A couple of days ago, Linus Torvalds got angry at someone over on the Linux kernel mailing list because this person was one of these anti-vaxxers. He was a vaccine skeptic and he was trying to spread some misinformation, some lies about the vaccine. And Linus Torvalds got angry and responded to the guy and he responded with a whole bunch of facts, well-researched facts. Actually I was a bit surprised because Linus Torvalds, of course, is not a medical doctor, he's a programmer. But Linus came back at this guy with all of these well-researched facts and really just shut the guy down. And then he told the guy to take his lies, his misinformation, his conspiracy theories, take that stuff somewhere other than the Linux kernel mailing list. Now I don't want to really dwell on the story of Linus and the guy on the kernel mailing list. You guys can read about that. There's plenty of news articles that have been written about that story. But today I wanted to take a little time to discuss critical thinking because that is really what is sorely lacking in the modern world. In recent years, critical thinking is not a skill that people embrace anymore. It's not a habit that people try to learn. It should be a part of everyone's life. We don't teach our kids about critical thinking. We don't teach them critical thinking skills. We don't teach them about reason and logic and facts. We don't teach them like the scientific method or anything like that anymore. These days it seems people are allowed to believe whatever the hell they want to believe. No matter how outlandish, how ridiculous those beliefs may be. So one of the things that really changed my life as far as how I think about things. And I'm not even kidding. I came across a journal article many, many years ago. This journal article was published way back in 1990. And it's The Field Guide to Critical Thinking by James Litt. James Litt was a college professor. May still be a college professor. I don't know. But he wrote The Field Guide to Critical Thinking and he talks about how you should be thinking about things. He talks about critical thinking skills. And it seriously changed the way I started thinking about things because I realized that some of the beliefs I had weren't really based in any kind of reason, logic, fact. You start challenging yourself on some of your beliefs. And that's a good thing. That's what everyone should be doing.  And the ones that do stand up, it just reaffirms those true beliefs even more. Now this article is not very long. I'm not going to read it to you, but I will link to it in the show description. But you know, I did want to hit some of the high points here. Let me zoom in a little bit so you guys can read this. So this is The Field Guide to Critical Thinking by James Litt and he talks about the reason he wrote this article back in 1990, mainly was because there was a rise of popularity of paranormal beliefs back in the United States in 1990. And I'm old enough, I know that especially in the 1980s, yes, you did have a large number of people all of a sudden seeing UFOs, flying saucers, little green men, things like that. And the rise of this popularity probably had a lot to do with the rise of popularity as far as movies, television, cable TV, back then the guy in Hollywood was Steven Spielberg. He was the producer. He was making all the big blockbuster movies, many of his big blockbuster movies involved aliens. He had close encounters of the third kind, then he had E.T., a lot of these people thought they were seeing little green men and flying saucers. What they were really seeing, they were seeing Steven Spielberg. Mr. Litt goes on to write that he thought the rise of popularity of paranormal beliefs in the U.S. back in 1990 was mainly because of the irresponsibility of the mass media who exploit public taste for this kind of nonsense. He's absolutely right. It's the media that exploits this kind of stuff. They put it out there mainly for money for ad revenue as far as print media or advertising revenue on TV especially. And however bad that may have been in 1990, it's 10 times worse here 30 years later. It's the media that stirs this stuff up. He also talks about the irrationality of the American worldview which supports such unsupportable claims as life after death and the efficacy of the polygraph. So he's basically saying the Americans are more irrational than other societies. He's an American. So he's speaking from that point of view. Well, that may have been true in 1990. Remember, this was before the internet, before the worldwide web. But since then, we're all connected, right? The internet has really connected the entire globe. And now I would say that's not the case. You see irrational beliefs from everybody in every country. You see conspiracy theorists from every country on the planet. Professor Led also talks about the ineffectiveness of the public education which generally fails to teach our students the essential skills of critical thinking absolutely. It's not a priority in schools anymore to actually teach people how to critically think. Schools these days don't want people to critically think about anything and arrive at their own correct decisions, right? These days you go to school and instead of, hey, here's how to think, how to arrive at a decision, schools you go to, especially high schools and colleges as you get older, you get, you know, teachers and professors that basically tell you exactly what to think. So reading this journal article a little further, it goes on to state that there are six rules to evidential reasoning. So there are basically six aspects to learning how to critically think. And the very first one is falsifiability. So what is falsifiability? Well it goes something like this. It must be possible to conceive of evidence that would prove the claim false. Now that's going to sound a little paradoxical, but in order for a claim to be true it must be falsifiable. The rule of falsifiability, it guarantees that if a claim is false, the evidence will prove it to be false. And if the claim is true, then the evidence will at least not disprove it. You know, it may not prove it true, but at least it won't disprove it. Falsifiability ensures that evidential reasoning matters, right? That the evidence matters. It's all about the evidence. You know, that's why we make sure any claim must be falsifiable for it to be a real claim. Otherwise it's just a meaningless claim. But conspiracy theorists and paranormalists, sometimes of people making spiritual claims, they love to make non-falsifiable claims. And a non-falsifiable claim is a claim where evidence doesn't matter. There's no possible way to view evidence on the matter anyway. An example of this with a conspiracy theory is, you know, years ago you heard all the time George W. Bush was behind the 9-11 attacks. And then, you know, somebody would say something like this and I would ask them, hey, what's your evidence? Well there is no evidence because it was all covered up by the government.  You're not going to find any evidence. So they make a claim and then as part of their claim they're also telling me there's no evidence, no evidence that could ever prove it to be false or to prove it to be true. That's a meaningless claim, right?  Non-falsifiable kinds of claims from paranormalists would be something like, you know, aliens are all around us. They're watching us. They're testing us. They're probing us. You know, they're doing all these experiments on people and nobody knows. And you say, well, there's no evidence of that. We've never seen any extraterrestrial being. Well, the reason is because this race of aliens, you know, there's so much advance we can't detect them. That's a non-falsifiable claim, right? That's essentially a meaningless claim at that point. Once you go in that direction, you know, if you talk about a spiritual point of view, the creationists love making non-falsifiable claims because the creationists will say things like, you know, that God created the world 10,000 years ago, right? And you say, well, we have observable light from stars that are billions of years old. Well, God created that light already at that position at that age 10,000 years ago. So they just move the goalpost and then you're like, well, what about dinosaur bones, dinosaur fossils that we carbon date and we know they're millions of years old? Well, he created those fossils already millions of years old when he created the world in the universe 10,000 years ago.  They're just going to put the hand up and say, nope, don't want to hear it, right? Your evidence doesn't matter. There will never be a piece of evidence that you can come to me with that actually matters because I'm going to keep moving that goalpost forever. So there's no reason to take these kinds of people seriously. There's really no reason to interact with these kinds of people, either whether it be the paranormalist or some of the weird spiritual claims people make, or especially with the conspiracy theorists.  One of the other rules for critical thinking is logic. Logic means that any argument offered as evidence and support of any claim must be sound. So, you know, he gives an example here of this statement here. All dogs have fleas. Xavier has fleas. Therefore Xavier is a dog. Now that argument obviously is invalid because anything with fleas does not have to be a dog. A cat could have fleas as well, right? So that whole train of thought there, that was not based in any real logic, right, where a better way to do this would be all dogs have fleas. Xavier is a dog. Therefore Xavier has fleas. Now that kind of tracks, right? That's, that actually is actually a valid kind of statement. The third rule that we need to discuss is comprehensiveness. And this states that quote, the evidence offered in support of any claim must be exhaustive. That is all of the available evidence must be considered. And this is where, especially when you get into the conspiracy theorist kind of crowd, that kind of mentality that's prevalent today is they don't want exhaustive research into anything. They don't want to really look at every single piece of evidence that's available, right? They want to pick and choose evidence. Anytime somebody makes some kind of extraordinary claim, and then the only evidence they provide is the evidence and support of their claim. And you know, there's evidence that doesn't support their claim out there. You should just ignore that person. The fourth rule is honesty. So part of critical thinking is being honest. That means quote, the evidence offered in support of any claim must be evaluated without self deception. Meaning you come at this, you know, with an open mind being unbiased, right? You actually want to know the truth. And this is something that many people don't actually want to know. Many people make a claim, but they don't really want to know if it's true or false. You know, they say this is true or this is false, but they don't really want to put it to the test. They don't really want to know the truth. The biggest violators of the rule of honesty or the paranormalist psychics, you know, people that believe in psychokinesis and telekinesis and you know, things like that, you know, they believe these outlandish things that there's actually real evidence against like, Hey, there's no way this is possible, right? I can actually prove that the claim you're making is in fact not true. And these people, they're one of these people that kind of move the goalpost a lot.  They like to use multiple outs and just like all the other rules we've discussed so far, somebody makes a claim and you think that they're not being honest, you know, and same thing with comprehensiveness and logic and falsifiability. Somebody makes a claim and you know, they're not, they're not honestly wanting to explore the evidence and find out if their beliefs are true or false. Again, it's probably best just to not have anything to do with that person. The next rule for critical thinking is replicability. Now, what this is, is it's basically the ability to put something to the test. So if the evidence for any claim is based upon an experimental result, or if the evidence offered in support of any claim could logically be explained as coincidental, then as it's necessary for the evidence to be repeated in subsequent experiments or trials. So for those of us that do bug reports on things like GitHub or GitLab, replicability is a big deal, right?  I followed these steps with your piece of software and then I got an error. Okay. And then I make that bug report and then somebody that's on that GitHub or GitLab repo, some maintainer or developer, he will try to replicate my steps exactly using the exact same methods that I did to get that error and he'll either get that error or he won't. If he can't replicate my error, then my bug report, it's a real bug report because I did get a bug. But what I think caused the bug wasn't actually what caused the bug. You know, sometimes you get these things that happen that are purely coincidence, right? And people will imagine that some sort of steps led up to that, right? But it's not really what led up to that event.  I don't know it's some electrical device, a TV set or something and, you know, and they stare at it for hours and hours and for days at a time. And one day the TV set actually does catch fire and they think, wow, I caused that. Well, no, it could have been faulty wiring.  They can't replicate it, right? So the first event was really just coincidence and that's really what replicability ensures is that we can test it over and over again and get the same result. Otherwise, if it's just a one-off event, it could just be a coincidence. And the sixth and final rule for critical thinking here is sufficiency. And this states, quote, the evidence offered in support of any claim must be adequate to establish the truth of that claim with these stipulations. One, the burden of proof for any claim rest on the claimant. And that should be pretty obvious why that's the case. Otherwise, you're just wasting my time. You're wasting everybody else's time. Don't come to people with a claim and expect us to prove or disprove your claim, right?   Two, extraordinary claims demand extraordinary evidence. So that's Occam's razor, right? The simplest explanation is usually the correct one. Number three, evidence based upon authority and or testimony is always inadequate for any paranormal claim. So sufficiency, this kind of rule here, this is violated all the time, especially from paranormalists and conspiracy theorists. So the burden of proof always rest with the claimant. And the reason it needs to rest with the claimant is for the simple reason that the absence of disconfirming evidence is not the same as the presence of confirming evidence, meaning just because there's no evidence to prove you false doesn't mean that your claim is actually true. That's just, you know, logical thinking.  Therefore, I'm right. That's that's a logical fallacy, right? I shouldn't have to explain the flaw in that kind of thinking. Extraordinary claims demand extraordinary evidence. I think most people understand why that's the case. I mean, you use this kind of critical thinking every day in life.  That's a normal kind of claim, right? You're just going to accept that, right? I don't need to bring extraordinary evidence to prove that, right? Because that's kind of a mundane kind of claim.  Because there's no way you would even consider that that could be true. Anything short of me having one of these Zoltarians next to me, right?  And that's really the problem with all paranormal claims. And really the problem with all conspiracy theories is they're always extraordinary, which means they always need to have extraordinary evidence, you know, to back them up. And of course, you're never going to find a paranormalist or a conspiracy theorist that has any evidence at all, much less extreme or extraordinary evidence. So that's just a little bit of the field guide to critical thinking by Dr. James Lead. Again, I'm going to link to the entire journal article. I'll have a link to it in the show description. Again, this particular article I read it many, many years ago and I've just kept it. I reread it all the time and it really has changed my life. It's kind of changed the way that I just think about things in general. So the next time one of these crazy conspiracy theorist kinds of people come up to you and they start talking about, you know, black helicopters, Illuminati, the New World Order, JFK's assassination, 9-11, Flat Earthers, Obama's birth certificate, RFID chips, Deep State, whatever it happens to be, refer to them to the field guide to critical thinking. Now before I go, I need to thank a few special people. I need to thank the producers of this show. I need to thank Absigay Mitchell, Akami Allen-Chuk, David Dillon, Gregory Irion, Paul Polytech Scott, Steven Smith, Wes and Willie. These guys, they have exceptional critical thinking skills. They're my high-steered patrons over on Patreon. Without these guys, this episode would not have been possible. The show is also brought to you by each and every one of these ladies and gentlemen as well. All these names you're seeing on the screen right now. These are all my supporters over on Patreon because I don't have any corporate sponsors. I'm sponsored by you guys, the community. If you'd like to support my work, look for Distro Tube over on Patreon. All right guys. Peace. I wonder if Ancient Aliens is on Netflix.


