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[Assistant] The fossil fuels that are buried that we're burning took millions of years for those, for the Earth to bury those, including those ancestors of Prochlorococcus. And we're burning that now in the blink of an eye on geological time scales. Carbon dioxide is increasing in the atmosphere. It's a greenhouse gas. The oceans are starting to warm. So the question is, what is that going to do for my Prochlorococcus?


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[Assistant] And I'm sure you're expecting me to say that my beloved microbes are doomed.


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[Assistant] But in fact, they're not. Projections are that their populations will expand as the ocean warms to 30 percent larger by the year 2100. Does that make me happy? Well, it makes me happy for Prochlorococcus, of course.


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[Assistant] But not for the planet. Uhm, there are winners and losers in this global experiment that we've undertaken.


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[Assistant] It's projected that among the losers will be some of those larger phytoplankton, those charismatic ones, which are expected to be reduced in numbers. And they're the ones that feed the zooplankton, that feed the fish that we like to harvest.


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[Assistant] So Prochlorococcus has been my muse for the past 35 years. But there are legions of other microbes out there maintaining our planet for us. They're out there


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[Assistant] Ready and waiting for us to find them so they can tell their stories too. Thank you.


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[Assistant] Well, hello and good morning, good afternoon, and good evening. Welcome to this English lesson about agriculture, about farming, about what it's like to be a farmer. Let's get started. So,


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[Assistant] A farm. A farm is simply a place where food is either grown or animals are raised for food. Notice I used two different words there and I'll get to that in a little while why there are two different ones. But a farm


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[Assistant] Yes, I do have the same microphone, but I took off this little piece because I'm not outside. So yes, same microphone. Sorry, I just saw that in the chat.


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[Assistant] The act of doing that, we would say, is farming. Okay? So that person is farming on that road. I wonder what that farmer is growing. I'm sure he's farming every, uh, moment of the day. Sorry, that was a bad example. But the act of doing it is called farming.


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[Assistant] The general term for farming is agriculture. Okay, so when you talk about all of the things that you can do that involve the growing of food or the raising of animals, the


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[Assistant] Proper term, the official term is agriculture.


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[Assistant] So in Canada, we do not have a government division for farming. We have a government division for agriculture. It's actually a ministry. It's called the Ministry of Agriculture and Food. So agriculture is your most formal term for farming.


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[Assistant] Uhm, I do want to pause and say uhm, hi to the 300 people that are watching. I'm actually surprised that that many people have joined already. I didn't think this would be a popular topic, but I'll tell you a little secret.


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[Assistant] I never know which topics are going to be the most popular. Sometimes when I do a topic that I think will be popular, it isn't. And sometimes when I do a topic that I think won't be popular, it is. So, uh, I see in the chat someone saying, is farming like a profession? Yes, that's correct. Um, generally if you live on a farm,


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[Assistant] You will probably live in a house, but we actually call it a farmhouse.


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[Assistant] So a farmhouse is the house that's on the same property. Uhm, a farmhouse is like the room I'm sitting in. I am living in a farmhouse right now.


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[Assistant] There's nothing different about a farmhouse compared to a regular house. It just happens to be on a farm. So on a farm, the type of house you would have there is a farmhouse.


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[Assistant] Some people really like farmhouses, uhm, because they are generally bigger houses with lots of space and they usually have really big kitchens. Uhm, I think because long ago farmers usually had lots of kids and so they needed a big kitchen to feed all their kids.


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[Assistant] The person who does the farming is called a farmer. Now there is no gender specific word for farmer in English. If you are a man or a woman, you are a farmer. I am a farmer. Jen is a farmer. We are both farmers. So the person who does the farming is called a farmer. Uhm.


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[Assistant] Let me get to the next slide here and then in a moment we will start on some questions. Uhm, the other building that you will see on a farm


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[Assistant] Another thing you'll see on a farm is something called a silo. You may have seen silos in some of my videos as well. The silo is the big round structure, the tower that you see on a farm. Don't get confused though, this is a grain bin.


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[Assistant] So the shorter structure that's usually made out of metal, we would call a grain bin, and the taller structure,


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[Assistant] That you see here, we call a silo. Often, I'm gonna call them city people.


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[Assistant] When you live in the country, you sometimes refer to people from the city as city people. So sometimes city people, uh, get these two names confused. So this is a silo. A silo is used to store feed during the, for the winter. So oftentimes farmers will put, uh,


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[Assistant] Lolly has given a super chat for Dave and Todd. By the way, thank you so much for all the super chats and everything from last week for Dave and Todd. I haven't told them the total yet, but uhm, they're pretty happy or they will be pretty happy.


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[Assistant] Again, this is a grain bin. So this is used to store things like wheat or corn, uh, what we call grain crops. So there is definitely a difference between the two.


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[Assistant] You will also find a building called a machine shed or a drive shed. So this is a place where the farmer will keep all of his or her tractors and equipment.


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[Assistant] So we on my property as well, when you watch my videos, sometimes you'll see the barn in the background. Sometimes you'll see the machine shed in the background. It has two names. You can call it a machine shed or a drive shed. Uhm, most farms also have a shop.


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[Assistant] or workshop and I wanted to put this one in here because the word shop in English has a number of different meanings. So shop can also be the short form of workshop. So my father-in-law


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[Assistant] Let's see here. Uhm, you might also on a farm see a chicken coop. So chickens get their own special name for the little building that they live in. A chicken coop can be outside, like the one you see in this picture. But a chicken coop can also be inside of a barn.


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[Assistant] Earlier Nate Indy asked if I had chickens. We do have chickens. We have ten chickens. Our chickens are in a chicken coop and the chicken coop is inside the barn.


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[Assistant] Notice I'm just going through all the different structures that you will see on a farm. So just a quick review. There's a farmhouse, there's a barn, silo, grain bin, machine shed, shop or workshop, and chicken coop. Uhm, I think that's all of them. There's a few other things you'll see on a farm as well.


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[Assistant] Uhm, if you have animals that graze, grazing is when animals eat grass in a field or pasture. But if you have animals like cows or sheep or goats, those are considered grazing animals.


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[Assistant] They sometimes will be in a pasture, especially during the nicer times of the year. We have a pasture along the river and sometimes our goats and sheep are out on the pasture.


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[Assistant] Uhm, but a pasture is a large field with mostly grass in it where animals go to graze. So I'm not sure if you know the word graze, but those are called grazing animals. Animals that eat grasses.


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[Assistant] Let me see here. That pasture is usually surrounded by a fence. A fence is a structure that you build so that animals can't get out of the pasture.


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[Assistant] When I was a kid, sometimes the cows would get out. So when I was a kid, we had a dairy farm. We had cows that we milked. And sometimes the cows would get out, uhm, because the fence was broken. So the fence is what keeps the animals inside of the pasture, uh, or the field.


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[Assistant] Hey, I just want to pause and say hi to the 447 people watching this lesson. If you're new here, there is a subscribe button right there. You should click it and then you will get notified when I do a new English lesson.


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[Assistant] And then the general term, let me make this a little bigger. The general term for any area of land where you grow things, uhm, is called... Sorry, I'm just gonna check something here. I think one of my slides is missing. Nope, it's there. It'll come in a sec.


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[Assistant] Uhm, a big area of land where you grow crops, where you grow plants, is called a field. So, farmers have many fields around their farmhouse, around their farm and around, sorry, and around their barn. I'm getting farm and barn mixed up. Uhm,


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[Assistant] Yeah, Nate Indy's asking if Oscar runs, uh, to kind of chase the grazing animals. He's not super good at it. He's not a good herding animal at all.


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[Assistant] Uhm, I just talked about fences. There is a saying in English, good fences make good neighbors. And I'm just curious, uhm, let me know in the chat if you have a similar phrase in your language. What this means is that


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[Assistant] When two people live beside each other and when they are neighbors.


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[Assistant] They are nicer to each other if there is a fence.


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[Assistant] If you have a desk that touches another person's desk, uhm, sometimes people will put up a little divider because good fences make good neighbors. Sometimes when you have your own space, it just works better.


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[Assistant] One thing if you have livestock, uh, if you have animals, you will have manure. So there's no nice way to say this. Animals eat and then animals pee and animals poop. So you end up with manure. We put straw into our pens and our animals


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[Assistant] And then when we clean out our pens, we put all of the manure in the manure pit.


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[Assistant] Some farms have a manure pile. It's just a different way of describing it. But when you have animals, you will have manure. Now,


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[Assistant] The good thing about manure is that if you let manure sit for one year,


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[Assistant] It composts and it turns into a really nice soil amendment.


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[Assistant] Uhm, it turns into really nice fertilizer. So, if you have livestock, uh, you will definitely


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[Assistant] Have manure. Uhm, but if you don't have a lot of manure, you will use fertilizer. So fertilizer comes in a bag. It's granular. That means it's small little pieces and you can just spread that on your land.


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[Assistant] Let's get into some of the things that you will see on a farm. Farmers always have farm machinery or farm equipment. You can use both names.


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[Assistant] Um, I have a lot of farm machinery. In order to operate a farm, you need equipment. You need machinery. You need machines that will help you do the things that you need to do. So let's, uh, I'm not going to go over all the different types of farm equipment, just about four. So if you're not interested in farm equipment, bear with me.


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[Assistant] So just like you drive a car, in English you drive a tractor. Okay, I'm gonna drive the tractor over there. Oh, he's out driving the tractor in the field.


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[Assistant] So you, uh, if you live on a farm, you will have a lot of tractors.


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[Assistant] Anything you pull behind a tractor, first of all, you pull it. So you pull things with the tractor. We would call equipment or we would call it an implement. Okay. So you could say there are a lot of farm implements or there's a lot of farm equipment or there's a lot of farm machinery.


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[Assistant] Uhm, another type of, uh, farm, piece of farm equipment is a combine.


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[Assistant] So, I didn't talk about this word last week, uhm, but someone asked about different pronunciations. This is a combine or a combine harvester. We usually just call it a combine.


