Lafutumia ona pale edgobare na ju ame fanya a post, aka sema a kandika headline, Klauchesa versus Klauchesa. Wewa ono nene, una sema je kusiana na yo story. Na ju edgobare si maria kwanza ana, ana ta futuriya story ni kona, jina li plutu ona jua. Mm hmm. Nemi ni so bisiana, ni ni so kwa wala ho kusinda wati siyana na e. Nia. Aka mahi ondi ona muna ake kutafutashi linki. Mm hmm. Acha na. I think, I think kia na Klauchesa siya nebel. Yeah. Mena sema kama ni na muna ake kutafutahunga edge. Ata futi. Acha, acha ata futi. Ay, asawa nabiya. Yusas, yusas, yusas, you know, you know when now things goes, kena hostel kidogo na ganao, seeing the truth aseme ata, ata adu jai meete. Mm hmm. So what we'll let you see, na ori di asak sema dueni Klauchesa. And maybe I don't need to Klauchesa anything. Okay, you know what Klauchesa is, eh? Mm hmm. Ono kwa nga pali kutafutah some things, you know? Yes. Wako pali kutafutah kutuka mafem. Mm hmm. Wako pali kutafutah. Kutafutah kutafutah kuna. Ongo? Mm hmm. You get. For me, for me, I would say that I'm famous, eh? Mm hmm. But I'll say that I'm a little bit popular among my fans and friends, eh? But you are famous, Klaucha. I'll just say you're famous, Betty. This is among the most influential. You cannot compare me the likes of Akina, Eric Komondi, Jalangon, Wasiwa Kakaen. Okay. I respect them and I take the footsteps of someone like Jalash to grow. Yes. Yes. So for me, I'll just say that I'm a little bit popular among my fans and friends, eh? Yeah. I'm not after fame. Mm hmm. Eyo kidogo, eyo popular kidogo ni ni kuna mi nasume mi ni Toshia, eh? Yes. Taza na Klaucha, ni gitafutah mi ni. Ni nyewe, ni nyewe. You have the money, you have the cars, you are in a happy relationship. Una hama, una enda kilimani. Ah, Pluto. Umeputah nyumba already. Taza, yo mama gajurana.  Taza, Pluto, are you being among the most influential people in the country we have, eh? Kuna istori na, kuna istori na ito blackmailing?  Is there another blackmail, Ushai Pata? Uh, Sidenin, Ushai Pata blackmail. Sidenin. Mm hmm. Eo na jufo mi, when it comes to issues with guns, eh? Yeah. Nakonga, nakonga very open and direct to the point. I'm not the girl who just go sleeping around. Mi ato nikipati, bimo na epatu ito my girlfriend, unona. Mm hmm. So, mi issues concerning girls, yo na yo. Sidenin, ninga kwa nimefika, apa penye nimefika, kama ninga kwa msoku protokana masiana. Yo, you understand it? Yeah.  Around things that concern, love me become my zone. But I would, I'll tell you the truth. In a week, maybe you'll understand it. Only like, two days in the afternoon, sipe kya ke, nifanya some videos, alafu lirudi nikianganya na videos, nye mi, nimefanya, peke anguni post polivo YouTube. But you need to take a layer pattern, take a layer something, eh? Mm hmm. So, mi sadafiki, yeah, that's my whole life. That is not even where my income comes from, unona. Yeah. Pia, mi nimona BSR na, ona jufo. Eh, even the title YouTuber, calling me a YouTuber all the time, eh? Eh. Eh, zamudai jufu mufi li kuwa, na jufu aikwati kuwa, ikwa that's not me, you get.  Just call me Pluto a businessman. A successful. Pluto a successful businessman. Tuna isabu pali views, alafu tuna isabu pesa. weiwa hisha kubuna niya main z devil or bulhina niya na ta niye low niya na na na na na na na na exists na na na na na na n movies na na n trazer지가 lehia na linda bink ni ya puni niro ni k monuments na iyo ni ki patia na nihe biha uko- دعl dizendo na iyo ni ki patia na ni ke 사ista evo n müin ni kwa ni makid me komichi opera na iyo ni ki tuzyei She's from the word go Yuh Eyo ni ki tuwa nili introduzing yub doey Ki tamu sana tunet liso Kuala And how is the situation with the now yub baby mama Mli sot mani nao ama ikuwaji? Adu kusot Waluwa siy wali sema Mutuyia kibumu kubu wa tunet afu da za Minda suynibia koto niki wira Wat, sosa wnanguwaja until 18 years Wazi yub wali sema Magiwa sosa yey mungu nimenki But how does that make you feel pluto, you know? Just not being able to see your child. Being around your son. It makes me feel bad, ya? Ya. But as long as I would want to have another child, ya? Okay. That does not mean that I have the the permission to go and mess around. Ya, I have a girlfriend. Ya. If there is something you guys can agree on, maybe get a child later when both of you are ready. Yes. So I don't think... Ya, maisha, sometimes na kuwatu. Ya, nikimutu tukupakano ya na kuja na zema atia, atia konambdu. Mudu otu kwa liya li impata li ini? Sipo wa sipo wa. Na kuja. Ya ni... So na mimi ni jido a cloud chasing, abu mimi ni me cloud chasing ni ini. Ya know, sometimes... Sometimes, sometimes Edgars to be serious. Ya. Edgars to be serious because, ya? Mm hmm. When he calls me cloud chasing, abu nimi me cloud chasing ni ini. Mimi, I'm actually the victim. Eh, labda na sema wumi organize ule cloud chasing mwingine? Sipo wa ni hangi biya syarakama iso my friend. Ya. Ula niku lizena vanya biya syarakama yondoni ni ni trend. Hehehehe. To be honest liya, lemi ask you a question, ya? Ya. Aya, nige takakutu... Chana liya ngu oke mungo mendi pateile fava, disaine zeka video, within 24 hours you cover 100,000 views because of God's favors, indio? Ya. Nige takakuwa silia otu hangu ma fansinu a mi ekitu. Nige na tukwa chaneli hangu, nika ekini na nika mwingi ekitu. Kwele. Pasa na na taftaji muntura na uko. Iwa chaneli ngewa mi postu liwa na taiku wa nasadz.  