Yes, hi everyone. My name is José Luis Millán. I'm coming here today to talk to you about ESIP, the SIPESTAC library. Well, I'm currently based in Berlin. I'm working for a company called Fraffos where we build SIP and media server which is actually in SDC and it also has WebRTC capabilities. ESIP is SIPESTAC. It's also an old ESIP library. Even though you can also find Debian packages and Bauer packages as well. I have seen before the Debian package maintainer here, David Pocock. And one huge feature for me is that it's fully documented. You can find the documentation in the website. Can you speak a little bit louder? Yes, sure, okay. So what's the motivation behind ESIP? There was a trigger in time which was the WebSocket Transport. When WebSocket Transport came to the playground, we saw a huge opportunity to make browser SIP devices. In such a way that these devices should be not only soft phones like not hardware would be needed, but so simple to use and to upgrade as well as reloading a website. So by making a JavaScript library, not only you can have SIP stack and make a new SIP in your browser, but you can upgrade to the new version by just upgrading the website. You download again the JavaScript file and you've got the new version of the ESIP. So it was also a nice excuse to learn SIP and JavaScript more deeply and I really think we were in the right moment at the right place when WebSocket was starting becoming a standard. Looking back, we started in 2011. That's where the development started and then that year we could already be able to make a SIP call from browser to browser or from browser to a legacy UDP or TCP SIP device. Of course, not with media because WebRTC was not yet already. So we started also writing draft to make WebSocket a standard transport for SIP. In that same year WebSocket became a standard. So everything was clear. I mean, once we were able to have WebSocket as a standard transport for SIP, then the image was perfect. We could perfectly see that. It would be easier once the standard WebSocket protocol, then current voice over IP servers could connect and create a new transport in order to be able to communicate these two words, the web and the SIP word. Then 2011, the first SIP call with media thanks to WebRTC and in 2014 the SIP over WebSocket became a standard. So there was no excuse anymore for SIP server vendors to implement the transport. There's a list of implemented RFCs. There are many, many more in the SIP ground, but I think these are no more nor less just those that we needed at that time and indeed right now. The API. Well, there were several points that were quite clear. We wanted to provide an API easy to use that could abstract the user from SIP internals. We were really aware about the fact that users making SIP applications with the ASIP didn't need to be SIP experts. So we wanted to abstract them from the SIP protocol internals. That's why it was a must that the API should be as simple as possible. So it's quite expressive. As you can see, we can create a SIP user agent by passing a basic configuration which only mandatory options are the SIP URI and a socket, a server socket to connect to. Then we can start the user agent, register and register. How can we call? Okay, just call. How can we send a message? Just call, send a message. Okay, also it is a call-driven API, meaning that the communication between the DSC objects and the user are the callbacks. So you define your callback functions in order to set your logic when a new RTC session comes, then you set a new RTC session callback function. You can then in the callback object inspect who is usually the direction is quite a common attribute of the DSC callback objects which tells you who is doing this action. Is this new RTC session being locally generated? Is it an output call? Is it remotely generated? Is it an input call? Then answer, check it, draw, react to whatever you need. So, at the glance, this is the DSC architecture. I think it quite well represents the core. We've got everything. All of these points are stand over the user agent who holds a transport that holds many sockets. Also, dialogues who on top of which RTC sessions are created. You can also do IAM message. We have a registrator attached to the user agent. So the user agent can register and register. And this basically is. So, as you can see, it looks like a modular design. It was also a must since the beginning. We wanted its element to take care of its things and abstract the others from its internals. As an example, we've got the transport. As we can see in the previous slide, we see a transport and multiple sockets. Okay, then why don't we see web sockets? Because actually, you don't need to use web sockets to use JSIB. We provide sockets interface, which is really simple, which needs to implement three methods, connect, disconnect and send, which will be called by JSIB when necessary. Also, three callbacks on connect, on disconnect, on data. So, JSIB is aware of whether it is able to send data to this transport or not. And it's got some mandatory attributes, well, which got their default values, which are via transport, URL, CIP, URI, who helps to help creating the SIP messages and setting certain non-standard values that some SIP server vendors require. This way, you are not attached to use web sockets. Of course, we provide a web socket built-in implementation. We also have a web socket node module. So, you can use JSIB in node. Of course, we are talking about signal in node media. And, yeah, that's all. So, you could send your SIP messages over HTTP or over some application over HTTP or over any other kind of transport that respects this and implements the interface. Another example of the... This is the communication, internal communication of the objects. We can see here this ONION architecture, where we abstract objects from others' implementation. So, a requester could be an IAM message sender or a dialogue or a registrar who wants to send, in this case, a SIP message. So, it delegates to the request sender who creates a SIP transaction and delegates the sending of the packet to the transport who uses the socket and everyone does its thing. So, for example, the request sender, in case there is a need to make a digest authentication, we don't deliver it to the original requester, but we absorb and consume it on the request sender, making this more modular and even cleaner. Another important part is the RTC session. Why is this important? When we are talking about media, we need to look at this class. This is the one that deals with WebRTC API, the one that adds and removes streams to the WebRTC engine, the one that requests the SDP so we can later send the SDP through a SIP message and, as well, once receiving an SDP, it feeds the WebRTC engine with this information so we can, magically, thanks to WebRTC establishing media connection. Apart from those actions, these are the typical SIP actions that we could expect from a session that are hold and hold, mute and mute transfers, DTMSCB info. We can also offer some callbacks so you can modify your SDP before, when you receive it from the network, before you fill it to the WebRTC core or after you are sending the SDP to your SIP server so you can adapt it to some circumstances, or, for example, a data channel, information, whatever you need. In order to communicate with the WebRTC engine, we use WebRTC adapter which solves incompatibility between naming mostly of APIs offered by different browser vendors. This way we just abstract, we just use the standard naming and we don't care which browser we are talking to. This library solves this issue for us. Let's go for a demo. This demo is a double demo. One of the first part is showing that we can build a node application in order to use JSIP for signaling and the other one will make a media demonstration. Okay. Saul, please. Can we use this? Here, the screen. No, no, this one, no. Where do you have it? The monitor? You don't have the monitor? No. The first thing of death. Did you shoot it? No, it doesn't matter. Show me your options. Where are the mirroring options? Hello. Houston, wait, wait. Move the screen. Okay, okay. How do I move it? Move the screen. Move it. Okay, okay. Okay, Saul. I need to split. Okay. I will. Okay. Okay. So, I will go for the second part of the browser, too. You want to mirror? Yes. What's the command to go for? Yeah, but it didn't show there.  There, mirror display. There you go. Okay, sorry for the inconveniences. Okay, I will need to do it in a single... Okay, I wanted to have this split it, so we could see the execution of the app in one side and the code in the other side. But I will... It would have made things a lot easier. So, please, if you're interested, pay attention because they will not happen at the same time. So, you can see my cursor. We are requiring JSEAP as well as the NodeJSEAP WebSocket because we are creating JSEAP user agents using the Node WebSocket transport. So, mainly this is the... In order to show how easy can we use it, this is the main function which just creates WebSocket Node WebSocket, creates a user agent with this WebSocket and starts the user agent. There are two callbacks predefined with just the back some information. The application allows us to be inside this script, so we will be able to control the user agent by executing commands. Okay, first of all... Okay, so I have enabled the Z-Blogging because I thought this was interesting for the first time. Okay, we can see here that the JSEAP is starting. We can see the configuration and it's auto-registering because, by default, it's auto-registered. We are registering in a testing service that we have in TragicJSEAP.net. Okay, now I will go out. I will disable JSEAP. I just wanted to show you the ZIP traffic here. Okay, now we are in the application. I made a very simple CLI where you can kind of control this user agent instance. We have already seen. And well, we can see the status. We are using this version. We are connected, registered. And I will establish a remote peer. Okay, peer. I will connect to my colleague, Njaki. I will try to establish a chat here. Hi there. Hi. Okay, so... Yep, okay. Oh, I'm sorry. Okay. Let's go. Yep. Hi there. Hi, how are you doing? Okay, Njaki is just there. Thanks. Yep. Okay, so let me just tell you what just happened here. We did a kind of trick here. So we were... the chat is based on SIP message request from one to another. And there was a cookie phrase which is invite plus something where we send Njaki a link, a URL to the Javascript.js demo web application which actually runs on top of the browser. So sending this invitation through a SIP message and he received this message and opened his browser with the given link. At the same time, I opened as well the browser. So we could make the media communication. That is it. I'm sorry for the inconveniences on the demo. I hope everyone understood my aim and I'm willing to answer any questions you may have. No questions? Yes? Do you have suggestions for backends especially concerning audio codecs between different browsers and different clients and so they are transcoded on the backend or what's the normal way to do that? Well, since there in WebRTC there are mandatory codecs. If you are talking with WebRTC endpoints you don't need to bother about transcoding because they should share at least the common codec. Otherwise, if you are trying to communicate with the legacy voice over AP network then you should take care of that and transcode accordingly. So it was it. Thanks.


