My name is Annette Klinkert. I am the director of UC. I will talk a bit more about this organization shortly. When I'm not working for UC, I am the founder and CEO of City2Science, which is a company working to bring together cities and regions, forming alliances which are sustainable, built upon the notion of open innovation, creating formats together, creating formal structures, but also events and strategies, linking research institution to strategic economic and urban development. So if you're interested in this topic, feel free to ask more about it. I will try to share my screen to talk about the European Science Engagement Association. Can you see my slides? It seems like it. Okay, thanks a lot. So I will try to make it a full screen. Okay, so this should work now. So today I'm talking about the European Science Engagement Platform, which has been developed by a community of public engagement and science communication professionals. And before introducing the platform, let me talk about who we are and what we do so that you can find out whether this could be an interesting community for you to join. We are very open to include new members, interested colleagues working in the field of psychome and public engagement across Europe. So if you find what we do is interesting, please stay in touch and let us know. We can include you to our newsletters, invite you to the conferences. It's a very open network. So here we are. You see the European Science Engagement Association. We are an international community of public engagement professionals. Our organization was founded in 2001, so we just celebrated our 20th anniversary. We have more than 110, even 120 today. I think it is member organizations across Europe and beyond. We have members in Russia, in Georgia, in, we collaborate with China, with South African colleagues, so our connections go way beyond Europe. And what we do is to support innovative engagement strategies and dialogues between science and society. This is our structure. We have a lot of universities and research institutions. More and more of these institutions are joining in as they see the need for science communication and public engagement as an integrated part of their research process. So we have more and more new applications from this side. We have some enthusiastic individuals doing psychome, some science centers and museums. We have foundations on board, science festivals, science show organizers, but also municipalities and regions joining with their science offices, national science institutions, academies, societies and some SMEs. So this is our structure. The events we conduct are really diverse and they keep changing monthly, basically, especially in the pandemic. A lot of new formats have been developed, digital formats, of course. So the range of the activities are very diverse and reflect what is going on in the larger European community in the area of psychome and engagement. You see some examples here. So from a traditional science festival, we also conduct science parliaments, make affairs, hackathons, public debates, living labs, and you will find all of these on the UC platform. Before I introduce the platform, just a short definition of what public engagement means to us. You will all know that science communication involves all kinds of different formats and ways to communicate. What we mean by public engagement is a two-way process that involves interaction and listening with a goal of generating mutual benefit. This is what is not done by a news article or even by a podcast or a blog. So what we are presenting today and what you see, basically, focusing on is how to create this two-way process, how to interact, how to listen to others, and in the end how to generate mutual benefit, which is not just on the side of the research, but also on the side of your partners, either stakeholders from municipalities, policymakers, citizens, or other experts in various fields. So the reason why we created the platform was that we decided we wanted to provide a set of practical resources for researchers, teachers, trainers, funders, and basically everyone who is interested in learning more about public engagement. We also said that we need new methods to engage audience. So this platform is also for us as a qualification opportunity, bringing in the knowledge and the practical experience of our members, sharing it with others, making it available, showing that the world is very diverse when it comes to methodologies, engaging stakeholders, and policymakers. So this is also what we want to show. Here is where you will find the platform. If you look at the website uc.info, you will find an extra slot science engagement platform. So if you click on this, you will find a platform that showcases inspiring and innovative ways to engage different publics with science. And the focus is on involving citizens in research and innovation processes across Europe and beyond. The examples you will find may have a certain topic, but most of them show the format and the topic is flexible. So if you have, for example, a science cafe, which is a traditional format, the format is interesting, and you can then use it for biotechnology, for physics, for philosophy, for whatever you want, as long as you understand how the format works in practice. So on the platform, you will find around 80 different forms of engagement plus resources and good reads. You will find them like this. So you find some tiles which you can click on.  And then when you click the format, you will find a description. You will find videos, sometimes even contact persons you can directly get in touch with if you want to know more about the format. And you will find digital formats as well as physical ones. And I would just encourage you to play around with this platform and find the activities you are most interested in. This is just showing a range. So you will learn more about workshops, which take the idea of a workshop out to the streets. You will find something about societal hackathons, about how to do scenario workshops. You'll find something about tinkering spaces, Hollywood physics, Mars experiments, design thinking workshops. So you see the formats are very different in their size. And you will find something which can be done by a little small group of researchers right in your very neighborhood, ranging from a science cafe to a large science festival. And we'll give you some information and background on all these different activities. So what you'll get is the name of the activity, its purpose, which is different, of course, for all of these different formats you see, you'll get an information about potential target groups to involve and address a description. We give you some of the benefits that we see are behind each of these activities, some hints on the preparation, some main steps to consider, and then what it could be even most important, some examples, contacts and further inspiration. You can filter your search by either your purpose, your target groups or some keywords that you want to look at. So you can also play around with this, but I would encourage you to just openly look at all the formats because in the end it's up to you where you see your purpose and where you see the need and which target groups you may want to address. What you will also find is a range of toolkits and good reads on science engagement because we thought we should filter for the community where we would see the most interesting tool. So this is not presenting each and every EU project on science communication, but some toolboxes which we found relevant. So you will find a SCICOM toolbox with practical advice that performed toolkits will give you advice on how to include art into science education methods. You will find something on diversity and equality plans on digitalization, on sustainable development goals. So just take some time to scroll through all these formats. You will definitely find some resources you can then use. What is important is that we have a European perspective, but we are open and have included examples from other countries, from other parts of the world. If you have any good examples that you would like to share, this platform is for you because we do invite the community to contribute their projects if you find them relevant. We will check them and we will discuss a bit whether we find them relevant for the overall community, but if you want to submit something just we can send you a template. You can get in touch via the website and you can contribute the name of your activity. Again, the purpose that you see, the target group, you would recommend a description. Basically everything that you will find on the platform is something that you can provide yourself, including examples, videos, anything you would like to share. And if we consider this relevant for the community, we will share it and upload it to the platform. This is a growing system and we also have a working group developing and shaping out the content of this platform. If you want to contribute to this, if you want to know more, get in touch with our colleague, Chris Stiles. He will find his email mentioned here. Just get in touch. He will also put you on all our distribution lists if you are interested in working together with UC. Just feel free to get in touch. Our next conference will be on the 6th and 7th of July in Cork, Ireland. So please have a look at the website to find out more. The topic will be co-creating the future. So this year's topic will be on co-creation, on bringing together stakeholders, researchers and other people interested in open innovation processes. So please get in touch. Again, we are a very open community. You are all welcome to join in. If you have any questions, please raise them now, if possible, because I may not be able to attend since my Spanish really is at the very beginning. I cannot really follow the discussion. So if you have any questions directly, let me know or send us an email anytime and we are happy to get in touch with you. Thank you very much.