Ya. A takama ni cloud chasing, nige liwa zeka maakina, lewa sewa kraga. Nige wa liwa ni ni SPM fansinu a mi eva zifu jumbona. You have the numbers. Ya. So, I think pia headiga mamu zingina bana. Mina sema aga some things call for maturity. Ya. Mina sema... Nakuanga one of his fans, but I am disappointed in him. Yes. Sosa mi mi akihaza kuni chokosa, wana taka tukwa lewa. Mi misikuli kukubo kame aki na ambare na aki na jibalu bana. Ya. Mi mi na jijen, kasa akihaza kuni kikimiza sa easy, na takani hanbuken na nana jijen ka. Pa nasiopuwa. Amen. So, pluto mi biku malizi, tuliona puwa wali, uleza kusimai kazi ya radio, watona tuwa wa api. Ya. Imesikiwa wa api. Ume pata, ume pigiwa simu ama. Ni ni ka postunili fanya apu evo ko Instagram story, se kakatriya ni misiko na jiyo kataenda na mnaiyo. Aha, pluto. Kuma tata kazi mitu sema. Lekini siyesi mind, nika puta jabu ko. Ya. Haa, hada na acha kukubo kufuja na nani. Una acha kusani chais wa tu. Una acha kusani chais kwa radio sasa. Nata kashikuli za muna ingiya radio, na jiyo kwa freshi. Ya. Aya, soa basi. Aki asante sana pluto kukongilesha SPM basi, ni trendy updates. Okay. Na tumeshkuru sana. Ya, thank you. Hopefully everything goes on well. Uta tu elezeya how things are going to you know, to go on with this particular case. Bata pole sana. Ya, thank you. Alright, thank you. Alright, thank you. Yes, thank you.


We're pleased to be here today at the OpenShift Commons Gathering, and the topic today is data science. And I'm Diane Fedema from Red Hat. I work in the AI services team. I'm here with David Cantor and Peter Madsen. David is the, excuse me, the executive director of ML Commons, and Peter is the president of ML Commons, general chair of ML Perth and staff engineer at Google. So Peter and David recently launched ML Commons, and we invited them to provide some background history on ML Commons and ML Perth. And I want to say that Red Hat is really excited to be one of the founding members of ML Commons. So to get us started, tell us a little bit about your backgrounds and some of the work that you do. So I'm Peter Madsen. I run ML metrics for Google. I'm interested in measuring all things about ML. And before that, I studied compilers at Stanford. I worked with a startup called Stream Processors, and we've had video for a while, lots of different opportunities to try and make complex things go fast, as it turns out, that used to be in a trinal need. So I decided to be trying to do that for ML and also try and make it better. So as we push forward, thanks for the ML Perth and the ML Commons. David. Yeah, David Cantor. And so, pre-ML Commons, I spent a lot of time in computer architecture. I actually started a microprocessor company that was sort of doing a fusion of compilers and hardware design to exploit more single-threaded performance. And then after that, I ended up consulting with a number of companies, one of which was Cerebra Systems, which is now, like Red Hat, a founding member of ML Commons, and that's sort of how I got involved in this. And I actually have a little bit of background in benchmarking, which kind of came in handy and is part of the reason why I got involved. And it's just, you know, it's very exciting to be able to build this kind of an open community. And we really do appreciate that the role that Red Hat is playing. Thank you. So, I don't know how many users are aware that ML Commons originated in ML Perth. What led you to start ML Perth, Peter, and what were its goals, and how did it evolve into ML Commons? Sure. So, about three years ago, we were looking around at ML and, in particular, ML hardware. In Google, I'm trying to understand how fast were different options. And we decided that we really needed to have a good ML performance benchmark. And there did not seem to be an industry standard solution for those. So, we rounded up a set of usual suspects. Anyone we could find that we found had done the hard work. So, folks like Greg Diamas from Baidu, who did deep bench, Stanford Don bench folks, Matai Zaharia and Peter Bayless, and the Fathom folks from Harvard. And I got everybody in a room and put forth the challenge, like, should we try and come up with one benchmark or could you use to make sure training performed? And everyone thought that was a great idea.  And the benchmark really took off. We had our first set of rules out in the middle of 2018. And then results by the end of that year, we've had several rounds since then, 2019 was a big year of growth. We got it to inference, we got it to HPC, 2020, we continue to expand. And we also started ML comments. Sort of the driving function behind that was we were looking around for a home for ML, wanted to put in a non-profit organization. But we wanted something that was engineering focused and ML focused. Open engineering and ML. And we couldn't find that particular combination. We could find large organizations like Linux. So, we're very focused on open engineering in general. We could find some that were focused on ML in particular, like Neuros, but they were more event oriented. And so, we decided to start one. We wanted an organization that that was their reason for being, was to try and come along and make ML better. And we put ML perf into ML comments. ML perf is still very much growing and growing, but it now has... Oh, we also looked at the field of ML and we feel like it's a very young industry, right? It really has a tremendous amount of needs to mature as a field. It needs the same