Module 129 in production analysis and we are going to study technologies with distinct outputs and inputs. Actually in real life we can see that there are very little or the small number of production functions that can be produced or utilized or expressed with only one or the two inputs. Mostly production functions are those that require more than two or the three inputs. A simple example if we want to take, so we take two examples, if we take one from agriculture, means there is a production on any form, so if we see that there is wheat production, so it requires multiple number of the inputs, it requires seed, it requires farmers practice in the form of you can say the labor, it requires pesticides or it can require water, it requires any type of the what you can say fertilizer and even fertilizer can be of the various types. Likewise if we take the example of any industrial production whatever there will be a type of output it will definitely be requiring. I mean if there is an example of the textile we say it means we require the labor, we require the energy, we require the resources in the form of capital, we require certain dyes, we require certain stitching, we require certain chemical, so mostly production function in the real life are those that include more than two or the three inputs, so keeping in view those real life practices we can say mostly production function they include n number of the inputs. So here if we say that there is a q level of the output that is being produced by mostly production function including mean there is a function of x 1, x 2, x 3 and x 4, x 5 and up to n, so here now n is the multiple or the many number of the input case. If this type of the production function is available to us then we can generalize our previous concept of elasticity of production or returns to scale even to this level of the production function. In our returns to scale example we have come up with the one conclusion that if the inputs they are being scaled up by any factor t then the output will also be scaled up by the same level of the scaling that can be t or greater than t or less than t. So if we look at this example we have seen that the same level of scaling means constant returns to scale or greater than one will be increasing returns to scale or less than one will be decreasing returns to scale. So when we have studied those two input scaling cases so we can apply them here as well. Now when we do multiple input cases then there will be only one difference that is as we said earlier that z 1 and z 2 are inputs and they are multiplied by their scalar t. So we said t is e 1, t is e 2 but now we are having more than 1, 2, 3, 4, 5 many inputs. So now x 1 multiplied by t, x 2 multiplied by t, x 3 multiplied by t. So whatever the series of the inputs we all are utilizing by the same constant factor t and that scalar value will increase that all inputs or the production function by the same factor and that t if of the same degree will be having the influence or impact in the form of the increased output by the same level then it will be constant returns to scale and in the same way now if our output increase compared to the increase of the input t then we will say that increasing returns and in the same way if it is less than that it can also be expressed as decreasing returns to scale. So in multiple input cases there will be some differences but mostly concepts of economics can be explained in the same way. Just like we used Euler theorem for two inputs, the same way we can utilize the Euler theorem for multiple inputs in the same way that means the marginal productivity of all the inputs, if we look at all these inputs, the marginal productivity of all these inputs when we sum up then definitely they will be equal to the total change in the output or the product exhaustion theorem that is the multiple inputs in the same way. Now coming to the next, if we look at all the inputs, we were multiplying t or k and k is equal to 1 then this is our constant returns to scale and in the same way if it is greater than 1 or less than then we can do increasing returns to scale or decreasing returns to scale but in this we have a crucial aspect which is that when we were doing two or three inputs then we assumed that the scaling that is constant for all inputs means the actual concept of scaling is that all the inputs of total production function are the same amount that will either increase or decrease and in the real world situation for us it becomes difficult to apply it in economics no doubt mathematically we can multiply it in the same way but if we go in the real world situation then you can see that in many things if we count as an example I had already put the agriculture in front of you then in the production of wheat it is possible that a farmer who was putting 40 kg seed in the field instead of putting 40 kg seed, we can say that he started putting 60 kg seed and if he was putting 1 bag of fertilizer first then he started putting 2 bags means he is doubling it but it is not possible that he says that as much as I have one bag of lands, I have to double it definitely because it will require some IPR or more cost is involved and in the same way sometimes we have a managerial skills issue and if we look at it we say that if any farm is there it is mostly a boss, now that boss or managerial can make its decision now if he has to enhance the production then he can enhance the inputs but the boss, the manager or the producer is also a part of the management team and if we are going to double the same then there might be a conflict between those instead of increasing the production it will start decreasing and in the same way we can say that the farmer who took the first example of agriculture that he might have had one bag of land to increase his production then he says that he should double his land now he takes two bags of land but production in that way and he also doubles all the inputs in the same amount he is adding as much water as he was putting the unit on one bag and he is doubling it in the same amount so now he expects that if the first farmer I had had 40 months then now I have 80 months from two fields but the possible farmer is getting 100 out of 80 and this also might be 60 out of 80 the reason being all the factors are constant but we have not included the fertility of that land meaning that was, that is not explicit if we say that this is an intrinsic or a latent quality and sometimes it is also possible that a particular weather condition and both the space of land are at a distance so one's weather and the other's are different so these are certain factors which if we say in real life then we say that that is not possible that the concept of scaling if we are in the case of multiple inputs then mathematically then maybe we can put all the rules in the same form and explain them and prove them but in the real life situation sometimes the concept of scaling for all types of inputs sometimes it becomes very difficult to put them on and that is why the law of diminishing productivity is in the same way if we call it diminishing returns to scale then we can utilize it in the same way because actually in terms of diminishing returns to scale because somewhere we will have some factors of production in that production function which we cannot scale which we have to keep fixed like we have already talked about the manager or the land or a farm which cannot duplicate its production unit so likewise there will be some aspect which will not be possible to scale in the actual form so the multiple input case mathematically and technically is going to follow all the rules that we have studied for two input cases and we have applied that as Euler theorem we have applied the rule of isoquant we have looked at the point of tangency we have looked at returns to scale they all will be applicable but in the real life situation sometimes it is difficult to follow all these rules thank you


It's been a long time since I've done a shopper job, which is Samantha Marches, will I buy it series? I just gave it a different name. Because quite frankly, I have not even been paying attention to the new launches being posted on Trend Mood. I've been quite uninterested. You know, if something comes out from a brand that I love and I love it, then I buy it. Today's gonna be a roast, because I've been getting a lot of questions about what I think of some new products coming out. So I thought it was a good time to do a shopper job. I've scrolled down a couple of weeks on Trend Mood Ones Instagram page, which I will link down below if you do want all of the information on new releases. If you're interested in my makeup look, I will have the products that I use down below. This tutorial I filmed for my monthly YouTube membership beauty buffs. I think by the time this shopper job is posted, I will not have this tutorial up yet, but this is what is up and coming for my YouTube membership. So if you are interested in joining, you just click the join button down there. And when you join, you get one monthly makeup tutorial. And this is this month's makeup tutorial and it's so fun. Anyways, let's get into the goods. I scrolled back about a couple of weeks. Things that I think are still somewhat relevant for me to talk about. And the first item that we have here is the YSL New Lip and Cheek Balmy Tint. I do believe this is launched now. I've never tried an item from the new line from YSL and I don't do why because it definitely is something that intrigues me and that I am interested in. And this product I am interested in for this time of year. I am a sucker for a product like this. I've been playing around a lot with cream blushes because it seems to be what you guys are interested in. I'm not gonna get it. If I do like a big Sephora haul or something, I think I'll pick one or two up. So I am interested, but I'm not like running out of my seat to pick this up considering I'd never tried anything from this line from YSL. I really am interested in trying a few products from this line.  I just feel like I have so much makeup that do I really want to add more products to my collection? I mean, I do, but do I need to know? But I'm interested in this. This is actually, I think, gonna give me the push to try other products from the line as well. So I am interested in that. If you've tried the line before, let me know what you think.  Oh, let me scoot over here, sorry. Any more room for the pictures. So coming soon to Sephora is Scarlett Johansson. Okay, Scarlett Johansson is launching a skincare line. I think it's smart. If celebrities are going to launch a beauty brand at this point, then it'd be skincare, but I am so incredibly uninterested. I am tired of the celebrity skincare and makeup brands, especially when the celebrity has like no background in the field.  