Daily Tech News show is made possible by its listeners. Thanks to all of you, including Paul Teeson, Ally Sanjabi, and Andrew Bradley. Coming up on DTNS, the modular laptop is having a moment, is ad supported free TV, the future of TV on the internet, and we have a theory that connects Amazon's Tomb Raider game to Middle Earth and orcs. This is the Daily Tech News for Thursday, December 15th, 2022 in Los Angeles. I'm Tom Merritt. The boss of Decks is Justin Robert Young. And on the show's producer, Roger Cheney. Today, exactly today, 22 years ago, I went on the first date with Eileen Rivera. Hey, happy at party. Thank you, thank you, thank you. Sarah Lane has the day off, but the quick hits do not. So let's start with those. Google finished rolling out the matter smart home standard support to Google Nest products and Android. Nest devices on the latest firmware and Android devices running Android 8.1 as well as an updated Google Play services all now support matter. The Nest Wi-Fi Pro, Nest Hub Max, and second gen Nest Hub are now thread border routers as well. The Nest Wi-Fi and thermostat will receive upgrades to act as matter controllers in 2023. For now, you can only use an Android device to pair matter devices to Google Home, but Google will update its iOS app to support pairing in early 2023. The Linux Foundation announced the formation of the Overture Maps Foundation with founding members, Amazon Web Services, Meta, Microsoft, and TomTom. The foundation will work to create reliable, easy to use, and interoperable open map data. This will integrate with existing open map data from OpenStreetMap and member contributed map data. The foundation expects to release its first data set in the first half of 2023. That sounds like a very busy time between our first two quick hits. Yeah, yeah, no kidding. Where's Google and Apple in that list? Oh, great. The Montrose California Search and Rescue team reports they received a call from Apple's Emergency SOS service after a car went over an embankment and down 300 feet on a mountain side in Angeles National Forest. The occupants of the car had no cell coverage, but used the new service introduced in September for iPhone 14 models. Apple's emergency service relayed the call to the LA County Fire Department, which looped in sheriffs and the search and rescue team in Montrose. Accurate latitude and longitude led rescue copter five to the two people who had mild to moderate injuries. They were transported to a local hospital. Hey, tech done good. Yeah. Drone delivery companies ZipLine expanded its partnership with the government of Rwanda to add delivery sites in rural and urban locations throughout the country. ZipLine expects the move will triple delivery volume and includes medicine, medical supplies, nutrition, and animal health products. ZipLine says it completed over 215,000 deliveries in 2022. The deal will also provide any government agency with access to ZipLine services. And the tech story in China is about to change the Wall Street Journal sources say Chinese government officials are reexamining its policies over the past couple of years toward the tech sector. They are preparing to wind up all those long running investigations into internet companies. You know, the ones that have caused companies to pull IPOs, the ones that have caused companies to get out of certain businesses. This could potentially see apps for DD Global's ride hailing service finally restored to app stores. And it's part of a larger effort to achieve economic growth goals for China in 2023. So winds are changing to not be headwinds on tech anymore. Don't know if their tailwinds quite yet. Somewhat related to those goals is the fact that Foxconn has ended its point to point closed loop production system at its iPhone plant in Zhengzhou, which restricted employee movements to dormitories and work sites. Remember they had a full on shutdown because of COVID that they've been in this closed loop system both before and after that that has caused delays in iPhone shipments. But it looks like all of that is winding up and local authorities have lifted the high-risk COVID status on the entire area earlier this week. I wonder what economic projections could have led to such decisions by the Chinese companies? It would seem like maybe they were not very good economic projections and they thought, huh, maybe what we're doing isn't good for these economic, I don't know, I'm not an economist or a Marxist. All right, let's talk a little more about Amazon. Big news today. Amazon Games is publishing the next Tomb Raider title. The game is being developed by Crystal Dynamics using the Unreal Engine 5. It will continue Lara Croft's story. It's not gonna reboot. We're gonna pick up where we left off. It'll be coming out in a few years. They're just beginning development. That's all very interesting. It's not gonna impact your daily gaming life for a while for a couple of years, right? But there's another interesting aspect of this announcement. Crystal Dynamics was recently bought by Embracer Group. If that rings a bell, that's because you may have heard in October that Embracer Group bought Middle Earth Enterprises, formerly Tolkien Enterprises. Middle Earth Enterprises is therefore giving Embracer Group ownership of the worldwide exclusive rights to elements of the Hobbit and Lord of the Rings, including things like names of characters, names of places, objects and events, phrases and sayings from the books. Licenses are complex. So, you know, look at what Sony has with Spider-Man, even though Marvel owned Spider-Man for an example. It's kind of hard to tell what's available and what's not to whom. But here's the interesting part of this. Amazon is making a very expensive Lord of the Rings TV series. It apparently got its rights for those directly from the Tolkien family and Miramax, not from Middle Earth Enterprises. However, Amazon is now working closely with the company that owns other rights it didn't get when it began making that TV show. So, Justin, let's do something we don't always do on this show. Wildly speculate. What could this mean? Well, obviously, if we're gonna draw a line from A to B, much in the same way that when Amy Pascal left Sony after the Hacks situation, you thought that, oh, okay, well, now there is possibly a situation where her as an independent producer could work with Sony and Marvel and make an intermediary deal. The obvious thing here is that either we start getting spin-off shows or Rings of Power is now all of a sudden able to introduce Gandalf's here. Or there's a various other, now we're gonna go to Hobbiton or Mount Doom or blah, blah, blah, right? The question is, who exactly owns the rights? And if there's no clear answer to that, the question then becomes, who's gonna sue if we start using these people's names and locations? Yeah, I guess that's the other way to come at this. I was looking at it as it's incredibly complex. If you don't know, the general consensus is that Amazon probably only has rights to use things that are in the appendix of Lord of the Rings. And that's because it didn't get some of the rights that are owned by Middle-Earth Enterprises. Middle-Earth Enterprises owns the rights that Miramax used to make Lord of the Rings movies. But again, see Spider-Man for how sometimes those license deals can lock up rights in ways that even the owner can't change for a long time. So it may be that what Amazon's doing is like, hey, let's get to work on Tomb Raider. And while we're at it, I see you have all of these other Lord of the Rings rights, sure would make it easier for us to do things with Rings of Power, other TV shows. We could cut you in on the action. Cause if you go back and you read all of Embracer, co-founder and CEO Lars Wingafor's announcements when they took Over Middle-Earth Enterprises, he's saying all the things you would say when somebody asked him about TV shows and movies, which is like, you know, we're taking a long-term view. It's a very valuable property. We're having some very interesting conversations. But if you plug into your head, those conversations were with Amazon, none of it doesn't make sense. It could very well be that Amazon has been talking to Middle-Earth Enterprises since October. Tomb Raider was the easier deal to do first. We know Amazon wants to make a lot of video game movies. They can sweeten the deal by saying, hey, you've got other video game properties there. Embracer owns a lot of things. We can give you a sweet deal and sell in your board games on amazon.com. You know, what else can we do to give us as many of those rights as we can? The larger question here is from Embracer's perspective is, what's the price here? Hey, Jassy, how much are you willing to write, check and how many zeros are going to be on the end of it? Because you went to the Tolkien family and, boy, you wrote a lot of zeroes. You wrote a lot of zeros. And you want to know what? Maybe you called our bluff. I'm sure that they had conversations before that deal got signed. And I'm sure Amazon initially wanted to buy everything so they could make something that referred to everything that you remember from the books and the movies. However, they didn't. And one would assume that that came about because they couldn't come to a monetary deal. Now Rings of Power has been made. Amazon remains an extraordinarily wealthy company that can cut deals. So maybe there is something here. And this is kind of a get-to-know-you experience. And when Middle-Earth Enterprises, when they didn't get the deal from Middle-Earth Enterprises, assuming they tried, which they probably did, it was under different management. You got different owners now and different incentives because of that. Middle-Earth Enterprises, selling keychains and board games, not nearly as much, Amazon can't have as nearly as much leverage as they can when they're making video games.  Let's do this. What else can we do to work together to make us all a big pot of whatever currency is in Middle-Earth? I can't remember what it's called. And that's something where, if you're Middle-Earth Enterprises, you are effectively monetizing rights that have existed for a long time and will exist for a long time and is fractured, right? As we saw with the Tolkien family. So they're doing their best to maximize their return on a finite resource that they eventually wound up selling out to another company because they were going to be the biggest money maker that they could have. Now that Embracer has spent the money to Middle-Earth, they're gonna have to recoup it. And you gotta imagine going to Amazon and figuring out a gigantic deal is probably the fastest way that they can do it. Yeah. I'm pretty positive. I'm like 71% sure. We're gonna see something come out of this. But they were all of them deceived. One license deal to rule them all. That's what we're looking for. All right, folks. Are you someone who regularly has wished for modular laptops? Well, my friend, this is your time. First and foremost, there is success of the framework laptop, a modular laptop you can buy right now. It lets you swap out ports, add more storage, swap out RAM, upgrade the processor. It's not Lego modular. Sometimes you have to use a screwdriver, but it's very well documented, the parts are very well sourced. And we have a lot of folks in the audience who are framework users and like it. Framework has been selling two versions of its Windows laptop for about a year now and recently introduced a Chromebook for $999. Now, yeah, that's a couple of hundred dollars more than a Chromebook of this kind would normally cost, but in gadgets, Nathan Ingram reviewed it positively, arguing that that higher initial price was worth