What are the three reasons why we should completely shift to electric vehicles and do away with any other means of transport? So if you look at any of the newspapers, we are in Delhi right now and the discussion is mostly on pollution. India has 13 of the 20 most polluted cities in the world. So to improve the health of our citizens, we definitely have to make this happen in terms of electric vehicles. So that's the first and primary reason. The second reason is we are at a point in history where electric vehicles are cheaper in terms of total cost of ownership compared to an internal combustion engine. So if you ask me this question five years ago, we weren't at a stage where we could say that in terms of TCO, total cost of ownership, electric vehicles were cheaper than internal combustion. So right now we are at a stage where it is cheaper to use electric vehicles than petrol or diesel powered vehicles. And the third reason is India wants to become a manufacturing hub in electric vehicles. So India is the leader in terms of two wheelers and three wheeler segment vehicles. We export our products not just to developing countries but to various developed countries as well. So to secure the future of manufacturing jobs in our country and to gain the expertise as well as the ability to export our two wheelers or three wheelers to other parts of the world, we need to invest in electric vehicle manufacturing, invest in business models that enable electric vehicle ecosystem, the swapping stations or charging stations. So that will make us future ready for dominating the two wheeler and three wheeler market segment specifically. So in terms of manufacturing, so the government has come up with 5% GST on electric vehicles which is fantastic. So it's a very good positive move from the government. So second thing they have introduced two wheelers and three wheelers in the famed scheme that is also a fantastic move from the government. They realize that it will be the two wheeler and the three wheeler segment that will get electrified soon rather than and the rest of the segments will follow later on. So in terms of one of the key gaps that we have observed not in terms of government but in terms of the financing of electric vehicles. So the banks are unwilling to finance electric vehicles because they haven't seen the track record and to be fair the banks have actually funded some of the low quality electric vehicles that have come up a few years back and they are skeptical because of that. So what we are asking the government is to have some kind of loan guarantee mechanism which will make it comfortable for the banks to basically fund new products developed by startups like us. So in our case if you look at any of the established players. So for them it's a small portion in their grant portfolio of products. Electric vehicles is one small portion but for a startup like us it's about survival. So once we are moving from hundreds of vehicles to thousands of vehicles this key financing, vehicle financing, electric vehicle financing is one key obstacle that we are facing right now and we are talking to various banks and government to come up with a loan guarantee mechanism that will make this happen. If you ask me this question three years ago I would have that doubt would we be able to compete with larger players but having interacted with them over a period of time. Having competed with them on a daily basis over a period of time. Having beaten them some of the very well established manufacturers over the two and a half three years time frame that we have. I am confident that the electric vehicle revolution will happen because of startups. It won't be the large established players which will be driving electric vehicle adoption. It will be the startups which will be driving electric vehicle adoption. So if you look at the market in US it was Tesla which had to drive this adoption. So the large established players are like dinosaurs. They take a lot of time to move and in a field where you need to keep changing, keep updating on a daily basis or on a monthly basis the reaction time is very slow. So for example one of the feedback from BigBasket one of our customers is that if we tell Gaia Motorworks to change something so that it becomes easier for adoption of electric vehicles they come back with a solution in three months. But if we do it to the larger company which has also sold some vehicles to BigBasket previously they haven't yet come back it has already been two years. So in such a fast changing environment for the large established players EV is a small segment in their grand portfolio of things for us it's about survival. So our existence depends on getting market share of electric vehicles as much as possible. So it will be the startups which will become big and force the established players to come into electric vehicle segment rather than the other way around.