I do like my skincare. I do love testing new skincare. However, my skin does not like testing new skincare, so I have to be very selective in the products that I choose. I'm not a big Scarlett Johansson fan. I don't watch very many things that she's in. I've just never, I think Jose likes her. I think she's one of Jose's favorite celebrities, anyways. Yeah, I'm not interested in this and this is random, right? Anyways, let's keep moving. We're gonna start off with a hot one here. This is the Pat McGrath Labs skincare, for first skincare item. It is the Divine Skin Rose 001, the essence. So it's a skin essence that's supposed to hydrate, revitalize, and give luminous skin. I'm dropping this, I am not buying this. This is like the first Pat McGrath item that I will be passing on. Don't get me wrong, it looks interesting. The packaging looks beautiful. I can get smart for her to include skincare, but Pat McGrath is a makeup artist. I'm not interested in really buying skincare from her. And like I said, this is just coming from a standpoint of I'm not a skincare influencer. I have very sensitive skin. I can't be messing around with my skincare routine too often. This just doesn't have a place in my skincare routine, so I'm not interested. If it was a color product, a makeup product, you know I'd be all over it. But this is the first Pat McGrath Labs item in a while that I will be passing on because I'm not interested. I don't need skincare, but skincare is huge right now, so it makes sense to tap into that market as a brand. But yeah, I mean, I thought it was a makeup item. When she was doing her sneak peeks and all of that, I was like, ooh, yay, exciting. And then it was this and I was like, but it is launching tomorrow if you're interested. I will make a community tab post if you do plan on picking it up, but just, I'm not interested in skincare right now. It's just not something that I need, you know? These look super interesting. These are from Givenchy and these are the Prismet Libre pressed powders. I am not as familiar with Givenchy as a makeup brand, so I will be dropping this from my list, but I'd be lying if I didn't say that this wasn't very visually appealing to me. It's something that I would like to pick up, but I certainly don't need it and I'm just not that interested, you know? Givenchy isn't a brand that I cover on my channel, but these look beautiful and I know Givenchy does gorgeous powders. I don't know if this is available yet in the US. Like, I feel like this is a product if I'm in a good mood, in a spendy mood and I see this in Sephora, I would pick it up. So I'm not completely crossing it from the list because I do like Givenchy powders and I love how they have these color correcting tones here, but I'm not going out of my way to pick it up because, you know, I don't need it, but they look stunning. Oh my gosh, there's an even bigger range. Wow, okay, these look awesome. It looks like it's going to be $46. Like, I'm totally interested, but I don't need it, but I'm interested. Ooh, okay, so Sol de Janeiro came out with a new hair and body fragrance mist. I love Sol de Janeiro, I love the bum bum cream. I have it in a perfume, in a body spray, though those don't last that long. This is Fruity Florals. The keynotes are Brazilian Jasmine, pink dragon fruit, sheer vanilla, throw a vanilla in there and I'm all over it. I'd be interested to smell this. My only hesitation is while I do love Sol de Janeiro and I love their scents, I don't think they last the longest on the skin. So when I use my fragrance mist from Sol de Janeiro, I spray a ton of it and it disappears. So I don't think I will like this, but I like the sound of it. I might want to smell that in person first. This looks extremely interesting from me. This is from Joan Road's Beauty, which is Boppy Brown's makeup brand and I mean, maybe it's just my feed, but she's going viral on TikTok, right? And I'm so happy she brought her brand to TikTok. I knew about her brand before, but I just don't think there was enough interest in the brand for me to justify purchasing her products. And now it seems that there is enough interest in the brand. I am very interested, interested. How many times did I say that? So this is the What the Foundation Tinted Moisture Balm. So it sounds somewhat similar to what Wayne Goss just launched, what Denessa Myricks just launched. We're getting a lot of potted foundations and of course the Joan's Roads Beauty brand is gonna be more about natural makeup, enhancing your natural beauty. That's not what I'm about, as you can tell, but I am super interested. I don't know, it's already launched. These are $44 each and I'm really interested. I don't know if I'm ready to pull the trigger yet, but I'm just, I'm gonna say shop because I do have it on my list of videos to eventually film buying a bunch of products from this brand and testing it out because I love Bobby Brown. I have the Bobby Brown books. I think she's just a cool lady. You know, I do like her perspective on makeup though it doesn't exactly align with mine. I'm interested in this. So I'm not pulling the trigger yet, but I know eventually I will try this and I got excited about this. So it says it's a tinted moisturizer balm meets traditional foundation. So I'm interested. I don't know, should I get shade light or beige? Okay, we have another complexion product. This is a sneak peek. I don't believe we have a launch date on this yet. This is from Hood of Beauty. This is the Faux Filter concealer. Have they come out with a concealer before? If they have, I don't own it. I haven't had the best luck with Hood of Beauty complexion products. I love their setting powder, but in terms of like foundation, I've never really liked their foundations, but I will be trying this when it comes available. So this is a shop, I don't know. I just curious, I need to know. I don't have a lot of luck with Hood of Beauty and Hood of Beauty is one of the brands that I cover on my channel. So this is something of interest to me. It says that this has a luminous matte finish. Not much more information on this, but you know, Hood of Beauty is a top selling brand and they have some major hits in their line. They also have some duds. So Hood of Beauty is one of those brands where they're very quick to get rid of their duds. If the people don't like it, they stop selling it and they reformulate it. This I believe is a reformulation. We'll see, I might be wrong, but I want to try it. Ooh, okay, so I did want to talk about this. Charlotte Tilbury, don't have a launch date on this yet but she's coming out with a beautiful skin sun-kissed glow bronzer. This is a face and body cream bronzer. This is one of the items that I'm most excited about in today's video. Love the powder bronzers. Super excited to see what we do with the cream bronzers. I just, I have a feeling that this is going to be amazing.  I just, I have a feeling. So it looks like it's going to come in four shades. It's going to be $55. I probably will pick up both fair and medium when I order this, when it becomes available. But I'm excited about this. This is going to be good, you guys. So the Charlotte Tilbury Cream Bronzer is most definitely a shop, undoubtedly. We're getting that, we're testing that. I also see that Psy, which is a new brand kind of on my radar that I'm low-key watching is coming out with the Hydrabeam Brightening and Hydrating Under Eye Concealer. So what I've been so pressed on lately is the Psy Cream Bronzer. This is the only product I've ever tried from the brand, but I'm obsessed with it. I believe it is a cream beauty brand. And yeah, I'm interested in this. I'm saying drop for now. I don't have much interest in running out and getting it, but it did become available in May 2nd. I mean, I haven't tried much from the brand, so I can't say too much about the brand, but I can say that the only product I tried, we have a 100% success rate. So I'm interested in eventually maybe giving this a go.  Ooh, okay, so this is interesting. So we have a first look, according to trend mood of the Better Than Chocolate Collection. Did we need this? Did anybody ask for this? No, nobody asked for this. It looks like the same palette that Too Faced has been launching for the past eight years. Neutrals with a pop of blue and a pop of purple. This is nothing new at all. Will I be buying it? Yes, I will be. I don't know what it is. I always come back to this. The lipsticks actually look quite pretty as well, but it's a whole collection. There's an eyeshadow palette, eight cocoa bold lipsticks with a white chocolate and raspberry scent. I'm a foodie, I like the way that sounds. A chocolate lip injection and then a liquid eyeliner. So this is supposed to be coming in July, but honestly a lot of times the stuff launches earlier, sometimes on QVC, HSN, Ulta. There is nothing interesting or new or exciting about this palette at all, but I think with a lot of us, the chocolate palettes hold such nostalgia. And if it's supposed to be better than the chocolate palettes, I'm just gonna get it to try. If I didn't have a YouTube channel when I buy it, absolutely not, but I'm shopping it. I cannot help myself, I have to try it out, okay? Side note, this is more news than it is at launch, but did you see House Laboratories by Lady Gaga has cleaned their Instagram? And this is usually what brands will do when it's time for a rebrand and it is overdue for a rebrand. Let me just say that. Nothing about this brand has ever interested me. The only times I've gotten anything from this brand were like in an Ipsy bag and I didn't even use them. This brand just has not appealed to me at all. I heard the products were decent, but nothing innovative or exciting about the brand. I mean, this is Lady Gaga's brand to me. It's just another celebrity cash grab, but yeah, I do think a rebrand is coming. So I'll be interested to see. I mean, I'm super interested in what is going on in the makeup market, but it's not a brand that has ever really interested me and I'm happy to see them going through a rebrand because I feel as though they probably needed that. This one is super interesting. So another celeb make-up brand, Alicia Keys is coming out with some color products in the Keys Soul Care. Now, Alicia Keys did recently come out with a skincare line and honestly that made sense to me more so than like the Scarlett Johansson line because Alicia Keys is all about the skin. She doesn't really wear makeup. She even said she wouldn't wear any makeup in the past. I think she's wearing some products now.  