Welcome folks, this is Tom O'Brien of TFNN. We have five days a week with seven hours a day. We go 24 hours a day on the internet at TFNN.com. Always remember folks, whatever you think about, you bring about whatever you focus on grows. Hope everyone's having a great day, safe date, to make it a great night folks. Let's take a look at one of our four agreements. Don't take anything personally. Your truth is personal to you. Your own opinions and point of view reflect your own agreements and are personal to you. It's no one's truth but your own. Mug it wise, let's take a look at it out here. We have the Dow Industrial's up 56, Nasdaq's up 8, S&P's up 7.5, Gold contract down $9.60 trading at $17.18 an ounce. We have Silver up 15 cents, $18.41 an ounce, Light Sweet Crude up $1.25, $83.19 a barrel, notes and bonds. Ten year note right now, that is down 66, trading $1.15, $31, the 30 year is down 12 at $133.26 and we have the 10 year yield and $3.28. So the highs for the last three months is $3.4, the low is $2.5. Let's just look at that for six months for a second, just to see. Look at that, yeah, six months, $1.8 and $3.4. And then a year, this is going to be shocking, $1.2, $1.2 or $3.4, still a big number. And King Dollar, King Dollar right here, down 157 ticks trading $109, $6.83, the Euro is at $99, the yen is trading at $144 and the British pound is at $114 to $1.00 US dollar. Our phone number is<PHONE_NUMBER>, give us a call folks, want to know what's going on in your world and the world of the S&Ps, let's take a look at them. What do you have? Well, let's take a look at this, babies. Well, I mean, well, let me pull up the S&P first, because this was something else. And you know, what happened, so you've heard me say this before, okay? In a bull market, all the surprises are to the upside, in a bear market, all the surprises are to the downside. And you know, you talk about volatility, man, you had this S&P get down 50 points like in a heartbeat, and you know, it hit a low, what it did is this, it came into the low that was established, well, above the low that was established at the opening bell. You know, that being said, it doesn't have any juice to the upside either. You know, what happened here, so I'm on a 10-minute bar, and this 10-minute bar is getting volume also. So that puts the odds that you're going to go right back downtown, you know, it brings the odds higher. Let's put it that way. There's no doubt about that. That's on the E-minis. If we go to the NQs, we take a look at the NQs, what you're going to see, I pull the NQs up, that's the Nasdaq futures. You're going to see that, did the same thing, let me see this, so we just got volume up, volume, yeah, it's going down to the lows, man. This thing's going to go after the lows once again. Pretty intense, man. That's volatility in spades, man. That is, let's see this thing. Yeah, I mean, you don't see a lot of 10-minute bars, folks, that have, this 10-minute bar is 50 points, 50, 5-0, and that 10-minute bar hit the bell at noontime today. Noontime was the number, so, problems in paradise. That's the way this is set up. Let's go take a look at some of the, well, actually, let's go into the NDX100 first and take a look at the NDX and see where this sets up. The strength, right, Gineron's got something going on, that's up 18, almost 19%, Moderna's up 3.5%, Mokata Libre's up 3.6%, and DocuSign's up 3.6%. I believe DocuSign's coming out with numbers after the close. Let's get away from it. Kraft Heinz is down 3.7, Pace Kair is off 3, NetEase is off 2, and you get Old Dominion is down 2.36. That's the Old Dominion, because what's going on there, one second, Old Dominion. Let me do it this way, one second. Because that's the trucking line, man, and if that's getting crushed, I see it's going to get down to the lower end of the consolidation. Okay, so if you start seeing these trucking lines get crushed, man, yeah, it's not that bad. That's off a high, but it's not that bad, that's the real bottom line. If we go take a look at the Dow industrials, take a look at the strength versus the weakness inside the Dow. The strength out here point-wise, you have Goldman Sachs, 26 positive points, United Health, 23, Salesforce, 17, taking away from it, Apple minus 14, you got Honeywell minus 13, 3M minus 9. Now let's go look at Harmony Gold, because we get some questions, there's no doubt about what the heck's going on with Harmony. This thing got absolutely smoked yesterday, and, well, not just yesterday, no, actually last week, okay? So let's bring this back. Harmony, when you take a look at this, so the low in Harmony is 216, 2.16 cents, the high's 550, that's this year, pull this back, okay, so, well, yeah, this still can test 211 or something, you see that breakout, that's where it broke out from, no, there's still, let me just look at where they're shaking out here, so, yeah, they're losing $1.72 a share this year. The thing that's really weird, man, is that they're saying that they're going to make money next year, but I don't know how they're going to go from losing $1.72 to making $7.91 cents in one year. The market's not saying that, that's for sure. I'll take a look at that a little bit more, but right now that's what it looks like it's going to go test, it's going to test that area out. Great Panther, since we're on it, that's, they're going BK. Great Panther, you know, bottom line, yeah, they're open, they're down 10 cents, but they filed, they filed for bankruptcy. This is a heads up in general, okay? The reason I would say it's a heads up is that, you know, you do have a producer that, you know, evidently ran into some trouble, because you can see they must have, you know, they're still doing 211 million, but bottom line is that they filed for bankruptcy yesterday, so. Some of the higher volume equities out here, and this will be a low volume market out here today, I suspect, unless we get another downdraft, but you get advanced micros up $2, you get Apple is down $2, Lyft is up $2, we got Verizon is up $0.12, Pelletier is up $0.15, Bed Bath and Beyond is up $13, Plug Power is up $1.20, stare at there folks, come right back.