It's the one o'clock clock on a given, what, Wednesday? And here in Think Tank, we're talking community matters and we're talking about Coded Bias, the movie with Matthew James Bailey, who joins us from Denver. Hi, Matthew. Hi, Jay. Great to be here. The same to have you. So let's talk about Coded Bias. So you wrote a book and this is right up your alley. The book you wrote, which we have discussed before, is called Inventing World 3.0, Evolutionary Ethics for Artificial Intelligence. And the book is remarkable in that it talks about how we got here. It's very important. You cannot understand the present or the future unless you understand the past. You must understand the evolution. And indeed we are in a transformational evolution for sure, you point that out in many ways. But here, we have things popping up on the landscape. This movie popped up on the landscape and won all kinds of awards. And it's like a home movie. There's a young woman, student at MIT, studying, I guess, computer science. And she finds that there's an inherent bias against blacks in artificial intelligence. Can you talk about the movie, Matthew? Sure, so the movie is the Coded Bias. And it's on Netflix, so people can watch it on Netflix today. And quite frankly, I think this is a movie that everybody should watch. It's very easy to understand how they explain a story of how Joy Buluwima, Buluwami, I think that's her name, an MIT genius, was looking at facial recognition software and realized that it's not very good to identify people of color. And there's this one moment in the movie, Jay, where the facial recognition can't see her face, but she puts a white mask on and the facial recognition software recognized her. So the Coded Bias is the beautiful story of her as she goes through this discovery of bias in artificial intelligence and how she ends up in Congress explaining the bias in artificial intelligence and how Congress then passed the law banning facial recognition in federal agencies. And it goes off into the UK showing racial bias used by the police in their facial recognition software. It goes into China and shows just how much facial recognition software is needed for you to get food, right? This social scoring. And it also branches into a beautiful story in Brooklyn where there's a group of residents that have to use facial recognition software to get into the building and also how the facial recognition software is being used to profile their activities within the building. It's quite fantastic. And it's a very educational and a video that will literally frighten people in a way to how much control there is artificial intelligence society. And there was one comment made within the movie that I really liked and that is this. We need to bake Western ideas into artificial intelligence and that's what the whole book reveals on how to do that. Yeah. Well, and this is perfectly in tune with your search for a transformational ethic. We live in a time where it's hard to get our arms around the new technologies. They run away from us. They run away with us. And this is an example of that. And just as you say, we may not be completely aware of how much AI plays in our lives and recognition and all the other things that flow from that. But in fact, nobody can escape, not in China and not in the US. I think the profound thing that it left on me was in China, all this is done by the government. In the US, it's done by Facebook and Amazon. Well, yeah, it's all done by big tech. And the European Union last week passed some regulation of artificial intelligence that literally changes the entire global landscape of artificial intelligence. Where AI, buoyed within European borders within two years has to classify it whether it's high risk, medium risk or low risk. Every single artificial intelligence has to be fine. And that changes the entire game. Big tech now has to become transparent. And the US has literally just fallen behind in the AI race to make it ethically aligned with society that honor the cultures, the beliefs and the values of society. AI to be a good digital citizen and not a citizen that influences our election. Yeah, we should go to that. But one comment about Europe and the EU and all strikes me that they're so far ahead of us in appreciating these issues and dealing with the business side of it, the ethical side of it, the social side of it. And you've got to give them credit for coming up with this. It's very courageous. And obviously democracy came out of grief. I think we can probably agree on that, which is in the European Union. And so it's not surprising. Now, the US itself, there are some good things happening in the USJ. Washington State have done something really incredible. They've passed for the Senate and it's going to the house now where everybody within the Washington State, they get user agency of their data, they get control of their data again, right? Which is way beyond what the federal government have done. And also every single AI that's involved in facial recognition has to pass a digital citizen test to ensure its quality to do well for all the diversity within society. And the book talks about this too. And obviously California with their data regulation laws, but I haven't seen anything where they've enforced it against Facebook or enforced it against Google or enforced against big tech. So the US literally has just dropped behind in the alignment of artificial intelligence as a beneficial citizen within society. Well, a year ago, maybe more, Congress seemed to wake up on the point and they had some hearings and testimonies from the big tech guys, the CEOs, and then, and if you watched it, and it was on C-SPAN and the media, if you watched it, you realized that the people who were asking the questions, that the sitting legislators in the Congress, they didn't have a clue that they were uninitiated. They didn't really know what to ask and they weren't getting any answers. Mark Zuckerberg was leading them around on a pretty chase. But the fact is they didn't know what to ask and they didn't get any meaningful information. A year goes by and they restarted those hearings with, I think, pretty much the same result. They had a year to get up to speed and I'm not sure that helped. And I'm not sure they're doing anything right now. I don't think Congress is doing anything about anything right now, except they did one good, one good thing today. I forget what it was. They did one good thing today, gotta get prepared. But by and large, Congress is not up to the task and I'm not sure when it's gonna be up to the task given the divisiveness. But what, go ahead. This is why innovation is returning back to the region or to the state level in the United States. That's why Washington State's doing that thing. Now, why it could do something, right? That's really exciting. Portland and Oakland have abandoned the racial recognition software in spite of the police force and federal agencies. So what I suspect is that the state and the region, Jay, will innovate much faster than federal government. And we need to look at the efficiency of Congress and the House on determining these issues. The quality of the mindset and the maturity in the debates from elected officials. The quality of whether they want America to do well and the societies in America or whether they just want big tech to do well. And so the problem with the U.S. at the moment is that it's looking to big tech to lead its future. And that isn't gonna work. It need to take a holistic approach where yes, we need to look at the military aspect of AI. That's important. But what's the point in protecting the U.S. borders AI is destroying society and the fabric of society. What are you protecting? So we need to take more of a mature and a holistic view where yes, military is important, but also we want the societies and the cultures within America to do really well as well. And that's important. And that I think is not seen as important within these debates. We feel quite terrible, really. Yeah. Well, and then going back to the, you know, the advance, if you will, in Europe, it strikes me that you had all these companies are global, you know, all the social media companies are global and they're powerful and they're worth billions and billions and billions and a lot of muscle there. So if you say in Europe, you have to, you know, you have to characterize the risk involved and we're gonna, you know, try to slow you down and bring some ethical overlay to all of this, which is really a good idea. That's gonna affect what, say, Facebook does in Europe, but query, Matthew, is that gonna affect what Facebook does in the United States or elsewhere? If I limit Facebook's activities in Europe, does that have a global effect on Facebook's activities elsewhere? Well, it may do. We may see Facebook being broken down and there has been conversations the same with Google, right? We may see broken down into separate businesses, where in Europe, it's giving an ethical experience without echo chambers and without control from advertising. And by the way, you know this, the facial recognition stuff you do on your phone, right? You hold up your phone and it basically says it's you. That's considered high risk in the European Union now. So what it means is all AI products and services will have to show whether they're high risk or low risk. So what I suspect is the social media experience in the European Union will be very different in two years' time than it is in America. Unless America decides to do something quite brilliant and enter into a mature and evolutionary mindset around AI and bring it as a purposeful technology to advance the whole of America and the whole of its societies. And if it does that, then it should be okay. But I don't see it yet. Oh, I don't see it either. One very interesting story that popped up in connection with the movie was his fellow who, his phone was broken, but he wanted to look at his mail. So he took his laptop to a parking lot outside, just see this outside a particular store that was giving away wireless. And he opened the top of the laptop and it came up with an error code. It said, you can't connect with these programs because your camera is an on. I said, what? What all of a sudden, it appears to him, it dawns on him that the programs he was looking at on his cell phone were turning his camera on. And because the laptop didn't have the camera on, it was showing him an error code. I find that fantastic. And this is, you talk about risk. People don't know this. They don't know how they're being pictured. Taking a picture of when they don't, nobody tells them, this fellow found out. And that's high risk. It is high risk. And that's why Cody Byers is an important discussion for the general public as a platform to understand where the issues are. So there's a great story in the film, isn't there? Of a teacher that gets all these awards in Houston, Texas, but AI has profiled him as a bad teacher. Yet, outside of technology, he's been recommended for this, he's winning awards for this, he's the best teacher of the month for this. And it just shows the disconnect between the big tech and what's really going on in the real world and how well people are really doing. And it shows a lack of nurturing. It shows a brittleness. It shows remote control. And it's not cool, it's not good at all. So that was a great story, I thought, about the teacher. And he actually went to federal court, isn't he? And there's also going on around this and say, tell us how did the AI algorithm come to this decision when I've got all these awards? Well, let's step back a little and talk about how AI works. Because, as you said at the outset, this movie actually helps you understand what it does and what it can do. And for example, why it's got implicit bias when it was not programmed to have implicit bias. It was not programmed very well in terms of excluding implicit bias, but nobody intended that it should be bias. It's just that the way AI works was by the, and what I mean by that, my perception of it, and I'm sure you have many more thoughts about it, is that it's like AI is fundamentally going to compare the subject at hand with millions, tens of millions of other records and make some conclusions. So for example, in the case of the African American, if AI looks through those tens of millions of records and finds that a large percentage of blacks are involved in crime, for example, or some violation of something, then it's going to rule against them and it's going to give them a low score. And even if they're good people, even if everything else points to a good person, that the comparison against some kind of demographic they look at is not positive. So the fellow who's using AI to hire, the fellow who's using AI to give a loan or sell a house, all that, it's a negative score. And it's not based on the individual. It's based on certain characteristics that go to a larger demographic, which may or may not be accurate, but that's the data. Bad data is the big weakness in AI. And maybe the data was right, but that doesn't have an ethical overlay. It doesn't have the American morality. It has a sad state of affairs in the United States is being perpetuated.  