So like who cares? Like she can wear what she wants. She's done with not wearing makeup. I'm interested in those pots. I won't be picking up anything from this brand. I'm not interested. Definitely gonna end up being too natural. Won't be a product that I would ever reach for. Much rather would try Jones Road's Beauty. But this is interesting that she's coming out with color products considering the stance she did have a few years ago about makeup. What do you think? I'm not interested though, so yeah. I'm personally not gonna buy this collection. So this is a drop. It may or may not come in PR. I can never tell. But ColourPop collaborated with Star Wars for this. And it's not that this collection doesn't psych me. It's just that I'm not a Star Wars fan so it just doesn't make sense for me. But if I was a Star Wars fan, I would totally get this. I love the color story of it. I feel like it's totally Star Wars-y. I love the galaxy colors that they have in here. And this is a fun one. Nobody does a collaboration better than ColourPop. This is really, really neat. I'm just not interested in Star Wars. So I wouldn't purchase it personally. But if I do get it in PR, honestly I would not be mad like at all. But no, I don't need this. Yeah, but it looks really cool. It's a drop for me though. But that's just based on my own personal preferences. I'm looking through. There's just so many gimmicky things on Treadmood that I am just not remotely interested in at all. So we have this collection from Morphe. I feel like Morphe's makeup brand has kind of fallen off. People aren't as interested in it. But I mean, I think Morphe is thriving as a company because they have so many companies under their umbrella. They came out with this Gilded Desert collection. And it's a lot of browns that we have going on. The palette looks extremely uninteresting to me like any other Morphe palette. Half of the palette is just repeating itself. The bronzers look nice. I mean, no shade to Morphe. I think it's really great. The quality products that Morphe can provide for the price point. I have a lot of Morphe products that I love in my collection. But this one does not appeal to me at all. It's just a lot of brown. Too much brown.  It's within your budget. This looks like a nice collection. Okay, the very last product that I wanted to talk about in today's video. Another exciting one from Charlotte Tilbury. So these are the Smart On The Go kits. These look super interesting. Though one of you guys or a couple of you said that this reminds you of like a cigarette pack. And that I do agree with. But it's supposed to be like an easy three step makeup routine. You can take it with you on the go. There are five different looks that you can get. I just, I love the whole marketing behind this. I think this is really cool. I picked up the shade Date Night in case you're wondering because it had like a pretty rosy eye color, a rosy cheek and lip color. It just really appealed to me. I wish instead of the highlight, we got a bronzer. People are stepping away from highlights now. It's more about the contour. But other than that, I'm excited. I will be reviewing it. There's $75 each, which is kind of expensive, which is why I only picked up one. But obviously if I love it, I will probably pick up a couple more. But I will be shopping this. I already did. I will be reviewing this. I am excited for this product. It looks really interesting. I don't want to say different, but it's different for Charlotte Tilbury. We'll see. But I'm excited about this. It's very intriguing of a product to me. It does not look like anything I need. It doesn't look like anything really innovative. But I'm excited for it and I'm gonna try it. So there we go, you guys. That was my shopper drop. It's been a while since I've done it. Felt good to just go through and trend mood and tell you what I think of the new products. So what are you excited about? What are you bored by? Do you agree? Disagree with anything that I said? Let me know. Thank you guys so much for watching my channel, liking this video, all that good stuff. If you aren't subscribed to me already, I would love it if you would consider doing that. And I will catch you guys in the next one. Bye guys, have a good one.


So we're here with an air button and who are you? Yes, I'm Auschwitz a co-founder of Everton So what is what are those buttons? Yeah, Everton is a battery-free wireless socket button for NFC Android phone and it helps people to control smartphone in one simple click So this is a NFC phone right here. Yes. This is a Sony Xperia Z1 Z1. Yes, and you put this button on the back and then what you can do with those buttons Yeah, I can show you. Actually, I already said some function here. Maybe I'll show you the first one here Once you pass, here you launch the camera and has one more button. Cheers You want to take a selfie? The same button or two different buttons? Only same button. Same button launch the camera Yeah, and also take the picture. Yes, and what is the other button? You have two there, right? Yes Another button is for a girl's use. When the girls may become home-nater and feel someone for her And what can she do? Just press the button and it will have the alarm and also the torch to threaten the phone Well, so this is a you can launch any app you want. Yes, you can set it in our app And in our app, you can see that there is many functions inside Here or here You can use any app on the phone. Yes, you can see there is many functions What is it possible to do something inside the app? Yes, we can check in Facebook for the latest version of Also, we can develop more functions with the intelligence device So how can you go inside the app and do something like the camera? You took a picture inside the camera app How you do? We develop our camera app, but maybe for Facebook we can use their API to make our own functions Right. So here's two buttons. Yes like this. This is one button. Yes, and it's touching and I can have 30 functions functions. How can I have so many I can choose all these Yes, and you can also combine that to form a millions possible combination Combine them, but you can only have a maximum how many to Yes, two buttons, but you can in one button click Single click you can combine many functions together. Is it possible to also use the NFC for payment and everything? It's not covering, right? Yes, no covering. You can use normal NFC. It doesn't block it Yes, no problem. So how much price? Where can people buy this? Yes? I we will do the car funding in Indiegogo very soon actually is in 27 of this month So 27 of October. Yeah And then how much for the two-button version is 21 US dollars Oh, of course if you come early to you can get the early bird offer. Yeah, what's the early bird offer? Yes, how much how much is 18 US dollar 18? How about the one button one button is 15 US dollar and the early bird offer is 12 so where are you based we based on Hong Kong and What you do before? I'm just study before study. Yeah, so you just come from school make this company. Yes, cool How's the response so far? How many people see your product? Awesome So many people like our product that because it is a quite still in the market and low battery But still can do a wireless control


I want you to give me, give an assessment of where we are in this battle about the future of energy. You've obviously had a huge impact, but the world seems to still be going against us. There is an energy crisis right now, and people are making a lot of really bad decisions. Our leaders are making a lot of really bad decisions, but as you said, it's an opportunity because people are thinking about these things. Give us an assessment of where we are and also how much of an impact you've had on intellectuals versus business people versus maybe policy people. I think of it as there are three big variables right now. You can think of it as the overwhelming anti-fossil fuel movement, the growing energy humanist movement, and then the current energy crisis. The overwhelming anti-fossil fuel movement, I think people are pretty aware of that, but basically you can think of it as the number one moral goal in the world today is rapidly eliminating fossil fuels. As evidenced by corporations say we're going net zero, which basically means rapidly eliminating fossil fuels, governments have all signed on to it. If you want status, just be anti-fossil fuels. I should say it's starting to change because of an energy crisis, but we'll get to that one in a second. That's a very bad sign, and that's been getting worse in many ways since moral case came out. The second thing, which is very promising, is what I'd call the burgeoning energy humanist movement. By energy humanist, I mean somebody who is thinking about energy and its impacts, a positive and negative, in a pro-human big picture way. I would put in that category me, Steve Kuhnen, Michael Schellenberger, Bjorn Lomborg, Matt Ridley, Robert Bryce, and more and more are coming up.  This false, you're either a believer or a denier in climate change, and that determines your position on fossil fuels. We've really changed it to, no, you have to look at the big picture, the full context. It's very possible that we could be impacting climate, that A, some of that could be good. In any case, B, that any negatives of that were far outweighed by the benefits of fossil fuels, including their amazing ability to protect us from climate by using machines to make it hot, to make it warm when we need it and cool when we need it and irrigate it, et cetera, et cetera. What's interesting about that is we've gotten, there have been many bestselling books in that school of thought. The Wall Street Journal, for example, has really picked that school of thought up. I mean they had at one point 11 things by Lomborg in a row in the lead to the COP26 climate thing last year. So, and of course we have somebody in Energy Humanities running for governor of California who's been featured widely and who's not apologetic about that at all. He's not apologetic even about his association with me, which I've told him, like, feel free to not, but he's like, no, he just says what he thinks, which I really admire, and he's coming on the podcast on Monday, actually on my podcast to talk about stuff. So that's good. Now there's the danger, though, when you're part of a movement that's burgeoning that you can kind of overstate how significant it is because it's still like being swamped in a certain way. And the third thing, but the most, maybe the most heartening thing to me is that the other side doesn't really have any answer to us. So they've resorted to a lot of smears. They do a lot of straw manning. So they did this to Kuna. They did the Schellenberger Washington Post tried to portray me as a racist. That was their answer to fossil future. So it's like, but they don't really do, they're not doing well. They haven't changed their arguments.  