Deep Future

This is a conversation with Bob Mumgaard and Steve Renter, founders of Commonwealth Fusion Systems in Cambridge, Massachusetts. So these guys spun out of MIT. An incredible, ambitious, company to figure out how to commercialize fusion, and it’s really the first fusion company in the world that has been able to show publicly that they have no new science needed in order to make it work, which is a major milestone. They also published a series of seven papers a couple of years ago now, showing exactly how they can build a fusion reactor. This is the kind of thing that has been a joke my whole life with physicists saying that fusion is only 20 years away and always will be. That might not be true anymore… Commonwealth Fusion Systems had a major breakthrough when they figured out how to make a super magnet, using a new kind of super conductor that’s appropriate for the task, and that really changed the game. Almost everything else they do, the science is the same as it was in 1970. They make a plasma that floats inside of what is called a “tokamak”, which is a kind of donut shaped toroid that has plasma floating on a magnetic field inside. So all this is like crazy, hard, technical science. None of it would have been possible without decades of government funded research. Multiple governments funding research. These guys were standing on the shoulders of a lot of giants who came before them. And they are very careful to acknowledge that all the time, which is great. And they’ve been very successful at showing that they can really make fusion happen. Now there’s a lot of engineering work that has to happen between here and there, but know they’re going at it with an extraordinary amount of ambition and they’ve hired a lot of really smart people. They have probably the best shot at achieving fusion of anything that I have seen. This would be the biggest upgrade for humans in our lifetime if we get there. And so it’s a very exciting project. I’m thrilled that I’ve gotten to know these guys a little bit and got to hang out with them their operation that keeps growing. I hope that you learned something from this conversation with Bob and Steve. Important Links: Commonwealth Fusion Systems Linkedin page Commonwealth Fusion Systems About Bob Mumgaard and Steve Renter Bob is the co-founder and CEO of Commonwealth Fusion Systems (CFS), a fusion energy startup company spin-out of MIT. He drives the company’s vision to accelerate the path to commercial fusion energy by managing its strategic partnerships and technical approach. He also believes in the power of technical and organizational innovation to facilitate the breakthroughs needed to combat climate change. The CFS team and Bob are working in collaboration with MIT’s Plasma Science and Fusion Center (PSFC) to realize the holy grail of renewable energy: fusion. Steve Renter is the Chief Growth Officer at Commonwealth Fusion Systems, designing and building commercial fusion systems to provide limitless, clean energy to the world. Commonwealth Fusion Systems (CFS) has the fastest, lowest cost path to commercial fusion energy. The ultimate mission is to deploy fusion power plants to meet global decarbonization goals as fast as possible. CFS has assembled a team of leaders in tough tech, fusion science, and manufacturing with a track record of rapid execution. Supported by the world’s leading investors, CFS is uniquely positioned to deliver limitless, clean, fusion power to combat climate change. Recorded on December 14, 2021The post Primer on Fusion Reactors — Bob Mumgaard & Steve Renter appeared first on .

Pablos: So what happens right now in scientific research is, if you’re going to do a research study on something, like “are M&Ms is bad for you?” It’s impossible to do that study. You have to be very specific and ask a much more fine grained questions like ” how many M&Ms does it take to, Kill a mouse?” or to cause a mouse to vomit. You just have to be very specific cause that’s something testable. You could test that, you can get multiple mice, you can feed them enough M&M’s that they eventually vomit. The whole research study can be done that way. And so when you read scientific research studies, that’s typically what you’re looking at is some very narrowly defined thing that they believe is correlated to a much more significant or bigger effect, but you can’t test the whole thing. You can’t ask questions like, “does this thing cause cancer?” You can ask questions like, ” does this amount of exposure to this thing over this much time cause this specific, type of cancer in this type of rat?” Things like that. So that’s great and all because it means, we’re structuring, tests that we can actually perform, but the downside is that for most people, what they would actually like to know is ” do M&Ms cause cancer or how many of them is too much, things like that. Getting those answers is often not straightforward from scientific literature. And so the way that we. usually try to compensate for that is to do what’s called a meta analysis. And a meta analysis is where somebody will go and dig up all of the studies on a given topic, combine them and try to say, “across a hundred studies involving M&Ms and cancer, this is kind of what happened” and, to just sort of give you a general sense of whether or not, the effect you’re interested in is happening. Good examples of this are like, chiropraction is largely, debunked. A lot of people get pissed off at me talking about it because it can be a deluxe placebo, but in clinical trials, very few clinical trials are performed. It’s hard to do them. Different practitioners have, different effectivity levels anyway. And so the problem is it’s hard to run those studies, but even if you do, you can’t find any indication that chiropraction actually cures anything. So this is a case where we don’t have good research and the only way to try and get to the bottom of it is with a meta analysis where you find the studies that have been done and you sort of combine their results and try to say whether or not chiropraction works. People, there’s no point arguing with me if you’re listening and you think chiropractic is great. Go nuts. I encourage you not to do that, but, whatever, do your own thing. But the point is the only way you could get a reasonable answer is with this kind of meta analysis. Now meta analysis is very time consuming and difficult to perform and often isn’t getting done, but what it really involves is just go read a bunch of studies. Well, it turns out that’s what an LLM is really fucking good at. So you, so