And it perpetuates their status as a underdog. And we've been doing this for a while. It's not just happening right now. And that's really a shocking part of the explanation of AI and how it creates bias, even without intending to do that. Am I right? What would you add to what I've said? Yeah, I would agree with you. Remember, there was a snippet of Steve Wozniak and there was a story where him and his wife have the same bank account, same everything. He applied for, I think it was a loan or a credit card and he got 10 times more credit than his wife and yet they hold the same asset. And there was an example about the AWS recruiting system, didn't it? Where it was biased against women and it was biased for men. And the European Union regulations called this out saying, no, no, no, no, no. You're not gonna have bias in AI and recruitment. You're not gonna have this bias anymore in these algorithms. So yes, the bias is proven to be in there. So the quality of the data and the quality of the algorithms combined determine the quality of the outcome. And unless we have ethics and an ethical intent with the data, that means there's transparency, there's government, there's user agency of data. So, unless we have ethics in the data and when we have ethics in the data and people involved in the conversation then we have more data sets because we're developing trust with the general public. More data sets means we can get AI better and more accurate in its decision making in the end result. That's really important. So yes, the algorithms need to be looked at but also it's the whole agency of the data ownership from the individual. This is what I say, Jay. Data is an extension of your human sovereignty and therefore as part of your human sovereignty you should be able to own, manage and have absolute transparency how your data is being used and what it's being used for. What do you say to the person who says to you, Matthew, I don't care. My life quote is an open book and quote they can know everything about me. I don't care if Google or Facebook or Amazon or Apple sells all my data. I don't care because my life is an open. What do you say to that person? Well, who gets to decide? So, is it big tech and government or is it the people? If I remember rightly, doesn't it start off with the people in the constitution? So, the destiny of the data should and how it's being used should come down to the people and the people's decision. That's why I think, and this is going to be really dangerous for people listening, we need a national referendum around user agency of data and a national referendum around artificial intelligence itself. We need to bring the public into the discussion and the decision making. So, to someone that says that, that's fine, but who makes a decision for the country? Who's deciding the future of data and artificial intelligence for the United States of America? Is it the people? That's what this movie shakes you up about because you cannot care whether your data is used, but in a demographic sense, in terms of the policies, social and business policies, governmental policies, it's, you do care. You do care because it comes right back around it and it affects you. But I'm going to ask you a hard question, Matthew. So, suppose you have this initiative at the governmental level. How exactly do you bring government in? I doubt the EU has gotten to this point. How do you make an algorithm? And we use the word lightly, and it sounds very high-tech, but an algorithm could be a skyscraper worth of code. An algorithm is a huge, huge thing. And how do you have transparency about that? How do you know what it does or doesn't do? Can you have the public go in and look and will they understand? And if they want to change it, who decides about the change? Yes, so that's a great question. So, all algorithms are a mathematics, right? And when you have self-learning aspects of artificial intelligence, and there's mathematics governing itself, learn, okay? So, it's all mathematics, really. Now, there are aspects, and this is why something called explainable AI is so important. Some of these algorithms, companies don't know how they're making decisions or why they're making decisions because they're teaching themselves. So, how do we get the general public to endorse maybe an algorithm? Well, it's very simple. We have a set of principles of what the algorithm must do and what it's for and who's it for and what are the benefits and how do we catch it if it goes wrong? So, there's a set of, and this is why I called it digital citizen test, is that there are a set of principles I believe we can put in place when short behavior of the algorithm. Now, that's the status today, Jay, what we call black box, right? It's like input stimuli, see what the black box does and see what the outputs are and see whether it does what it is. Where we need to go next is putting ethics, ethical mathematics into the algorithm itself. So, it's naturally ethical in all its different aspects of self-learning and all its different aspects of delivery of services within society because it has ethical mathematics. Now, this isn't the advancement in artificial intelligence mathematics and it's an opportunity and I think we're going to have to invent this, Jay. So, those... It would be overarching. It would say no matter what this algorithm might otherwise do, we are going to say, it takes me to the movie 2000 Space Odyssey. You know, I can't do that, Dave. I have an overriding constraint here. It's built into my DNA. My algorithm is controlled. So, I can't do that, Dave. And somebody got to figure out, A, what those rules really are. It's an establishment of the rules of our society, our morality, our ethics and impose them on whatever the algorithm might do. Yeah. So, ethics is the framework that's being used around the world now to try and align the diversity of humanity and the morality that we are in humanity with artificial intelligence and try to bring them together in a common singularity of meaning and purpose. So, AI ethics is literally about bringing the algorithms in line with societal values, right? And I'm saying societal value is not the exact values, right? That's what ethics are all about. Now, ethics will vary based on a nation's culture, maybe a spiritual culture or a belief culture or religious culture or your family culture or the personal culture or your organizational culture. It needs a diversity in its ethics in order to be able to perfectly serve people well in society. And if we don't do this, Jay, the public will reject artificial intelligence. Well, and maybe it should. It should because artificial intelligence is so powerful that it changes our lives. You know, one of the things, you know, I've always spelled that you go into a different firm and I'm sure you'll agree with this. And you say, you know, guys are using yellow pads. We have to get you up to stuff here. We have to, you know, show you about computers. We're going to computerize the firm. And this happens all the time. And in the process of computerizing the firm, you change everything. The firm is completely different at the end of the process. No yellow pads, but all the rules have to be rethought. So I think what you're saying is rewriting the algorithm, putting these restraints on the, you know, imposing ethical standards, moral standards, social, religious, cultural stamp, putting it all in there. That is rewriting not only AI, but our entire society. Am I right? Yes, absolutely. On the money. That's a great example. Thank you. That's right. That's the right, right?  But unless ethic and morals are put into artificial intelligence and the algorithms or at least the way they operate, then we're moving towards separation of what humanity is really about. And artificial intelligence is being controlled by six to nine companies in the world based on their values and based on their view that profit is before people and planet. You know, one of the things, and I, we only have a few minutes left, but maybe we can at least touch on it and then come back in another show, but this is so huge. This movie opened my eyes, you know, why, really why that is coded by us to show me that it was not just that they were, that these organizations, both in, you know, in authoritarian countries and where the government does it and in America where, you know, the company, the corporations do it, that they have a profile of us. They gather this information, they exchange it, they sell it, they build huge storehouses of data about all of us independently and maybe even collectively. And they know who we are, even if we don't care that they know, they know everything. And with mathematical formulae, those algorithms, they can predict what we want. That's why when you go on a given website, you see something you've been looking on, looking at on another website because you have demonstrated an interest in that product or service. And so it's all over your profile and somebody else is buying your profile and now they're advertising something you expressed interest in elsewhere.  They can predict your purchasing, they can predict your habits, they can predict your travel, they can predict your job performance. Everything can be predicted. It's like that movie with Tom Cruise, pre-crime. They can predict if you're gonna commit crime using AI. Well, it gets worse and I'll stop in a minute. It gets worse because they can predict how you're gonna vote. They can predict what your sensibilities are about voting and this is the worst part of all, they can predict your vulnerability. Your vulnerability to being lied to, to being manipulated by social media and the like. This is exactly what has happened with the internet research agency in Moscow with Cambridge analytics, Analytica, whatever, in London, with Vladimir Putin trying to affect public opinion in our elections. And there's no sign that that's stopping. There's no sign that that's even subsiding. And that is the scariest part of all. Am I right? That's absolutely right. I can't add anything to other than it is clear that Facebook is being used allegedly to influence elections in the foot of the day leading to the European Union and also in the US. And so it may well be caught in the middle of all this, which is probably the case, but it needs to do better and put guard rails. But you're absolutely right, Joe. That's a great analysis. Well, I'm concerned that it's gonna happen again. And he who uses, or she who uses AI for these vast of the purposes to determine our tastes and vulnerabilities, our weaknesses and then turn right around and get into those vulnerabilities and weaknesses and try to change our opinion, not just me and you, but millions of us. At the end of the day, there's a really good example of this in the movie, it was Facebook, they changed some leaflet they were sending out some message they were sending out to add some thumbnail photographs. And that resulted in a 300,000 person switch just by adding thumbnails on the bottom. You remember that part that was extraordinary. And so it's not just you and me, it's the population in general can be affected. Will you talk about it? Yes, this is actually a form of social scoring actually at the manipulative level, very subtle. At least the Chinese are very honest, right? We're gonna take your data and that's the way it is. Okay. In America, it's very different. And so what you're talking about is that you see a picture and you say, well, all my friends were really close to me that Facebook knows they all voted this way. And so it's like, well, I'll probably vote that way now because they're my friends and I trust them, we have great conversations. I know they're kids, they know mine. So it's subconscious manipulative. And so the European Union talk about this, there will be no more conscious manipulation within social media, which will change social media in the European Union completely two years time. So yes, Jay, these are the subtle things. And this was a Facebook project, Jay. This wasn't a Cambridge Analytica. This was Facebook doing a project. Now, this is not ethical. It's not good for the citizens. It's not transparent. It's not mature. And it's not the leadership of the future for the United States of America. Yeah, that's really scary, hard to control. And I'm not sure that Congress understands what we're talking about or that would take affirmative steps or that if you explain it to state legislators around the country, whether they would know what to do with it and how to follow it. And finally, and this is a good point to ask you for a final question is if we find a way to stop them, isn't it so just like hacking, isn't it so that we're in a spiral and they will find a way around us? And so we can close one window, they're coming in the other. Isn't that what would happen in the ordinary course? That's one potential reality. The other way to do it is innovate past them. Simple as that. So we're seeing this with Patreon. What you do is you make them irrelevant. You create ethical forms of social from the, you make it transparent. You give people user agency of data. You're clear in how data is used and what algorithms are in play. You're clear with a new ethical transparency. You just simply innovate past them. And this is a huge opportunity to make Facebook irrelevant actually. Now what's suspect is if Facebook truly want to become a meaningful experience going into our future over the next decade, they'll have to reinvent themselves because what they're providing at the moment is being a good measure for how we're not doing well on social media and how it needs to improve. So how Facebook decides to change and pivot and transform to become aligned with the values in society, aligned with the constitution, honouring diversity and equity. That will show how good this company really is. And if it doesn't, then I believe it will become irrelevant in the future. I hope so, but does that come from public concern as it come from governmental action? And when I ask you that question, I'm thinking of Fox News. And for that matter, the New York Post in the last few days have published and broadcast stories that are absolutely untrue.  It's not the first time, obviously, it's not the first time, but they would claim that if they had some belief that it was true, even though they really didn't, that would fall into the First Amendment and we can't stop them with that. And so it's hard to stop AI or social media from telling lies because what is a lie? Somebody has got to decide what is a lie. Can you rely on AI to decide what is a lie? I think we will do eventually. I think AI will become, as we talked about, our personal, digital body or guardian or digital angel that will protect us from all the manipulations that are going on. I think this will happen. And by the way, AI is being used to write articles in mainstream media, as you're aware. I think what we have to return to, Jay, is critical thinking. And if we return to critical thinking and we start to empower ourselves to assess what is the truth and what isn't the truth for us. Well, I want to assure everybody that inventing world 3.0, evolutionary ethics for artificial intelligence by none other than Matthew James Bailey was written by a human being person. And it was a gift to me by Mike Fitzgerald also in Denver. And I really appreciate that. It has opened my eyes and so have you, Matthew. And I hope we can do this again and drill down some more because there's one thing for sure. We're going to hear more about these issues. That sounds great. Thanks very much, Jay. I appreciate it. Thank you. Aloha. Thank you, Matthew. Aloha.