And I think people are starting to see that. I mean, you saw, for instance, Koonan was on Joe Rogan, which I think is a big kind of cultural sign. So the energy crisis is then. So I was already optimistic that we could make a lot of progress even before the crisis. And in part, I knew one was coming at some point. I talk about it at the end of the book. But now there's a heightened awareness that it is that that today there's something very wrong with today's policies because people are paying higher gasoline prices. They're seeing more blackouts.  We're in an energy transition. So you see like at gas stations, the the Joe Biden, like I did that stickers pointing, you know, it's an arrow pointing to the price. So you've got openness. This doesn't at all guarantee that the right narrative will take over. But it gives an opportunity and it particularly gives an opportunity if those of us who have been right, take credit for being right and criticize the others for being wrong. So you remember when 9 11 happened, like people like Daniel Pipes, who had said things about, hey, we need to be worried about this threat. They rose in credibility. But look what happened to Peter Schiff with the financial crisis because he had that highlight reel of things that he said, which is not to say he's been right about everything since, but he had that highlight reel like on Art Laffer's show and stuff. And he just skyrocketed to prominence because it's like he predicted this crisis. And so one thing I'm very deliberately doing and unapologetically is I'm looking at my track record, like, for example, I testified in front of Congress warning about all of this in 2016 in front of the Senate. And I was ridiculed as I don't want to be lectured by a philosopher. And I said, you have to look at the big picture. You have to look at the benefits of fossil fuels. And Barbara Boxer didn't and look at look at where we are. So we have to really take credit for having been right about this. And then and then really clearly put forward an alternative view. And so that's why I'm very happy to have a book coming out that that's a total energy reeducation right at this moment when people are open to it. So that's that's why you don't know what's going to happen. But you don't want to be pessimistic if you see something growing and you see an opportunity. I should also say with with the groups you mentioned in the last couple of years, I've been quite influential in politicians. I now work with over a hundred elected officials and offices. And you're starting to see more of them talk well. And right now I'm working on an energy freedom platform, which I think will be the next level of influence. But already I'm consulted again by dozens of different offices. I meet with people all the time with, you know, with industry. I've definitely had a large influence. You're seeing CEOs speaking out more and more, which never, you know, at the beginning, we never has never happened when we would talk about this 20 years ago or whenever I got started on this.  Some of the a lot of the free market energy people have definitely been influenced. And I get a lot of support from them. But one of my real focus in fossil future is really breaking through to as many kind of influencers, whether in energy or outside, by just giving a totally airtight case. The moral case was great, but it wasn't super comprehensive. It wasn't nearly as step by step airtight. And I mean, I'm dying to see what just people on the fence think of this. Like, I'm so curious what their answer is going to be, because it's it's like, I spent three years trying to refute it. It's by this time, it's really hard. So I'm so curious. You see intellectuals out there on this issue being on the fence. Are there intellectuals on the fence on this issue? Well, yes. And I guess I should say influencers. So intellectuals, if it is it, you know, my professors at Duke University, maybe some of them, but not so much. But I'm thinking even more of the even if you just take the kind of middle slash open to the right people like Joe Rogan, Barry Weiss, you know, something like Stephen Pinker is really interesting. I think he cites moral case in his first book. I don't know if he's read the whole thing, but I would love him to read this. You know, even Sam Harris is that's a really interesting one because he has had a lot of antagonism toward fossil fuels. But I think he so those people matter alone more than they used to. Yeah, he's he hasn't unblocked me from Twitter yet. So we're baby steps. He is praised in the book and criticized in the in the book. So I'm not going to bet anything in his case. But, you know, I think I think it's there's there's more of a blend than there used to be between influential people intellectually in the culture and then in academia. So for me, it's just there are hundreds of kind of smart people out there whom who are very influential that I think would be open to this. And I'm very curious to see how they react. I've gotten some initial good signs, but I want to see like, does this take off? Do people start talking about knowledge system designated experts ignoring benefits, catastrophizing side effects, climate mastery, like climate mastery denial, all of these things. I think there's a good chance. Cool. So let's see. So first, I want to remind everybody about buying the book. We got a bunch of new new people joining. So don't forget to buy the book. You can buy it on Amazon or pretty much any bookstore out there. You know, it's it's great in order to get on the best sellers. We're on a lot of individual orders. So go out there and buy a book for yourself. Buy books for your friends. Use Amazon, use bonds and mobile, use other websites. You don't buy as many books as you can. And the key is to buy it this week, really, the sooner, the better. Yeah, before, before basically before the end of next weekend, like by next Saturday. Yeah. So over the next seven days, six days, by the book. And it's it it's available on May 24th. But if you go today and buy it, that counts. If you buy it a few days after it becomes available, that counts still. But it really is that first few days that are the key to getting on the best seller list to go out and and and buy the book.  Not it won't be huge, but it'll it'll significant. It'll it'll help. It'll bring some. I think if everyone who listens to your show bought the book, certainly if everyone bought two, it would go in New York Times bestseller list based on how many it sold already. I think that's right. And knowing that the numbers for the New York Times bestsellers are not that huge as one is some millions, right? It doesn't take millions on the on the bet New York Times bestsellers to take tens of thousands and tens of thousands. We should be able to do quite easily. So so so do it by a couple of books. I've already bought the kindle. I don't know if the kindle counts. Is kindle count? Yes. Yeah, it does for New York Times. I believe it does on an audience. I need to send you a signed real copy. I believe audible does. I don't know exactly. But so I might buy I'm probably going to buy an audible, too, because I'll probably I'll probably do my I read it quickly, I guess, months ago when I wrote the blood. And then but it would be good. It would be good to listen to it on one of my walks. And I recorded, I should say, I recorded. Oh, you took me a long time. I recorded that thing for, yeah, for various reasons. It took longer than I thought, but it's 16 hours. And it took me 35 hours to record. So I would have more than 35 hours. So that's pretty good. Oh, my gosh. Well, I would have. Yeah, I would highly. I would say I put a lot into recording this thing because no one really wants the authors to. And it's not some Shakespearean thing. And my I want Alex's voice in my ear for for for 16 hours. Yeah, that's that's what it is. It's it's that people don't because imagine. I mean, you know me well, like just listening to my book and someone else's voice, even if it's an amazing voice, it's a little bit weird. So I it's not my favorite thing and all to read things out loud precisely. But I did it because people value it. So I hope a lot of people enjoy the audible. All right, we're going to jump into the super chat because there are a lot of questions. Some of them are comments, some of them are questions, almost all of them related to what we're talking about. Some are not. But we'll let Alex decide if he wants to answer them. No, they're all good. They're all positive. So this is some Jeff, it's 200 plus Canadian dollars. So I'll read it. I'm going to read it. We are we're not yet in the dystopia of Anthem, but it seems that they have us on a backward trend towards candles and barely being able to care for ourselves. Thanks for keeping up the fight. So it's more thank you than anything else. So thank you, you're welcome. Maybe it is the time to highlight another positive vellum. I'm seeing that didn't wasn't existing when moral case came out was just more and more people from the poor parts of the world standing up for themselves. I was just talking to a guy right before this, who's an agricultural engineer from Kenya. And he's he's trying to get his education in the UK. And he was a Greenpeace activist. And now he's a huge champion of fossil fuels. Like great. Think about that. They co-opted people in poor countries even. And it's like, but you're seeing more and more people. I met a guy at a conference recently from South Sudan. And he's like really influenced by my Google talk and real. So it's exciting to see. And the cool thing is this is almost accelerating because there's not much opposition. And the more people who talk about these things, the easier it is and the harder it is to just be dismissed as a climate denier. Yeah. And in my view, in a sense, it's much easier for them to to accept this in poor countries because it's a life of death issue for them. Yeah. A life of death issue for us as well. But it doesn't seem like a life. Like it's not it's not it's not imminent. It's not concrete enough. And for them, it's imminent. It's concrete. They know exactly what's at stake. They're still poor. They know what poverty looks like. They know what death is in a kind of a sense that I don't think we realize in the West. And so I think this should take off in places like Africa. I certainly hope so. And it makes me optimistic about the potential for Africa. Thank you for listening or watching the Iran book show. If you'd like to support the show, we make it as easy as possible for you to trade with me. You get value from listening. You get value from watching. Show your appreciation. You can do that by going to Iran book show dot com slash support.  Also, if you'd like to see the Iran book show grow, please consider sharing our content. And of course, subscribe. Press that little bell button right down there on YouTube so that you get an announcement when we go live. And for those of you who are already subscribers and those of you who already supporters of the show, thank you. I very much appreciate it.