it for some people when you balance it out against the excellent upgrade ability and repair ability that you get in that laptop. The framework is not alone, at least in talking about the concept. You're right, Tom. Dell keeps teasing that it would like to provide you another option. Last year it showed off Concept Luna. It's take on a modular laptop and back then it wasn't really modular, but Dell has improved it a lot and no longer use the screws, you stick a pin in the hole of the security lock, pop off the keyboard. That gives you immediate access to the speakers, fan, motherboard and battery, which are now modules. There are no cables, adhesives, or other types of connectors. And if you put a pin in the hole under the screen, you can pop off the LCD and replace that too. Dell is not talking about releasing this though and it may never release this. It may stay in the concept stage. However, Dell says it is looking into automation techniques that scale a lot of the things it's learning by developing this concept to let it scavenge parts from used laptops and reuse them. They say like, we'd like to use a part as many as four times over its life. And yes, some parts have wear and tear and that doesn't make them useful for this, but there's a lot of parts that you can get a lot more life out of than the laptop they were originally in. It's also researching recycling parts that are no longer useful into materials for new devices. So when you get to the end of life of that part, you don't just throw it in the bin. You're actually melting it down, pulling out pieces, maybe getting some rare earth metals out of it, stuff like that. In other words, concept Luna is the hook to get people to talk about Dell's wider efforts to conserve materials and improve repairability across its lines. That includes things like using robots to do automated disassembly, automated part evaluation and reassembly to bring down the cost of doing this kind of reusability and recovery as much as possible. Dell has been doing some things like this. Let's bring in our producer, Roger Chang, who follows this sort of thing. First of all, you've got a good example of what Dell has done already that's out in the marketplace. And I want to get your thoughts when framework is doing well, should Dell just kind of go into this modular laptop? Yeah, so if you're not familiar, a lot of workstation laptops are built on a very common chassis and it's actually one quanta out of Taiwan that builds a majority of these. But if you look at a lot of the features on that notebook are swappable. So if you go to Dell's precision workstation line, you can actually go through and pick up a manual and you can remove and replace the keyboard. You can remove and replace the drives, the GPU in some cases, the screen, and it's all documented. Now it's designed for your I company's IT department to handle, it's not necessarily, I've never done this before, let me pull out my jeweler screwdriver and try it for the first time. But it is really flexible. I bought my data, used one of these, and I've managed to swap out the drive, I swapped out a bum track pad on it, and it works great. The thing I think, and what's fascinating is that framework is doing something that a lot of other companies have tried over the years without too much success. And that is to make a modular laptop that's successful enough for them to keep doing it as a business. Once in a while you'll see one or two, but they don't go very far because there isn't enough uptake. And I think framework's approach of putting that front and center appeals to those types of people who are very open to selecting those types of products. I think what Dell would need to do is to not just do one, but to support it. In other words, just don't have it as an afterthought.  One of the things that bug me about the precision work line is they don't actually make enough of the drives or whatever, like the swappable CD, DVD drives they used to make. They only made a limited set. So if you wanted to get a new one, you would have to go to eBay and find one from a used person. So they really need to support it like sincerely support it. And I think they also need to work with companies like framework and develop a common set of standards. So you could maybe buy a framework laptop and then fill it with Dell parts or the reverse have a Dell laptop and hey, I want to swap out my ports. I can use these framework parts as well. It makes it so much more appealing. Yeah, I think you're onto something there. Framework is probably a unicorn in a lot of ways. It's really hard to make this work and what framework has done is work really hard to make it work. They have provided quality parts. They have done the work to get it out there. They've done the work to get the press to get people on board and they've created a sustainable business. I think what Dell's looking at is like, yeah, that's not a great idea for a company as big as us who's trying to make a bigger profit. That seems like a lot of work but if we scaled it somehow across our entire line and that's where when you bring up the Dell precision and say, let's keep what we've got going with repairable enterprise laptops already and make that even more repairable then suddenly we're selling to businesses and the scale makes it worth all of the hard work. Exactly. So yeah, I like what you're throwing out there. I think phase two is like, okay, then maybe we talk about a standard that goes across different brands but that's kind of, you gotta have more than one successful brand for that to happen, obviously.  Get in touch with the DTNS audience at DTNS show on Twitter, at Daily Tech News show on TikTok and DTNS pics, DTNSPIX on Instagram. Five ad agency executives told DigiDay that Netflix is delivering about 80% of the audience that expected for its ad supported service. That means Netflix is having to grant refunds since it did not include make goods in their contracts. Most advertisers believe the service will continue to grow and suspect the shortfall is down to the rushed launch. Netflix's ad supported platform are available at a discount but it may want to consider an entry into the world of free. Indeed, friends, the fast world as seen in the high growth area of streaming TV. Would you say fast and free, E.S.? Yes, get in the fast lane, life in the fast lane. I live life 30 second spot at a time. Fast stands for free ad supported television. Examples, Pluto, Tubi, Roku channel, Free V, Zumo, Local Now. The thing that comes up on your Samsung TV or your Vizio TV.  The promise of fast is that it provides an easy familiar landing space for U.S. households that are cutting the cord. 6% of U.S. households are cutting the cord every year and that percentage is probably gonna rise. Fast services often include a cable TV like grid so that you've got a very familiar interface. Hundreds of channels, so you got lots to choose from. Familiar brands, even if it's not the actual channel that's on cable, it's stuff from that kind of channel. And the only cost to try out a fast service is your internet and watching ads. And it's bringing in money, baby. S&P global market intelligence estimates that the U.S. fast business will bring in around 4 billion this year and that should increase to almost 9 billion by 2026. Deloitte notes that all major subscription services will have cheaper ad supported tiers by the end of next year and about half of those will either have or roll out fast services. Yeah, so one example is Paramount Plus. You've got Showtime on the top end. You have Paramount Plus, which you can get with or without ads. And then there's Pluto, which is owned by the same company. Paramount's chief of streaming business development, Jeff Schultz, says to be a successful fast channel on something like Pluto. You need content that people know. They have to recognize it when they see it and want to watch it. And it should probably be episodic, like a procedural or a sitcom, something that you recognize and you can just drop in and start watching. For example, the CSI channel on Pluto became number one the day they added it to Pluto and it has stayed there ever since. Unlike so-called SVODs like Netflix, streaming video on demand that you have to pay for, you're not looking to avoid churn if you're doing a fast service. You're not looking to keep people from canceling a subscription because there's no subscription. You're looking for engagement. You want to keep them there. You want to get them in and keep them watching. So there's a lot of excitement around this, Justin, Robert Young. What do you think? Is this the future of TV on the internet? Well, to say it's the future would ignore the fact that it's the past too. On linear television, cable television, but also throughout many other services, including like Hulu, you know, Hulu for a very long time was a service that you could watch some stuff for free on. Here's my thought. I don't doubt that there is a ton of content that a lot of these stakeholders are willing to put on these services, name content like CSI, that they would also like to license out for various other streaming on demand services. And I do think that there's enough of a delineation you're not only from a customer base, but also from a proposal of, hey, watch this stuff ad free, that you can not damage your licensing of a valuable property by putting it on a fast service. I don't doubt that there is a customer base for this because subscription fatigue means that there's a lot of folks who just want to kill time and watch something that they know they're going to like to veg out to and don't want to necessarily have to pay for it. My thought here is not on those two, but the third element of this that needs to be there for it to work. And that is, are there display advertisers who want to spend the kind of money at scale that would make these truly revolutionary services? We have seen a decline in buyers for these kinds of ads in the past, specifically on linear television and on cable. Is this a place where people are just waiting for the platform to pour the money, turn the gigantic spigot back on? Is there a new class of advertisers that really want to do this? I don't know. And at this point, I am hesitant to say that that absolutely exists. Yeah, so you went right to the heart of this, which is the money, right? I think it's great at customer acquisition because it's free and Nick with a C was asking a pertinent question. It's both linear channels and on demand. So whichever one you want, all these services usually have at least the on demand part, but also a lot of them have the grid. So it's both. It's really easy to just start watching. I think the programming is pretty cheap because they're usually doing reruns of stuff. They're using back catalog of stuff. They need things with, this is syndication. This is replacing syndication of the old broadcast model, which is like, we need lots of episodes. We can't afford to do a lot of originals. Roku is doing some originals, but they're kind of doing them to get you to sample. And then the bulk of the programming is stuff that's cheap to carry and show you. So the cost is low. The question is, can you bring in enough of the money? The theory in the industry is that what, and this is what Netflix said when they just said, when they revealed why they got into ad supported versions of their service, there was so much money coming from cable television as subscriptions decline that didn't have a place to go on Meta and Alphabet or on Google specifically, Google and Facebook specifically, right? And that was video ads. And so these places are now gripping a windfall. There's money to be spent advertising on