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[Assistant] Uhm, and then what's tricky about this is it looks like the word combine. So you can combine two words together to make a new word. You can combine ingredients to make something in your kitchen. But this is a combine. Notice the slightly different pronunciation. You can combine two things.


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[Assistant] But this is a combine. I'm not even sure if you can hear it, but it's definitely a slightly different pronunciation.


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[Assistant] Uhm, but a combine is used to harvest. So combines are interesting pieces of farm equipment because they are incredibly expensive.


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[Assistant] Probably almost a million dollars for a combine now. And interestingly, it's only used


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[Assistant] A little bit. It's used just a little bit in the fall and summer to harvest crops. Uhm, many farmers will have different types of wagons. Uhm, so they'll have wagons like the top wagon here we would call, uh, just a wagon. This one we would call a grain wagon. So if you are harvesting, the crop would go in the grain wagon.


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[Assistant] Oh, yes, sorry, that was the, I could talk about farm equipment all day, but I thought those were the ones that I should go over in an English lesson. So, uh, let's look at the different types of farms, but give me one second, uh, before we do that. Um, actually, no, sorry, let me go back.


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[Assistant] I'm losing track of what I'm doing. Let's look at a few different types of farms, then I'll do some questions. So if you raise cows to milk them,


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[Assistant] They milk the cows once or twice a day, sorry, two or three times a day, not once. I grew up on a dairy farm. I should know this. They milk the cows two or three times a day, uh, and the milk goes in a large tank and a truck comes and picks the milk up every other day.


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[Assistant] But interestingly enough, most dairy farms now in Canada have a robot that does the milking. So my grandfather milked by hand. My father and mother had milk machines that milk the cows. They had to put the machine on the cow.


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[Assistant] That's what a dairy farm is. If you have cows that you are raising for beef, uhm, for in North America, the fast food industry needs beef. People barbecue a lot and they need beef. So you would have a beef farm, okay? So a dairy farm is for milk.


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[Assistant] A beef farm is for beef or meat production.


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[Assistant] Uhm, you might have a chicken farm. There are two kinds of chicken farms. There are chicken farms that produce chickens for meat. So my other neighbor has a chicken farm and they raise chickens for meat. You can also have a chicken farm where you have chickens for egg production.


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[Assistant] If I go down the road a number of kilometers, there is another farmer and he has a chicken farm and they produce eggs. Okay? Uhm.


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[Assistant] You might have a hog farm or pig farm. There are two different names. If I, uhm, sorry, I'm not sure why. Just one sec here. Also my camera decided not to focus on me, so I just fixed that. Uhm, if I look across the river,


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[Assistant] Okay, so again, uhm, interestingly enough, when you go to the grocery store, if you want to buy meat, and if it's from a pig, we call it pork.


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[Assistant] Uhm, and then there are some goat farms in Ontario. There aren't a lot. Goat farms can be either farms where they milk the goats so that they can have goat milk and make goat cheese.


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[Assistant] Uh, my family to eat goat meat. Um, I think because we came from Holland originally, we, it's just not part of something we eat, but it is a very common meat, so.


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[Assistant] Um, and then let me see here. You might have a sheep farm. So a sheep farm obviously is a farm where you have sheep. There are not, I don't know any farms.


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[Assistant] I know in most countries there are farms where they milk sheep and they make cheese out of the sheep milk. Uh, in Canada there are not very many farms that milk sheep. Almost all of our sheep are raised for meat.


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[Assistant] There's also something called a vegetable farm. Uhm, so.


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[Assistant] Let me make this a little bit bigger. A vegetable farm. Notice I went to a different country for my picture this time, because I thought I should be a little bit more equal. I picked mostly pictures about Canada, but I thought I should pick pictures from around the world.


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[Assistant] A vegetable farm grows vegetables and I forgot to put a slide in for fruit farm. So a fruit farm grows fruit.


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[Assistant] There are many vegetable farms north of Toronto. I know that might seem strange. It's somewhat a little bit colder north of Toronto, but there are a lot of vegetable farms in a place called Bradford, Ontario.


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[Assistant] Uhm, they just have really good soil and they grow things like onions and carrots and all those kinds of things. So again, just imagine there's a slide that says fruit farm.


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[Assistant] A fruit farm is a place where you grow fruit. A fruit farm would grow things like peaches and apples and pears and plums and nectarines, all of the different types of fruit.


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[Assistant] We don't grow bananas in Canada. So again, thank you if you are from a country that grows bananas. If you have a banana farm and you are watching this video, you are my hero.


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[Assistant] You are awesome. But in Canada, we can't grow things like that. Uhm, you might have a flower farm.


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[Assistant] You might recognize this. So you can see in this picture, you can see my drive shed or machinery shed or machine shed. You can see that I, oh, I can't put my hand over top of the picture. Can I?


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[Assistant] You can see the two silos, you can see the barn, and then in front you can see the flowers. So there are farms that grow flowers, we would call them a flower farm.


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[Assistant] Now, I forgot to put fruit farm, but I did remember to put orchard.


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[Assistant] Uh, an orchard is a place where you grow fruit. So if you have a bunch of trees in a certain place on your farm and you are growing apples or pears or other kinds of fruit, we would call it an orchard. Um, orchards are really nice places to work because it's almost always shady. Um, that's probably the best thing about orchards.


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[Assistant] Uhm, let's see here, I'm just checking where I am. Oh yes, and then there's of course, uh, vineyards. So, close to me, uhm, I live close to an area where you can grow grapes. A vineyard is a place where you can grow grapes. Uhm, so close to me, probably about half an hour's drive, there are many, many vineyards.


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[Assistant] I live close to Lake Ontario, and Lake Ontario is a really big body of water.


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[Assistant] That creates a microclimate to the south of it. A microclimate is when the weather is a little warmer or cooler because there is a lake or body of water close by. So I live close to Lake Ontario. Lake Ontario creates an area where you can grow grapes in Ontario. So there are a lot of vineyards.


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[Assistant] They grow grapes for eating. We call them table grapes.


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[Assistant] They also grow grapes to make grape juice and to make wine. There are a lot of wineries close to me. So if you ever come to Canada and you are a someone who likes drinking wine, you will probably visit that area because there are a lot of wineries where you can go and you can taste wine.


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[Assistant] Uhm, let me get to the next slide. Uhm, we have a phrase in English called farm fresh. When you go to the grocery store, uhm, sometimes you buy food that is farm fresh. This simply means that the food went from the farm


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[Assistant] Uhm, if you really want farm fresh food though, if you want food that is really fresh, I would buy it at a farmer's market. The farmer's market where we sell flowers. There are several farmers there. Oh, the fly is back.


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[Assistant] There are several farmers there that sell fruit and that sell vegetables and I would say if you want farm fresh food,


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[Assistant] Yeah, anger in North America because of what's called factory farming. So in Ontario, Canada, we have family farms.


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[Assistant] But we also have farms that have grown so big


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[Assistant] But doesn't always care too much about the animals that they are raising. First of all there are no factory farms growing vegetables. There are no factory farms growing fruit.


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[Assistant] Factory farms are always farms that are raising some kind of livestock. So uhm, right now in Canada there are uhm, people who would like laws changed so that factory farming can be changed to be more.


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[Assistant] Uhm, friendly to the animals that are being raised. So you might hear or read the word phrase factory farming, uh, when you are studying English.


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[Assistant] Uhm, anything that an animal on a farm eats is simply called feed, okay? So there's chicken feed, there's pig feed, there's rabbit feed, uh, there's every kind of feed that you can think of. We buy our feed from the feed mill.


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[Assistant] Anything that a farmer grows is called a crop, okay? So even though we grow flowers, we say that, oh,


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[Assistant] We're getting, it's a pretty good crop of flowers this year. It's a pretty good crop of soybeans this year. It's a pretty good crop of wheat this year. Uhm, oh, the crop's doing well out in the field. The crop is doing well. Sorry, I'm shortening my words a little bit.


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[Assistant] And so, Mahdi says, people feed. Yeah, we don't have people feed. You don't go to the people feed store to buy, uh, to buy feed for people.


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[Assistant] Uh, but yes, anything that a farmer grows is called a crop.


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[Assistant] When you put seeds in the ground, you plant them. So my neighbor comes and he will plant my crops for me. Okay. So the verb is to plant. So he plants my crops. He puts the seeds in the ground for me.


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[Assistant] Uhm, when he comes in the fall with his combine, he harvests the crop. So again, at the beginning of the growing season, so the time where you grow things, uhm, is called the growing season.


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[Assistant] Uhm, at the beginning we plant our crops, at the end we harvest. Gonna jump to the chat. Brent says, I'm sad this will be the last Friday livestream I will be able to attend for a while. School starts next week. So Brent, have a great school year, first of all. And then second, I'm not sure what time I will be doing the Friday livestreams.


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[Assistant] Starting in a few weeks. Next week will be the same. The week after will be the same. Uhm, but at a certain point, I'm not sure what time this will happen at. It might be a little earlier or a bit later. We'll see. So anyways, let's get to the next slide here.


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[Assistant] If you live in a place where it does not rain very much you will have to irrigate your crops. So when you irrigate it means you use


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[Assistant] Uhm, pumps and pipes to put water onto your crop.


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[Assistant] I almost hit my microphone. Uhm, that is called irrigating, okay? We irrigate our flowers. We do not irrigate our bigger crops. We just do not have the equipment to do it. Uhm, so our flowers we irrigate. If you watch the video about uhm, learning


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[Assistant] Oh, the tour of the farm that I did a couple weeks ago. Uhm, maybe Todd or Dave can find that video, but a couple weeks ago I did a video about our flower farm. Uhm, and in that video I show you some of the ways that we irrigate. When you irrigate, it means that you put water on the crop so that it will grow. Uhm, and then just to review,


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[Assistant] Sorry, I don't know who this guy is, but I thought it was a funny picture. When you grow plants, you use the word grow. Okay, so we grow flowers.