Good afternoon. I want to welcome these leaders who are coming in to have this very important discussion about some of the most pressing issues of our time. I am Kamala Harris. My pronouns are she and her. I am a woman sitting at the table wearing a blue suit. Excuse me. What? My pronouns are she and her. I am a white woman with long brown hair. I'm wearing a red dress and I'm wearing a see-through mask so you can see my red lips. I don't care. I am a black woman with curly hair and... It's over. We are screwed. I'm a Latina with long highlighted hair and I'm wearing a gray blazer over a black cheap dress.


In the raaadest are absolutely on fire right now. Not only to get a whole new coaching staff that plucks everybody from New England basically. With the signing of Devontae Adams to a brand new deal, allegedly Devontae was a lifelong Raiders fan. This is a dream come true. And his college quarterback, college roommate Derek Carr is over there. But still, nobody saw this happening because Aaron Rodgers and Devontae were a tag team that nobody could stop. But how does Aaron Rodgers feel about this? Allegedly he was on board and knew about this?  I know Lazard's a stud. M.V.S. what? He's still a free agent out there. Big Bob Tunney is still a free agent out there. Big Dog's still a free agent out there. Who's he throwing the rock to? But this is an interesting time for Green Bay Packers fans.


Hi, this is Dr. Don. I have a problem out of chapter 2 about the empirical rule and Z scores. The problem gives us the mean and standard deviation of a sample of farms. The mean X bar is 1500 and the sample standard deviation is 100. It says the data set has a bell shape distribution which is a clue that it's normal or approximately normal. It says use the empirical rule to determine which of the following farms are unusual, defined as more than two standard deviations from the mean, and very unusual more than three standard deviations from the mean. We're going to do this using basic Excel. Okay, I have an Excel workbook open with a blank worksheet and I've hidden the grid lines. You can go to view and click the grid lines on and off. I've cleared them off here just to make it a little bit easier to see. I've entered the sample mean of 1500 X bar and the sample standard deviation S of 100 and then the six values of X that we need to find the Z scores for. Remember the Z score formula is equal to X the value we're interested in minus the mean. Here we're using X bar and the sample standard deviation S. Now remember you can also use the population parameters which would be mu instead of X bar and sigma instead of S. But here we have a sample information so we use X bar and S. I'm going to click in this first yellow cell and my color notation is important. I use a light blue to tell me that's just raw data I've typed into a cell. I use light yellow to say that's a cell where I have a formula. Now we enter formulas by clicking in the cell hit equal to start entering the formula here. We want to put this formula in and we need to tell Excel to do this subtraction before it does division. Remember there's an order of operations that Excel will follow like you had to learn in high school. Here we use parentheses to guide Excel. I'm going to open up.  I'm going to subtract my mean X value up there in B1. Now I want to be able to copy this formula down so I can complete this spreadsheet more quickly. And I'm going to use a function key the F4 function F4. Well I've got that B1 selected and it enters the dollar signs before the column and the row designator. And that makes this an absolute reference which means I can drag the formula down and it will always refer back up here to cell B1. So I want to close that part with a closed parentheses. I want to divide by hitting the slash. And I want to divide by my standard deviation in B2. And again we use the function F4 function F4 to convert that to an absolute reference that I can click enter. And I want to show you how to we can then drag it down because we've got those absolute references. I'm going to just click in that cell get my cursor over to the black plus and then I can drag down to copy that formula and it copies it all the way down. And you can see as we go down it changes the first cell B6 is now X2 that's a relative reference but the absolute cells were locked and didn't change. One final thing I want to show you here I'm going to expose those formulas to help me remember Start typing FORM for formula and Excel will offer up formula text which is what I want. I'm going to double click that to enter it. I need to give it the cell reference. I want to use this one here to the left and just hit enter. Now I've got the formula in that cell and I can just drag that formula down to expose the other five formulas to help me remember what's in those cells. Okay now let's look at this. The first Z score for 1331 is minus 1.69. If I look over here on my empirical chart which shows 68% with the one standard deviation 95 within two standard deviations 99.7 within three standard deviations minus 1.69 would be somewhere in here. That's 1331 which is not more than two standard deviations so that's not unusual. 1787 is over here and you always should draw a sketch. That's more than two standard deviations obviously as we can tell by our Z score so that is unusual. If I go down here I can find 1120 which is minus 3.8 which is way over here on the very very small left side way beyond three standard deviations from the mean so that is unusual too. So I hope this helps. Learn to use basic excel. It can go a lot faster than this video that I'm trying to show you and then you can by formatting and labeling this and then saving your excel work with a good name you can reuse this the next time you need to find Z score. So I hope this helps.


how white is it? And we do have some availability in England, but I believe it's more limited than it is here in the US. But that's something that we're working on as well. I really appreciate you bringing up the plastics part of this, because that's something we're encouraging and trying to have our safer choice partner companies talk with each other about how to address single use plastics. It's something the United States is entering into negotiations on a global plastics agreement. And so it's something that's really top of mind for a lot of people. But it doesn't mean you have to completely change the way you do things. And it can be effective, maybe even save some money by using those concentrates and watering them down yourselves, rather than buying the single use.


Let's say for example, we want to narrow down our our search just a little bit more say I want to look at all of my Only my Saturday Coffee and special drinks. I want to see basically how many times people are going into our shop and Basically buying coffee or special drinks now. I want to throw out one more thing I want to see sort of when the hotbeds were and hotbeds I mean for example if we look you know New Year's Day for example does or this day after New Year's Doesn't exactly look like we're making a lot of business there makes perfect sense. It's the day after New Year's So I want to go ahead and narrow this down So one of the things that I was doing was I was running through my filter But what if I want to be a little bit more explicit with my filter? Well, let's say for example, we click on this amount filter One of the things you notice is that it also has this number filter section and that same number filter section if you notice these are very precise numbers, you know, I don't want to pick say for example Only show me when it's $323.35 I want to say something like show me when it's above $300 now with that number format section that actually allows me to do that I can actually hover over this and then select greater than What that's going to do is pull up a dialogue box that it does exactly that I can Specify now that I am looking for amounts that are greater than 300 as soon as I hit. Okay, not only do I see the Saturday specialty drinks and coffee drinks, but I see only 300 and above


SCP-472 is a red garnet of the pyrope spesartite variety. The phrase, for man looketh on the outward appearance, but the Lord looketh on the heart, has been engraved in two millimeters, high lettering on the stone's surface. Relevance of the phrase is unknown. When any organism possessing a heartbeat passes within an 18 meter or 60 foot radius of SCP-472, that subject will begin to hear the distant beating of a heart within their head. The heartbeat heard directly corresponds with the subject's own heartbeat, with the frequency of the palpitations increasing or decreasing with the pulse of the subject. Prolonged exposure causes a variety of additional psychological effects.


Recognise your own biases as a designer. Be conscious about your thoughts. Listen to your users, don't just hear them. Understand your personal preferences. Don't assume ask questions.