cable TV that now wants to be spent on the internet because that's where the people are. I think what you rightly point out is, sure, there's a lot of money coming over right now and it will keep coming over for a while. And so there's a windfall here, but cable had carrier fees. They were locked in and that was a big part of what made a channel successful was that you got that carrier fee. Even if you weren't ESPN, you got a carrier fee. There's no carrier fee in a fast service. So at what point do you reach that limit of growth where you don't want more users because you can't fill the ad inventory anymore? It's probably a few years down the road, but that is a fair question. Here's, I generally am a skeptic on them, but I will give you one ray of hope and something that is built in and baked into the proposition here to advertisers that Facebook and Google cannot match, which is at their biggest in their video ad division, which would be Facebook itself and YouTube, you cannot guarantee brand safety in the way that you can on a fast channel where you know that you are running against something that cleared standards and practices and it's not a random video, even if it's something syndicated from television or something like that. You know exactly what you are getting. You're not gonna accidentally show up to something that you are not into based on your brand. So I think that in that case, it is a safe place to advertise the likes of which that no user generated platform will ever be as safe as. Yeah, no, it's got a big advantage over something like YouTube in that respect. I think that's a fair point too. I do think that we're, I'm shifting where I used to think, oh, the future world will be a Disney Plus, a Peacock, a Paramount Plus, you know, there'll be three or four of those and they'll all have a fast service and a premium service like a Showtime or an HBO. I'm starting to shift my emphasis to like, I actually think, I think the fast services are going to be the interface. Those are going to be what the majority of people experience and it will be used to try to upsell you to one of those two other tiers and it won't be the entry point the way I was thinking. It will be the entry point instead of the premium services. I'm gonna press X to doubt on that. I think that your initial projection is more correct, but only time will tell. Indeed, all right, speaking of time, it's time for the mailbag. Indeed, Bodhi writes, I like Paul's idea of using AI to help users understand complicated terms of service. Even though this doesn't currently exist, I think we should start the process of branding this AI. Please consider terms of service as a service. I wanna say the acronym, but it seems fraught with peril to try to pronounce T-O-S-A-S out loud. So I don't know, Bodhi, we may need to workshop this. I like this though. I like this as a starting point. There's no bad ideas in frame starting. No, but I do think that it shows, one of the things that I really appreciate about what OpenAI has done with chat GPT is showing what natural language chat back and forth can be as an entry point. And I do think that if you look at a very complicated terms of service and you are immediately able to generate what people want to know, the most popular questions that were asked and then putting those answers in plain language with sourcing throughout the gigantic eulahs that people have to scroll a million pages down and then just click agree to anyway. I think that that is something that could be very valuable and I would not be shocked if in the next few years we see that just become a standard. I mean, we have had eulahizer was something that did this. There's click wrapped and tossback and there's some Chrome extensions out there, getterms.io, terms of service didn't read. These are all manually done. There's a little bit of automation, but I feel like we're halfway there. We have services that do this. So the question is, do people not use them more often because they don't know about them because they aren't as effective as they should be because they have to be done manually and maybe they lag behind a little. Or what I suspect is people say they care more than they actually care and they don't wanna install. And I think that that's probably the case as well. There's that in general as much as TOS situations are annoying and you are worried about a worst case scenario. We don't hear about them all that often and so therefore people just understand them to be a random thing they click yes on so they can get to their program. You know, I'm glad I randomly clicked yes on Justin Robert Young all those years ago and got to know him and bring him into my podcast. Here's the service. Justin, what have you got going on these days? Well, Tom, I got a program called We're Not Wrong. It stars myself, Jen Briney and Andrew Heaton. And on said program, we discussed this week the defection of Kirsten Sinema from the Democratic Party. We break down what a quality candidate is, especially in light of the midterms. And one of my favorite things is our male section, which we do a little bit differently compared to other shows. And mostly because I ruthlessly edit everybody's email. But there's one email this week for which I had to print the entire thing. Come, be a part of the story, the beginning, the dawning of the masked ombudsman on this week's edition of We're Not Wrong. Yeah, and a topic dear to my own heart there. You got to go check it out, folks. We're not wrong. I cannot wait for you to hear it. Thanks to our brand new boss, Brian, who just started backing us on Patreon. Thank you, Brian. You know what Brian gets? What's that? He gets rewarded for loyalty. Yeah, every three months you stay as a patron. At every level above the opening level, there's the production assistant level, which basically just gets rid of the ads. But if you're at any level above that, you get some extra perks, including every three months, we're just gonna send you a thank you gift. Might be a sticker or a mug or even a hoodie at one of the upper levels. And Brian, start the clock ticking on that. Thank you, Brian. Be like Brian if you aren't already at patreon.com slash DTNS. Patrons, stick around. The show goes on for you in good day internet. I have an update on my top hat. You can also catch the show live Monday through Friday, 4 p.m. Eastern 2100 UTC. Find out more at dailytechnewshow.com slash live. Back tomorrow, speaking of We're Not Wrong, talking about how to live as a digital nomad with congressional dishes, Jennifer Briney and Len Peralta will be here too. Talk to you then. This show is part of the Frog Pants Network. Get more at frogpants.com. Diamond Club hopes you have enjoyed this program.


million followers on Instagram.   They ain't doing it like me. Got the beats on, you know what I'm saying? Pow, what's up everybody? Once again, it's Ram and Shawn and we got to talk about the problem with Boonk and a problem that so many artists face. It's a true artist dilemma in this social media era. So let's touch on Boonk's rise real quick. For those of you who don't know or just, you know, don't know too much about Boonk, Boonk is a rapper right now, but he really became pretty damn famous for coming out with these pranks. And the thing is what he was doing wasn't completely abnormal.  He branded it after himself, his own name, and that really attached something to him. He made a movement out of it. I'm talking about, I'll be walking through the mall, little four year old kids talking about Boonk gang, Boonk gang.  It's a real thing. Boonk gang is synonymous with doing that type of stuff like catching a football is synonymous with Randy Moss. And people will say Moss or the younger generation will say Odell. Moss is definitely better. And it has to be noted that early on when he started to catch this traction and this awareness, so many people talking about him. I mean, even Blackie Speaks did a video on him. He said himself that he wanted to be a rapper. He was doing all this to get attention. There's a publicity stunt. So now that I got, now that I got up there, now I'm trying to get my music back in. On one side, I know a lot of people are like, yo, this dude has millions of followers from it and all that kind of stuff. That's great. That's amazing. But there's one problem when it comes to that. And that's the fact that he did it so well that as a rapper, he's having a hard time getting real traction and overshadowing what he already did on this side of the world. Because that's the key to switching lanes. And a lot of artists, I've talked to artists or seen artists who are trying to go from comedian to rapper or they're trying to go from personality to rapper or a cover artist to singer, whatever it is. It's hard to do that switch when you did something so well at a high level. And now when you try to do something else, they can't see you in that role yet. It's like when you see movie characters or TV characters that just they didn't do it so well that you're like, I'm seeing you in this other role, but I'm still thinking about this other person. That's all it is. But it can be done. Look at Cardi B. Cardi B was stripper girl. She overcame that with becoming IG personality girl. So then she was IG personality stripper girl. And then she was on love and hip hop. This is all in the mix. She was coming out with music and the music was not hitting until she came out with bodac yellow, which was pretty much undeniable. Once she had that, it overshadowed any other level of greatness that she had touched on before. And this leads to the solution for so many artists that are going through this issue or comedians or whatever you're doing and trying to switch lanes to. Remember, you're doing one thing here. And if you do something very well and you get attention and you get known for that thing, the solution is number one, creating something in the other lane that's better quality than what you were already doing, but also getting the awareness out for that other thing. So you need products and you need distribution. It all comes back to the same thing. If I'm a rapper, but I want to become a comedian all of a sudden, but I have like a hit album, I need to come out with a comedy special that's so drop dead funny and get so many people to see it and find out about it that they have no choice, but to now they can meet as that or say he does this just as well or even better than that other thing. So they'll have no problem accepting you in that new role. That's an artist dilemma. And that's what Boonk is going through right now, because his music is not anywhere near of the part to the movement he created with Boonk gang. It just isn't. I know he gets quite a lot of views on his videos because he's posted on World Star constantly, but at the end of the day, his quality of music just is not there. Once again, especially in comparison to the damn near legendary thing he did with the Boonk gang situation. Take those things in and remember that as an artist, it's not necessarily being locked in a lane. It's just only about you being able to produce something that's better than what you did before in the other lane. Other than that, I would love to know you guys thoughts as always. Don't forget if you're at a stage where you're really focused on building your music brand and you want to create a foundation and understand the strategies to use to level up and have some leverage, you can look into the link in the description below at the Master Music Branding Guide. Other than that, if you liked this video, go ahead and like button. If you like it, might as well share it and if you're not subscribed, you know what to do. Hit that subscribe button.