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[Assistant] Uhm, but we raise chickens, okay? So notice the difference. If you're talking about plants, you use the verb grow. So we grow flowers, I grow soybeans, we grow hay. Anything that comes out of the ground that is a plant, we grow.


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[Assistant] Uhm, Vladimir says it's perfect when you have rains to irrigate. Yes, it's really dry right here, right now though, Vlad. We're a little worried that it needs to rain soon. Uhm, not for the flowers, but for the bigger crops. So again,


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[Assistant] You grow plants, you raise animals, okay? So he raises ducks, he raises cows, he raises pigs. Uhm, that is the difference there. And then, here we go.


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[Assistant] The difference between an acre and a hectare, or a hectare. So we, in Canada, measure all... one sec.


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[Assistant] In Canada we measure all of our pieces of land in acres.


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[Assistant] In most parts of the world, you measure in hectares. A hectare is about two and a half acres. So an acre is smaller, but if you buy a farm, you say, how many acres is that farm? Okay. And then you buy the farm, buy the acre. When you sell a farm, you say, okay, 200 acre farm for sale, X amount of dollars per acre.


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[Assistant] Um, uh, if you live in a different part of the world where you use the metric system, you would use hectares, which is a hundred meters by a hundred meters. Um, but yes, there are certainly different ways to measure the size of the farm.


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[Assistant] I'm a monster truck, but I'm very friendly.


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[Assistant] My family just moved here. Wanna see something cool?


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[Assistant] Tire Town School. Episode 47. Recess Race.


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[Assistant] Hey, slowpoke! Zippy yelled. Zippy took off. Grrrr! Said Eddie. He raced after the balloon.


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[Assistant] Ha ha! said Zippy. You're slow!


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[Assistant] Hi Poppy, said Eddy. Poppy glared at Eddy. Don't say hi to me, she snapped. You forgot to help me.


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[Assistant] The Squire made a vow to feed ten thousand Buddhist monks. He will surely give you some food.


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[Assistant] You also had the two horses that were stolen from his stable. We got everything from the real robbers.


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[Assistant] Oh, you got everything from the real robbers.


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[Assistant] Tell me, where are the real robbers now, hm?


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[Assistant] We can't go to jail! We're making an important journey to visit Buddha!


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[Assistant] What are you talking about? You killed Squire Ku!


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[Assistant] Why did you tell the judge that the Tang monk and his companions killed me?


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[Assistant] If you don't, I will haunt you for the rest of your life!


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[Assistant] We forgive you. The Squire was a kind man. His death is a terrible tragedy.


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[Assistant] Wukong brought the king of the black rooster kingdom back to life. He turned to the monkey. The sage, Laozi, helped you that time. Will you ask him for help again?


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[Assistant] The Squire may return to Earth until it's time for him to come back here.


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[Assistant] When your life is over, you will return to your job here.


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[Assistant] It's an awful feeling. Every now and then I become aware that I have a tongue inside my mouth. And then it starts to feel all lumped up. That's the most stupid thing I've ever heard.


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[Assistant] I think your magic fingers left your lunchbox back at the bus stop.


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[Assistant] Journey to the West, chapter 100, a terrible robbery.


[User] Please transcribe this text

[Assistant] For over a month, the traveler stayed at Squire Koo's house.


[User] Please transcribe this text

[Assistant] Every time they tried to leave, the Squire begged them to stay longer.


[User] Please transcribe this text

[Assistant] After breakfast, Wu Jing got the horse from Squire Coo's stable.


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[Assistant] Bajie gathered the bags. The Tang monk thanked Squire and Lady Ku, and the travelers headed west.


[User] Please transcribe this text

[Assistant] The next morning, Lady Ku ran into the town's courthouse. Tears filled her eyes. I must speak with the judge. She cried. The judge rushed to her.


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[Assistant] Ask the judge. Lady Ku gritted her teeth. The Tang monk and his companions!


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[Assistant] Wukong laughed. You don't realize who I am. I'm Sun Wukong, the Monkey King.


[User] Please transcribe this text

[Assistant] The Tang monk raised his eyebrows. A squire?


[User] Please transcribe this text

[Assistant] Wukong quickly recited a spell, which froze the robbers.


[User] Please transcribe this text

[Assistant] Wu Jing rushed to the horses and opened one of the bundles.


[User] Please transcribe this text

[Assistant] Wukong recited another spell, and the robbers became unfrozen.


[User] Please transcribe this text

[Assistant] The monkey grew large and fire burned in his eyes.


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[Assistant] The travelers headed back toward town with the squire's horses. Soon they saw a group of soldiers on horseback.


[User] Please transcribe this text

[Assistant] One of the soldiers pointed a sword at the travelers.


[User] Please transcribe this text

[Assistant] Oh, it's kind of you to say it. I do want to do that. Humanity has, uh, obviously a lot of issues and, and, uh,


[User] Please transcribe this text

[Assistant] You know, people at times do, do bad things, but you know, despite all that, uhm, you know, I, I love humanity and I think we should, uh,


[User] Please transcribe this text

[Assistant] Yeah, no, that was extremely stressful. No question. Uhm, we obviously could not.


[User] Please transcribe this text

[Assistant] Uhm, let them down anyway, uhm, so.


[User] Please transcribe this text

[Assistant] Extremely stressful I'd say, uh, to say the least. We did, I was confident that at the time that we launched.


[User] Please transcribe this text

[Assistant] No one could think of anything, uh, at all to do that would improve the probability of success. Um, and we, we racked our brains to think of any possible way to improve the probability of success. We could not think of anything more and, and nor could NASA. And so.


[User] Please transcribe this text

[Assistant] Then that, that's just the best that we could do. So then we, we had, we went ahead and launched. Now I'm not a religious person. Um, but I nonetheless got on my knees and prayed for that mission. Were you able to sleep?


[User] Please transcribe this text

[Assistant] Yeah, for high stress situations, I find it's not so much elation as relief.


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[Assistant] And uhm, you know, I think once, as, as we got more comfortable and proved out the systems, because, you know, we, we really, uhm, you know, you gotta make sure everything works. Uhm, I was, it was definitely a lot more enjoyable with the subsequent, uh, uh, astronaut, uh, missions. And I thought the,


[User] Please transcribe this text

[Assistant] The inspiration mission was actually a very inspiring, uhm, inspiration for mission. Uhm, I'd encourage people to watch the inspiration documentary on Netflix. It's actually really good. Uhm.


[User] Please transcribe this text

[Assistant] Orbit that, uh, in like 30 or 40 years or something, the only one that was higher.


[User] Please transcribe this text

[Assistant] Was this one shuttle, sorry, a Hubble servicing mission? Uhm, and then before that it would have been, uhm, Apollo in 72. It's pretty wild.


[User] Please transcribe this text

[Assistant] So it's cool, it's good, you know, I think, uh, as, you know, as a species, like we want to be, you know, continuing to do better and reach higher ground and, and


[User] Please transcribe this text

[Assistant] I think it would be tragic, extremely tragic if, um, Apollo was the high water mark for humanity, you know, and that, and that's as far as we ever got. Um, and it's, um, it's concerning that here we are, um,


[User] Please transcribe this text

[Assistant] 49 years after the last mission to the moon and so almost half a century, uh, and we've not been back. Um, and that's, that's worrying. It's like, is that, does that mean we've peaked as a civilization or what? So.


[User] Please transcribe this text

[Assistant] Like I think we got to get back to the moon and build a base there, you know, a science base. I think we could learn a lot about the nature of the universe if we have a proper science base on the moon.


[User] Please transcribe this text

[Assistant] You know, like we have a science base in Antarctica and you know, many other parts of the world and.


[User] Please transcribe this text

[Assistant] Uhm, so that, that, that's like I think the next big thing we've gotta have like a, a serious like moon base, uhm, and then get people to Mars and, you know, get, get out there and be a space-bearing civilization.


[User] Please transcribe this text

[Assistant] Yeah, I mean, during the launches itself, so I mean, I think, I think maybe some people know, but a lot of people don't know is like, I'm actually the chief engineer of SpaceX. So, um, the.


[User] Please transcribe this text

[Assistant] You know, I've signed off on pretty much all the design decisions. Uhm, and, you know, so if there's something that goes wrong with that.


[User] Please transcribe this text

[Assistant] About all the things that like, so, so when I see the rocket, I see all the things that could go wrong and the things that could be better. And the same with the dragon spacecraft. It's like.


[User] Please transcribe this text

[Assistant] Other people say, oh, this is a spacecraft or a rocket. And that's what looks really cool. I'm like, I've, I've like a readout of like, this is the, these are, these are the risks. These are the problems. That's what I see. Like, so not what other people see when they see the product, you know.


[User] Please transcribe this text

[Assistant] No, it's actually, by far the biggest thing absorbing my time is engine production.


[User] Please transcribe this text

[Assistant] Not the design of the engine, but I've often said prototypes are.


[User] Please transcribe this text

[Assistant] So we have the most advanced rocket engine that's ever been designed.


[User] Please transcribe this text

[Assistant] That's the Russian engine basically, uhm, and uhm, and still, I think an engine should only count if it's gotten something to orbit. Uhm, so our engine has not gotten anything to orbit yet.


[User] Please transcribe this text

[Assistant] Uhm, but it is, it's the first engine that's actually better than, than the, the, the Russian RD engines which were amazing design.


[User] Please transcribe this text

[Assistant] Well, it's, the Raptor is a, a full flow, uh, staged combustion, um,


[User] Please transcribe this text

[Assistant] So one of the key figures of merit, perhaps the key figure of merit is, uhm, what is the chamber pressure at which the rocket engine can operate? That's the combustion chamber pressure. Uhm, so a Raptor is, uh, designed to operate at, uh, 300 bar, possibly maybe higher, that's 300 atmospheres. So,


[User] Please transcribe this text

[Assistant] Uhm, the record right now for operational engine is the RD engine that I mentioned, the Russian RD, which is I believe around 267 bar.