So, welcome back after having seen the property changes that happens in the subcooled or compressed liquid region when you go on compressing the subcooled liquid to higher and higher pressures we had seen that what is this percentage change that happens in this properties. So, on this slide I can again show you the same table where we saw that with the compression of the liquid subcooled liquid from its PCAT value which is 0.15 MPa to going to a very high pressure in fact above the critical pressure of water we saw that the value of V changes by only 1.21 percent compared to its VF value or VF that is a value at the saturation pressure of water alright corresponding to its saturation value if you see these changes are with respect to the VF value which lies on the two phase region or LV line. So, if I compare this property changes at higher and higher pressure with VF, UF and SF these are just close to 1 percent just above 1 percent I should say. As far as H is concerned the variation is little more than other properties so what do I conclude from here? It is very important conclusion that can be drawn from these figures from these numbers. So, we can see that if I just concentrate on the first column or the second column the property column which is specific volume we can say that the specific volume at 25 MPa can be approximately be equal to specific volume at 5 MPa or for that matter 10, 20 MPa and also all of these are equal to VF at 0.15 that means specific volume at 0.15 MPa or on the LV line on the two phase curve alright. So, these changes whatever are happening because they are happening in the fifth decimal place or the changes are just above 1 percent we possibly can neglect those changes even after compressing from 0.15 to 25 MPa these changes are approximately negligible if I assume this we can say approximately V25 is equal to V5 is equal to VF 0.15. We can conclude one more thing that specific volume which is a function of pressure and temperature I can say that specific volume in this region subcooled or compressed liquid region is not a function of pressure that is what we have seen here even if I went on compressing I could not see a effect a significant effect because of this compression process. That means p parameter here possibly is missing and I will say in this region in the subcooled or compressed liquid region specific volume does not depend on pressure it depends only on temperature. When I say it depends only on temperature I have not shown this but you can verify it using the steam table alright. Similarly now if I look at other properties if I look at thermal energy you can see this percentage change or hardly again matters so much and again can conclude that Upt is approximately equal to Uft so at higher and higher pressure these properties is the same as what it was on the saturation pressure line on the LV line alright. So I will say that again it is independent of pressure it does not depend so much on the pressure similarly I can see for the S also or for the entropy also because this variation also is negligible I say spt in the subcooled or compressed liquid region does not depend on pressure it is approximately equal to Sft that means p is not there at all what do I say from this I will say that the weak dependence on pressure in this region the properties V, U and S have weak dependence on pressure and why is this why am I making such a statement because if you remember right in the first lecture we had tried to compress liquid alright if you remember the compressibility of liquid we had said that liquid is incompressible so even if I compress liquid we had said that it does not get compressed so much the density changes the volume changes were hardly anything then as compared to that for the gas. Gas is compressible but liquid we had concluded was can be considered as incompressible so this is the reason the weak dependence on pressure is basically we say that liquid is incompressible so in this region of subcooled or compressed liquid because we know that liquid is incompressible even if we go on compressing liquid it makes hardly any changes in the properties of this subcooled liquid or a compressed liquid at higher and higher pressures and that is why we say that Vpt is equal to Vft, Upt is equal to Uft and spt is equal to Sft P is missing from these values because in this region of subcooled liquid this fluid is incompressible alright pressure will not play a significant role in this case. Now I am talking only about three properties well the fourth property was enthalpy and enthalpy I can write HPT enthalpy as you know is H is equal to U plus PV enthalpy is equal to U plus PV so if I write dependence of enthalpy so H depends on P and T generally is equal to Upt plus P and Vpt as we know but in this region we have already concluded that HPT is equal to Upt is Uft so if I go on writing those values Upt is equal to Uft and Vpt is equal to Vft because I know that the dependence in this region on pressure is negligible I can write Vpt as Vft and Upt as Uft so if I see overall enthalpy dependence in the subcooled region I will be getting governed by this equation now Uft plus P into Vft what do you mean by this what do you see from this if I go back to the table again I see that the enthalpy dependence on the pressure if not very very significant it is still there the changes had been of the order of 3 to 4 percent as against 1 to 1.5 percent in other properties it does show that as you go on compressing this liquid further there is some dependence on the pressure and why does it show it shows because of this presence of P here if I come back to the equation you can see that this is the pressure which plays important role because even if Upt is equal to Uft and Vpt is equal to Vft there is a P term that appears there which directly relates Hpt or the enthalpy to the pressure term. So if I go on increasing the pressure the pressure will show up on enthalpy because of this formulation alright in the other case there is a weak dependence but there is the pressure dependence in this case that is why you see in a table that for enthalpy I cannot assume that Hpt is equal to Hft I cannot do this assumption well I can do the same for V, U and S but not for H because of the presence of this P term here in this particular equation for enthalpy. So approximation I can do with volume with respect to volume thermal energy entropy for subcooled liquid may be taken same as P sat itself if I want to find out the properties the values of this properties at higher and higher pressure I did not go to higher and higher pressures I can do the same thing at P sat value only knowing that higher and higher pressure because this subcooled liquid is incompressible the properties will not change so much and therefore properties like V, U and S can be taken directly at P sat itself yeah this is the reason V, U, S at Pt is equal to Vf, Uf, Sf at P sat t alright. However enthalpy has to be calculated at the particular point as it is pressure dependent which is what we have seen that Hpt cannot be approximated as Hf P sat t which is what we could do because of the basic formulation of the enthalpy itself as we have done this formulation I have shown this formulation earlier alright. So properties can be taken V, U, S at P sat but not the enthalpy enthalpy can be directly computed from this formulation why did I do all these things it was first of all to show you that such an approximation holds good for V, U and S but importantly there are lot many steam tables which do not give all the properties the one which we are giving you it gives the properties at higher and higher pressures only no problems you can go into the details and find out all the properties at higher and higher pressures there are some steam tables which do not give the complete data for subcooled or compressed liquid regions they may give you properties at 0.15 for example and the next property may appear at 20 MPa state away or 15 MPa state away it is expected that you find out the value at 0.15 MPa or P sat and you can take the same values for 1 MPa, 2 MPa, 3 MPa with the approximation that that subcooled liquid is incompressible alright. In our table as far as the table that we have given that is not a problem because you got the values at 0.15, 0.16, 0.17, 0.2 etc where all these values can directly be taken from the steam tables but there are some steam tables which do not give the complete data for subcooled or compressed liquid in such cases properties at higher pressures may be approximated using P sat values why I need to take only the values at P sat and assuming that the liquid is incompressible I use the same values for further calculations hope you are clear with this approximation which we may not use but I expect that all the students of thermodynamics should know about this approximation just because of the fact that subcooled liquid is incompressible thank you very much.