We're all better for knowing Matthew Slater, and if you've got to spend some time with him, which a lot of you guys in this room have, you know that to be true, so we're all better for Matthew Slater. To watch his growth from, you know, when he was a rookie, come out of UCLA, and trying to find a little bit of position on offense and defense, and ultimately, you know, becoming, I would say, good special teams players that have ever played this game, and certainly he has everything to back that up based on his long sustained success and being the targeted guy every week, and his leadership and presence for the team, not just the players, the organization, the staff, and these inspirational all of us.


The overall goal of conquest is to increase our interoperability with our partners, all our multinational partners, particularly the Mongolians. This is a huge way of showing that we can work with multiple nations. They're not just the Mongolians here, we have the Canadians, we have the Koreans and the Germans as well. So that interaction with all these other forces shows us that the United States can interact with anybody. I remember it was in 2011 and we used to have like 300 or 400 patients a day. Now whereas we are saying like in the afternoon we have already gone through the 600 patients. So by showing up to their houses that shows the United States is fully committed to showing how we are willing to participate with the Mongolians, work with the Mongolians and show the Mongolian people really that the Americans are a very good friend to have.


CHAPTER I I COME FROM haunts of coot and hern, I make sudden sally, and sparkle out among the fern to bicker down a valley. By thirty hills I hurry down, or slip between the ridges.  I chatter over stony ways, and little sharps and trebles. I bubble into eddying bays, I babble on the pebbles. With many a curve my banks I fret, by many a field and fallow, and many a fairy foreland set, with willow weed and mellow. And here and there a foamy lake, upon me as I travel, with many a silvery water-break above the golden gravel, and draw them all along, and flow to join the brimming river, for men may come and men may go, but I go on for ever. CHAPTER II Song from Maud See what a lovely shell, small and pure as a pearl, lying close to my foot. Frail, but a work divine, made so fairly well, with delicate spire and whirl, how exquisitely minute, a miracle of design. What is it? A learned man could give it a clumsy name? Let him name it who can. The beauty would be the same. The tiny cell is forlorn, void of the little living will, that made it stir on the shore. Did he stand at the diamond door of his house in a rainbow frill? Did he push, when he was uncurled, a golden foot, or a fairy horn, through his dim water world? Slight to be crushed with a tap, of my fingernail on the sand. Small, but a work divine, frail, but a force to withstand, year upon year, the shock of cataract seas that snap the three-decker's oaken spine, a thwart the ledges of rock, here on the Breton Strand. CHAPTER III Flow down, cold rivulet, to the sea, thy tribute wave deliver. No more by thee my steps shall be for ever and for ever. Flow, softly flow, by lawn and lee, a rivulet than a river. Nowhere by thee my steps shall be for ever and for ever. But here will sigh thine alder tree, and here thine aspen shiver, and here by thee will hum the bee, for ever and for ever. A thousand suns will stream on thee, a thousand moons will quiver. But not by thee my steps shall be for ever and for ever. CHAPTER IV SONG FROM MOD Come into the garden, mod, for the black bat night has flown. Come into the garden, mod, I am here at the gate alone, and the wood-bind spices are wafted abroad, and the musk of the roses blown. For a breeze of morning moves, and the planet of love is on high, beginning to faint and the light that she loves on a bed of daffodil sky, to faint and the light of the sun she loves to faint in his light and to die. There has fallen a splendid tear from the passion flower at the gate. She is coming, my dove, my dear.  The red rose cries, she is near, she is near, and the white rose weeps. She is late, the lark spur listens, I hear, I hear, and the lily whispers, I wait. She is coming, my own, my sweet, were it ever so area tread. My heart would hear her and beat, were it earth in an earthy bed. My dust would hear her and beat, had I lain for a century dead, would start and tremble under her feet, and blossom in purple and red. CHAPTER V. BREAK, BREAK, BREAK. BREAK, BREAK, BREAK, on thy cold grey stones, O sea, and I would that my tongue could utter the thoughts that arise in me. O well for the fisherman's boy, that he shouts with his sister at play. O well for the sailor lat, that he sings in his boat, on the bay, and the stately ships go on to their haven under the hill. But O for the touch of a vanished hand, and the sound of a voice that is still. BREAK, BREAK, BREAK, at the foot of thy crags, O sea, but the tender grace of a day that is dead will never come back to me. CHAPTER VI. Love took up the glass of time, and turned it in his glowing hands. Every moment, lightly shaken, ran itself in golden sands. Love took up the harp of life, and smote on all the cords with might. Smote the cord of self, that trembling, passed in music out of sight. Many a morning on the moorland did we hear the copes' ring, and her whisper thronged my pulses with the fullness of the spring. Many an evening by the waters did we watch the stately ships, and our spirits rushed together at the touching of the lips. O my cousin, shower-hearted, O my Amy, mine no more, O the dreary, dreary moorland, O the barren, barren shore. CHAPTER VI. SONG FROM MAUD. Go not happy day from the shining fields. Go not happy day till the maiden yields.  When the happy, yes, falters from her lips. Pass and blush the news over glowing ships, over blowing seas, over seas at rest. Pass the happy news, blush it through the west, till the red man dance by his red cedar tree and the red man's babe leap beyond the sea. Blush from west to east, blush from east to west, till the west is east. Blush it through the west, Rosie is the west, Rosie is the south, roses are her cheeks, and a rose her mouth. CHAPTER VIII. SONG FROM THE PRINCESS. Sweet and low, sweet and low, wind of the western sea, low, low, breathe and blow, wind of the western sea, over the rolling waters go, come from the dying moon and blow, blow him again to me, while my little one, while my pretty one, sleeps. Sleep and rest, sleep and rest, father will come to thee soon, rest, rest on mother's breast, father will come to thee soon, father will come to his babe in the nest, silver sails all out of the west, under the silver moon. Sleep my little one, sleep, my pretty one, sleep. END OF CHAPTER VIII. CHAPTER IX. LILLIAN. ARI. FARY. LILLIAN. FLITTING. FARY. LILLIAN. When I ask her if she love me, claps her tiny hands above me, laughing all she can.  When my passion seeks pleasant in love sighs, she, looking through and through me, thoroughly to undo me, smiling, never speaks, so innocent arch, so cunning simple, from beneath her gathered wimple, glancing with black beaded eyes, till the lightning laughter dimple, the baby roses in her cheeks, then away she flies. Pry thee weep, may Lillian. Gayety without eclipse, wearyeth me, may Lillian. Through my very heart it thrilleth, when from crimson-threaded lips, silver treble laughter trilleth. Pry thee weep, may Lillian. Praying all I can, if prayers will not hush thee, airy Lillian, like a rose leaf, I will crush thee, fairy Lillian. CHAPTER X RING OUT WILD BELLS. Ring out wild bells to the wild sky, the flying cloud, the frosty light, the year is dying in the night. Ring out wild bells and let him die. Ring out the old, ring in the new. Ring happy bells across the snow. The year is going, let him go. Ring out the false, ring in the true. Ring out the grief that saps the mind, for those that here we see no more. Ring out the feud of rich and poor, ring in redress to all mankind. Ring out a slowly dying cause, and ancient forms of party strife. Ring in the nobler modes of life, with sweeter manners, purer laws. Ring out the want, the care, the sin, the faithless coldness of the times. Ring out, ring out my mournful rhymes, but ring the fuller minstrel in. Ring out false pride in place and blood, the civic slander and the spite. Ring in the love of truth and right, ring in the common love of good. Ring out old shapes of foul disease, ring out the narrowing lust of gold. Ring out the thousand wars of old, ring in the thousand years of peace. Ring in the valiant man and free. The larger heart, the kindlier hand. Ring out the darkness of the land, ring in the Christ that is to be. End of chapter 10 CHAPTER 11. FROM THE PRINCESS TEARS. IDLE TEARS. I know not what they mean. Tears from the depth of some divine despair rise in the heart and gather to the eyes and looking on the happy autumn fields and thinking of the days that are no more. Fresh as the first beam glittering on a sail that brings our friends up from the underworld. Sad as the last which reddens over one that sinks with all we love below the verge. So sad, so fresh, the days that are no more. Ah, sad and strange, as in dark summer dawns the earliest pipe of half-awakened birds to dying ears, when unto dying eyes the casement slowly grows a glimmering square. So sad, so strange, the days that are no more. Dear as remembered kisses after death, and sweet as those by hopeless fancy feigned on lips that are for others. Miss love, deep as first love, and wild with all regret.  