[User] Please transcribe this text

[Assistant] And the difficulty of the chamber pressure increases on a nonlinear basis, so 10% more chamber pressure is more like 50% more difficult.


[User] Please transcribe this text

[Assistant] But that, that chair pressure is, that, that, that is what allows you to get a very high, uh, power density for, uh, for the engine. Uhm, so, uh, enabling, uhm,


[User] Please transcribe this text

[Assistant] Exhaust, the effective exhaust velocity of, of the gas coming out of the engine. Uhm, so, uh,


[User] Please transcribe this text

[Assistant] With a, with a very high chamber pressure, you can have, um, a,


[User] Please transcribe this text

[Assistant] In a, in a staged combustion, a full flow staged combustion, there, there are many.


[User] Please transcribe this text

[Assistant] Uh, feedback loops in the system. So you, uh, basically you've got, uh, propellants and, and, and, uh, hot gas flowing, um,


[User] Please transcribe this text

[Assistant] Simultaneously to so many different places on the engine, uhm, and, uh, they, they all have a recursive effect on each other. So you change one thing here, it has a recursive effect here, it changes something over there and, and it's, it's, it's quite hard to control. Uhm, like there's a reason no one's made this before. Uhm, but, uhm,


[User] Please transcribe this text

[Assistant] Uhm, so in order to make a fully reusable rocket, uhm, that's really the holy grail of orbital rocketry.


[User] Please transcribe this text

[Assistant] You have to have, everything's gotta be the best. Uh, it's gotta be the best engine, the best airframe, the best heat shield.


[User] Please transcribe this text

[Assistant] Extremely light, uh, avionics, um, you know, very clever control mechanisms. Uh, you've got to shed mass in any possible way that you can. Um, for example, we are, instead of putting landing legs on the booster and ship, we are going to catch them with a tower to save the weight of the landing legs. So that's like, I mean, we're talking about catching


[User] Please transcribe this text

[Assistant] On a giant tower with, with chopstick arms. It's like a karate kid with the fly, but much bigger.


[User] Please transcribe this text

[Assistant] This probably won't work the first time. Anyway, so this is bananas. This is banana stuff.


[User] Please transcribe this text

[Assistant] We'll, I think we will, we'll get Starship to work.


[User] Please transcribe this text

[Assistant] Uhm, there's a question of timing. How long will it take us to do this? Uh, how long will it take us to actually achieve full and rapid reusability? Uhm, because it will take probably many launches before we are able to have full and rapid reusability. Uhm,


[User] Please transcribe this text

[Assistant] But I can say that, that the physics pencil's out, like, like we're not, uh,


[User] Please transcribe this text

[Assistant] Like at this point, I'd say we're confident that like, let's say I'm very confident success is in the set of all possible outcomes.


[User] Please transcribe this text

[Assistant] For a while there, I was not convinced that success was in the set of possible outcomes, which is very important, actually. But, so, uhm, uhm. You're saying there's a chance. I'm saying there's a chance, exactly.


[User] Please transcribe this text

[Assistant] I'm just not sure how long it will take. We're a very talented team, they're working night and day to make it happen.


[User] Please transcribe this text

[Assistant] Like I said, the critical thing to achieve for the revolution in space flight and for humanity to be a spacefaring civilization is to have a fully and rapidly reusable rocket, orbital rocket. Um, there's not even been any orbital rocket that's been fully reusable ever. And this has always been the.


[User] Please transcribe this text

[Assistant] The, the, the, the holy grail of rocketry. Uhm, and, uh, many smart people, very smart people, uh, have tried to do this before and they've not succeeded. So, uhm, cause it's such a hard problem.


[User] Please transcribe this text

[Assistant] I mean, for me, it's simply this, this is something that is important to get done. Um, and we, we should just keep doing it, um, or die trying and I, I don't need.


[User] Please transcribe this text

[Assistant] I like saying like, like physics is law and everything else is a recommendation. Um, like I've met a lot of people that can break the law, but I haven't met anyone who could break physics. So, uh, so first for, you know, any kind of.


[User] Please transcribe this text

[Assistant] Technology problem, you have to sort of just make sure you're not violating physics.


[User] Please transcribe this text

[Assistant] You know, uh, first principles analysis, I think is something that can be applied to really any walk of life, uh, any, anything really. It's just, it's, it's really just saying, um,


[User] Please transcribe this text

[Assistant] You know, let's boil something down to the most fundamental, uh,


[User] Please transcribe this text

[Assistant] Uh, that's, you know, so that's just to establish, is it, is it possible? And then another good physics tool is thinking about things in the limit. If you, if you take a particular thing and you, uh, scale it to a very large number or to a very small number, how does, how do things change?


[User] Please transcribe this text

[Assistant] Like manufacturing, which I think is just a very underrated problem, uhm, and, and, uh, like I said, it's, it's much harder to


[User] Please transcribe this text

[Assistant] Uhm, so let's say you're trying to figure out is, uhm, like why is this, this, uh, part or product expensive? Is it, uhm,


[User] Please transcribe this text

[Assistant] Because of something fundamentally foolish that we're doing, or is it because our volume is too low? And so then you say, okay, well, what if our volume was a million units a year? Is it still expensive? That's what I'm thinking about things to the limit.


[User] Please transcribe this text

[Assistant] But like that's a common thing in rocketry because the unit volume is relatively low. And so a common excuse would be, well, it's expensive because our unit volume is low. Um, and if we were in like automotive or something like that, or consumer electronics, then our costs would be lower. I'm like, I'm like, okay, so let's say now you're making a million units a year. Is it still expensive? The answer is yes. Then, uh, economies of scale are not the issue.


[User] Please transcribe this text

[Assistant] Is, uhm, if you take any, uh, any, any product, any machine or whatever, uhm, like take a rocket or whatever, uh, and say,


[User] Please transcribe this text

[Assistant] If you've got, if you look at the raw materials in the rocket, uhm, so you're going to have like a, I don't know, aluminum, steel, titanium, inconel.


[User] Please transcribe this text

[Assistant] What's the weight of the constituent elements of each of these elements and what is their raw material value? And that sets the asymptotic limit for how


[User] Please transcribe this text

[Assistant] And then when you do that, call it like maybe the magic one number or something like that. So that would be like if you had the.


[User] Please transcribe this text

[Assistant] So then, and that is always a, almost always a very low number. Uhm, so then, what's actually causing these to be expensive is how you put the atoms into the desired shape.


[User] Please transcribe this text

[Assistant] Yeah, I mean, I think if you, if you are really good at manufacturing,


[User] Please transcribe this text

[Assistant] You can basically make at high volume, you could basically make anything for a cost.


[User] Please transcribe this text

[Assistant] That asymptotically approaches the raw material value of the constituents plus any intellectual property that you need to do license. Anything. Right.


[User] Please transcribe this text

[Assistant] But it's hard, it's not like that's a very hard thing to do, but it is possible for anything.


[User] Please transcribe this text

[Assistant] So what will often happen in trying to design a product is people will start with the tools and parts and methods that they are familiar with, uhm, and then, and try to create a product using their existing tools and methods. Uhm, the other way to think about it is,


[User] Please transcribe this text

[Assistant] Uh, actually imagine the, try to imagine the platonic ideal of the perfect product or technology, whatever it might be.


[User] Please transcribe this text

[Assistant] Uhm, and so what is this, what is the perfect arrangement of atoms that would be the best possible product? And now let us try to figure out how to get the atoms in that shape.


[User] Please transcribe this text

[Assistant] Well, just as a function of inertia, people will, uh, want to use the same tools and methods that they are familiar with. Um, they just, that's what they'll do by default.


[User] Please transcribe this text

[Assistant] And then that that will lead to an outcome of things that can be made with those tools and methods, but is unlikely to be the platonic ideal of the perfect product.


[User] Please transcribe this text

[Assistant] Then so that's why it's good to think of things in both directions. So like, what can we build with the tools that we have? But then, but, but also what is the.


[User] Please transcribe this text

[Assistant] What is the perfect, the theoretical perfect product look like? And that, that theoretical perfect product is going to be a moving target because as you learn more, the definition of, or for that perfect product will, will change because you don't actually know what the perfect product is, but you can successfully approximate, uh, a more perfect product.


[User] Please transcribe this text

[Assistant] Um, so think about it like that and then saying, okay, now what tools, methods, materials, whatever do we need to create in order to get the atoms in that shape?


[User] Please transcribe this text

[Assistant] Uh, you know, it's, it's fundamentally, um, you know, engineering the, the vehicle, um,


[User] Please transcribe this text

[Assistant] I mean, Starship is the most complex and advanced rocket that's ever been made by.


[User] Please transcribe this text

[Assistant] I don't know what a magnitude or something like that. It's a lot. It's really next level. So.


[User] Please transcribe this text

[Assistant] Uhm, and the fundamental optimization of Starship is minimizing cost per ton to orbit and ultimately cost per ton to the surface of Mars.


[User] Please transcribe this text

[Assistant] Um, like there is a certain cost per ton to the surface of Mars where we can afford to establish a self-sustaining, uh, city. Um, and, uh, and then above that, we cannot afford to do it.


[User] Please transcribe this text

[Assistant] Uhm, so right now you couldn't fly to Mars for a trillion dollars. No amount of money could get you a ticket to Mars. So we need to get that above, uh, you know, to get that like something that is actually possible at all. Uhm, but, but then, but that's, that's


[User] Please transcribe this text

[Assistant] We don't, we don't just want to have, you know, with Mars flags and footprints and then not come back for a half century like we did with the moon. Uh, in, in order to.


[User] Please transcribe this text

[Assistant] Pass a very important to great filter. I think we, we need to be a multi-planet species.


[User] Please transcribe this text

[Assistant] This may sound somewhat esoteric to a lot of people, but, uh, eventually given enough time,


[User] Please transcribe this text

[Assistant] You know, eventually, if none of that happens and somehow magically we keep going, uh, then the sun will, the sun is gradually expanding, um, and will engulf the earth. Um, and probably earth gets too hot for, uh, life in, uh,


[User] Please transcribe this text

[Assistant] Cause the current situation is really remarkable. Um, and kind of hard to believe, but.