Let's sing a song you don't hear every day It's your old friend calling again Hello, sweetheart, it's smiling Ed Mcconnelly, a Latin lamp man again Have you heard this one lately?  Well, down at our store we've got a whole lot of new and unusual things to show you Which reminds me of one of the most unusual and exciting things I've ever seen for the home Lamps with lighted bases Yes sir, Aladdin lamps with lighted bases These cleverly designed lamps have bases made of alicite A material developed by Aladdin engineers That permits the use of a small bulb in the base of the lamp The Aladdin alicite base gives a soft mellow light That accounts for the fine light those lamps provide Yes sir, Aladdin lamps with lighted bases Topped by lovely Aladdin Whipple light shades Will add something a little unusual to your room Now you see them at our store soon, will you? And now for our him There's within my heart a melody Jesus whispers sweet hand alone Fear not, I am with thee Peace be still In all of life's end and flow Jesus, Jesus Sweetest name keeps me singing That's all for today, honey This is smiling Ed Mcconnelly, Aladdin lamp man Saying bushels of love And thanks for listening Be with us next time, cause you know we'll be back To sing a song You don't hear every day When we all come calling again


Hello everybody and welcome to another product review video. This is gonna be the first of these shorter series of product reviews I'm going to do Hopefully you'll see more of these over the coming months. I'll try to slot these in where I can for cool stuff I like Today we're gonna be talking about the exemplar wet palette my favorite wet palette. So let's head over the desk and take a look The strict techno man sir that is Vinci V. Let us get to the technique and learn it Vinci V So here we are we've got the exemplar wet palette It's a really nice construction. So overall, I'll just tell you straight up front I quite like this wet palette a lot I think it's one of the better investments you can make if you're gonna get a wet palette It's one I would say to pick up, but let's talk features and benefits and stuff like that The wet palette itself is quite sturdy. It's well made. You can completely lock the thing so it can pick up without issue We need to actually close it and lock it. There we go You know the whole thing. I don't know how much cause there would ever be to actually do that But you can do it just in case you would need to The wet palette itself Really does lock has this little guy on top Wearing you can it has a little dry palette you can put brushes and stuff in there Which is actually rather handy. That is a nice way to transport stuff. So I've used that many times This also does pop out by the way So you can actually transport more stuff or use your dry palette somewhere else you would want to There's even a little spot here where you can put your cell phone again I have not a feature I've used very often, but you can rest your cell phone right there. So hey fun stuff What I like is it has this little Situation up here that you can control how much airflow is getting in and out so you can control the humidity There is a little Thing you can pop in there to close it off completely if you want or have one open or as I do have both open I'm in a very dry environment And so I need to make sure that it actually stays hydrated and doesn't get overly humid inside there The wet palette itself the paper is really nice. I like the way it hydrates the paint The nature of the sponges is such that you can actually double stack The sponges so for example, I have two sponges in here right now So you can see there we go And the reason for that is because again my environment is very dry And so as a result I have two sponges and a lot more standing water inside If you only have one sponge, it's it's lower in there And then you don't have to have as much water creating less humidity of an environment when you actually close the palette And making it so you have to sort of refill the water less I have to refill the water quite a bit. So the palette itself is good. It's durable. It's quality I like the paper that actually matters quite a bit to me. There's nothing wrong with Reynolds Sort of paper and using non wax paper for it, but this actually hydrates really well It seems to let out more or less exactly the right amount of liquid up into the paint The exemplar wet palette is basically 35 dollars To order it from game envy directly, which I think is a pretty reasonable cost for the quality of the product the refill packs which come with additional new sponges and 50 sheets of the paper are 12 bucks. So again, nothing that's gonna break the bank. They're too bad Now do you need this wet palette? No, of course not It's not going to change your life in any significant way. It is still a wet palette and does the same thing as you know, most other wet palettes on the market that is to say if you've got your master's sending you like it or you made something out of You know sponges and some ziploc containers. Hey, no problem It's not like there's something here that is so revolutionary. It's just completely changing the way you paint But if you are in the market for a good durable quality wet palette made of good materials that will last you That has nice features This is it. I mean, I once I got the exemplar. I honestly haven't used anything else and have no desire to use anything else This is more or less everything I want. It sits there. My paint will stay workable Again, it depends on the you know individual paint some are more hydrophilic than others And so we'll kind of get worthless when I paint stays workable certainly all day You know, I'll be sitting here painting for 10 12 16 18 hours And I my paint stays completely workable where I'd want it even in a very dry environment So good paper good One thing about the sponges is they are anti microbial So I've never had any problem with mold and if there's anything that would make you upgrade to a nicer wet palette over Something like a traditional Masterson. It's the quality of the sponge here. The sponges are really nice Never had any problem with in any way. It's smelling funky or anything growing in there or anything gross like that It just works and keeps all the bad stuff out Which I very much appreciate because I don't want a stinky wet palette Nobody does So there you go. That's the exemplar all in all pretty straightforward Like I said 35 bucks for the wet palette. I'll include the link down below. This isn't sponsored or anything This is just my palette that I own So, you know, they didn't give it to me for free or anything like that I have used this more hours than I can count over the past many months And I think it's a worthwhile purchase. So if you're looking for a new wet palette, hey, check it out. There you go So there you go, that's the wet palette overall, I give it a solid a rating totally worth a buy If you're looking for a new wet palette, so I hope you enjoy as always don't forget to hit like Subscribe for additional videos. We have new hobby cheats here every Saturday Product reviews will be intermittent as they can There's a patreon down below if you want to support the channel and take your next step on your hobby journey But as always, I thank you for watching this one and we'll see you next time


The title of my talk, Experimental Quantum Computing at IBM, it's a very generic title, but what I wanted to talk about is the types of devices that we have and we use at IBM and focus on what type of controls that we use to implement quantum gates and also the different methods that we use to characterize and mainly to understand our quantum system and that would help us improve our devices and move forward in terms of trying to use this as a good quantum computer. So, you know quantum computing technologies, there are many types of quantum computing technologies and you could ask question, what's your favorite qubit and some might answer ions, photons, nanowires, solid state defects, neutral atoms, but at IBM we like superconducting circuits. So in this talk I'm going to focus on this superconducting circuits and a very brief outline as I said I want to, the main part of this talk is going to be understanding our quantum system and discuss different things and I know there's the topic of this workshop is quantum application, near-term applications or approximate quantum computing. So briefly I will talk about what can we do with noisy quantum system, which is I'm just going to talk briefly on our recent results on quantum chemistry. So, from a very basic the type of qubits that we have is a single junction transplant qubits. We have, doesn't show much. So here we have our drossosome junction, just a layer of aluminum, aluminum oxide, aluminum and the drossosome junction is nonlinear inductor, which is for a transplant qubit is shunted by a large capacitor. So rather than having a harmonic oscillator, you can make this unharmonic oscillator so that the lowest two energy level is a little separated from the higher levels and we're going to use the lowest two energy level as our qubits. So here is our qubit and what does it happen when you couple this to a resonator. A resonator is just a regular LC circuit and here's the Hamiltonian of the interaction between the qubits and the resonator and then the dispersive limit where the qubit frequency is well-detuned from the cavity frequency. The cavity frequency depends on the state of the qubit. So that is how we are going to read out the state of the qubit. Here's a sample of a two qubit device, two transplant qubits coupled by a coupling cavity which I'll call a bus. And each qubit has this readout cavity. And depending on the state of this qubit, when you put a tone, a microwave tone in this cavity, sweep the frequency, you'll see a state-dependent resonance. So this is how we are going to probe the state of the qubit. And typically we would have an amplifier attached to the readout resonator and we could do a high-fidelity readout. Here's a histogram of the ground state and the excited state of the qubit. And you could see that the states are very well separated and you could get a readout fidelity from that. So in terms of readout, so currently we have a fairly high-fidelity readout using some type of quantum limited amplifier such as JPCs, Tupas. But right now we have a fairly slow readout and cavity emptying. That is due to the design that we have. We have a relatively small chi and kappa. We also have a fairly slow