Thanks so much. Thanks for having me. So before starting the presentation, going into the meat of it, I thought I would do comments about what we have done over the last few years. It's been about five years since I was with you guys at the San Diego meeting, and we wanted to get a bit more active in the community. So I hope this gives you some context of what we might be able to contribute. So first, my lab is consisting of a diverse set of people having a lot of different interests. So we're working in a variety of areas, but I think the tools that we are applying and the lessons that we gleaned from it, they transfer very well into what the old proposal was trying to achieve. So I've run through a couple of these projects and make some comments also relevant to the discussion we had last night about the machine learning and AI infrastructure while I was at the intensity. So in my lab, we are working on lab automation, back to discovery project and engineering, our methodology. And we are also in this consortium which I'm writing which is called the Consortium Molecular Designs. We're trying to a very close test and build cycles together with chemical engineers and biology colleagues. So our journey into AI really started in 2018 when I attended the CAS 13 conference right after getting the academic position, and then shortly after we had the San Diego meeting for the open postage group. And there we were just done retraining Alpha 4.1. It was sort of our hello world program where we tried to democratize something that didn't seem to become an open source solution at that point. And so we put a couple of reports on it and one I wanted to point out because if you have you have asked me about it is this one where we have shown that if you take two amino acid sequences that are very similar to each other, they only have a couple of mutations different. Some neural networks are actually able to get structural differences right. And so here we showed that across one network was able to get the contacts correctly predicted for the different folds, which was something that was at a fold, for example, couldn't do at that point. And then there were a few other articles. One thing that we were really interested in understanding is if these type of deep learning models infer any insights about physics. And while looking at it, we realized no, it's not the case, because deep learning is always some sort of shortcut learning. It will always exploit some underlying bias and transition that from your training data into the test data and hopefully it generalizes, but it won't necessarily use anything physical to get to it. Yeah, so the code is our first attempt to be open source and do some things when we find afterwards published their reports, they kind of mentioned it. So we hope we have a little historical footnote that maybe we have a little bit reshaping the publication strategy and making some of that outcomes publicly accessible. After that, we thought, well, what do you do when you do machine learning? The standard problems are work the docking and doing hand side identification. It seems to be always the first application everyone gets their hands dirty on. So what we have tried to do is to go one step beyond basically docking tools by saying, hey, there's so many docking tools, they all have different random number generators at the end. So maybe there is a signal there if we build a consensus model that uses machine learning to find the underlying pattern. So we trained the machine learning model for mid-dock that uses five classical force fields and uses all of the terms that come out of them. So a set of about 50 teachers runs that for a shallow neural network and then was able to differentiate quite well, at least on our test data set between actors and decoys. And we're currently applying that actively in the cash challenge that some of you are aware of and we have used it now on enemy and sink. It's pretty expensive when you're in that many docking to it. So not everyone is excited about it, but we know that there will be some results that we're using it going forward. I'm personally very excited about the work the open three energy group is doing and I hope that we can contribute with this pipeline to it in the help of the benchmark. Then with regards to image annotations, everyone wants to build a really nice image classifier for cats and dogs. It works wonderfully because we can agree what they look like. When you ask pathologists about cancer types, there's a lot less consensus in the room. And so why for the last 15 years has no one been able to put a clinical approved prostate cancer machine learning model into operation? It's a good question. We wrote a review paper to come out where we show that the problem is really that there are no unbiased data sets and the bias that exists between a pathologist looking at an image in this orientation. That orientation is as bad as the difference between a pathologist and the best AI that you can have today. So very interesting and I'll answer the question to what type of data sets do you need to use if there is bias in the data and do you want to capture something that has to meet the relevance and I think there are some insights learned here that can transfer in our machine learning situations as well. We're also doing some more classical bioengineering. So here's a study where we looked at a biosensor that has a very broad ligand spectrum and we tried to reduce the ligand spectrum by rational design. So we went some knocking on it on some active site neighbors that seemed like potentially relevant, created the library and then tested it and we found one point mutation that was able to become inactive for a specific substrate. So making that sense a little more specific. The reason I'm presenting it here is because after the rational design we run in these simulations already because the crystal structure sort of all looked exactly the same. So the question is why is the difference in behavior and in these simulations they showed that there's a shift in the Boltzmann ensemble of confirmations and that is really what determines the function here and so when we talk about Alpha 402 or some of the structure-based models we are just not at the end of the journey yet because it's not enough to get static structures. We really need to go into structural insolments and probabilities of structures given whatever conditions might be present in the cell in order to fully understand what Boltzmann does. And so that led us to the question of what can we do with machine learning in the field of enzyme design. We just wrote a video paper on that and found that it's a very hard problem. So pretty much everyone tries to guess that and machine learning at least in 2021 was very limited in its application. So we started working in that field and we applied some large language models. So by now there are a few other tools out like protein MPNN for example, Sega Eugenicov is doing a lot, Baker is doing a lot again. But when we investigated these models we realized that there's a bit of a systematic error in there because when you look at the learning objective that these models have is they always try to take a structural confirmation and try to optimize the free energy around that confirmation completely ignoring the rest of the energy landscape. And so there's a high chance that you find the structure that may be very optimized but it does also have a different energy minimum and then you can get misformers and misholding events. And so when you look into the reports you can find that people are always surprised at why the natural language model is giving you such a great idea of where to go. It works only in a certain sense of the cases. And our hypothesis is that there are actually alternative confirmations that are being also optimized and people are not aware of it because the learning objective is just not properly defined. And so this preprint, which hopefully is going to come out soon, in the journal we show that there is a way of rectifying that by using base rule and by doing some tricks to the way we use these language models and we applied that to an enzyme in nanolubes and we're able to stabilize over a wide range of temperatures which gives us a good idea that this model might be able to help with the hard task of protein engineering in the future. What it really showed us though is that if you bring people in the room and also the digital pathology showed us that they have a very strong machine learning background they might be able to do a really nice job at giving you an architecture that predicts something that's very accurate but it is just not the right objective function because if you don't have the domain expertise and all the implications of it and what else could be happening it's very easy to be misled and go for something that has absolutely no relevance like a capital value of one when you train an AI model for cancer classification where the data set was created by one pathologist on data set from one hospital and completely ignoring the heterogeneity that you normally have when you travel across the country and ask multiple pathologists. A great machine learning model people publish it but at the end of the day no one will use it because it just won't generalize the remains of the AI bar and the same thing that happened in biology systems as well. So we need to bring together people that have domain expertise as well as the machine learning and background to get these products to work. Then CAS 14 happened and I was really invested into the trust by product and we thought we could make this something that would revolutionize the field had some nice attempts to improve on it and then of course after fall two put us all into shock. During the conference we created this little self-help group to meet once a week and kind of overcome the stress of having the likelihood of our funding completely destroyed. I'm actually called an open fold and we had a weekly meeting trying to understand what is it that makes AI bar 4.2 so great. We had a lot of external speakers come in, Fabian folks talked us about the SE3 transformer and we were wrenching into these mystical fields of math and physics and how to integrate them until eventually we realized that Alpha 4 talked a little bit more about what could have been done than what they actually did. The interesting thing is of course that these concept like SE3 variants are very powerful and can be used in other contexts. However in these discussions we realized that retraining Alpha 4.2 would be too expensive for the resources that we had. I checked this morning who is left from the group and the only one left in our lecture was Mohammed. I guess he liked Alpha 4 so he stuck with it afterwards. Good. We are stuck with equity variants instead. One thing maybe that I learned and one of you pointed that out to me. They said if I come up with good names I should do a better job of announcing them to people and so here's the model of our lab. We call it the data rhinos because we created this integrated data science path at BYU where we take students that are very promising STEM students like Bryce who is presenting with me. He worked with me on the prosper model since 2018 and then give them the ability to work in consortia with industry partners together so that they come out at the end with a degree where they have a data science applied background that helps them to become a real contributors for the rest of their career. I like the tagline we're quitting unicorns, only real ones, tougher ones, right?  