[User] Please transcribe this text

[Assistant] Uh, Earth's been around four and a half billion years, and this is the first time in four and a half billion years that it's been possible to extend life beyond Earth.


[User] Please transcribe this text

[Assistant] And that window of charity may be open for a long time and I hope it is, but it also may be open for a short time. And we should, uh, I think it was wise for us to, uh,


[User] Please transcribe this text

[Assistant] I mean civilization could get, uhm, could die with a bang or a whimper.


[User] Please transcribe this text

[Assistant] You know, if it's a, if it dies a demographic collapse, then it's more of a whimper, obviously. Uh, but, and if it's World War III, it's more of a bang. Uh, but, but these are all risks.


[User] Please transcribe this text

[Assistant] I mean, it's important to think of these things and just, you know, think of things as like probabilities, not certainties. Uhm, there's a probability that something bad will happen on Earth. I think most likely the future will be good.


[User] Please transcribe this text

[Assistant] I think you might be right about that. Uh, so, then, uh, you know, we should basically


[User] Please transcribe this text

[Assistant] And have a second planet with, with life. That would be great. They can't bring themselves there, you know, so if we don't bring them to Mars, then they will just.


[User] Please transcribe this text

[Assistant] For sure all die when the sun expands anyway, and then that'll be it.


[User] Please transcribe this text

[Assistant] Uh, no, they could certainly return, some will return back to Earth. They will choose to stay there for the rest of their lives. Yeah, many will.


[User] Please transcribe this text

[Assistant] But, uh, we, you know, we need the spaceships back, like the ones that go to Mars, we need them back, so you can hop on if you want, you know, but we can't just not have the spaceships come back, those things are expensive, we need them back, I'd like to come back and do another trip.


[User] Please transcribe this text

[Assistant] So, and like I said, we can't get there with.


[User] Please transcribe this text

[Assistant] Yes, ideally less than, much less than a million times, but if it's not, like it's got to be.


[User] Please transcribe this text

[Assistant] How much can society afford to spend or just want to spend on a self-sustaining city on Mars? The self-sustaining part is important. Like it's just the key threshold.


[User] Please transcribe this text

[Assistant] Uhm, the great, the grateful to what will have been passed when the city on Mars.


[User] Please transcribe this text

[Assistant] It doesn't matter what the reason is, but if they stop coming for any reason, will it die out or will it not? And if there's even one critical ingredient missing, then it still doesn't count. It's like, you know, if you're on a long sea voyage and you've got everything except vitamin C.


[User] Please transcribe this text

[Assistant] It's only a matter of time, you know, you're going to die. So, so we're going to get Mars, Mars city to the point where it's self-sustaining.


[User] Please transcribe this text

[Assistant] Uhm, I'm not sure this will really happen in my lifetime, but I hope to see it at least have a lot of momentum.


[User] Please transcribe this text

[Assistant] Uhm, and there's a lot of uncertainty about this. You could say like, I don't know, it's probably at least a million tons. Uhm, cause you have to set up a lot of infrastructure on Mars. Uhm, like I said, you can't be missing any, anything that,


[User] Please transcribe this text

[Assistant] Iron ore refineries, like you need lots of things, you know, uh, so, um, and Mars is not super hospitable. It's the least inhospitable planet, but it's definitely a fixer upper of a planet.


[User] Please transcribe this text

[Assistant] There might be some great planets out there, but it's hopeless.


[User] Please transcribe this text

[Assistant] We currently do not know of any means of going faster than the speed of light.


[User] Please transcribe this text

[Assistant] Like, there, there are some ideas about having space, like so, so,


[User] Please transcribe this text

[Assistant] If this is possible, the amount of energy required to wolf space is so gigantic, it's boggles the mind.


[User] Please transcribe this text

[Assistant] Well, as I was saying, really the Holy Grail is a fully and rapidly reusable orbital system.


[User] Please transcribe this text

[Assistant] Falcon 9 is the only reusable rocket out there. But the booster comes back and lands, you've seen the videos, uh, and we get the nose-conal fairing back, but we do not get the upper stage back. So...


[User] Please transcribe this text

[Assistant] Uh, that means that we have a minimum cost of, of building an upper stage.


[User] Please transcribe this text

[Assistant] You can think of like a two stage rocket of sort of like two airplanes, like a big airplane and a small airplane. Uhm, and we get the big airplane back, but not the small airplane. And so it still costs a lot, you know, so that upper stage is, you know, at least 10 million dollars. Uhm, and then the,


[User] Please transcribe this text

[Assistant] Degree of the, the booster is not as reuse, it's not as rapidly and completely reusable as we'd like in all of the fairings. So, you know, our, our kind of.


[User] Please transcribe this text

[Assistant] Minimum marginal cost, not counting overhead for per flight is on the order of 15 to $20 million maybe. Um, so.


[User] Please transcribe this text

[Assistant] Uh, with full and rapid reusability, we can reduce the cost per ton to orbit by a factor of 100. Just think of it like, uhm,


[User] Please transcribe this text

[Assistant] I can imagine if you had an aircraft or something or a car, and if you had to buy a new car every time you went for a drive, it would be very expensive. It would be silly, frankly, but, um, but you, in fact, you just refuel the car or recharge the car and that's, uh, makes your trip


[User] Please transcribe this text

[Assistant] I don't know, a thousand times cheaper. So it's the same for rockets. Uh, if you, it's very difficult to make this complex machine that can go to orbit. And so if you cannot reuse it and have to throw even any part of any significant part of it away, that massively increases the cost. So.


[User] Please transcribe this text

[Assistant] You know, Starship in theory could do a cost per launch of like a million, maybe $2 million or something like that. Um, and, uh, and put over a hundred tons in orbit. This is crazy. Yeah.


[User] Please transcribe this text

[Assistant] No, no, there's no, there's no brilliant break. No, there's no, it just, we're going to make the rocket reusable. This is an extremely difficult engineering problem. Got it. Uh, but no, no new physics is required.


[User] Please transcribe this text

[Assistant] Well, it would be a new frontier and an opportunity to rethink the whole nature of government, uh, just as was done in the creation of the United States. So.


[User] Please transcribe this text

[Assistant] You know, a coercion of the politicians and that kind of thing. Um, so I, I'd recommend, uh, that, that there was just.


[User] Please transcribe this text

[Assistant] You know, there's like always like a slight amount of trepidation when you click accept cookies. Like I feel as though there's like perhaps like a, like a very tiny chance that'll open a portal to hell or something like that. That's exactly how I feel. Why, why do they, why do they keep wanting me to accept it? What do they want with this cookie?


[User] Please transcribe this text

[Assistant] Like somebody got upset with accepting cookies or something somewhere. Who cares? Like so annoying to keep, keep accepting all these cookies.


[User] Please transcribe this text

[Assistant] I think fundamental problem that we're, because we've not really had a major.


[User] Please transcribe this text

[Assistant] Be immortal, um, cause some of the rules and regulations that are put in place will be counterproductive, uh, done with good intentions, but counterproductive. Sometimes not done with good intentions. So.


[User] Please transcribe this text

[Assistant] Um, if you just, if rules and regulations just accumulate every year, um, and you get more and more of them, then eventually you won't be able to do anything. You're just like Gulliver with, you know, tied down by thousands of little strings. And we, we see that in, um, you know, U S and.


[User] Please transcribe this text

[Assistant] Like basically all economies that, uh, have been around for a while.


[User] Please transcribe this text

[Assistant] Uh, and, and regulators and legislators create new rules and regulations every year, but they don't put effort into removing them. And I think that's very important that we put effort into removing rules and regulations.


[User] Please transcribe this text

[Assistant] Yeah. So yeah, something needs to happen.


[User] Please transcribe this text

[Assistant] Or, or just the civilizations arteries, arteries just harden over time. And, and, uh, you can just get less and less done because there's just a rule against everything. Uhm, so.


[User] Please transcribe this text

[Assistant] So I think like, I don't know, for Mars or whatever, I'd say, or even for, you know, obviously for Earth as well, like I think there should be an active process for removing rules and regulations and questioning their existence. Just, uhm.


[User] Please transcribe this text

[Assistant] Like, if we've got a function for creating rules and regulations, because rules and regulations can also think of like, they're like,


[User] Please transcribe this text

[Assistant] So it's like we shouldn't have rules and regulations, but you have code accumulation, but no code removal. Uhm, and so it just gets.


[User] Please transcribe this text

[Assistant] Um, and, and it's just, it makes it hard for things to progress. So I don't know, maybe Mars, you'd have like a.


[User] Please transcribe this text

[Assistant] It should be easier to remove a law than to add one because of the, just to overcome the inertia of laws. So maybe it's like, uh,


[User] Please transcribe this text

[Assistant] I mean, that's happened to me so many times, I think maybe even literally.


[User] Please transcribe this text

[Assistant] I never quite understand this whole smart contract thing. Uhm, you know. I mean.


[User] Please transcribe this text

[Assistant] I mean, my general approach to any kind of like deal or whatever is just make sure there's clarity of understanding. That's the most important thing.


[User] Please transcribe this text

[Assistant] Um, and, and just keep any kind of deal very, very short and simple, plain language. Um, and just make sure everyone understands this is the deal. Is everyone, is it clear? Um, and, uh,


[User] Please transcribe this text

[Assistant] And then what are the consequences if various things don't happen?


[User] Please transcribe this text

[Assistant] You know, business deals or whatever are way too long and complex and overly layered and pointlessly.


[User] Please transcribe this text

[Assistant] Need to have a different currency because you can't synchronize due to speed of light.


[User] Please transcribe this text

[Assistant] No, not easily. So it must be completely standalone from earth. Well, yeah, cause the.


[User] Please transcribe this text

[Assistant] Mars is at closest approach, it's four light minutes away roughly, and then at furthest approach, uh, it's roughly 20 light minutes away, uh, maybe a little more.