initialization because we're not doing any active reset. And this is also without active reset, so for active reset we actually need to do, you have to read out and you have to determine the state very fast. So I placed this latency budget with this small kappa and small chi. We need at least three microseconds, usually more. And this latency budget, what I mean is that from the time you start the measurement until the cavity is emptied. So within this latency budget right after this you could run some other qubit gates. But this doesn't mean, well, and then I'll just discuss what's in progress and what we're working on. What we like to have is fast readout and also fast reset. So with that using FPGA we could do fast readout and cavity emptying just by designing, just by engineering, just changing the kappa and chi's. And you could also do fast initialization by doing active reset. And here, a two latency budget, depending on how we designed the kappa and chi, we could have this latency budget to be less than one microsecond, or with the higher chi we could actually reach this 500 nanosecond. And using FPGA this latency budget actually would include at the time it takes to determine the signal. So you could do an active reset right after this 500 nanosecond and then we start a new experiment. So this is something that we're working on. And now on coherence and scaling. So throughout many years, over the years we have been superconducting qubits, we have made tremendous improvement in coherence time. And now we're reaching over 100 microsecond using a 10 to 100 nanosecond gate times. So it's very important to note not just the coherence time, but to understand that we need fast gates. Having 100 microsecond gate coherence with microseconds and tens of microseconds of gate is not going to do much. And this is also an active area of research where we're studying some materials or other things to try to improve coherence. So in terms of scaling, here are different devices that we've had at IBM, starting from the two qubit device that I showed you earlier, 3, 4, 5. This is one of the quantum experience device, the 7, 8, and then the 16 qubit 22 buses. That's the newer quantum experience device, IBM QX5 that we have now. And we have also announced our commercial program, the 20 qubit and 50 qubit device with these connectivities. So we're always, along with improving coherence, we're improving, we're increasing the number of qubits. And what are the other things that we're working on? So quantum gates. So this again is going to go back to basic. How do we control the qubit state? So for single qubit, you want to bring qubit on this box sphere. And how we do it is by putting this microwave tone through this readout resonator. Our typical qubit frequencies are around 5 gigahertz. And by putting this tone, you could rotate the qubit, you could derive the oscillation. And by pulse shaping, you could prepare like an X gate or a Y gate. And you could calibrate that well.  Okay. So here I'm showing two different phases. So as I said, depending on the pulse shape that you make, you could rotate the qubit, you know, 90 degrees. And then just by changing the phase, you could do a Y 90 operation. So this is the same calibration method you use, calibrate X 90 gate. And just by having an extra phase or an angle changing the angle, you could apply a Y 90 gate. So how about Z gate? Z gate is a little bit different. And you could look at Dave Mackay's paper. It's a special gate where it's just done in software. So as I said, going from X 90 to Y 90 is just the change in the angle. So for phase gate, the way we implement the gate, you could do this in software. So it's kind of a virtual Z gate. So this gate for our system doesn't cost any time. So you could think of it as a free gate that you could apply. These were single qubit gates. How about two qubit gates? In superconducting qubits, there are different types of two qubit gates that you could use. Here's some lists. But for this talk, I'm going to focus on the first one, cross resonance gate. It's a CR gate. And the pro is that you could use fixed frequency qubits and it has fairly long coherence. But the cross resonance gate work well within certain frequency range. So that could be difficult. Now unless we have qubits where the cross resonance gate is an all microwave entangling gate. So as I said, you could use this fixed frequency qubits. And two qubits are coupled with this static, there's a static J coupling through this bus that hybridizes the qubit levels. And so here's qubit one, qubit two. By driving the first qubit, the control qubit, at the frequency of the second qubit, qubit two tone, you could drive this ZX term. So that it only drives the second qubit depending on the state of the control. So this ZX that you get from this cross resonance gate, that is the gate that we use to make a CNOT gate. So back in 2011, there was the first experimental demonstration using this cross resonance gate. And back then there was only, you know, you use this single cross resonance gate. And the fidelity of the gate was in the order of 81%. But over time, we've implemented echo sequence and more recently have done an active cancellation. The same echoing sequence with the active cancellation to cancel out extra terms in the Hamiltonian. So the cross resonance gate has the ZX term, but there are other terms that we don't want when we're making a CNOT gate. So with that, we have reached 99.1 gate fidelity looking at the interleaved randomized benchmarking. So here up to here is single qubit and two qubit, and what are the other multi qubit characterizations that you could do? So with two qubit, the typical experiments that we run, because we have this always-on coupling with this bus, we typically look at ZZ coupling, the static ZZ that exists. So the type that we run, the experiment that we run, we call it the joint amplification of ZZ, the jazz. And we run two different experiments. So the first qubit, this is the qubit that you're going to be measuring. You bring it to, you apply a pi over two, and you do an echo, the pi, and then another pi over two in a different angle. So it's not too important here what we're doing here, but the difference is that for the first experiment, we have the second qubit in excited state, and the other experiment, you run it without this pi. And then you're going to compare the frequency difference that you observe on the first qubit. By comparing this frequency, you obtain that for this sample, for this two qubit, we had a 300 kilohertz static ZZ. So you could run this ZZ experiment, the jazz experiment, on a multi qubit system. This is from an IBM QX1 device. It was the first IBM Q experience device that we had, and here's a table of ZZ between all the pairs. And these epsilons are just, if the ZZs are fairly small, which makes sense. With the D1 and D3, it's not on the same bus, so there's a negligible ZZ coupling. So as you see from this table, D1 and S1 has the highest ZZ, just about 90 kilohertz. So when you characterize the qubits, you could get the frequencies, and then to characterize the gates, you could run randomized benchmarking. So typical experiments that we do to verify the gates are running individual randomized benchmarking.  And you could also run simultaneous randomized benchmarking. That is, you run, proliferate randomized benchmarking on these single qubits all at the same time. And what I want to show is, comparing this row and this row, the largest change that you see in the error are on D1 and S1. So this randomized benchmarking result is capturing this ZZ, the high ZZ that I have between the pair. This is one method of looking at crosstalk on a multi qubit system. So what are other things that we could look for? So when I run this 422 code experiment, this looking for error wasn't the point of this experiment, but, nonetheless I was running, looking at the 422 code just to briefly go over what this is, is the 422 code is a four qubit code. There's two logical qubits, logical state that you could encode, L1 and L2. And the idea is that L1, one of those two qubits, two logical qubits, could be prepared full-torrently, but the other one is not. So, for example, the logical 00 state, the little P, that's the protected qubit, and then the other one is the gauge qubit. So the protected qubit, this is the one that you could prepare full-torrently. And these are the two stabilizers, and you could define all these logical, a bit flip, and phase flip for each of the logical states. So the experiments that we run was to first prepare a logical plus-plus state. That is by running the X stabilizers, and then preparing the state by measurement. So I start with the syndrome qubit at the excited state, and then at the end I only post-select when the syndrome is at one, and this would prepare this plus-plus state. So once you prepare by measurement, you could do a post-rotation to run state tomography, measure the rest of the four qubit, and make a reconstructed states. So typically for reconstructed states, you'll use a computational basis, but to look at these logical qubits, we're going to define a new basis where the first two strings are going to be the logical states. And then the third and the fourth are syndrome bits, which one of them detects the phase error, and the other one detects the bit flip error. So these syndrome bits could be flipped by using these destabilizers, and these change the stabilizer values without changing logical observables. So looking here, so you could start from, say, a zero-zero or a plus-plus state, and here I'm writing a perfect zero-zero, the SZ and SX is zero-zero. So this is the proper logical plus-plus state, and by applying either a phase flip on the logical one or applying destabilizer, you could change these bits.  