things that drove sort of the industrial revolution. Great ways of measuring things. It needs good raw materials. Aided in the case of ML. And it needs good ways of making things, standard ways of making things. A shift from doing things in your basement to assembly line production of high quality. And we wanted to see whether we could form an organization that would answer that call and try and provide those things and really move the field forward. Yeah, that's great. So, that's sort of the driving motivation. And I think we kind of ended up with three key pillars that we like to talk about. And that would be the benchmarks and metrics, which we've talked about ML perf, as well as building large open data sets, which we think are another key ingredient towards really democratizing technology, right? And the same way that open source really has enabled and fundamentally transformed like the art of software, whether software as an art or as an engineering, it's just utterly unrecognizable compared to 30 years ago. And sort of the analogy is that data is sort of that same raw ingredient that you need to start building up machine learning. And the more large and open data sets we have, the more folks are able to extend ML capabilities and use them in products and extend those benefits to the whole world, right? And the third pillar is best practices. And I like to think of this as removing friction, right? And or perhaps the transition from sewing your own clothes to having an abstracted assembly line where there's a real flow. And today with ML, there's a lot of things, whether it's model portability or just even deploying a model is tremendously high friction. But if we want ML to become pervasive, we need to drive those sources of friction down so that maybe in the future, doing things with ML is almost as easy as grabbing a library off of GitHub and then looking at the comments and maybe asking some questions on Stack Overflow about gluing it together. Like that's a future we would love to go towards. And we are very fortunate that when we went out and started talking about this vision, you know, it really resonated with a lot of companies. You know, Red Hat is a founder. We've got about 39 companies that are founders and a total of over 60 members.  And so we've really built this just tremendously vibrant community to focus on advancing innovation in machine learning and kind of extending those benefits through all of society. And it's very much organized in the principles of open source, right? We're very open. We like to move fast and iterate. Okay, great. So are most of those members then hardware companies? Can you just give me a little bit of a breakdown there? Sure, yeah. So we absolutely have a lot of hardware companies. You know, Peter named a few like Intel and NVIDIA as well as startups like Cinti and so forth. But we have a number of cloud services companies and software companies as well. We really see this is a big tent where there's a lot of folks who can play. You know, to name an example of sort of a more purist software company in some sense, VMware is involved. There are a number of ML software companies and then a lot of cloud providers who provide computing services in one fashion or another. As well as, you know, sort of very ML focused companies. There's a couple of startups that focus on replicating experiments and things like that that are engaged. So it's a really lovely and diverse community and also across all GEOs. This is both a blessing and a curse. For those of you in distributed organizations, you know the challenge of finding a time that works for folks in Asia, folks in Europe and folks in America, which is there is no such time. But, you know, it's great to have such a diversity of participation. Can you give me some examples of projects that are going on in ML Commons? Absolutely. So I'll probably start off with, you know, one or two. So the ML per benchmarks are pretty well known, but one of the things that we are doing is trying to sort of grow the footprint and move into, you know, some new areas that need attention in terms of ML. We started, as Peter mentioned, with training. I got involved and helped to lead doing inference benchmarks. And then one of the things that we branched off to do was to start focusing on mobile phones and ML in that context. And then there's some efforts that we have around, you know, sort of the internet of things in tiny devices. That's one way that we've been expanding with different projects in the metric side. And then one of the things that I think, you know, actually, you know, brought us together, you and me most literally, was ML Cube, which is one of our best practices. And that is a set of conventions around containerization that help you sort of abstract the machine learning away from all the other pieces of the infrastructure. And, you know, I like to talk about this in terms of both portability and reproducibility. And one of the examples I give of how this can help is when I think about a game-changing innovation like BERT, it was first published as a paper by Google. And there's probably some code in TensorFlow. But if you wanted to wrangle that and try that with your customers, you might spend a month or two doing that. And, you know, the vision is that maybe one day we can get that down to a day or so, or less, or maybe even hours, so that, you know, if you want to use an