[User] Please transcribe this text

[Assistant] I don't know if Mars would have a cryptocurrency as a thing, but probably seems likely. But it would be some kind of localized thing on Mars. And you let the people decide.


[User] Please transcribe this text

[Assistant] Yeah, absolutely. The future of Mars should be up to the Martians. Uh, yeah. So, um, I mean, I think the cryptocurrency thing is an interesting.


[User] Please transcribe this text

[Assistant] Okay, you mean literally, that's literally what's happening. In batch mode.


[User] Please transcribe this text

[Assistant] Okay. Yeah. Pretty the poor bastards who have to maintain that code. Okay. That's it.


[User] Please transcribe this text

[Assistant] That was a pain, that was pain. Not even Fortran, it's Cobalt. Yep. It's Cobalt.


[User] Please transcribe this text

[Assistant] And this increases the error in the database that is money. So I think money should really be viewed through the lens of information theory.


[User] Please transcribe this text

[Assistant] So think of money like that, basically. Uhm, I think that's probably the right way to think of it. And then say what, what system, uh,


[User] Please transcribe this text

[Assistant] Like I said, just think of money as information. People, uhm, often will think of money as having power in and of itself.


[User] Please transcribe this text

[Assistant] It does not, money is information and it does not have power in and of itself, like applying the physics tools of thinking about things in the limit.


[User] Please transcribe this text

[Assistant] That's helpful. If you are stranded on a tropical island, uhm, and, uh, you have a trillion dollars, it's useless.


[User] Please transcribe this text

[Assistant] Cause there's no, there's no resource allocation. Money is a database resource allocation, but there's no resource to allocate except yourself. So money is useless.


[User] Please transcribe this text

[Assistant] If you're stranded around desert island with no food, you, uh, all the Bitcoin in the world will.


[User] Please transcribe this text

[Assistant] Not stop you from starving. Yeah. So, um, so like just, just think of money as, as a.


[User] Please transcribe this text

[Assistant] And uhm, and then what, what, what system, uh, is, what, what, in what form should that, that database or data system


[User] Please transcribe this text

[Assistant] What would be most effective now that there's a, there is a fundamental issue with, um, say Bitcoin in its current form.


[User] Please transcribe this text

[Assistant] Uh, in that it's, the transaction volume is very limited.


[User] Please transcribe this text

[Assistant] And, uh, the latency, the latency for a properly confirmed transaction is too long, much longer than you'd like. So it's not, it's actually not great from, uhm, transaction-wise standpoint or latency standpoint.


[User] Please transcribe this text

[Assistant] Yeah, like you're operating an economy. Um, and you need to have some thing that.


[User] Please transcribe this text

[Assistant] Uh, allows for the efficient to have efficient value ratios between products and services. So you've got this massive number of products and services and you need to.


[User] Please transcribe this text

[Assistant] You can't just barter, barter. It's just like, that would be extremely unwieldy. Uh, so you need something that gives you the, the, uh, uh, uh, uh,


[User] Please transcribe this text

[Assistant] Probably the reason why I think there's some, um, merits of Dogecoin, even though it was obviously created as a joke, um, is that it actually does have a much higher


[User] Please transcribe this text

[Assistant] Uh, transaction volume capability than Bitcoin.


[User] Please transcribe this text

[Assistant] And the, you know, the costs of doing a transaction, the Dogecoin fee is very low. Like right now, if you want to do a Bitcoin transaction, the price of doing that transaction is very high. So you could not use it effectively for most things. And nor could it even scale to a high volume.


[User] Please transcribe this text

[Assistant] And when Bitcoin was, you know, started, I guess around 2008 or something like that.


[User] Please transcribe this text

[Assistant] And I think there's some value to having a linear increase in the amount of currency that is generated.


[User] Please transcribe this text

[Assistant] So because some of the currency like if a currency is too deflationary or like, or should say if if a currency is expected to increase in value over time, there's reluctance to spend it.


[User] Please transcribe this text

[Assistant] Cause you're like, oh, if I, I'll just hold it and not spend it because it's sketchy is increasing with time. So if I spend it now, then I will regret spending it. So we'll just, you know, hodl it. Um, but if there's some dilution of the currency occurring over time, that's, that's more of an incentive to use it as a currency.


[User] Please transcribe this text

[Assistant] Well, you can look at the evolution of ideas.


[User] Please transcribe this text

[Assistant] Um, and then I like, I don't know exactly, obviously I don't know who created Bitcoin for practical purposes, but.


[User] Please transcribe this text

[Assistant] What is the name anyway? It's a name, a name attached to an idea. What does it even mean really? I think Shakespeare had a.


[User] Please transcribe this text

[Assistant] I think that's where we first like connected really was the autopilot stuff and autonomy.


[User] Please transcribe this text

[Assistant] So, um, Andre is awesome and obviously plays an important role, but we have a lot of really talented people driving things. So, um, and, uh, Ashok is actually the head of autopilot engineering. Uh, uh, uh, Andre is the director of AI.


[User] Please transcribe this text

[Assistant] Yeah, just, uh, you know, people will give me too much credit and they'll give Andre too much credit, so.


[User] Please transcribe this text

[Assistant] I thought the self-driving problem would be hard, but it was harder than I thought. It's not like I thought it would be easy. I thought it would be very hard, but it was actually way harder than, than even that. So.


[User] Please transcribe this text

[Assistant] What it comes down to at the end of the day is to solve self-driving, uh, you have to solve, uh,


[User] Please transcribe this text

[Assistant] You basically need to recreate.


[User] Please transcribe this text

[Assistant] What to what humans do to drive which is humans drive with optical sensors eyes and biological neural nets.


[User] Please transcribe this text

[Assistant] I think these sort of control logic conundrums are not the hard part.


[User] Please transcribe this text

[Assistant] Beautiful complex problem. So it's a lot of freaking software, man. A lot of smart lines of code.


[User] Please transcribe this text

[Assistant] For sure, in order to have, uhm, create an accurate vector space, uh, so, like, you're coming from image space, which is like this flow of


[User] Please transcribe this text

[Assistant] Photons, you're going to camera cameras and and then, uh, should you have this massive bit stream.


[User] Please transcribe this text

[Assistant] Effectively compress, uh, the, a massive bit stream, uh, corresponding to photons that knocked off an electron in a camera sensor, uh, and turn that


[User] Please transcribe this text

[Assistant] By vector space, I mean like, uh,


[User] Please transcribe this text

[Assistant] Uh, traffic lights and that kind of thing. Uhm, once you, uh, have an accurate vector space, uhm, the control problem is similar to that of a video game, like a Grand Theft Auto or Cyberpunk, uhm, if you have accurate, accurate vector space. It's the control problem is,


[User] Please transcribe this text

[Assistant] Insurmountable thing. It's, it's a, it's, but, but having accurate vector space is very difficult.


[User] Please transcribe this text

[Assistant] And, and giving you an image that is a very cleaned up image. Like when we look around here, we see, like you see color in the corners of your eyes, but actually your eyes have very few, uh,


[User] Please transcribe this text

[Assistant] Cones like a cone receptors in the peripheral vision. Your eyes are painting color.


[User] Please transcribe this text

[Assistant] In the peripheral vision, you don't realize it, but their eyes are actually painting color and


[User] Please transcribe this text

[Assistant] Your eyes also have like this blood vessels and all sorts of gnarly things and there's a blind spot, but do you see your blind spot?


[User] Please transcribe this text

[Assistant] No, your, your, your, your brain is painting in the missing the blind spot. You're going to do these like.


[User] Please transcribe this text

[Assistant] See these things online where you look, look here and look at this point and then look at this point and it's.


[User] Please transcribe this text

[Assistant] The rain is doing crazy amount of post-processing on the vision signals from your eyes. Uhm, it's insane.


[User] Please transcribe this text

[Assistant] So uhm, and then, and then even once you get all those vision signals, uh,


[User] Please transcribe this text

[Assistant] Your brain is constantly trying to forget as much as possible. So human memory is perhaps the weakest thing about the brain is memory.


[User] Please transcribe this text

[Assistant] So because memory is so expensive to our brain and so limited, your brain is trying to forget as much as possible and distill


[User] Please transcribe this text

[Assistant] You can sort of look inside your brain or at least I can like when you drive down the road and try to.


[User] Please transcribe this text

[Assistant] Think about what your brain is actually doing, consciously.


[User] Please transcribe this text

[Assistant] And it's, it's, it's, it's, it's, it's like, you'll see a car that's, because you're, you're, you're, you don't have cameras, you don't have eyes in the back of your head or the side. You know, so you say like, you're, you're, you're basically, your, your head is like a, you know, you basically have like two cameras on a slow gimbal.


[User] Please transcribe this text

[Assistant] Uhm, and, and what's your, and eyesight's not that great. Okay, human eyes are, you know, like, uhm, and people are constantly distracted and thinking about things and texting and doing all sorts of things they shouldn't do in a car, changing the radio station. So.


[User] Please transcribe this text

[Assistant] Having arguments, you know, it's like, um, so, so then like say like.


[User] Please transcribe this text

[Assistant] Uh, like when's the last time you looked right and left and, you know, or, and, and rearward, uhm, or even diagonally, you know, forward to actually refresh your vector space.


[User] Please transcribe this text

[Assistant] So you're glancing around and what your mind is doing is trying to distill the relevant vectors, basically objects with a position and motion, uh, and


[User] Please transcribe this text

[Assistant] Indirectly. You need to like establish vector space and then actually have predictions for.


[User] Please transcribe this text

[Assistant] Uh, those vector spaces. So like, uhm, you know, like if, uh,


[User] Please transcribe this text

[Assistant] There's people, before you drove past the bus, you saw people crossing, just imagine there's like a large truck or something blocking sight. Uhm, but before you came up to the truck, you saw that there were some kids about to cross the road in front of the truck. Now you can no longer see the kids.


[User] Please transcribe this text

[Assistant] But you, you need to be able, but you would now know, okay, those kids are probably gonna pass by the truck and cross the road.