And just to note that I'm going to define the acceptance probability, which means the probability that the state is in this encoded state as probability of SZ and SX being one. Sorry, being zero-zero. So here's the result when you use that C0 gate that I had from the five qubit device. And here, corner on the yellow corner, this is the qubit sets in the logical space. And when you actually look at the acceptance probability, it's very low. It's only, it's less than 30%. So clearly there are a lot of states that is outside in this code space. And so from this, you could see that the code is very sensitive to certain errors. So when I was looking at these two qubit gate and run around as benchmarking, each individually, these two qubit gates had a decent gate fidelity. So I didn't assume to get this bad of acceptance probability. So what is the type of error that we have? So I talked about cross resonance gate a little bit earlier. And this ZX, so this is the drive Hamiltonian, the CR drive Hamiltonian. And this ZX term, this is the one that you want to make the C0 gate. And so this is the terms between this control and target qubit. And when you apply this echoed cross resonance gate, what you're doing is you're cancelling out all these terms, except for, except for Iz in this line. But when you consider not just this two qubit, but other qubits that's coupled to this pair, say D2, 3 and 4, which I'll call them spectator qubits. And when you actually consider other Z terms that's associated with it. This echoed cross resonance gate only cancel these terms out and there are several other Z terms that's left. So how do we get rid of that? So you could do some other echoing scheme where you could divide it up to four cross resonance gate and do a four CR pulse C0 gate. So by doing, by splitting these gates, you could cancel all these other Z errors. So here, so there are four pairs of CR and all the CR, the C0 gates were less than 0.02, 2.5% error. And for the four pulse CR, the error per gate was a little higher. That's mainly due to the gate being a little bit longer and also having more pulses. Nonetheless, when you actually run the same experiment trying to make this logical state, the 422 code state. So here's the previous result using the two pulse CR and this is with the four pulse CR. So now as you see, most of the states are in this accepted state that it's 79% acceptance probability. And then, so you could see and all the errors that we had previously is gone. So by running this state tomography of this 422 code, we noticed that there was some sort of error. It didn't tell us what exactly, except for that it was a bit flip, but in plus plus states, so it's more of a phase flip. And then we were able to come up with a different scheme of gates so that we get rid of this error. But this is not a very convenient way of figuring out that there's an error on your multi-cupid system. And the state tomography does take a long time. It's compared to methods like randomized benchmarking, which doesn't take a lot of time. It's fairly easy. So what are some other methods that we could use to understand our gates? So some of the verification toolbox that we have discussed are the randomized benchmarking. So we have the standard RB, interleaved RB. I didn't talk about purity and leakage, but these are all kind of standard randomized benchmarking that you could run on single qubit. And for multi-cupid, so you could run the standard and qubit RB. So I've done the two qubit RB, but you could think about doing a three qubit RB. And the simultaneous one qubit RB, this was done on this device where we saw some ZZ errors. But also, instead of just running this two qubit RB and a single qubit simultaneous RB, you could run this simultaneously to see what other errors that you might see that there is an error. So here is a picture of our IBM QX, the five qubit device. And so these are the typical numbers that you would get on our quantum experience website, the T1, T2s, and the single qubit air per gate, two qubit air per gate. And also we have this ZZ information on our spec sheet, which you could get it from our Qiskit or our GitHub. Okay, so now this two qubit RB, this is the number that we provide. But let's start looking at some other things like simultaneous two qubit with single qubit RB on our current IBM QX4 device. So one of the pairs, C0 to 0. Here's the number that you get from a two qubit experiment, two qubit RB experiment. We get about 2.4 air per gate. And when you actually include this other spectator qubit and run two qubit and single qubit RB, actually for this gate, it doesn't change much. And this is showing that there's not a lot of crosstalk, which is good. So let's look at another pair, CR34, so CX34. So again, the air per gate is less than 3%. But once you add this central qubit, now the air per gate is above 7%. So just by doing this simultaneous two qubit and one qubit, we clearly see that there is some sort of crosstalk and we see this air. So now you could use, this is a fast method to see that there is some type of crosstalk. And now we could try to think about how we could correct for this. So just to kind of see, this is some new experiments that we're running. There will be a new manuscript by Dave Makai soon on Archive, I hope. So some three qubit RB could be another way of seeing some multi qubit crosstalks. So it's just a standard three qubit RB. And depending on the connectivity, so you see, so usually we don't have a three qubit entangling gate, we would have a two qubit entangling gate. But if they're fully connected, you would to create one three qubit Clifford, you need about three and a half C knots. And if it doesn't have a full connectivity, it requires more C knots. So clearly you would be able to run it better when you have a better connectivity. So here's some results from IBM QX4. So here's the three qubit benchmark RB. And I'm putting down the two qubit RB results just by looking at the two qubit individually and then by looking at two qubit and one qubit. So again, so this gate doesn't change much and none of these really made a lot of difference. And the number we get from the three qubit air per Clifford is sort of in the order that we would expect from this two qubit gate. So with the same pairs, but with limited connectivity, so that I took out one of the gate, one of the C knot. Now you're using a lot more C knot gates per three qubit Clifford. Now the three qubit air per Clifford is a little higher. But again, by knowing how many C knots and these airs, the air per Clifford matches fairly well to what we would expect. So here's probably what you might want to see, our new 20 qubit device. So here there are 20 qubits with all the couplings. It's showing the T1, T2s and the C knot gate between the pairs that are coupled. And as you see, it's the, you know, we have decent T1 and T2s for all the qubits. And this is very different from, you know, the type of device that we have from the quantum experience, five qubit and 16 qubit, mainly on, in terms of the first devices that we're showing where, you know, it's not, it doesn't, you could control some qubits that are not on the edge of the sample. So, you know, these are just the numbers that we would typically put on the similar number as what we would put on in the quantum experience. And on this device as well, we've run a three qubit RB. And again, so for this one that didn't run the simultaneous two qubit and one qubit, but using the two qubit RB from the, from the mapping, the previous mapping, you get, from these numbers, it should be, the error per cliffer might be, should be a little lower. But probably by looking at the two qubit and single qubit RB, you probably could be able to see a fairly appropriate number for the three qubit error per cliffer. And again, same, same pairs, but with different, with the different connectivity, and you see that the error per cliffer goes up. So, now, so all that together, I'd like to discuss a little bit about quantum volume. So quantum volume is something that, at IBM, we've been talking about, started talking in terms of what type of metrics that we could use to describe what, how good our quantum processors are. So as we increase the number of qubits, you know, more number of qubits is good. But if you don't decrease the error rate, it doesn't do much for us. Right? So you want more qubits, but less error. And from the three qubit RB as well, you see that more connectivity that you have, you could run more things. So the more connectivity is better. And also gate sets. So right now we have, you know, just a C not gate for an entangling gate, but if you have some other gates that would help you in terms of creating some algorithms. So to quantify this, trying to quantify this quantum volume, you could think of the number of qubits as a width, and some depth D to think about this circuit over some gate set. And the total space time volume circuit V is this number of qubit times the depth. And this is limited by the effective error rate. So what we want to come up with is a number where it actually kind of describes how good this device is. And so we want to come up with the largest square here. So we're going to define quantum volume as two to the minimum of either the number of qubits or depth.  But just with two qubit, even if you do run more and more depth, you know, you could easily simulate two qubit system. What we want is that good low error, two qubit error rate, and also the depth. So the modal algorithm that we are going to use is, so this, this is just a random two qubit gate unitary, the SU4 gate. Choose from some SU4 gate, SU4 gate, you choose, you permutate these qubits and you choose another random two pairs from the set of qubits. And how we're going to define in, of a unit of depth is just operation of unit, two qubit unitary on a pair of qubit. So we're going to assume that that circuit is, we could, we could simulate this circuit. And so we're going to have this ideal output probability and then we're also going to have this experimental probability, output probability distribution. And you could consider two different metrics. One is how far away these ideal and experimental states are. It's L1. And then you could also think about probability of heavy output, which is described in this Aaronson and Chen paper. I won't explain it here. So just, just an example, this was a data taken on our old quantum experience device, IBM QX2 device. But, so here's a simulation with depth one. So that requires, so this is on five qubits. But with, for depth one, you only requires, for this example, you required 16 knots. And then this is the experimental results.  But with depth four, and you know, this is taking, this is requiring now 39 knots. Now the output distribution is fairly random now. So when you plot this out, the number of qubits, you look at different number of qubits on the same device. And then you run this, this modal algorithm many times on different, different depth. And you could plot out the probability of heavy output. And we kind of just could define, you know, success at, as say two-third, if you have the probability of heavy output as greater than 0.6. And if you define it this way, we get a quantum volume of eight.  