Life is filled with regrets. It's not often surprising when, in our adulthood, we look back with regrets about things we could have done but didn't do. It can be easy to miss out on too many needful things to do in our 20s because we think we'll always have the time and opportunity to do them later. This decade may seem like a period to waste time and enjoy life to the fullest since there is almost no restraint to what you can do but it's the right moment to do most of the things we should do so we don't have regrets later. Here are some things you might regret if you don't do them now that you are in your 20s. 1. Being responsible with spending You might have read that it is crucial you save a percentage of all that you earn or that you learn to practice delayed gratification or that you shouldn't spend all you have but learn to budget. All these pieces of advice may mean nothing to you but soon, when you grow older, you'll understand why it was vital that you adhere to these pieces of advice. The blessing of being responsible with your spending isn't just that you have so much in your bank account. It saves you from frustration that comes with money mismanagement. Also, if you're irresponsible with money, certainly you will not be rich because it requires a deal of diligence to be able to manage money. Anyone who cannot manage money cannot make money. Anyone who cannot control his spending will almost never be debt-free because you will always never have enough for all you need. You don't have to buy what you don't need. Buy only what you need, save some part and invest the rest and it isn't bad to have a fixed budget for everything. 2. Better planning As a teenager, I never thought planning was necessary. I faced life as it came and this bad habit caught up with me. Looking back now, I regret not having planned my life early so that I can be prepared for a better future. Though I got lucky but we don't always have to bank on luck. Refusing to plan is planning to fail.  Because you didn't plan for success, you will never know when you've succeeded, if you ever succeed.  If preparation meets opportunity, then it is inevitable that lack of planning will make you keep losing opportunities. Because you won't know when opportunities come knocking. If you learn to plan your life now in your 20s, you will move further in life in your 40s. 3. Seizing more experiences If you aren't paying attention to experiences, you will regret not trying new things, not visiting some places, not learning new skills, not becoming the person you could have been, not taking the courses you could have taken. Some people regret not taking the decision or step that could have made them rich. They could have visited some places but they didn't. Now they are shoved in between a family having to work harder with spouse and children. You will do less tedious work in your 40s when you have invested your 20s into doing the work and gaining the experiences that will be useful for you in your 40s. 4. Living a more active lifestyle We have been told to exercise more often but it's easy to think this is just some needless gibberish. This decade of our lives is an opportunity to party without restriction and have all the fun we can, simply because we have the strength and time with us. Yet, refusing to move your body regularly will eventually tell on you in your 40s and 50s. Once, I ran a few minutes because I was late for a meeting with a client. Soon as I got to the client, I felt so faint I thought I would die. It didn't take long for the client to know. Young as I was, I hadn't been exercising. Being a health worker, she said it was dangerous. You may not love to exercise now but you will wish you had exercised sooner when you hit your 40s and 50s. 5. Pursuing a more meaningful career How many of us look back to regret the opportunities we have to change our career but never did? Many people wish they had taken a career leap instead of being too afraid and staying on a job they hate. They look back knowing they could have taken a better job which brought them meaning but they stuck with a frustrating job. Life can be beautiful but we occasionally look back with regrets and sigh, wishing we had planned more and done more with the freedom and energy we used to have. If you don't want to have this regret then it's time to start to pursue a meaningful career, one that you enjoy and not one that frustrates. 6. Investing early Too many businesses die in less than 18 months they've started. It is often because most of the entrepreneurs have almost no experience in business and investment. It is great to desire to have a lot of money on your retirement but if you don't start to invest early, you may not be as rich enough as you would want to be when you retire. The sooner you begin to invest, the earlier you can retire. You can be sure you will retire rich. No matter how hard you try, you can never return to your 20s to change anything. So it is very important that you learn to invest now in your 20s so you can get more riches, rest and save your strength and sweat in your 40s and 50s. 7. Connecting more with family Many adults live and die alone. And before they do, they regret not having shared time with families and friends. It may be fun to walk alone now, never having a social life and never having people you share your life with. But when you grow older, being alone will be one of the worst things that could happen to you. Humans are social beings. We are strengthened in relationships and weakened when we are alone. You may not be the best person you can be but love and relationships will strengthen you when you grow too old to mind these things of life. You never know how long people around you are going to live. Cherish them while you still can. 8. Building healthier routine and habits The 20s come with energy and freedom and so it is easy to think habits won't catch up with us. Sadly, they will. You can self destruct on pornography, binging on alcohol, overly partying when you should be in school and all other stuff that harms your health, waking up, eating well, moving your body regularly, etc. These are a whole slew of habits that can serve you well in your 20s.  9.  If you learn to go out of your comfort zone more often, it soon becomes a habit as you grow older. If you don't go out of your way to advance your career and personal life by taking more risks to meet and build relationships with people, you may regret it later. Now that you are in your 20s, you have a lot of room for more activities that will push you out of your comfort zone. You can do a few things a year that stretch you and you can do them each month. This way, you will experience profound growth which you will certainly enjoy in your 40s and 50s. If this video inspired you, like this video. We love you.


Late night, Lakeside, you can get breakfast at 11 o'clock at night and I love breakfast for dinner. Lakeside always is great and then our Ferguson Student Center, the food court, Delta has the best options, Wendy's their 4 for 4 will keep you stuffed every day. I personally love the Ferguson Center, so inside they have a Wendy's Chick-fil-A, just a wide variety of food options so whenever I'm waking up one morning I'm pretty sure the fur can handle whatever type of hunger I'm craving for that day so that's what I like to get done. We got a Chick-fil-A in Ferguson. Chick-fil-A, Chick-fil-A. Can I say Chick-fil-A? Chick-fil-A! Chick-fil-A definitely. I definitely love Chick-fil-A, all of my dining dollars go to Chick-fil-A and Starbucks. It's a dining hall, fresh foods is always going to be my favorite, it's right next to all my classes, really easy to go in and out of.  This is an easy one for me, it's probably where most of my dining dollars go is those food trucks, specifically the local Roots Truck. They are stationed all across campus every day, it's kind of a different location so make sure you check your email to see where they're going to be placed for that day but often times they're on Gorgas Library which is right next to the business school, one of my favorite places to get a bite right after one of my classes. I don't have to be burnt because we walk in late at night and we go get ice cream cones from their ice cream machine, so that's my favorite.


with the fact that we need to actually tackle all of the challenges at the same time. And I'm very glad that the European Union does that. I'm in the European Commission, the European Parliament. I'm the rapporteur on the Committee of the Regions of the Green Deal, and I also am of the same opinion. So we need to do recovery and fight COVID, but at the same time, do not lose a green deal from our side, because we need to actually engage in in promoting our priorities and realizing our goals simultaneously. And this is really important, and that's what is on the table, fortunately. Now, there is a certain disjunct, because unfortunately, our government, the conservative government, peace government, is not very keen on fulfilling green deal priorities. Whereas most of the opposition and obviously the mayors of the biggest cities who are either independent or represent opposition, they want to do just that because we know that there is no other way.  Secondly, because if we fight for quality of life in our cities, we need to fight for clean air and at the same time fight climate change. And that's why we, for example, should do as much as we can when it comes to saving energy, taking the diesel powered buses off the streets of our cities, investing in retrofitting and so on and so forth. What are the, what is the real problem? The real problem isn't, and as to, you know, actually addressed it, as always, point on, and that's what the position of the EPP is, that we cannot lose the people. And now the situation of Poland was difficult, especially a few years back, because we are very much dependent on coal, and we simply cannot lose so many jobs. Of course, there were also worries about price of coal, because, you know, we were so much dependent on it that changing from day to day to new energies would also be very difficult financially, because green energy 10 years ago, five years ago was much more expensive. Now, the situation changed completely. And, you know, I was also Minister of European Affairs and I negotiated climate change in 2014. And then our government, civic platform government, agreed for ambitious goals for 2030. It was 40 percent then. Now we know that we need to be more ambitious than then, than that. And what we agreed on was also, you know, all kinds of compensation mechanism, which would allow us to transform our energy mix towards a much more flexible and much more green energy mix, and also save jobs. That's what we did. Unfortunately, the current government didn't do anything in the past five years in order to really transform the sector. And the situation changed completely, because now, just in a few years' time, the energy from Polish coal is one of the most expensive in the world, because, you know, it's 1,000 meters underground, and green energy becomes much, much cheaper. There are possibilities with the money that the European Union earmarked for Green Deal to actually invest in new jobs and to actually invest in transformation. And thirdly, and most importantly, if you do not invest in those possibilities, you're not going to be innovative at all. And of course, you know, the world is changing in times of COVID. We reassess almost everything. And we need to reassess that as well. And if you, and that's what I tell all the conservatives in Poland, even if you do not believe in climate change, because some of them believe you do not, but some of them do not believe in climate change, even if you are worried about jobs, I mean, invest, invest and invest, because at the end of the day, the decisions will be taken, and we will simply be on the margins economically, and we need to invest in innovativeness.


The next set of dilutions that you will be required to do in the lab is a serial dilution. So in a serial dilution, all the solutions that you make up have the same dilution factor. Now that is different from a dilution series where in a dilution series, the different dilutions that you make up have different dilution factors. So that is something important to bear in mind. Now I am going to show as an example, I'm going to make up a series of one in three dilutions. So that means when I'm finished making, I'm doing my serial dilution, all my test tubes except for the first one which has the stock solution is going to have a dilution, each of these test tubes will have a dilution factor of three since we're doing one in three serial dilutions. So the first thing of course to do is to add water to your test tubes. Here I added two mils of water to each of the test tubes and then the idea here is that first I'm going to take a mil of my stock solution, mix it into two mils of the first test tube, then I transfer, I take out a mil and put it into the next test tube I mix and I do the same thing, taking a mil from the last test tube, putting it into this one and I continue doing this until I have done one in three dilutions in every single step. So that is how you would do a one in three or a three fold serial dilution. So this is how I will do this. So I already have my water in my test tubes, so the only thing I need now is to add my one mil of stock dye, this is blue dye and I'm going to make sure I mix it by piping up and down so I mix it thoroughly and I'm going to transfer the solution I made, one mil of the solution, into the next test tube contained water. Again I mix thoroughly and then again I'm going to take one mil of this solution, add it to two mils of water in the next test tube so as you notice as I continue my stock dye is becoming more and more diluted and I will continue this process of serial dilution until I get to the last test tube. So in order to keep all the volumes equal I will just discard one mil of my last solution and then when you look at all of them, when you compare all the solutions together you will notice from left to right, trying to hold all of them together, that the solution gets, the dye solid gets less concentrated this is the stock dye and this is the most concentrated dye. So each of these solutions has a dilution factor of three, if you wanted to determine the final dilution factor of this last solution you would have to multiply three by three by three by three, so you will multiply in three by itself five times and that would give you the final dilution factor of this solution. So making serial dilutions are important, for example, in medicine when they want to determine a correct amount of dose of a medication to give to a patient, if you're not sure exactly of the dose that will work for a patient, you can do a series of dilutions to determine what dose is best suited that will probably manage the patients' complaints or the patient's illness. So that is how basically you do dilutions in the lab.