CHAPTER 12. SONG. FROM THE PRINCESS. The splendor falls on castle walls and snowy summits old in story. The long light shakes across the lakes, and the wild cataract leaps in glory. Blow, bugle, blow, set the wild echoes flying. Blow, bugle, answer, echoes, dying, dying, dying. O hark, o hear, how thin and clear, and thinner, clearer, farther going. O sweet and far from cliff and scar, the horns of Elfland faintly blowing. Blow, let us hear the purple glens replying. Blow, bugle, answer, echoes, dying, dying, dying. O love, they die in yon rich sky, they faint on hill or field or river. Our echoes roll from soul to soul, and grow for ever and for ever. Blow, bugle, blow, set the wild echoes flying, and answer echoes, answer, dying, dying, dying. END OF CHAPTER XII. CHAPTER XIII. FROM ENIC ARTON. The mountain wooded to the peak, the lawns and winding glades high up like ways to heaven. The slender cocos drooping, crown of plumes, the lightning flash of insect and of bird, the luster of the long convalvuluses, that coiled around the stately stems, and ran even to the limit of the land, the glows and glories of the broad belt of the world, all these he saw. But what he fain had seen he could not see, the kindly human face, nor ever hear a kindly voice, but heard the myriad shriek of wheeling ocean fowl, the league long roller thundering on the reef, the moving whisper of huge trees that branched, and blossomed in the zenith, for the sweep of some prespicious rivulet to the wave, as down the shore he ranged, or all day long sat often in the seaward gazing gorge, a shipwrecked sailor waiting for a sail. No sail from day to day, but every day the sunrise broken into scarlet shafts, among the palms and ferns and precipices, the blaze upon the waters to the east, the blaze upon his island over head, the blaze upon the waters to the west, then the great stars that globed themselves in heaven, the hollower bellowing ocean, and again the scarlet shafts of sunrise, but no sail. End of Chapter 13, Chapter 14 from Enoch Arden. But Enoch yearned to see her face again, if I might look on her sweet face again and know that she is happy, so the thought haunted and harassed him, and drove him forth at evening, when the dull November day was growing duller twilight, to the hill, there he sat down gazing on all below. There did a thousand memories roll upon him, unspeakable for sadness. By and by the ruddy square of comfortable light, for blazing from the rear of Philip's house, allured him, as the beacon blaze allures the bird of passage, till he madly strikes against it, and beats out his weary life. For Philip's dwelling fronted on the street, the latest house to landward, but behind, with one small gate that opened on the waist, flourished a little garden square and walled, and in it throwed an ancient evergreen, a yew-tree, and all round it ran a walk of shingle, and a walk divided it. But Enoch shunned at the middle walk, and stole up by the wall, behind the yew, and thence that which he better might have shunned, if griefs like his have worse or better. Enoch saw. Chapter 15 The Charge of the Light Brigade.  Forward the light brigade, charge for the guns, he said, and to the valley of death rode the six hundred. Forward the light brigade, was there a man dismayed? But though the soldier knew, some one had blundered. There's not to make reply, there's not to reason why, there's but to do and die. Into the valley of death rode the six hundred. Cannon to left of them, cannon to right of them, cannon in front of them, volleyed and thundered, stormed at with shot and shell, boldly they rode and well into the jaws of death, into the mouth of hell rode the six hundred. Flashed all their sabers bare, flashed as they turned in air, sabering the gunners there, charging an army, while all the world wondered, plunged in the batteries smoke, right through the line they broke, Cossack and Russian reeled from the sabers' stroke, shattered and sundered. Then they rode back, but not, not the six hundred. Cannon to left of them, cannon to right of them, cannon behind them, volleyed and thundered, stormed at with shot and shell, while horse and hero fell, they that had fought so well came through the jaws of death, back from the mouth of hell, all that was left of them, left of six hundred. When can their glory fade? Oh, the wild charge they made! All the world wondered. Honor the charge they made. Honor the light brigade. All six hundred. CHAPTER 16 FROM THE MAY QUEEN You must wake and call me early. Call me early, mother dear. Tomorrow will be the happiest time of all the glad new year. Of all the glad new year, mother, the maddest, merriest day. For I'm to be queen of the may, mother, I'm to be queen of the may. As many a black, black eye, they say, but none so bright as mine. There's Margaret and Mary, there's Kate and Carolyn, but none so fair as little Alice in all the land, they say. So I'm to be queen of the may, mother, I'm to be queen of the may. END OF CHAPTER 16 CHAPTER 17 SONG FROM THE PRINCESS As through the land at Eve we went, and plucked the ripened ears.  And blessings on the falling out, that all the more endears, when we fall out with those we love and kiss again with tears. For when we came, where lies the child, we lost in other years. There above the little grave. Oh, there above the little grave, we kissed again with tears. END OF CHAPTER 17 CHAPTER 18 FROM HEROLD TOASTIC What for Norway, then? He looks for land among us, he and his. Herold. Seven feet of English land, or something more, seeing he is a giant. Toastic. That is noble. That sounds of Godwin. Herold. Come thou back and be once more a son of Godwin. Toastic turns away. Oh, brother. Brother. Oh, Herold. Laying his hand on Toastic's shoulder. Nay, then. Come thou back to us. Toastic. After a pause turning to him. Never shall any man say that I, that Toastic, conjured the mightier Herold from the north to do the battle for me here in England. Then left him for the meaner, thee. Thou hast no passion for the house of Godwin. Thou hast but cared to make thyself a king. Thou hast sold me for a cry. Thou gavest thy voice against me in the council.  Farewell for ever. Exit. Herold. Onto Stamford Bridge. End of Chapter 18. Chapter 19. From the Revenge. And the sun went down, and the stars came out, far over the summer sea. But never a moment ceased the fight of the one and the fifty-three. Ship after ship the whole night long their high-built galleons came. Ship after ship the whole night long with her battle thunder and flame. Ship after ship the whole night long drew back with her dead and her shame. For some were sunk, and many were shattered, and so could fight us no more. Not of battles was ever a battle like this in the world before. And the night went down, and the sun smiled out, far over the summer sea. And the Spanish fleet with broken sides lay round us all in a ring, but they dared not touch us again, for they feared that we still could sting. So they watched what the end would be, and we had not fought them in vain. And in perilous plight were we, seeing forty of our poor hundred were slain, and half of the rest of us maimed for life in the crash of the cannonades and the desperate strife. And the sick men down in the hold were most of them, stark and cold, and the pikes were all broken or bent, and the powder was all of it spent, and the masts and the rigging were lying over the side. End of Chapter 19. And also the end of Beauties of Tennyson.


Neuroimaging has revolutionized our understanding of brain function and has become an essential tool for researchers studying neurological disorders. Functional magnetic resonance imaging, fMRI, and electroencephalography, EEG, are two widely used neuroimaging techniques to review changes in brain activity. fMRI is a non-invasive technique that uses magnetic fields and radio waves to produce detailed brain images. And EEG is a non-invasive technique that records the brain's electrical activity through electrodes placed on the scalp. This review overviews recent developments in non-invasive functional neuroimaging methods, including fMRI and EEG. Recent advances in fMRI technology, its application to studying brain function, and the impact of neuroimaging techniques on neuroscience research are discussed. Advances in EEG technology and its applications to analyzing brain function and neural oscillations are also highlighted. In addition, advanced courses in neuroimaging, such as diffusion tensor imaging, DTI, and transcranial electrical stimulation, TS, are described, along with their role in studying brain connectivity, white matter tracts, and potential treatments. This article was authored by Chiawei Yan, Chie Lee Lin, and Ming Cheng Cheng. We are article.tv, links in the description below.