So similarly, you could run it for the 16 qubit device. And here you could run it on three qubit, four qubit, five qubit, and even long more. But again, you don't reach, you don't reach any improvement in terms of depth. So for the IBM five qubit and 16 qubit device, even though we have the more numbers of qubit on the 16 qubit, we have equal quantum volume, which now we have it as eight. So here, you know, when we went from five qubit to 16 qubit, we didn't really improve too much in terms of the gate air. So, you know, this is shown from this quantum volume metric. So to finish up the first part of the talk, or most part of the talk, we talked about the qubits that we have and some characterization methods. And so we're always working on improving coherence, gate fidelity and readout as we scale up. So that's what we need. And we have defined a metric quantum volume to kind of start using to understand that how well we're doing, how well we're improving on all these aspects of the device. So just very, very quickly, and I think most of the people in the audience probably know this experiment well. But the quantum chemistry with noisy superconducting qubits, I could probably skip the motivation. And the idea is to find the minimum energy of this electronic structure problem. And that could help you to find the reaction pathways, reaction rates and molecular geometry. So, again, so the type of experiments that we want to run, we run was this hybrid quantum classical approach. Some references here. So we would map the problem, the electronic structure problem to qubit Pauli's. And I think, I'm not sure if Sergey is here now, but you could ask Sergey all about this method that we use to lessen the number of qubits required to run this. Later if you want. And then we prepare at some trial state using the hardware efficient way. And then you do a partial state tomography to obtain the energies and you feed it to the classical computer. And then from that, using a classical optimization, you come up with the different parameters and you run the experiment over and over to minimize the energy. So the hardware efficient trial state preparation uses some SU2 gate, which we could use using the single qubit rotation with some face gate. And here this is the U entangling gate. So this could be any entangling gate that you could have in a device. So this is the hardware efficient part. For the paper, what we did was not actually use like a C knot gate, a calibrated gate, but we just turn on the CR tone. The CR tone, as I discussed earlier, has this DX terms and there are some other terms as well. But for this entangling part, it's okay to have some coherent, if it's a coherent operation, it's fine. So you don't want to run something you don't understand, but just by applying some CR gate, you're applying some sort of entangling gate. And with 3D plus 2N variational parameters, you could make these trial states. And also this depth, that's the number of entangling gate that you apply. You could set that by depending on the amount of coherence that you have. So just quickly, for the hydrogen, I'm showing the two different, placed with the two different interatomic distance at equilibrium and dissociation. So depending on that distance, you would have a different Hamiltonian. And these are the terms, the poly terms that you want to calculate. So we have five poly terms for the hydrogen. And out of these five, we usually would put them together and only run a few experiments, the partial state tomography. So for these five poly terms, we only had to measure two different states to get those numbers. For lithium hydride, we use four qubits, 100 poly terms. So it goes up quite a bit. But again, you could put them into sets of 25 and then even more for the six qubit bellerium hydride simulation. You're 165 poly terms, but you could kind of group them into 44 sets. So this sort of came up yesterday as well. But so this dotted line on this graph, this plot is the actual energy. The black dots are the experimental results with these density plots is from the numerical simulation using what we understand about the device. So these are some things that we know about the device. So what brings this error is the coherence, sampling errors, limited iteration, accuracy of the classical optimizer, and also insufficient depth. So this kink is due to not having enough depth. So all these experiments were done with the depth one. So now it's just the conclusion. So I want to point out three points from our quantum chemistry paper.  And then also this hardware efficient trial state preparation. So this is very flexible to other hardware problem platforms. And also we use this fast and classical optimizer that is robust to stochastic errors. And the point was that we understand we get the energy that we got is not, you know, at the accurate level, but it's very we could be understood it by running this numerical simulation. And by understanding this experiment, you know, there is is promising in the path forward with error mitigation method, or you could see Kristen's paper and he's sitting somewhere on here so you could ask him about that. And just to wrap it up. So what we do, what do we want to run this better? So we want to increase sampling that would improve the energy estimate and that will require some reset. So I talked about doing some fast read out fast reset. So that's that what we're working on that is going to help us with being able to take more samples and increase coherence that will let you do more depth. Have more depth in the circuits. And along with that, if you have more connectivity, you actually would require less depth. So that's also what we want. So at the end, we want to work towards larger quantum volume, which should improve in all aspects of our experiment. Thanks. Thanks, Micah, for a fascinating talk. We have time for one or two quick questions. Hi. So in the hardware efficient mapping and very simple approach that you're doing, I'm worried that, I mean, it looks to me like you're doing sort of a random circuit. And then because you have these gates with sort of random parameters, and then you measure something and then you're going to try to optimize those parameters to converge to what you want. But I think that, you know, when you do that and you measure pretty much whatever you measure, you're going to concentrate exponentially into the average value over the Hilbert space. I think you will have to take exponential number of measurements to them find better values for the parameters. I may bring over that. Sorry, this is for the hardware efficient mapping hardware efficient, you know, optimization that you're doing of the parameters for chemistry. So for this experiment, we fixed the amount of time that we applied across the resonance gate, which we know how much zx we had, how much, you know, ix or other terms that we had. So we use that number as a model and run numerical simulation. And so this parameter, the length of the CR or the angle of the CR, this also could be parameterized. So right now the n plus two times, I'm sorry, three plus two times n parameters that we run over, those were just for single qubit rotations. And we didn't actually change the entangling part, but that is the parameter that we could easily add into. I don't know if that. No, no, not at all. I mean, so the parameters, you know, it's okay, it's not a big number of parameters. I'm worried that when you try to measure to then get, you know, whatever observable to optimize whatever you're doing, in this case, you know, getting closer to the ground in the state of a molecule.  And then you're going to take an exponential number of measurements to be able to, you know, do a gradient descent or whatever you want to do to move the parameters to a better setting. I know not to worry about the number of parameters. It's the number of measurements to get the signal. The number of...  And then I guess if you want to scale up, we're going to go with the mixture between the C-onsets and the hydrogenation. So if you just follow up, we'll be able to do that. That's fine. It's the sign. Okay, other questions? Yeah. On the final molecule, I think it's brilliant hydride. When you show the results of the simulation of the model, there's a second curve that appears above the ground state curve. And so I was wondering, is that the classical optimizer in conjunction with the noise model finding another local minimum in the result? Yeah. Oh, for this. Yeah, yes. Yeah, no, for the other one with the two different results. Other questions or comments? I just want to ask, you did a lot of characterization and verification. And as we heard yesterday in Shelby's talk, theorists like to come up with, as she put it, all these sexy machine learning algorithms that experimentalists don't really want to touch. And I was wondering, as your systems getting bigger and bigger, have you ever tried machine learning to perform some of those tasks? Or have you ever started to think about that? I mean, we haven't implemented or machine learning, but I think there's a direction that we all need to think about in terms of characterizing multi-cubit. Last question, Nathan. All right. So those fancy machine learning methods are pretty cool for the record. But anyways, the question I have is for the 20-cubit system that you were looking at, did you consider changing the effective number of qubits in order to try to optimize the quantum volume? Because you don't necessarily get the best quantum volume by turning on all the qubits. So is that the way you want to go forward? Or should you always just give the quantum volume for the entire chip? Oh, the quantum volume question, there's a Lev or Andrew in the audience. Andrew or Lev? Could I just maybe ask, like, why optimize the quantum volume? I mean, I'm not saying it's poorly motivated. I'm just saying it's clearly a, what's the word I'm looking for, a proxy. So why optimize the proxy when you know for a fact that it's a proxy? All right. So anyone else want to say something? But for quantum volume, this is not the metric that we're thinking, the way that we describe as the only thing that we need to think care about. But we want to come up with a simple metric that we could, you know, study over different types of devices that we could easily implement to kind of have to be able to compare. So, you know, there might be other methods. Okay. If there are no more questions, let's thank all the speakers from the afternoon session.