Anyway, so one thing we also did is we were very heavily invested in a company called Zonto that does lab automation. She signs up inside that organization with us acquired by Broker two weeks ago, which is nice because it gives us some funding routes that they didn't have before. So due to that I'm able to find the consortium to make it a design a little bit better at BYU and for example contribute Bryce for the next three years to the open forestry initiative and have them work between some projects that will hopefully enable science a lot of scale. Yes, for sure. I forgot that I picked up somewhere. Okay, so but what we really took away from these CAS 14 results was that the idea of inductive bias is super important. And when we train machine learning networks the way we can go a level beyond what everyone can do is by putting some hard math and physics into it. And so what we did then with Fabian Fuchs together is took one of his SE3 transformers and pimp it up a bit. He had trained it on the terrible QM9 data set if I can quote John from yesterday and we retrained it on the Any1 data set. And just to show that this will be able to give us a nicer performance and the initial results look pretty good. So we presented it at a new website event and today we're going to show you what happened in the next iteration of that network. Before pointing that out I just want to also highlight a different area of application because the question came up yesterday when will ML replace normal MD simulations for force fields in our domain? I don't know in our domain but we wrote a review paper on what happens in the field of molecular simulations for molten salts and in that area we see an exponential growth of purely ML based simulations because they need to have very polarizable force fields and you can only get that with AIMD and all this up-in-issue stuff is always limited to 100 atoms, few picosecond simulations. It's not enough to get them the thermophysical properties that they want and so they're applying right now all types of crazy potentials that have a bunch of underlying systematic errors. So one thing that they love to do is run an MD simulation up-in-issue, the DFT one, and then they fit a Bela Parinello system on it which was optimized for single atomic types and when you read the literature you will always see them say this works great for two species molten salt but when they go to four or five atomic species it completely breaks because the input vectors are hard-coded to correspond to an average chemical environment which obviously shifts inside of the simulation box but they haven't quite caught up on that yet and so I think that collaborating with the open force field group can help us transferring some of the insights that you have developed and best practices into that field and hopefully have this vertical domain also to make progress but with this I'm going to transfer over to Brice so you can tell you a bit more about the new model of TRIP. Yeah so the TRIP was the next iteration of our SE3 transformer-based neural network so in context there's there's a ton of different neural network potentials for example LaShunet, Bela Parinello, Annie but the majority of these neural networks they only work with scalar type features which for molten salt simulations you need polarizable force builds which can't which aren't be able to which these scalar networks can't predict the dipole moments correctly and another big limitation of these is that a lot of them require handcrafted input features using symmetry functions so what we wanted to do is instead work with an aqua variant type neural network which has a lot stronger math which has a very strong mathematical foundation based off of spherical tensors which transform co-variantly under rotation so an example of why these are useful is aqua variants is a principle that allows physical properties to be encoded so for example on this figure in the bottom right diagrams what exactly aqua variants can mean so if you go down then you calculate forces on a molecular system and then go right you can rotate those forces but you end up getting the same forces as if you had first rotated the system and then evaluated the forces so you can generalize this beyond just vectors to higher order geometrical objects that these tensors that we work with so we're just to say we're not the first ones that have done this other people have also been working on this but our method is more general than for example neck whip which just worked with tensor field networks our method uses sd3 transformers which also incorporate attention mechanisms which allows it to then have angular degrees of freedom in addition to the radial degrees of freedom so some of the features of our network is we trained it on the anime 1x data set which supports carbon hydrogen not nitrogen oxygen species and we use an atom agnostic architecture which is something that we don't really see many other people do and what I mean by an atom agnostic is that the majority of our parameters are shared between atomic species the only atomic species dependent layer is the atomic the species embedding this allows it to then work for many different species in the future where we want to transport and transport to new systems for example molten salts a problem with like Baylor polymelo is that as you increase the atomic species the input vector increases dramatically and so does your primary account so by having this species agnostic architecture you're able to limit the parameters and then also allow information to be generalized between atomic species another thing that we added is we we have added correct atomization energy and repulsion as someone mentioned yesterday if you run with any potentials you can end up with fusion and we've corrected that by adding a nuclear repulsion term and then we also added an atomization energy so that your molecules don't cause power bearing simulation and to help what the areas that might not have been trained by data we we bias it by using our physical knowledge of how the system should behave and then the last thing that we added the last feature we have is that our network is smooth it says in the mathematical sense that our derivatives and all their derivatives they're all smooth they're all continuous that helps prevent some of the instabilities that you have with other neural network potentials so we benchmarked our network on what's called the Comp6 benchmarking set and this generalizes beyond the molecules that are in the training set so it has larger molecules that the network was trained on so it really gives you an idea of how well your network can generalize beyond the molecules it was trained on that's one of the things that a lot of the network potentials are looking out is that they're trained on a very small collection of molecules just with different confirmations from the test set it's just different confirmations of the same molecule but to have a general potential you want to be able to say how will this potential work on molecules it's never seen and we find that our network performs better than any one X anyone all the other published methods and we're really excited about that because it means that we're going in the right direction and that our architecture has potential we also did energy surface scans of H2O and this kind of diagram's what I was saying earlier about the atomization energies and the nuclear repulsion because if you look at that all three of the different methods for calculating energies they all have the same similar minimum around one angstrom but if you look at any if you go smaller than one angstrom then it actually doesn't have the repulsion term that you'd expect from physically but like DFT does but our method does have that because we have hard coded that into our architecture and then another issue is that if you start pulling it apart then you end up with another minimum which isn't physically realistic but our potential overcomes that issue by having the correct atomization energy we also did a torsion scan of a bedroom and we found that our method got slightly higher RMSE values and that we were able to predict the correct structure of the torsion scan we're hoping to benchmark it on the bigger dataset of torsion scans that was introduced yesterday though and then we also ran MD simulations using our different using different potentials we used the amber 14 with the tip 3 water uh and then also any 1x and trip potentials using um solvated models that and the water molecules their forces and and energies are actually predicted by the networks rather than tip 3 um we find that we're able to simulate molecules for 20 nanoseconds and then get a good understanding of the statistical landscape of the MD the MD system so we calculated different MD statistics of the secondary structures what what are the average pi triangles what's the standard deviation of those and then how often is each of these uh potentials how often do they predict that they should be in one second their destruction versus another and we found that the anyone acts um it's it samples um regions of the the rhomachandron plot that generically aren't accessible but our our approach um limited the limited mainly to um the more common rhomachandron areas um yeah so going forward we're hoping to apply it to enzymes and I'm gonna pass it back to Dennis just a quick conclusion so uh thanks Bryce I think the potential has a lot of potential the question is now which data set do we need to train it on to get something really important out of it one thing we hope is set by teaming up with open force field some groups from the molten salt community will feel more inclined to share their trajectories right now everyone runs these expensive trajectories and locks them up which I think is a waste we could train on those and then really expand the network to different atomic species like Bryce mentioned transfer learning is completely possible you don't have to retrain anything you take the model as is and fine tune it on the next atomic species and it shouldn't lose its ability to work on the initial data set um yeah and then of course it opens up the door to reactive force fields which I'm really interested in for the case of enzyme design we have done so much enzyme simulations and tried to work with the QMNM simulations it's always a pain being able to have one force field that does the reaction of the active site correctly but then also models the water molecules correctly about being dependent on some our integration is a this powerful promise we have to see where it really needs the future so with that I'm just going to point out that I'm excited about collaboration if you have some data sets where you'd like to try to try this out we can train that guy very rapidly takes a couple days on our GPU cluster and we can bring you some benchmarks on that and we hope that together we'll define some best practices that will inform our collaborators and colleagues in domains that have not yet the 40 years of experience that we have with water models and solvents here so with that I'm at the end of the presentation thank you for your attention