All right, so we are going to talk about Canopy. Canopy is, yep, Canopy is Pinecone's open source rag framework, and Pinecone, if you don't know, is a cloud native vector database. Okay, so Canopy is an open source rag framework. It's written in Pinecone, and it's from Canopy, as I said before, and what Canopy, or from Pinecone, and what Canopy does is abstract away all the non-trivial tasks involved in creating a rag GenAI app. And the point of Canopy is that by abstracting away all of these non-trivial tedious tasks, it frees up your time as a developer to concentrate on what we think really matters, which is the end product. So Canopy abstracts away all the work involved with data chunking, generating the vectors slash embeddings. We're gonna use them interchangeably in this presentation. Setting up your vector database, query optimization, context generation, and LLM orchestration, and management. All you need is a Pinecone API key and a Pinecone environment, which you can sign up for very easily, pinecone.io. An open AI API key, we currently use open AI embedding models and text files to populate your Canopy index with. You can have Parquet, JSON-L, TXT, or CSV files. And since it's all backed by Pinecone, you get free storage and compute up to 100,000 vectors. That's about 15 million words or about 30,000 pages of text. And you have the ability to scale to meet production demands seamlessly. You also get a very nice Pinecone dashboard, which if you use Pinecone before, the same exact dashboard, it's right in the same dashboard with all of your regular Pinecone indexes. And we're HIPAA, GDPR, SOC2 type two, compliant and certified. And all of Pinecone's infrastructure and algorithms are purpose built for vector computation and storage. So this is something I'm sure you all are familiar with. This is the typical gen AI workflow. So a user will issue a query to an LLM. That LLM will answer the user. They might say, what is the most colorful bird in the world? They'll send this query to an LLM, likely made by open AI, cohere hosted on hugging face, et cetera. And the LLM would say the most colorful bird in the world is a parrot. But when we talk about RAG, which is retrieval augmented generation, if you don't know, when we talk about RAG, cool, okay. When we talk about RAG, we put these two more steps in the gen AI workflow. So your user query gets ported over to a vector database. Hopefully that would be Pinecone. From the vector database, you get vector search results. We call these context. And then together the vector database results and your user query get ported over to the large language model and then the large language model using that context would answer the user. Whoops, too easy. So we have our same scenarios before, but this time let's say we have some proprietary, very cool, very private bird documents. And now we know that the most colorful bird in the world is not just a parrot, but it's actually a Wilson's bird of paradise. And this is not public information. The LLM could never have known this in the whole world and it can only know this because you use RAG in your gen AI application. And you can see the two little, the yellow highlighted bit, that's the combined user query with your context. And so they go both together to the LLM in order for the LLM to have access to information it otherwise would never have known. And well, this is all well and good. The vector database and context retrieval aspect is easy, but tedious. And it requires dev hours and also research in order to actually do well.  And then finally prompting that LLM with system level prompts and context prompts and all the prompts. And all of these things just takes a lot of time. But with Canopy, you don't have to do any of it. I will note though that Canopy is fully, completely open source. So if you do have the know-how and you do want to have more control over any of these things, there's an extremely easy configuration files. There's a YAML that you can put all of your gadgets and digits in and make Canopy as fancy as you want it to. If you don't want to go with our defaults. So there are two deployment options for Canopy. One, you can develop it as a service. So you can spin up the whole Canopy stack in the Canopy server. Our app.py file has all of our endpoints and they're all wrapped in fast API decorators. So it's super easy to use out of the box. You can also use Canopy's modular components, all or two or three or one, as libraries embedded in your own GNAI stacks. If you'd rather just pick and choose, cherry pick what you want out of the Canopy library. Alrighty. And this is my favorite part of Canopy. This is what a developer would see probably as a first touch point when using Canopy. This is the CLI. And this is where pretty much everything gets done with just a few commands. We'll have a live demo of this later. But all you have to do is do Canopy chat and essentially you're just chatting with all the documents that Canopy indexes into your index for you. And notable with the CLI is that this is a development tool. So the CLI is used to compare and contrast different configurations for your RAG pipeline. So if you have a higher temperature in your LLM or you have a different chunk size token overlap, things like that, you would chat with your documents after each of those iterations, figure out which one is best, and then go from production after you figure that out in the POC phase. All right, so if we go below the surface of the CLI, there are three main components, each embedded within the other, but modular, so they can be decoupled. So first is the chat engine. That's what you interact with primarily when you're hitting the CLI. The chat engine handles your prompts and saves your chat history. It can also do multi-turn conversations, multi-agent conversations. It's really wonderful. It saves your state and all that. The context engine builds and manages your context from your pine cone vector database, and the knowledge base orchestrates all the scary things. So like the chunking, the vectorization, building the actual pine cone database, and upserting those documents to pine cone. All right, so now we're gonna go through a little bit of before and after to show you just how much work Canopy can save you. Okay, so without Canopy, as I'm sure a lot of you know, if you've tried to build a RAG pipeline, getting the data into a good state is very annoying, and it creates a lot of ambiguity, and you have to do a lot of research. There are really good tools out there now. We have Lang Chain, Lama Index, et cetera, but it's still just time, and we don't have time for these things. So without Canopy, you would have to figure out your chunk size, and there's lots of strategies for doing this. You can divide your text document into chunks by paragraph, by sentence, by some n number of tokens. You can configure how many tokens across chunks overlap, so that's how many tokens at the end and beginning of each chunk are the same.  There's lots of things that I don't wanna think about, I just want to build cool LLM applications. So with Canopy, all of this is abstracted away for you, and all of the heuristics that we've put into the default YAML file were developed by a team totally and only dedicated to researching this product, so it's all with best practices in mind, and they all have PhDs and they're very fancy, so we should all trust them. By default, Canopy sets the maximum tokens in each of your chunks to 56. This is pretty small, you can change it if you want to, but we've found that generally, for most text-based LLM RAG application use cases, that's a good chunk size. We extend LangChain's recursive character text splitter and some other methods from LangChain in order to chunk up your documents intelligently. We do things, what was it? We keep the markdown separators, and we split on those to things like headers and new lines, things like that, and then also for each chunk, Canopy will format it into an object that is ideal for indexing into Pinecone, so the data you put into Pinecone needs to be in a particular format, Canopy does all of this for you and it will include automatically any custom metadata fields that your data has when you upload it, right? So vectorization, without Canopy, figuring out what model you want to use for vectorization is difficult. There are hundreds of embeddings models out there and each one is pre-trained on a specific task or ideal for a certain domain and it's really hard to figure out which one to use and even when you figure out which one to use, actually hitting the model is confusing too. Do you hit it through an API? Do you host it locally? If you host it locally, will it crash your computer? Like it did mine a bunch of times. All of these things are very complicated. Canopy though, does it all for you? So by default, we use A to two, which is an open AI model, it's a text vectorization model, but as of today, literally at like 9 a.m. this morning, as of, I guess, version zero, five, oh, we support cohere and any scale embedding models. So that's really exciting, especially if you want multilingual rag applications, cohere embedding models, our multilingual, which open AIs are not, which is awesome. We also generate the embeddings for you in batches. We have a default batch size of 400. We send that to the open AI API, that's why you need your API key. And we do this all with fancy Python syntax, generator objects, all of that good stuff, error handling, retries, all that jazz. All right, indexing without canopy.  I don't wanna have to deal with yet another thing. Every time I say, okay, I'll just do this one thing manually, that thing gets up to 20 items long and then I've missed my dinner. So configuring the index is annoying. You have to just figure out the dimensionality that you want your index, what similarity metric you might think you need for your particular use case. Hybrid search needs dot product, well, regular search needs cosine, et cetera. You also, as I said before, need to format these data objects. So pine cone objects need to be with a particular format. It's essentially a map of ID vector metadata and then the metadata has to be a nested dictionary with lots of fields. And then absurding these objects into pine cone if you're dealing with a really large scale is non-trivial. So you need to do this either in batches or multi-parallel or multi-processing in parallel, keeping bottlenecks, retries, et cetera in mind. Both canopy, we do all that junk for you. So by default, the pine cone index that canopy spins up for you is the one that we see most people using. It has cosine similarity as a similarity metric. It runs on a P1 pod type, which is basically, we have three pod types. This P1 is the one that has the best balance between cost and performance. And it's the most popular pod type we have. And also canopy will intelligently pull the dimensionality from whatever text embedding model it knows you're using to generate your vectors.  