How's it going everyone Caleb here with Leighton sports cards next up tonight David B Has one box of the sports card Almanac personal edition volume number two box number two. Thank you so much David B Let's get it going Dude, honestly, though. Yeah, that mixer is something you kind of have to be playing for months ahead of time Yeah, like in all seriousness Thank you very much David B back in here big card again man, we're on a roll Bowman Sterling 1099 Bobby which junior? Double 10 edges and corners 9 5 centering in a 9 surface 10 on the auto 92 of 99 we're on a roll right now very very nice That's a great card Congratulations David B box number two. We'll have it right out to you. Wow


Good afternoon and welcome to the fall assembly. This is about you. This is about the individuals at the University of Alabama who make a difference. Thank you for your focus on our mission and for making sure that we achieve remarkable things in the way that the University of Alabama continues to do. The fact that we consistently recruit the best and the brightest to the University of Alabama is a testament to you, to your work, to your dedication, to your commitment to our students and their desire to be at the University of Alabama. You know, to quote our commercial, this is the place where ambition meets opportunity and it's each one of you that provides that opportunity to our students to reach their dreams and achieve their dreams. We all come together to make a great university even greater and when it comes all down to it, it is our people that make the University of Alabama great. So as we commemorate the beginning of the fall semester, I challenge you to continue to be those legend makers. Few people can claim that title, but you can. You and your peers, our students are all part of that group that are legend makers here at the University of Alabama. Thank you for what you do every year. Thank you for what you're going to accomplish this coming semester in serving our students and serving our programs. Know that the impressions that you leave on this university will be here forever as mirrored in the lives of our students.


Hi, good morning, and welcome to today's product and focus so the terror attacks across over and And Paris initially caused the global markets to sell off Towards the end of the session there on Friday evening. We actually gap down a little bit lower this morning on the US 30 as you can See here, we've already made a little bit of gain back up to the bottom of Friday's candle nevertheless potential supports at 17 0 34 general theme that we're seeing this morning following Falling in Paris is a Kind of wait-and-see approach. You've seen a little bit of interest in the US dollar Certainly, you've seen interest in gold gold spike a little bit higher It's not had a huge impact on the global markets currently And oil prices are still quite low. They've been lower at the end of Friday's session They managed to bounce back a little bit But we'll come back to that in a second so Where we always had the bounce first thing this morning We had been slightly lower actually so it looks like we we gap lower and then move lower only for us to then bounce But 17 0 34 is the potential support from back here in December And that looks to be quite an interesting strategic level. So we're in the middle of the two ranges right now You've got 17 361 be the next potential resistance and then this be the next potential support So moving on to the UK 100 also had a bounce gap lower again commodity heavy and Copper and West Texas could not really do the huge amount this morning 6073 as the support level from back here on October We've not had a proper technical break of this level But it looks to be that 60 73 is going to be quite strategically important in the short term as well for the UK market So jumping on Japan 225 Gap lower again bounced higher You are looking at 19104, which is the tip of this candle here from July has been the potential support That would also coincide to the 21 period SMA more economic data that came out of Japan this morning I think slightly disappointed by quite a lot look at GDP in fact They were expecting something a little bit better right there, but it did fail But again that this adds more on us on potential monetary policy a stimulus sorry in Japan 225 So that's why that mark is not reacting in a negative way to the Macra data coming out So having a look at dollar yen You can see that the US dollar had a bit of a bounce as for the US dollar sometimes can be a flight to safety But I would have thought the yen actually would have benefited a bit more But the benefit the reason why that's not been the case is the week GDP figure that's come out Makes it look like that. There's gonna be monetary stimulus more QE It actually weakens the Japanese yen So usually the yen is a safe haven but people have been jumping on gold because it has got the biggest potential Because it's been squeezed so much over the last couple of sessions. So that's kind of where we are for it with Dolly M 121 18 spot 87 is a potential support level to be aware of So moving on to West Texas the West Texas came off quite aggressively there on Friday has been lower The candle that we've seen so far today is in decade with a get a gapped up But it's not really doing huge amounts for far today looking at it from an entity chart perspective It's slowly grinding higher, but I don't think the fundamentals really have changed that much 4199 basically $42 is going to be a potential resistance longer term potential support As you can see it's a tip of this but a tip of this candle down here 3750 as a potential support So let's have a look at gold so gold's had a decent bounce, but it could be capped by this potential support level Basically $1100. This is very interesting for gold very strategic level keep your eye on it Regardless of your view if you bullish a bearish and gold this level is important today So then moving on to the FX pairs so your dollar to finish things up bounced off the session lows around about one spot zero six It is going to feel the pressure around about one way I've Rebalanced to redrawn the support resistance levels on your dollar to take the tip of the candle from May 27th And as you can see it matched up quite nicely to to July and also where we are just now in November longer-term potential support one spot zero five 24 So then moving on to GBP USD to finish things off We've managed to Break above one spot to 173 Last week. We're still keeping our head above there just now There could be a slight drift if the US dollar does become flavor of the month as I said Haven asset class Where we could see a slight drift back down to one spot 51 72 71 sorry And it's when we get to here that things get a bit more interesting these dology formations Just now to show an unwillingness to push on higher for GBP But let's have a look at the macroeconomic data. So today brings your whole host of Eurozone CPI That's pretty much it and that's at the 10 a.m. UK time and if you go on to Tuesday, we've got UK CPI PPI and RPI so a whole host of quite important data for the UK that could be good for a GP USD You have the ZDW business report very important German bed data And then you've gone the consumer price index for the US at 130 UK time on Tuesday And then if you go on to Wednesday, then we've got our our crude oil inventories have switched back from from from Thursday to Wednesday So back to crude oil Wednesday. So that gives you a bit of an idea what to expect to start off the week Make sure you keep your eye on the chart form make insights part of your late going forward and join me again tomorrow to find out What happened next?


Hi you guys, Lindsay here. Welcome back to my channel, Inside the Hymn. So I have to start this off by apologizing. It seems I've been teasing you guys with this make for far too long. In all honesty, I thought I had posted it already. So you've seen my DIY pumpkin decor project using these fabrics. You've seen a bit of this dress in my snaps tutorial, but now you finally get to see the whole thing. Are you ready? Here she is. This is my mixed gingham dress I made by combining three different sized ginghams. As you can imagine, the hardest part about this make was assigning the ginghams to the different pattern pieces and then cutting it out. So let's start from the beginning. I got all three fabrics from Stylemaker fabrics last year. They are quarter inch, half inch, and one inch black and white gingham. I had one yard of each fabric and used up just about all of it. As for patterns, I knew I wanted a dress. Originally, I thought I would be making a traditional shirt dress, but I ended up using this variation of a shirt dress when it came out earlier this year. This is McCall's 7889. I made VUB pretty much entirely as it was designed. I had enough to think about with the fabric, so I didn't want to complicate things with the pattern. The pattern is described as a very loose fitting top and dress with a button front closure with separate front band, double front and back yolks, stitched plate detail at waist, and neckline sleeve and link variations. VUB has bias cut yolks and lower bands. VU's B and C have a tie belt and VUD has a neckband with tie ends. I knew I wanted the body in the larger gingham. That was easy. I just thought that the larger print would be more flattering. Then I started filling it in with the half inch gingham. I ended up using that for the front and back yolk, the belt, and the bottom bands. The pattern will have you cut the bottom bands twice the length and fold it in half before attaching it to the bottom of the bodice, but because I wanted this cut on the bias, I didn't have enough fabric for that, so I cut half the pattern piece and did a baby hem instead. All that was left was the front band and the sleeves, so that's what I used the quarter inch gingham for. The quarter inch gingham sort of looks like a solid gray from far away, so just be mindful of that when placing yours. There are a ton of different combinations for where you can place the different ginghams. Try not to think about it too hard and just go for it. The biggest tip I can give you for this is to cut your bodices on the straight of grain and then cut everything else on the bias. It's much more visually appealing to not have everything going vertically. As I showed you last week, I opted for snaps instead of buttons, which made quick work of the closure. There is a lot of talk on review sites about this pattern being huge. I would first like to point out that the pattern does describe it as very loose fitting, but I used the finished garment measurements for the waist to make sure that it would fit nicely and I feel like I got the fit pretty good. It's loose across the bust and hip naturally, but the waist is fitted, which is super flattering. The belt also helps cinch in any extra bulk that's there. For the next version of this dress, I would lengthen the belt. I can't tie it into a proper bow because it's just not long enough. I would say it needs another six inches, maybe more. I would also lengthen the dress entirely. I would lengthen it from the cut edge of the bodice and not the band, though. I think the length of the band is proportionate as is. Another couple of inches would be in order for me. My next version is going to be made from a cotton ball, which is a little lighter weight than this gingham. It will be interesting to see how the pattern looks in different weight fabrics. I think the sleeves will lay closer to the body as well as the skirt. There will be a much more relaxed look to the garment altogether. Anyway, I really enjoyed making this and had so much fun thinking outside of the box with the fabrics. Print mixing is so striking when done correctly. I hope you are inspired to try it out for yourself. Well, that's going to do it for me today. Thank you so much for watching. I will see you all very soon. Bye!