Alrighty guys, what is going on got Kyle and Sean here. We've got the sports cards Almanac collectors edition volume one This is case break number one. We did a random for the case. We got number nine for our first one here and we did a random of Did a random for the spots I'll show you guys again We had Ramirez up there with one Chad C with two Brandon a with three James H four Candler with five Brandon a six James H seven Benjamin with eight Brian R with nine and Jonathan W with ten All righty guys. Good luck again. I will mention the rules Um, no influencing the drafts of any kind guys and no talking about card values. That is it. Enjoy the show guys appreciate it Case number nine first case number nine. Let's see what Lane's got in stock today. I Don't know what that means his kid is right outside though right outside the door He does work here Alrighty guys, good luck. Good luck. Let's do box one box number one Open these there we go. Look good luck. Alrighty guys again. No influencing the draft. No talking about card values. Those are our two rules What's up, Sam? It's going on everybody first card is gonna be a PSA nine It is a 1995 Panini smash hits of Kurt Cobain on this sticker. These are sweet 1995 Kurt Cobain on the PSA nine Oh, I got you. I got you Kurt Cobain first pick our first one there. Yeah, let me let me fix that real quick guys Alrighty guys chat is open to everybody again guys. We have two rules. No talking about card values No influencing the draft Sean is ready to go if you guys are uh breaking our rules man Sean is ready to go Alrighty guys box two later Dylan 1995 sub good year. Yeah, it's the one you were born in it's pretty good So we got a booklet this one is gonna be remandre Stevenson on the rookie jumbo prime signatures Look good there. We'll show you here real quick Bad King bot is ready to ban man. So we got remandre Stevenson on the Jersey auto booklet Rookie from last year's NT 2021 nice little four-color patch on that as well Remandre put that one back in Righty guys box three box three No scared of Sean You might you might want to be Box three here. He is here is the architect the architect box number three It is Joe Montana a nice one there on the throwback five out of 25 on the Jersey auto little chiefs Joe Montana there Nice one there Don't take on the seat and seeing how many people he could instigate to dunk him Yeah, don't take this they take man some money that is from 2012 tops supreme there Lee Joe Montana Jersey auto What up Austin? What up chiefs little chiefs Joe Montana? What's up? Montana Yeah, I can open these without So I think I can rip the sticker without this how are you? Alrighty guys box for Timmy Got a PSA 10 nice one there. It's Traylon Burks on the silver rookie auto. He's signing with the black ink there Nice Traylon on the PSA 10 Yeah, he got the he got the Sharpie didn't get the blue ink memo nice one there on the PSA 10 rookie auto Traylon Burks Yes, sir can I got pick five good luck handler here's box five Pick one that is right. Oh Hope everybody's having a good Thursday Appreciate all of y'all jumping in and grabbing spots this. Yeah Out fast This one is a PSA three They can vintage nice. It's 1959 tops of willy mace PSA three that is not bad for 59 man That is not bad for a 60. What four-year-old card Little willy mace there on the PSA three 1959 tops Hey, what's up Nicholas? Afternoon afternoon. I Can't I think I picked the Lions in my pick em league, but I it was pretty close. It's pretty close box six I was having a Oh Box six here guys box six good luck This one is nice. We got OBJ on the totally certified that one's an RPA OBJ RPA that is correct four out of five nice one there. That is from 2014 totally certified To the OBJ I'm on the Giants man. That was serious Nice one there OBJ on the RPA Righty box seven You see the Victor Cruz interview about them going to Miami There's only an interview where they like interviewed Victor Cruz about the whole Giants like receiving. Oh the boat Oh, I forgot about that. He was like OBJ was only wearing wearing my tins because he came to Miami with no shoes and was like You got shoes. He was like I got an extra pair of tips. Alrighty guys box seven Box seven we got Desmond Ritter. There we go from 2022 obsidian on the yellow RPA numbered 25 out of 25 That'll work PSA nine on there. It's pretty good great for a thick card, too Yeah, a little three color little number patch nice one there on the rookie Jersey, Inc. Yellow PSA nine writer. Good luck. Everyone have fun tonight. Yeah guys Also, we got Lane and Forrest over on fanatics live You guys trying to get some group breaks going they got some Bowman Crow one case of Bowman Chrome left some four box mixers And then they've got Flawless flawless PYT style Blair. You are right guys box eight. Hey, thank you Blair. Thank you Like Sean said you were awesome appreciate everybody hanging out with us so far today Good luck everybody who got in today got ten cases coming ten cases. Hey, what's going on, sir? Let's get this This one is another throwback It is 1967 on the tops Mickey Mantle another PSA three the mic 1967 tops nice one there man I like the vintage for sure Willie Mays Willie Mays and Mickey Mantle Some some pretty good vintage guys right there Mickey Mantle there 1967 Now we got box nine Alrighty guys again our two rolls no influencing the draft no talking about values. That is it guys That is it. Everybody. Have a good time. We appreciate everybody Yeah, let everybody let everybody make their own decisions here guys All right guys box number nine Mac it is wow Colorblast Drake London from 2022 prism little rookie color blasts These are not easy to hit man. No one in every 20 cases or so. I believe on the colors Let's go nice one there some nice Falcons in this case some nice young Falcons Nice one there color blast Drake London We'll take that And one more here for our first one Yes, yes, you guys are enjoying the stream, please do Number 10 appreciate all of you box number 10 Yeah, like I was saying me and Shawn didn't really see but it was much in here. So we we're coming in blind. I'm excited This is nice That's a Dylan card right there from 2019 Hupes premium stock we got Tatum on the PSA 10 auto Nice one there Jason Tatum 2019 premium stock think we got some more up there. I only got three of those kind. Yeah, I grabbed those ones Alrighty 2019 Hoops premium stock Very nice very nice. Love the Tatum. Love the Tatum PSA 10 Alright guys, we'll get these all set up and we will get our draft going guys again We'll get a minute on the clock for everybody and No talking about card values. That is our only rule guys No card values and no influencing the draft. So don't say what you would take anything like that guys Anything like that. So have some fun with this. Shawn is ready to ban if you guys are Breaking our rules. No problem. Let's get these cards set up And we gather Mars with pick one and again guys If you do have your pick up Just need your We just need your zip code with your pick Man that is Backflip Sean kidding me so I can do a backflip. Yeah That's right, baby. Nicholas, you know it sheriffs in town boys. Yeah, you don't want to mess with Sean How much was this a spot like 180? I believe yes around 180. I believe All right guys, let me get these set up Spread them out a little bit Good day, sir. How are you? Alrighty? I'll get a Get a better angle for you guys All right, Ramars is up first Ramars is up first Pick number one. Thank you. Second get a timer ready to go I'll write one minute on the clock of Mars and here are your picks Got the Tatum over here. We got Drake London on the color blasts Mickey Mantle and Willie Mays both PSA threes Got a PSA 10 Traylon In the back. We got Ritter on the RPA to 25. We got a OBJ RPA from 2014 totally certified to five. We've got a Joe Montana out of Jersey Auto There is a rookie Ramondra Stevenson Patch booklet and Kurt Cobain on the PSA nine 1995 Stumped it to Yeah, dead man, that is that is breaking our rules right there saying who what you want to pick That is breaking rule one and two actually I believe. Um, yeah, I can get them. Yeah, just time them out first Alrighty guys from Mars is up The Tatum Yes, sir, hello. Alrighty Good good paper Mars. Nice one there on the Tatum PSA 10 from 2019 hoops Nice man. Nice pick there. We'll get that right out to you, sir. Thank you. Thank you Alrighty, there is pick one now up. We got Chad see Chad see with pick two Good luck Chad And let me know if you guys do want to see some cards closer. I'll try to get them all get them all in here Yeah, let me know if you guys do want to see anything closer. Um, anything specifically I can pull it up Chad see is pick number two here got a minute on the clock Chad What year was the mantle mantle was 67 1967 tops PSA three And um, will he maze was 1959 Yeah, guys, so I'll reiterate again guys two rules no influencing the draft guys. Don't say what you would pick Um, don't try to say like anything about picking. Um at all just let uh, let let whoever's up make their pick They're free to choose whichever card they want Yeah, you can talk once the once the whole draft is over we can talk but No, it's okay dead man. It's okay. Yeah. I'll just let you know So those are our two rules everything else We are good. Hope everybody's having a good day I'm gonna have a good time tonight. We got 10 cases going. We got the remandre booklet in the back Um, can't see that one remandre rookie in t booklet the london 49307 heard gotcha Nice pick there chad on the color blast jake london These are sick man. I always love a color blast Very nice one there chad Drake london on the rookie color blast from 2022 prism That is the uh, that's the uh bag the team bag there to that little mark kind of hard to see there, but Nice one chad good pick on the second next up. We've got brandon a brandon a with pick three Can you see the