[User] Please transcribe this text

[Assistant] Even though you cannot see them. So you have to have, um, memory, uh,


[User] Please transcribe this text

[Assistant] Uh, or a toy or whatever, and you put it behind your back and you pop it out. If they don't, before they have object permanence, it's like a new thing every time. It's like, Whoa.


[User] Please transcribe this text

[Assistant] Uhm, memory across both time and space. Uhm, so, uh, no, you can't remember.


[User] Please transcribe this text

[Assistant] Um, and, and then you also have things that are stale if, if, if they're remembered for too long. And then you also need things that are remembered over time. So even if you like say have like.


[User] Please transcribe this text

[Assistant] If you see the full, the full, like, uh, array of neural nets that, that, that are operating in the car, it kind of boggles the mind. There's so, there's so many layers, it's crazy.


[User] Please transcribe this text

[Assistant] So yeaah, uhm, but, and we started off with simple neural nets that were basically image recognition on a single frame from a single camera and then


[User] Please transcribe this text

[Assistant] Trying to knit those together with, you know, with C. I should say we're really primarily running C here because C++ is too much overhead. And we have our own C compiler.


[User] Please transcribe this text

[Assistant] So to get maximum performance, we actually wrote our own C compiler and are continuing to optimize our C compiler for maximum efficiency. In fact, we've just recently done a new rev on our C compiler that will compile directly to our autopilot hardware.


[User] Please transcribe this text

[Assistant] There's a lot of hardcore, uh, software engineering at a very sort of...


[User] Please transcribe this text

[Assistant] Uh, cause we're trying to do a lot of compute, uh, that's constrained to the


[User] Please transcribe this text

[Assistant] Uhm, we really put a lot of effort into the efficiency of our compute. Uhm, and, uh, so there's actually a lot of work done by


[User] Please transcribe this text

[Assistant] You know, uh, doing matrix math dot dot products, uh, like a bazillion dot products. And it's like, what, what, what are neural nets? It's like computer wise, like 99% dot products. So, you know, um,


[User] Please transcribe this text

[Assistant] I think one of the things we're, uhm, moving towards now is no post-processing of the image through the, uhm, uh, the image signal processor, so uhm,


[User] Please transcribe this text

[Assistant] Like, what happens for cameras is that, almost all cameras is they...


[User] Please transcribe this text

[Assistant] Uhm, there's a lot of post processing done in order to make pictures look pretty.


[User] Please transcribe this text

[Assistant] Uh, and so we don't care about pictures looking pretty, uhm, we just want the data. So we're moving just raw photon counts. So the system will, like the image that


[User] Please transcribe this text

[Assistant] That the computer sees is actually much more than what you'd see if you represented it on a camera. It's got much more data. Uh, and even in very low light conditions, you can see that there's a small photon count difference between, you know, this spot here and that spot there, which means that, so it can see in the dark incredibly well.


[User] Please transcribe this text

[Assistant] Because it can detect these tiny differences in photon counts.


[User] Please transcribe this text

[Assistant] That's much better than you could possibly imagine. Uhm, so, and then we also save, uh, 13 milliseconds on a latency, uh, so,


[User] Please transcribe this text

[Assistant] From removing the post-processing and the image? Yes. It's like uhm.


[User] Please transcribe this text

[Assistant] But if you've got a stack up of things going from the camera to the, to the computer through then a series of other computers and finally to an actuator on the car. If you have a stack up of.


[User] Please transcribe this text

[Assistant] If you have just, if you have fixed latency, you can anticipate, um, and, and, uh, like say, okay, we know that, uh,


[User] Please transcribe this text

[Assistant] So then, uh, then you're going to say, okay, well, we're going to.


[User] Please transcribe this text

[Assistant] And so we know it's 140 milliseconds, so we're going to take that into account and, uh,


[User] Please transcribe this text

[Assistant] And compensate for that latency. However, if you've got then 113 milliseconds of latency plus a hundred milliseconds of jitter, that's which could be anywhere from zero to a hundred milliseconds on top. So then your latency could be from 150, 250 milliseconds. Now you've got a hundred milliseconds that you don't know what to do with. And that's basically random. So getting rid of jitter is extremely important.


[User] Please transcribe this text

[Assistant] The cars is going to fundamentally maneuver better with lower jitter. The cars will maneuver with superhuman ability and reaction time much faster than a human.


[User] Please transcribe this text

[Assistant] I mean, I think over time, the autopilot, full self driving will be capable of maneuvers that, um, you know, uh,


[User] Please transcribe this text

[Assistant] You know, are far more than what like James Bond could do in like the best movie type of thing. That's exactly what I was imagining in my mind. As you said, it's like an impossible maneuvers that a human couldn't do, you know, so.


[User] Please transcribe this text

[Assistant] Yeah, so, uh, I mean, you can see that anybody who's been following the


[User] Please transcribe this text

[Assistant] Also driving beta closely, uhm, we'll see that the, uhm, the rate of disengagement has been dropping rapidly.


[User] Please transcribe this text

[Assistant] You know, per million miles has been dropping, uh, dramatically at some point.


[User] Please transcribe this text

[Assistant] Then of course, then there's going to be a case of, okay, well we now have to prove this to regulators and prove it to, you know, and we want a standard that is not just equivalent to a human, but.


[User] Please transcribe this text

[Assistant] Uhm, we were hoping to get 11 out this year, but it's, uh.


[User] Please transcribe this text

[Assistant] A single stack for all, yeaah, one stack to rule them all.


[User] Please transcribe this text

[Assistant] But, but they're just some really fundamental, uh,


[User] Please transcribe this text

[Assistant] Like we have this working on like sort of alpha software and it's good, but it's, uh,


[User] Please transcribe this text

[Assistant] It's basically taking a whole bunch of C, C++ code and leading a massive amount of C++ code and replacing it with a neural net. And you know, Andre makes this point a lot, which is like neural nets are kind of eating software.


[User] Please transcribe this text

[Assistant] We want to just, we need another layer of neural nets on top of that to take the giant bag of points and distill that down to


[User] Please transcribe this text

[Assistant] Vector space in the neural net part of the software as opposed to the heuristics part of the software. This is a big improvement.


[User] Please transcribe this text

[Assistant] Neural nets all the way down is what you want. It's not even a neural net, but it's, it's, it's, uh, this will be just a game, this is a game changer to not have the bag of points, the giant bag of points that has to be assembled with, uh, many lines of C for C++, uh, and, and have the,


[User] Please transcribe this text

[Assistant] And have a neural net, just assemble those into a vector. So, so that the neural net is outputting, uhm,


[User] Please transcribe this text

[Assistant] We've done, I think, quite a good job of, but it's, it's a, it, we're kind of hitting a local maximum on the, how well the C can do this.


[User] Please transcribe this text

[Assistant] So this is, this is really, this is really a big deal. And just all of the networks in the car need to move to surround video. There's still some legacy networks that are not surround video.


[User] Please transcribe this text

[Assistant] It's just quite a big reset on the training because the system's trained on post-processed images. So we need to redo all the training, uh, to train against the, the raw photon counts instead of the post-processed image.


[User] Please transcribe this text

[Assistant] Yeah, well, we'll actually need to incorporate, uhm, sound as well, uhm, cause you know, you need to like, listen for ambulance sirens or firetrucks, you know, uh, or somebody like,


[User] Please transcribe this text

[Assistant] You know, yelling at you or something. I don't know. Just, there's a little bit of audio that needs to be incorporated as well.


[User] Please transcribe this text

[Assistant] Honestly, frankly, like the ideas are the easy thing.


[User] Please transcribe this text

[Assistant] Like the idea of going to the moon is the easy part, but going to the moon is the hard part. And there's a lot of like hardcore engineering that's got to get done at the hardware and software level, like optimizing the C compiler and just, you know, uh,


[User] Please transcribe this text

[Assistant] Cutting out latency everywhere. Like this is, if we don't do this, this system will not work properly. Uhm, so.


[User] Please transcribe this text

[Assistant] The sheer scale of it is boggles the mind, like the training, the amount of work done with, like we've written all this custom software for training and labeling, and to do auto labeling. Auto labeling is essential.


[User] Please transcribe this text

[Assistant] Cause especially when you've got like surround video, it's very difficult to like label surround video from scratch is extremely difficult.


[User] Please transcribe this text

[Assistant] Like take a human such a long time to even label one video clip, like several hours, uh, or the order label it.


[User] Please transcribe this text

[Assistant] Basically, we're just applying like heavy duty, uh,


[User] Please transcribe this text

[Assistant] And guess what all the things are that are going on in this round video. And then there's like correcting it. Yeah. Then the, then all the human has to do is like tweet, like say the chain, adjust what is incorrect. This, this is like increase, increases productivity by effect a hundred or more.


[User] Please transcribe this text

[Assistant] I mean, I think if you say like, uh, extrapolate to, you know, many years in the future, it's like, I think, uh, work will become optional.


[User] Please transcribe this text

[Assistant] Um, and then there's like dangerous work and basically if it's dangerous, boring, uh, it has like.


[User] Please transcribe this text

[Assistant] Um, and then we'll have to pair that obviously with some kind of universal basic income in the future. Uh, so I think, um.


[User] Please transcribe this text

[Assistant] Yeah, I haven't really thought about it that far into the future, but I guess that there may be something like that. Um, so.


[User] Please transcribe this text

[Assistant] Yeah, actually it's funny you asked this question because normally I do try to think pretty far into the future, but I haven't really thought that far into the future.


[User] Please transcribe this text

[Assistant] With the, with the Tesla bot or it's codenamed Optimus. I call it, I call it Optimus subprime. Because that's not, it's not like a giant, you know, transformer robot. Um, so, uh,


[User] Please transcribe this text

[Assistant] But it's meant to be a general purpose, health, health or bot.


[User] Please transcribe this text

[Assistant] I think, uhm, is the mo- has the most advanced real world AI.