Like what am I gonna do? Doesn't matter, pine cone takes care of all of that alignment for you. It also, as I said before, formats those data objects into all the fields, the nested dictionaries, yada yada, that pine cone needs objects to be in for indexing. And then it batch upserts your objects again with fancy, wonderful Python syntax, this time in batches of 200. Lastly, prompting. So there's a whole field now, prompt to engineering. Without canopy, it's a little bit confusing what you should do, what format your prompts should be in. For most LLMs, you should really be doing a custom system prompt, this tells the LLM how to act, whether or not it's okay to hallucinate a little bit or whether they have to be 100% accurate because you're dealing with medical cases, anything like this, and it's really hard to know what words matter, what line breaks matter, all of those things. Luckily, again, canopy does this all for you. The picture on the right hand side is a screenshot of the YAML, which I'll actually show us live soon. But basically, we do a system prompt for you again, super easy to change, but basically it says, don't hallucinate, only use the context, answer as if it's your own knowledge, don't act robotic and weird. And then something unique to canopy, which I hadn't heard of anybody doing before I started working on the canopy product was we issue a retrieval prompt. So if you guys have worked with vector databases at all and LLMs, you know that sometimes whatever question I as a user might ask, an LLM might not be optimized for vector retrieval. So on the back end of canopy, when I ask a question, let's say it's really long or really complex or has lots of, I don't know, entities that are confusing to an LLM at face value, canopy will actually use chatGBT 3.5 turbo and optimize that prompt by splitting it into sub questions that are optimized for vector retrieval for you. So that you never have to worry about like, is my prompt good for both an LLM and a vector database? I don't know, it doesn't care. Canopy will take care of that for you. And as I said before, it'll format it all, line breaks, et cetera. Miscellaneous things that can change the behavior of the LLM are taken care of for you. All right, we're gonna do a live demo. I'm really scared to do this, I've literally never done a live demo, so we're gonna see how this goes. All right, and now with this double screen thing, it might be even harder. Okay, so, let's see. So this is my, I made a little pine cone index and all I had to do in the CLI was say canopy new and I had an environment variable that said my index name. AI dev demo and it prepositions everything with canopy dash dash. All right, so we have zero vectors in here, cool, cool, cool. I'm using my coworker James's dataset who is here. He put this onto Huggingface, it's just a bunch of archive.org research papers, cool, cool, cool. Behind the scenes, I took 10 of these research papers and I put them into the format that canopy likes and we are going to play with it. So, oh I have to drag my terminal, hold on. Where's my mouse? Oh, oh, okay, do I drag it this way? Okay, so I'm in a poetry environment right now, this is what you would be in if you were to contribute to the library, otherwise you can just pip install everything. And I'm going to do, nope, I'm going to do canopy start. This should start up the canopy server, which is a G unicorn, Gunicorn, whatever it's called, server, that guy. All right, cool, so we're up and running. So now canopy is alive, the server is up and running, I can do a bunch of stuff with it. So, oh and actually I just realized one thing, hold on, I'm quitting this for a second, let's quit that for a moment. We have no vectors in our index, so obviously I want to put vectors in there, which I did not do. So, okay, so I'm going to do canopy upsert, which is our pinecone word for inserting and or updating vectors. And I'm going to do the name of my JSON file that has those 10 archive.org papers that just looks like this, so I'm going to go ahead and dig a little JSON file, cool, cool, cool, I'm going to copy it, going to copy it, going to bring it back here. All right, cool, so I'm telling it right now, grab that JSON L file, upsert it, or chunk it, vectorize it, upsert it, do all the fancy things and we'll see what happens. Cool, so this is one of my favorite parts as well. It'll show you a preview of how it has understood your text file and then it'll say, does this data look right? And you can be like, yes or no. So we're going to say yes, it does look right. Now we have a little progress bar on the side here and we can watch things trickle in. That was loading. All right, we got 200, let's see if we can, all right, we're at 40%, you can see it going, all right, now it's 289. Do we think it auto refreshes? Maybe, let's see, 289, let's see if it goes higher. Oh, we're at 80%, 635. All right, 80%, almost there, ding, ding, ding, ding. Cool, we have a success message. If it was not successful, it would die until you immediately, so you don't have to wait like two hours just to get an error message. All right, so we have a total of 805 vectors. Those vectors represent chunks of those archive.org articles, so just 10 articles generates nearly 1,000 vectors. That's just kind of cool. And then on the dashboard, you can see here previews of all these vectors. So you have the vectors, the document ID, the source, et cetera. And one of these articles is this guy, which I loaded up here. De-coupled weight decay regularization. Doesn't sound super fun, but archive.org research papers are not always that fun. So I don't feel like reading this. I just want to know essentially what this is about. And I see this dude named Acacin mentioned everywhere. So I took a sin. Nope. H, c, see anything? T, C, H. Yeah, this dude. All right, this guy, Acacin. Like who is he? What does he say? I don't know. Oh, God. All right. Now, all right, cool. So now that we have all of our stuff in canopy, we're gonna do canopy start again, which we did before. Start up the canopy server. Pretend we didn't do that before. That is gonna start up. And you can see here, this is for debugging only. Again, this is like for POCing stuff. This isn't for, you're not gonna like launch into production through the CLI. That would be crazy. All right. So now I'm gonna do the command canopy chat and this no rag flag here means that the answers I get will show me both with and without rag. By default, it's just with rag, but I wanna show you how cool canopy is, so we're gonna do both. All right. So we are gonna start this little chat interface up. Cool, cool, cool. And then I have some questions that I put here. And these I purposefully made pretty long and pretty complex with reference entities. So who is this Acacin guy? Has he said anything about weight decay? If so, what is he said? This part's not immediate. It has to go through the API, two API calls. One to chat GBT to reformat my query into sub queries. Another one to chat GBT the LLM. All right, so we have Acacin as a person who has discussed weight decay in the context of Bayesian filtering. Yada, yada, yada. Cool, this is all from that article, but without rag, chat GBT says without more context it's difficult to provide a specific answer. There are several individuals named this name. Blah, blah, blah, blah, blah. If you provide more details, I might be able to assist you further. That is annoying. I don't want to assist you further. You're supposed to be in AI. Just like tell me things. All right, what if I say, please tell me about more about Acacin's theoretical framework. Cool. From what I remember of playing with this before, this is gonna be a biggie, which I like. All right, so this is all about a theoretical framework, which is super cool. And it specifically says as mentioned, whoops, as mentioned in the context, which I like as an end user, because I know that it's actually reading my context. I don't have to go back into the article and like copy paste answers to see if the answer that my rag pipeline gave me is actually mentioned in the paper. And then it also gives me the archive.org citation, which is awesome. And that's the citation for my paper. So again, I can confirm that what I'm doing is actually making an impact on the end product. And without rag, again, given the lack of specific information, it's challenging to provide a perfect answer, blah, blah, blah, blah, blah. It's just asking for more and more details about Acacin, but like listen, I already put them in the vector database. Like sorry, you don't know about it. And that, that is our live demo. So I think it's really exciting. Everybody should use it. And more things, more good things are coming to the future of Canopy. We have more model options that were in the process of deploying. I personally am working on an Azure deployment right now. So like all your Azure models, you can put them into Canopy or hit their endpoints, host them Azure through Canopy. We're also trying to get local deployments to work with Canopy. I personally would love to see, and I know the team is working on direct file uploads. So like you can just drag and drop a text file or a PDF file directly into the CLI right now. Evaluation support, whether that's native or through a third party, I think as a search engineer, I think it'd be really exciting to have like ranking differentials between different configurations of Canopy. Advanced retrieval features, like adding in diversity, which is especially important if you're doing things like e-com search, and much more. And that is the end. My name is Audrey again, our forum. If anybody has questions and wants to join the community is community.pinecone.io, and that is it. Sorry for the weird presentation format, but thank you. I don't know if we have question time. Go ask a question, I don't know, yeah. Yes, so this again is a configuration parameter you can tune, but basically five of your chunks, the top five most relevant chunks from your query, then get packaged with your query. So like what is a dog? If I send that to the vector database, I get five chunks about dogs. It would send what is a dog, that query, plus my five chunks I got from pinecone to the LLM, correct. The answer to that actually, I know pinecone has security measures for like the vector data in the index itself, but when we send it to a third party LLM endpoint, I'm not sure, I know the data's encrypted in transit, but that's, well sure, but yeah, I don't know. James, do you know? Yeah, that would be the local model integration if you never wanted it to leave your ecosystem, yeah. Cool, we do lots of FinTech stuff, but yeah, not with the third party LLMs yet. All right, thank you.