writer? Yes, sir Got a writer. Um, this one is from obsidian rookie to 25. It's the book in there 25 out of 25 PSA nine on the uh, not bad on a fit card. Um great either fit card with the windows Can be tough to get 10s on those for sure Yeah, I know you do sav. I know you love those color blasts You still have the brady color blast. I forget I was trying to buy that from you at one point Yeah, let me know if you want to see anything else Hey, what's up chris? What's up kevin? What's up brandon louise evan? Hope everybody's having a good day. Yeah, again, no worries on that dead man. Just um Letting everybody know the rules here. Yeah, just letting everybody know the rules. No worries at all guys Um, like I said, we'll we'll time you out for the first time for a couple minutes And then we'll have to ban you if you guys keep uh, the willy yep 1959 tops ps a3 on the maze Not a bad grade for a 60 something year old card Take that willy maze The giant's logo ain't changed much in 60 years Oh righty about um 30 seconds left brandon If you want to get a pic going Oh, yeah, you got rid of because it was the the new england brady. I got you Hey, nice at work at luxer Let's go. Let's go Let's see if we can get you a pic one in one of those the willy 233624 for Yep, cool Perfect. Alrighty nice pic there You go brandon on the 1959 tops willy maze ps a3 That is crazy, man. That's a throwback. I love the vintage man. I'll hopefully hopefully we see some more today ps a3 willy mace Alrighty guys next up we got james with pic 4 james h Minute on the clock sir John you got 10 man. Yeah, i'm sorry johnathan got 10 on this one Um, I did repost the results to our results section of the website So um, you guys can always check it there And get these moved over get some more up front Yep, and we're on four is james h james h some angles going on those And guys the back cards we have a joe montana That's james s Oh, yeah, it is james s james s. Sorry about that. It's james s Yeah, james s. I have it. It's james s here You interesting No, yeah, it is james s. Sorry about that Let me know if you are here james s Otherwise, we will pick um, we will pick for you Mr. Bean back in the day. I do remember some mr. Bean I do remember some mr. Bean Jordan loves prices. Definitely man.  We'll see you soon man. Appreciate you hanging out with us so far Alrighty james james s White box 101 rp. I love I like that Alrighty guys, I think we're gonna have to pick for james here Um james has pick four and pick seven I think we're gonna go with the mickey mantle on the first one here mickey mantle for james 1967 tops ps a3 For james here on pick four james s Alrighty and then candler candler on number five I'm sorry can I snag your uh, what you were gonna pick? Sorry about that bud So again guys, let me know if you want to see anything closer. We got candler now candler now Does shawn ever pick shawn could pick you could have shawn pick Yeah, there is a uh 1995 cobane um ps a9 sticker We've got the remontre stevensson nt. Um jumbo rookie prime signatures. That's the rpa booklet It's a 99 um rookie and we had the joe montana from totally certified out of 25 Jersey auto for the chiefs chiefs joe He only picks dolphins cards. That's about right. It's about right. I don't think we have any uh any any former dolphins in the Here, so the ridder is 25 at 25. Sorry candler 25 at 25 It's the book in there 25 out of 25 Dual rpa ps a9 Got the ridder gotcha. Yeah, let me know your uh Yeah, give us your zip real quick candler again guys if you are making picks That's all we need is the zip code with your pick you can confirm it is you And then we'll have brandon a up next to your guys with pick number six. We'll have brandon a thank you Alrighty nice pick there 2022 um rpa of desmond ridder 25 out of 25 The bookend all righty now. We've got brandon a backup pick number six Oh, it's a sick card Yeah, no, that's good. Yeah, you want to see the booklet? I gotcha can take it out So this is from 2021 into it is remandre stevensson on the um booklet jersey auto so a little four color patch there Sean's favorite dolphin of all time marino marino 100% like Remandre on the booklet Is 57 and 99 this is um j or brandon a brandon a was six Remandre is a rookie from 2021 into I don't know 30 seconds for you brandon Sean's favorite dolphin of all time Daniel Wes welker Dolphin Remandre got your brandon got your brandon. Yes. The obj is a rookie 2014 totally certified. It's number two five All righty, we're taking the uh remandre stevensson rpa booklet from 2021 in t Nice pick there brandon. Thank you, sir. We'll get that right out to you. So next up. I've got james s again James s again With pick number seven big j fielder There's some definite names of some dolphins over the years that you could some obscure names. You wouldn't think we're on the dolphins The chrome dust it does happen. It does happen. It happens. We're not even opening anything today And then we're still getting dusted Still getting chrome dusted All righty guys james s. Let me know if you are here, sir. Um, we made a pick for you on the first pick This is your second pick here number seven. We've got four cards left We've got the trail on berks psa 10 auto We've got odell beckham on the rpa to five. We've got a um the 25 joe montana jersey auto and we got our Kurt cobain 1995 Um sticker ps a nine. Hey, what's up, michael? Evening sir.  Good day, right? All righty guys. I'll give about um 15 more seconds here for james s. We did make his first pick So I think we're gonna have to do it again here. Oh, no, sorry committual bad luck and finest again Sorry about that, sir. Yeah, dave wants that The joke Dave wants that. I don't know. I've never heard that name before Alrighty guys, we'll make another pick here for um james s. We will go with the trail on berks We'll go with the trail on berks ps a 10 on the rookie auto ps a 10 titan's rookie receiver Trail on berks here Nice one there james Appreciate you sir. Grabbing a couple spots there and next up. We'll have benjamin here with spot number, um eight Spot number eight for benjamin. Just three to go guys got the obj rpa to five We've got um joe montana 25 and we got a kurt cobain ps a nine Um, this is called almanac mitch. Um, mitchell. We actually put this um lane puts this together It's our own repack products. So um, we sell 10 spots in here. We have 10 boxes We let everybody um or we take out all the boxes Everybody has an order before that we randomize and then we do a live hit draft So um, we're picking one through 10 here. This is pick number eight for benjamin l So we get 10 people in here and we do a hit draft Of course james is using your stream elements. What's up ill? What's up ill? So how we doing today? Yeah guys benjamin l here pick number eight got about uh, 30 seconds to go here ben Appreciate everybody uh following our rules so far. It's been very easy Very easy for us guys again. I'll mention again our rules. Um, No, uh, no influencing the draft and no talking card values. That is it guys. That is it obj Got you ben. Got one four five six four good to go Nice one there obj on the rpa rpa out of five that one is four out of five from 2014 totally certified obj made a uh made his name with the giants for sure Nice one there ben appreciate you and pick number nine will have brian r brian r or pick nine got a pick between the uh, joe montana jersey auto and kurt cobain From 1995 panini smash hits psa nine sticker Good luck brian Got a minute on the clock for you, sir Hey, of course ben of course. Thank you for joining Thank you for joining sir. Yeah, that is a nice one man. I haven't seen much obj from uh Rpa's from back in the day. They don't sell too often I like it I'm proud of guys brian r got two picks here and then um, jonathan w will get whichever one we don't get picked here Again, this one is five out of 25 on the joe montana jersey auto. That's from 2014 All right 2012 2012 um top supreme And then we got the kurt cobain psa nine brian r here Cobain, yeah, yeah It's sick. I think they have a couple different stickers like it's a couple different um like angles That's Yeah, really man really some vintage Some nice rpa's. Yeah, that's the only case one. Yeah, we got nine more We got nine more. Um, I don't know michel. I didn't actually look at what's in here, but I believe there should there could be Yeah, very very well could be. Um, it's always a nice mix between vintage soccer um, all the big sports Alrighty, um Last call here for Brian r pick number nine And we will uh, we will pick one for you sir Yeah, there's usually a one or two soccer cards. I don't know that there is this time, but we usually depth. It's always multi sport. Um Never really know what we're gonna get out of here.  That's not even a multi sport But it's a sick one All righty last call brian r pick number nine It's new blind and one one time. Really? Yeah, that's pretty cool That's fair evan. That's fair good. Uh, it's a good chance of that for sure Yeah, he does he does lane works hard on these man. Yeah works hard to make sure it's a good value for you guys Everyone has fun some cool cards. Alrighty guys, we'll pick for brian r. We're gonna do the joe montana here five out of 25, um top supreme from 2020 uh, 2012 2012 joe montana autograph relic from top supreme that one will go to brian r with pick nine And that means mr. Jonathan He will get the uh, 1995 kurt cobain sticker with the 10th pick there psa nine On the panini smash hits kurt R. I. P. Kurt cobain Alrighty and that will do it for our case number one guys Appreciate everybody. Um hanging out with us. That was pretty simple. I appreciate that guys following our rules Everything we will get case number two here going in just a moment