innovation at Amazon or Facebook and try it out on-premise or in a different cloud altogether, that becomes frictionless. And I remember, you know, one of the first things that brought you together with us was you were working with some of our benchmarks and trying to get them to work on Red Hat. And, you know, it was a bit of a struggle. And so in some sense, it was born out of that need and desire. And, you know, we also have some dataset projects and I'll let Peter talk about those. As David said, there's three big pillars for us, which are benchmarks, best practices, and dataset. I think in many ways, datasets are the new code. They are the way you express what you want your machine learning product to do. The models are in some sense a lossy compiler for them. And one of the key kinds of datasets that really drives innovation in the field is public datasets. You think about what ImageNet has done for the field, right? That costs something on the order of $300,000 to build and arguably it's created modern machine learning. We can't build performance benchmarks without good datasets. You can't do good academic research on anything without a good dataset. And a lot of the datasets we have now that are really best for their task. And then we're kind of created haphazardly, you know, an academic group needed something specific. They created the dataset and then moved on. And there's a dataset out there. Usually, you know, a very modest size compared to what's actually industry, often under restrictive licensing terms. And it's not growing and evolving with the field. And so what we would really like to do with ML Commons is create a center of excellence for public datasets. A group of people who are really excited about making sure there are good public datasets out there that are growing and evolving to suit the needs of the field. Both actual datasets, for instance, we just announced the people's speech. The largest publicly, or soon to be the largest publicly available speech dataset by order of magnitude, that includes a diverse range of languages. I think it's over 60 languages. More diverse range of speakers than what's available now. We really want to push that forward because, you know, that makes speech-to-text technology accessible globally if we can get this right. We're also looking at, essentially, datasets for recommendation systems, which are incredibly important industry, and, essentially, a framework for doing very privacy-protecting, medical datasets for accuracy validation for people looking to say, will this model really work in clinical practice? We've got a wide range of projects we're looking into all around the sort of central theme of make good public. Hey, well, that is great. So if someone in the audience right now is really interested in getting involved and, you know, in one of these areas that you've discussed, you know, I'm just wondering where do you need contributors right now, and how could they go about getting on board and helping out?  And, in fact, you know, I just, to give you an example of that, I originally showed up to a meeting at, I think, the Stanford Faculty Club, one of our early ones, that was posted through a call on the comp.arcusenet, right, and I showed up and, you know, eventually I did so much good work that I got punished and they made me executive director, right? Take that. We are an extremely open organization. So, if you go to our website to mlcommons.org, there's a page about getting involved that lists out all of our working groups. You know, we talked about like three or four projects, but there's over 10 different working groups, you know, everything from focusing on low-power embedded benchmarks to logging to algorithms. And so, each of those working groups, we have chairs.  And so, if you go to the page on MLCube, you'll get to see, you know, a bit about Diane and what the project focuses on. So, you can look through those and, you know, we are open to individual members and many of our projects are open source in nature. So, you know, you can stop by GitHub, sign the CLA, and, you know, if you see some bugs, we always love those getting fixed. And, you know, I think, again, like a lot of open source communities, it's something that, you know, you get as much as you get, right? It's the potluck model. And so, I think there are a number of folks who have kind of wandered in randomly and found that it is, you know, really fits their interests. Some of the folks on the dataset side are just phenomenally passionate about speech and this is just, you know, a really wonderful thing that just aligns with what they want to do. So, we'd love to see more folks getting engaged. But both from industry and academia, we have quite a few faculty already involved and we'd like more, we'd really like to maintain that balance in the end, just like. A community that's really open and wants to push innovation to go forward. Okay, fantastic. So, and then if you want to get, like, the links and things, go to mlcomments.org, is that right? Yup. Okay. Yeah, I think it's a great group of people, very friendly group, so glad I joined it. And so, thank you so much for being here today and talking to us. Thanks for having us. It's been great. Yeah, thanks for the invitation. And also, you know, thanks for all of your contributions to the community as well. You know, it's been a great partnership. Yeah, been a lot of fun. Thank you.