[User] Please transcribe this text

[Assistant] Uh, for interacting with the real world, which you developed as a function of to, to make self driving work. Um, and so.


[User] Please transcribe this text

[Assistant] You know, uh, hardcore low level software to have it run efficiently and be, you know, power efficient because, because, you know, it's one thing to do neural nets. If you've got a gigantic server room with 10,000 computers, but now let's say you just, you have to now distill that down into one computer that's running at low power in a humanoid robot or a car.


[User] Please transcribe this text

[Assistant] So, so since we're kind of like solving the navigate the real world with neural nets problem for


[User] Please transcribe this text

[Assistant] Cars, which are kind of like robots with four wheels, then it's like kind of a natural extension of that is to put it in a robot with arms and legs, uh, and actuators.


[User] Please transcribe this text

[Assistant] Hard things are like, you basically need to make the, have the robot be intelligent enough to interact in a sensible way with the environment. Uhm, so you need real world AI and you need


[User] Please transcribe this text

[Assistant] I mean, to be, to be honest, I have not actually thought about it from the companionship standpoint, but I think it actually would end up being, it could be actually a very good companion. Um, and it could, you develop like a personality, uh,


[User] Please transcribe this text

[Assistant] Match, match the, the, the owner or the, you know, yes, the owner, uh, whatever you want to call it.


[User] Please transcribe this text

[Assistant] Because, you know, like there's a Japanese phrase, I like the, uh, wabi-sabi, you know, uh, the subtle imperfections are what makes something special and the subtle imperfections of the personality of the robot mapped to the subtle imperfections of the robot's human


[User] Please transcribe this text

[Assistant] Friend, I don't know, owner sounds like maybe the wrong word, but, um, can actually make an incredible buddy basically.


[User] Please transcribe this text

[Assistant] Yeah, in fact, if you think of like C3PO and R2D2,


[User] Please transcribe this text

[Assistant] Like they actually had a lot of like flaws and imperfections and silly things and they would argue with each other.


[User] Please transcribe this text

[Assistant] Were they actually good at doing anything? I'm not exactly sure. They definitely added a lot to the story.


[User] Please transcribe this text

[Assistant] But, but, but there's, there's sort of quirky elements and, you know, that they would like make mistakes and do things, like, it was like, uh, it made them relatable, I don't know, um, endearing.


[User] Please transcribe this text

[Assistant] So, so yeah, I think that that could be something that probably would happen.


[User] Please transcribe this text

[Assistant] I'm confident we'll get it done. I'm not sure what the exact time frame is, but uh, like we'll probably have, I don't know, a decent prototype towards the end of next year or something like that.


[User] Please transcribe this text

[Assistant] So yeah, it's, it's, it's using a lot of, you know, it would use the autopilot inference computer and, um, a lot of the training that we've done for the four cars in terms of recognizing real world things could be applied directly to the, to the robot. Um.


[User] Please transcribe this text

[Assistant] Uh, yeah, it's literally, uh, it was basically, um, uh,


[User] Please transcribe this text

[Assistant] It should be titled engineer wars, uh, essentially like, like when there's a rapid change in the rate of technology, then, uh,


[User] Please transcribe this text

[Assistant] How far back in history did you go? Did you go World War II?


[User] Please transcribe this text

[Assistant] It was mostly, well, it was supposed to be a deep dive on fighters and bomber, uh, technology in World War II, uh, but that ended up being more wide ranging than that.


[User] Please transcribe this text

[Assistant] Uh, one country would make this plane, that would make a plane to beat that, and that's what I'm trying to make a plane to beat that. And really what matters is like the pace of innovation, uhm, and also access to high quality, uh, fuel and, uh, raw materials.


[User] Please transcribe this text

[Assistant] So, like Germany had like some amazing designs, but they couldn't make them, uh, because they couldn't get the raw materials, uh, and, uh, they, they had a real problem with the oil and, and, and, uh, fuel basically. The fuel quality was extremely variable.


[User] Please transcribe this text

[Assistant] Uh, yeah, like the US had kick-ass fuel, uh, that was like very consistent. Like the problem is if you make a very high-performance aircraft engine,


[User] Please transcribe this text

[Assistant] Uhm, in order to make high performance, you have to, uhm, the, the, the, the,


[User] Please transcribe this text

[Assistant] The fuel, the aviation gas, uh, has to be a consistent mixture and, uh, uh, it has to have a high octane.


[User] Please transcribe this text

[Assistant] Like high octane is the most important thing, but also can't have like impurities and stuff, uh, cause you'll foul up the engine.


[User] Please transcribe this text

[Assistant] And German just never had good access to oil. Like they tried to get it by invading the Caucasus. Uhm, but that didn't work too well. That never works well.


[User] Please transcribe this text

[Assistant] So Germany was always struggling with basically shitty oil, uhm, and then they couldn't count on high quality fuel for their aircraft, so then they had to have all these additives and stuff.


[User] Please transcribe this text

[Assistant] Uh, whereas the U.S. had awesome fuel, uhm, and that provided that to Britain as well. Uhm, so that allowed the British and the Americans to design aircraft engines that were, uh, super high performance, better than anything else in the world.


[User] Please transcribe this text

[Assistant] Germany could design the engines, they just didn't have the fuel. And then also the, like, the quality of the aluminum alloys that they were getting was also not that great, and so.


[User] Please transcribe this text

[Assistant] Yeah, I find history fascinating.


[User] Please transcribe this text

[Assistant] Um, there's just a lot of incredible things that have been done good and bad, um, that they.


[User] Please transcribe this text

[Assistant] Help, help you understand the nature of civilization, uhm, and individuals and.


[User] Please transcribe this text

[Assistant] I mean, some of these things do, I mean, if, if you, like, there's a lot of human history. Um, but most of it is, uh, actually people just getting on with their lives, uh, you know, and, and it's not like human history is just.


[User] Please transcribe this text

[Assistant] And, um, you know, I would have to say like, there aren't very many books that I, where I just had to stop reading because it was just too, too dark. But, uh, the book about Stalin, the court of the red czar.


[User] Please transcribe this text

[Assistant] I mean life was really tough.


[User] Please transcribe this text

[Assistant] Most of the history, uh, I mean, probably for most of human history, um,


[User] Please transcribe this text

[Assistant] A good year would be one where not that many people in your village died of the plague, starvation, freezing to death or being killed by a neighboring village.


[User] Please transcribe this text

[Assistant] It's like, well, it wasn't that bad. You know, it was only like, you know, we lost 5% this year. That was, uh, it was a good year. You know, that would be par for the course. Like just, just not starving to death would have been like the primary goal of most people in through throughout history is making sure we'll have enough foods last through the winter and not get in our freeze or whatever. So, um,


[User] Please transcribe this text

[Assistant] Now food is plentiful, I have an obesity problem, uhm, yeaah, so.


[User] Please transcribe this text

[Assistant] Sounds cool and that looks cool. Uh, well, it's, it's, you know, it's, it's, uh,


[User] Please transcribe this text

[Assistant] It takes a moment to read Cyrillic. Once you know what the Cyrillic characters stand for, actually then reading Russian becomes a lot easier because there are a lot of words that are actually the same. Like bank is bank.


[User] Please transcribe this text

[Assistant] If you can, if you can sound it out, there's at least some commonality of words. What about the culture?


[User] Please transcribe this text

[Assistant] Yeah. I mean the Soviet Union, Russia and, uh,


[User] Please transcribe this text

[Assistant] Uhm, one can, cannot help but admire the impressive rocket technology that was developed.


[User] Please transcribe this text

[Assistant] The Olympics would be boring if everyone just crossed the finishing line at the same time.


[User] Please transcribe this text

[Assistant] Nobody would watch. And people wouldn't try hard to run fast and stuff. So I think friendly competition is a good thing.


[User] Please transcribe this text

[Assistant] Yeah, Tim Dodd is really, really great. If you're interested in anything to do with space, uhm, he's, in terms of explaining rocket technology to your average person, he's awesome. The best, I'd say.


[User] Please transcribe this text

[Assistant] And uhm, I should say like the, probably the reason I switched us from, like Raptor at one point was going to be a hydrogen engine.


[User] Please transcribe this text

[Assistant] But hydrogen has a lot of challenges, it's very low density, it's a deep cryogen, so it's only liquid at a very, you know, very close to absolute zero. It requires a lot of insulation, it's uhm, so there's a lot of challenges there.


[User] Please transcribe this text

[Assistant] Uhm, in much lower cost, like in optimizing cost per ton to orbit, cost per ton to Mars, uhm, it's, uh, I think, uhm, methane oxygen is the way to go.


[User] Please transcribe this text

[Assistant] Uh, yeaah, give us an 8 out of 10. What do you think about nuclear power? Uh, I'm in favor of nuclear power. I think it's, uh,


[User] Please transcribe this text

[Assistant] In a place that is not subject to extreme natural disasters, I think nuclear power is a great way to generate electricity.


[User] Please transcribe this text

[Assistant] I think people, there's like a lot of fear of radiation and stuff.


[User] Please transcribe this text

[Assistant] And it's, I guess the problem is like a lot of people just don't.


[User] Please transcribe this text

[Assistant] I didn't study engineering or physics, so they don't, it's just the word radiation just sounds scary, you know, so they don't, they can't calibrate what radiation means. Uhm, but radiation is much less dangerous than, than you'd think. Uhm, so uhm,


[User] Please transcribe this text

[Assistant] Like for example, Fukushima, you know, uhm, when the Fukushima problem happened, uh, due to the tsunami, the,


[User] Please transcribe this text

[Assistant] I got people in California asking me if they should worry about radiation from Fukushima.


[User] Please transcribe this text

[Assistant] Like the dangerous is so much overplayed compared to what, what it really is that I actually flew to Fukushima and I donated, uh,


[User] Please transcribe this text

[Assistant] A solar power system for a water treatment plant and, uh,


[User] Please transcribe this text

[Assistant] And I made a point of eating locally grown vegetables, uhm, on TV in Fukushima.