With this political, economic, and social tendency to think that everybody can and should work longer, we then have lost all support for better funded pensions, universal coverage of pensions, and indexation of pensions from longevity and inflation. So we've lost support for old people because we've actually turned old people into pretend young people. I'm Teresa Gillarducci. I'm the author of Work, Retire, Repeat, The Uncertainty of Retirement in the New Economy, and I'm a professor of economics at the New School for Social Research in New York City. You probably remember the Washington Consensus, and for everybody else who doesn't remember it, the Washington Consensus referred to a doctrine that really guided a lot of policy, the International Monetary Fund policy, world policy. Most leaders in developed worlds, and that was the idea, that in order to make the world better, to make them more equal, to bring low income countries up to the middle and even higher income countries, to make people grow and grow in a way that was shared. Higher prosperity were free markets, lower trade restrictions, lower welfare payments, get everybody to work by taking away their benefits, and that was very much a consensus among people who were modern and progressive. It was the answer to everything, and it was hardly questioned. I find it another consensus being developed, and that's the idea that solutions to our aging populations, which is because we've really curbed a lot of infant mortality and people are living longer at age 50 and age 60, a little bit at age 80, but that's not as important. It's just really getting people into their retirement years, and the fact that we've underfunded pension plans. The solution to that has been this consensus that people should work longer, and it is so entrenched in all right thinking people's brains that it's very hard to question it. In my profession, among the group of intellectuals that I sit with, I've been an unwelcome guest. I have been the person to say, hey, there are hidden costs to this so-called policy free lunch, where we get to solve our pension system and our aging populations with this really neat, free fix, which is to make people work longer and to grow the workforce with people over 65. Why should this embracing that people are young at 65 and young of heart and young of mind and creative and productive and engaged at older ages? That seems like a very progressive cultural and political and economic fact to behold and to embrace. How does that good thing match with this bad thing, which is that the most people can't work longer at 65, and the conditions with which they are retired is much worse. It doesn't look like they're connected, but they are. Because with this political, economic and social tendency to think that everybody can and should work longer, we did have lost all support for better funded pensions, universal coverage of pensions, and indexation of pensions from longevity and inflation. We've lost support for old people because we've actually turned old people into pretend young people. But many people know in their bones that people can work longer, and we shouldn't have a society that throw people away. So I am not in favor of throwing people away, and I am in favor of a progressive country letting any adult who wants to work to work as long as they want without fear of age discrimination. So let's set that aside. But the myths behind the idea that it's good policy to solve our problems by making people work longer is based on three things that are wrong. The first one is that work is good for people. In fact, a big part of this book is to review the extensive literature in fields that aren't my own, that are in gerontology and psychology, sociology, even anthropology, that shows that being engaged, controlling the pace and content of your time, having meaningful things to do, those are all good things. But work does not deliver those good things to most people. And in fact, if you are, for example, an older woman who is in the service sector or in the home health care sector, the actually largest and fastest growing occupation in most countries, if you're an older woman in that profession, work kills. It kills by raising your cortisol levels because you're under constant stress of being subordinate. It kills because it disrupts your sleep cycle, which mediates through cortisol and heart disease. And it also kills because it's physically demanding. It isn't just women in those occupations. It's any older person who is in a physically demanding or job or a job where they're subordinate to somebody, which is to say most older people are in those kinds of jobs.  We are finding among the elder populations evidence for injuries that come from stooping and bending, and that's basically warehouse work, and it's basically in Amazon warehouses. Look behind the counter at CVS, and you're going to see Granny taking her cane and going to the cash register, and it's different other parts of the life. New York is a little younger workforce, but go anywhere else and you see this phenomena. Go anywhere else in Europe and you don't see this phenomena. There's another myth, and that's the idea that if somehow we pay for pensions, and we can talk about policies to do that and how much they cost, but if we pay for pensions or embrace this idea that older people should retire, then we're taking money away from children. This idea of greedy geezers are taking away from people, and I hear it all the time, just the other day. A progressive person said, well, teachers' pensions are so expensive and are causing schools to close their libraries. As if teachers were at public enemy number one, or old people were at public enemy number one because they need pensions. I look at 186 countries over a 30-year period, and the countries that take care of their old are also countries that take care of their young. Spending for children and spending for the old people are correlated, not uncorrelated. There is no evidence that providing for vulnerable older people takes away from children. The third one, the third myth, is that we can't afford for people to retire. It's a myth because we spend a huge amount of money on rich people's pensions through the tax code, and economics is called the Hidden Welfare State. It's the Hidden Welfare State. It's hidden because it goes to the top. We spend $250 billion per year in tax breaks for people to save in their retirement funds. The people who save in their retirement funds are higher-income people at higher marginal tax rates, so they get basically thousands of dollars from the government. Somebody who is at a lower wage, a lower tax rate, who saves the maximum into their retirement plan gets $100 or $50. It's like $100 to the lower middle class person, and $7,000 to $10,000 to the high-income person, and that costs $250 billion for a year. The money is already there, and so I know people don't like the word, but a little bit of redistribution is in order. It seems as though I'm just talking about what we need for people over 65, but I'm actually talking about the hidden cost of people working longer to us right now. Because if you increase a labor supply to an economy, you're going to shift out that labor supply curve. The labor demand curve doesn't catch up, and you have lowered wages or you've lowered working standards for everybody else. So I document in my book the cost of not having a good pension system to young workers. So that's that's one hidden cost. The other hidden cost is the increase in inequality of some of the most basic things we care about. So if one thing that we care about is dignity as you age and the dignity of worker, and part of that dignity is to have the time to create your own personal narrative, which often means controlling the pace and content of your time, connecting to what you care about, connecting to nature, connecting to other individuals, and you deny that to some parts of the population and not another. The hidden cost is the dignity of your nation. We know that longevity and health has become much more unequally distributed. So at the same time, we're forcing people without money to work longer. We also have built a system where they get sicker faster and die earlier. So the hidden cost is that foreshortening of healthy retirement time. And that's a reversal to what we used to have when Social Security and Medicare came in the 1960s and really increase in the 70s. You saw the bottom coming up. We saw more equality after age 65 than we did in those years before. And now we're just seeing the inequality supernova really grow in old age. So one of those other hidden costs is that hidden cost of inequality. The 401k system came in 40 years ago, and it's a failed experiment. It was never meant to be the American retirement system, or else it wouldn't have been called after an obscure section of the IRS code. It's called the 401k, but it has become the American retirement system. We know the system has failed. We are coming into a period of time in the next 10 to 20 years where we're going to have massive numbers of people who are middle-class workers be downwardly mobile into poverty. And the hidden costs of that are what it does to communities, what it does to the aggregate demand in communities, and what it does to the adult children who have to deal with impoverished parents. Not everybody has a spare bedroom or a garage they can refurbish for their aging and poor, stunned parents. That's a hidden cost. So the 401k system was a voluntary, individually directed, commercial plan. And we were waiting around for a whole generation to work under it to see whether or not it would get an A, B, C, D, or F. And all of us experts say, well, that system was an F, except for the top 10%. And then that may raise it to a D minus. So my great new deal reassembles the 401k system, reassembles the social security system, and reassembles our thinking about what people deserve as workers, what dignity as a worker means. And so the great new deal increases social security benefits. The great new deal universalizes pensions. There is a bill going to be introduced in Congress. And I have worked about 35 years for such a bill, so I want to talk about it a little bit. It basically universalizes a pension for everybody. And it's even better than what I thought of with my guaranteed retirement account plan 35 years ago and have written about it since. Because it delinks having a pension from a particular employer. And that really gives employers a relief. Because even the good ones have been trying to get their people to invest well and to put enough money in it. And the way the system is structured, the employer really can't do that. And so they feel what they're doing is a waste of time and money as well. So this bill that will be introduced in Congress will let everybody who doesn't have a pension today join the federal plan. The federal employees have something called a thrift savings plan. And it's a really good plan. It's paid for by the employer and by the worker. The administrative fees are very low because there's no profit motive in it. And so the bill will set up an ancillary or a sidecar benefit for 57 million people to join that plan. And the government will provide a 3% match to their contributions. And this is something Democrats would love. And they would have, if they'd been in control, they would have passed something like this 30 years ago. But this bill has support for Republicans as well. And a lot of that is because of the protests from the Occupy, from the good work by Nobel Prize laureate economists. From statements from the World Bank and the IMF, from the Black Lives Movement. That this inequality of wealth is not stable. So whatever the motivation on one side of the aisle of the one of the Democrats, the Republicans have other motivations for this bill. And I've been able to aid some good people who have lobbied for this. And it took a year and a half, but we've created a bill that will be introduced called the Retirement Security Act for All Americans.


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YouTube team keep it clean. What's going on? It's engraving here with another video and in this video Post practice post practice post practice. So apparently Weddo said that the team drafting Lamar Jackson I know some of y'all tired of hearing this story and tired of hearing the back and forth and tired of hearing that He say she say and tired of hearing. Oh is Joe Flacco. Did it change him? Is he gonna play better because of this is it gonna be this is it gonna be that but Eric Weddo said today that The Ravens drafting Lamar Jackson and lit a fire up under Flacco And we're gonna talk about that and hopefully that fire it burns all season long And it can burn us through the playoffs and burn us to the Super Bowl and burn us to win that too So we'll see and also We got an update on John Brown. We got an injury on John update injury on John Brown, too So I Told y'all man. I told y'all I told y'all I told y'all man I said it I said don't don't believe that it's minor Until you actually see him practicing But anyway before we get into that may I mean graven vid this my YouTube channel engraving vids I'm a Ravens fan.  They don't like doing that I'm tired of YouTube doing this thing. It's annoying. It's annoying for y'all. It's annoying for me But we got to try to make make the best of it. But anyway First and foremost the injury update let's talk about that first because that's a lot quicker What's up savage milkshake JB smooth Joe walk appreciate y'all? The injury update the John Brown they I said it this morning whenever they say an injury is minor Don't believe them until you actually see the guy out there practicing Don't believe it until you see the guy practicing and they said yesterday They said that they said the injury that occurred yesterday and he finished the practice or whatever So it's no big deal. It's fine. It's not serious anything like that. But then they said he didn't practice today So again, I'm not trying to hype up the injury not trying to downplay it or make it bigger than what it is But just know that It's That could mean that it is actually a little more than they thought or they could just be holding them out as a precautionary Measure, so hopefully it's the second one. Hopefully they just hold them out for safety purposes Um, and hopefully it ends up just being nothing. That's what we're hoping for. Um, so there was that Uh, but back to the widow talking about flacco saying them drafting Lamar Jackson little fire under flacco So flacco has just been looking so good and been performing so well and practices camp all that good stuff Um, hopefully that's the case and hopefully flacco just goes out there and kills it this year That's what we all want to see. That's what we're all hoping for. I guess a bug got in my car and it's trying to swing on me I'm trying to get this thing Did I get it? I think no I didn't ah, there we go. Oh, I got it now. It's right. Oh, yeah There's a camera. There you go. It's not it's not clearing up on the bug right there on my on my knuckle But I got them. I got them. Anyway, um So, yeah, so with this, I mean They've been saying this all off season. They've been having so many different uh stories and whatnot Um on the Joe flacco and Lamar Jackson thing and basically my response to this I'm just ready to for them to play some football man. I'm ready for them to play some football. I'm just Getting tired of hearing the Joe flacco, Lamar Jackson saga. I'm just ready to see these guys play some football Um, I'm just ready for them to preseason to start then the regular season I just want to see them play football I I don't want to hear anymore that he say she say stuff This and that I just want to see these guys come out Both do thing at quarterback whatever packages they're going to be running and whatnot. Um, She was going to add another add a new little wrinkle to the offense but one thing that I uh One thing that we talked about yesterday just keep in mind, man We'll see if it's a if it's an alex smith thing Um, which happened to him twice and we'll see if it's also A donovan mcneb thing too because alex smith wasn't the only person it happened to I mean, and it's happened it's happened to other quarterbacks too But remember when um, of course alex smith with the chiefs and with the 49ers once cap and it came in with alex smith They started running little packages and stuff They started running little packages and then they say, you know what alex smith I think cap and they can run a show ship them out Then with the chiefs they drafted patrick mahomes in the second round last year and then this year alex smith got him to the playoffs, but they still said, you know what alex smith You're out patrick mahomes is in um, they shipped them off to washington But then in philly when they got michael vic They got him um First they got him when he was all fat and stuff Um, he was fat. He looked just nasty in the preseason. He looked out of shape Which is understandable because he was just locked up or whatever for the past Year and a half or half a long it was but then um They had them I think they had them for a year and then they shipped mcneb off to washington to the redskins And vic became the starter so I don't know it it could be oh, they had them for they had vic for two years Or it was that long so I don't know it could it could end up being The same thing with flacco. I thought it was no I'm saying they had him for a year first and then in his second year That's when they shipped off mcneb to the redskins. So two years will be right um, and then and he did his thing vic did his thing and then Yeah, they ended up going downhill from there. But yeah, it I don't know. We'll see how it plays out But those are some scenarios where teams that have had quarterbacks that have been starting for a while No, none of those teams won superboats with those quarterbacks. But still those quarterbacks have been starting for a while They had been a starter of the team and then uh Quarterback was more mobile more athletic whatever younger Cheaper or not younger and vicks k or is vic younger than mcneb He might be but either way Um, they the the team bringing a quarterback Uh, and that quarterback ends up taking over the quarterback gets stashed for a year They and they they know what did was was very um What's very uh interesting is that all these teams? They ran uh Packages with these quarterbacks. They ran packages with these quarterbacks um the first year and then The next year they ended up trading them So I mean, hey, we'll see what happens. We'll see if it ends up being the same thing Uh, if the um if it ends up being the the same, uh Predicament or whatnot. Um, it's it's gonna be it's gonna be very very very, uh, very interesting Um, as it always is, um, of course, um I don't know because with I don't know la mar jackson because they said they're gonna they're gonna really have this dude on the field They're gonna really have him um in the different packages and whatnot. They're really gonna have him Um They're gonna get him involved. They're gonna have him involved and he is going to be Uh on the field. They say he's gonna be active on game day So I think this almost is I think depending on how far he comes along to This could say something about rg3 too um, but for now I'm like before I was like 99 percent sure they were gonna keep three quarterbacks Now like at like 98 um But I don't know. We'll see man. We're gonna see because depending on what we'll talk about that in another video So I mean, yeah, we'll see if that if this fire that's lit under flakko carries out. Hopefully it doesn't blow out Uh before the season starts. Hopefully it's burning and it just burns more and more. Um As the season goes along so Hope flakko can do his thing. I hope just this team can do his thing Yeah, no, thanks to youtube youtube just always they they starting this stuff again, man So hopefully hopefully hopefully flakko is on point this year. Hopefully he kills it this year And i'm just i'm hoping he really just goes off man. Hopefully he just really goes off and the next year It's this this is such an interesting uh two years, man I mean football season is always interesting for ravens, but this these two years will be so interesting just to see how um How everything progresses and how everything uh turns out. Um, it's gonna be crazy. But anyway, appreciate y'all Thank y'all for coming through. Um, and i'm out man. We gone


केमरमें सनप्री तनाल, नपिंदर सिंग ड़ार, निवदे टीं, शंपू बेरीया.   आजी जेट सरगार मान जे जी है, गता नी बैरी केट को तुटना जी. नहीं, बैरी केट तोडी का दिली जामागी. तबनु लकता है कि रें मशीन तोडी देखी, थी किสonner पाकादा enough य जद याद बख़ाना गूल देष हम था�jis � some ladies to see if a machine on hands destroyed just in case to selk the cart with big holes and begun a professional achievement of black intriguing the sound engineer officials आख ह punt आप स्कलोता, अज्यान्त वह देष हैं, एग ग citation is الزब then i call on villagers for a path to achieve enhancements.  对柏 vin nasoka ho Juga ka ma karna.  ಹೆ ಜ್ಮರ inauguralಯೆ discrete of course ಳೋ Ländern ರೆ ಯರೋಶರೋ..  ఇohlంనులిని పైనికీనికీన్యమస్తరి తకుసకినినోటినిసర్ తిసాను సానినోఱచేనై నుముతాందినిసపిానే . ۷ ۬ ە ۖ ۮ ۤ ۢ ۜ ۖ ۷ ۜ ۗ ۜ ۤ ۜ ۪ ۛ ۗ ۜ ۗ ۜ ۪ ۛ ۖ ۚ ۛ ۛ ۜ ۖ ۜ ۜ ۛ ۜ ە ۛ ۛ ۛ ۚ ە ۛ ۛ ە ۜ ۔ ۛ ۖ ۙ ۜ ۓ ە ۛ ۔ ے ۜ ۖ ۮ ۜ ۉ ۔ ە ۛ ە ە ۖ ۜ ۜ ۜ ۜ ۝ ە ۛ ۓ ۙ ۜ  జజజజజజజజజజజజజజజజజజజజజజజజజజజజజజజజజజజజజజజజజజజజజజజజజజజజజజజజజజజజజజజజజజజజజజజజజజజజజజజజజజజజజజజజజజజజజజజజజజజజజజజజజజజజజజజ बेद शक्ती शाली मशीन इसरू मन्ने जान्दा तस्वीर देखो तेंक वर्गिया च्यनाने तले ताकी हलात कोई वि होन, तस्वीर कोई वि होगे, स्तिति कोई वि होगे ये रूके ना ते चाल्दी जावे, ताकी बेरिकेद जडे या उ तोडे जासकन उलहाल एद तस्वीर तो आदे समने, एद दूर तागी तो आदी, नजर मार्लोगे किटी के लंभी, मशीना किनी कवडी, मशीना, एद मशीन आई कित होगा, इनु लेके कोन आया, ते इस मशीन आलग, किवे बेरिकेडा जडे उ तोडे जाने ने, आखर प्रभांत जडे ने प्रभाद वाले ने, एप वाद आले वीर होनी, मशीन लेके आया, बैजी, बेरिकेड बोध मजबो देखे गे, और तोडी, मशीन भी बवाद ताकड लगी जंदी या, इस मशीन नूल लेए अन दी मनशा किया, ते जे बेरिकेड तोडे ने, तोडे ने, एद नाल तुट तोडी, मैं देखे आं के पिषली बारिए सी देख्या, के जोभ्द्रों किसे किसमदा टैक हुंदा, जाव चडप हुंदी या, तो उदे वेच्यो निक्सान्दा वी खत्राए, एद वेच्यो गए निक्सान्द, पुडी है भी चद्र लाई हूँँँँँँ, आप पाँँची ने पानजगरं मी दोईए, देशा बसी देगीए लेएए. abling to hit the fault wibyắm ะิ ฺิ ฺิ ฺิ จิ ษ Nederland ชิamba glits ศิlafurPoint ศิlafur ศิlafur สิ Rising today´s container, do you have to do it in a bear aggregate that you didn´t love, that you have not given capital for work I would have put the driver apply labor I would have delayed the job So, it seems that he would be forced to rip the bear here and he will break the load but now, he thought to solve the problem and try again �ARA आद か श्रात लग्व श्ताटुर उकदSL देना लग।, ये wrest the now token is ready to wash by the great moonoooooon,... to make you realize new and cured us new.