right now we’re in a stunted position because one of the big problems with OpenAI and ChatGPT is they’ve crippled ChatGPT. It doesn’t read scientific literature and even if it does, it’s not really allowed to comment on it. So they’ve crippled the thing to keep you from talking to it about anything that might be health related and stuff like that. What you would really want an LLM to do, and one of the things that would be really good at is doing ad hoc meta analysis. So you could just say, “Hey, I feel like I’m getting a cold, should I take zinc?” There’s people marketing zinc for that purpose. We’ve all been told to take zinc, but I don’t fucking know if that’s an old wives tale, Ash: It’s like echinacea, zinc, doesn’t matter, it’s all those things. Pablos: I don’t have time to go read every scientific research study, but I bet you collectively we have that answer, and so if I could just ask an LLM. Ash: Wasn’t wasn’t IBM’s Watson at some point pretty good? Watson Health actually had all this. Pablos: That’s probably what they were trying to do. Ash: They were doing it and they were doing pretty well. They weren’t they weren’t using a full LLM model. That’s that was the whole breakthrough. Pablos: They were kind of in the pre LLM days. It was LM. It was just LM. It wasn’t LLM. Ash: Just language models. And they were taking huge amounts of data. But what they had is they had their own normalized structures underneath. So that was the difference, right? They didn’t let the structure form itself. But what you’re saying is true. Pablos: You’re right, and we could probably build like a Watson for health in a weekend now using, Stable Diffusion or something. It would be way better. You would just basically load it up with all the research and let it go nuts and then let people ask questions like, ” Hey, should I be taking zinc?” Ash: The problem is reliability score. Pablos: Oh no, it’d be terrible, but it’s already horrific. Right now, we’re just going off superstition. I mean, literally that question of, should I take zinc? You’re gonna get as many answers as people you ask because somebody’s Chinese grandmother said You should be, taking echinacea instead. Ash: You should listen to my first class. The first part we were talking about is what is known as “triangulation of information truth.” What is provenance for data. Then you have to figure out, how do you weigh it? LLMs are fantastic, like you said, because they can take all your source inputs. So if you go back to, to signal analysis, or analytics for like intelligence again. We’ll just lean on that for a moment. Truth is great if you’re playing with mathematics. You get QED and you call it a day for the most part. But for other things, truth, zinc, for example, like your zinc example. There’s some balance between like how much did it really? Was it an emotional support protocol? Did it help you because you were convinced that, your grandmother was right or whatever’s happening to, to actual physical actions internally, right? We can be scientific about it, but it comes back to source and information. If you pick a really, really dangerous topic and we won’t go there, but let’s just pick Gaza for one second. How do you find what’s really happening? Well, you hear a lot and someone’s like, “well, I read it in the Wall Street Journal.” I read it here. I heard it there. I took Al Jazeera. I did Briebert. Whatever you picked. The question was, did you do it in all the languages? Did you listen to a local radio station? Did you find someone’s signal data from nearby? What was happening? Did the bomb go off or did this happen? If you look at information, just like you’re looking at these scientific papers, the question becomes the weighting factor. We as humans, I think one of the things we know how to maybe do, at least a good analyst should be able to do, is try to give weighting based on time and location and stuff. And I think the large language models have to start to put in context again. I think they have to add one more dimension. Pablos: For sure. And I think that you touched on the other thing, which is that right now, all this information is like floating around without, tracking provenance, and so, interestingly, like in scientific research, you at least have citations. which is a lightweight form of provenance. It’s a start, but ultimately, the way these things all need to be built, not only , the LLMs for doing meta analysis, but really every knowledge graph needs to be built off of assertions that are tracked. You keep track of provenance, okay the sky is blue, well, who said the sky is blue? Where did you get that from? And that way, whenever you’re ingesting some knowledge, it’s coming with a track record. That’s how we’re going to solve news online, eventually. Ash: Kind of like, the Google Scholar score or whatever. I go back to my partner, to Palle, right? So Palé actually has a patent. It’s probably expiring soon, so for those of you who want to do this, we should go do it. He owns webprovenance.com. And he owns the patent on how you check provenance. One of the things that came out of the BlackDuck software stuff was that at BlackDuck, we needed to know who created something. So do you remember the Sun Microsystems, IBM, lawsuit, Java? If you’re a compiler theorist, then you know that, just because West Side Story takes place in New York, You could probably say, well, doesn’t it sound exactly like, Romeo and Juliet? So maybe you change the variables, but it’s the same stuff. And the idea was that when we were looking at, open source, with open source, the interesting thing is you’re trying to figure out, where did this little rogue piece of code, this little GPL or LGPL infection come from? You need to find it. So it’s one thing to talk about the combinatorials, but the other was to find it. And then Palle was like, well, I can do something cooler., He said, if Brewster Kahle’s Way Back Machine, remember the original Alexa project? So If you could go in and take all that data, he’s like, I could pretty much tell you like who killed JFK. You can find the provenance of almost any information. He wrote this wild algorithm for it. I’d love to see some of that incorporated into the LLM stuff because that algorithm, and again, we would happily, anyone out there if you’re willing, this has been a project we’ve been looking at for the better part of 15 years. Pablos: Well Stability might pick it up. They love that kind of stuff, that would be a huge coup for them. Ash: Well, we should, we should have this conversation offline, but it’s a, it’s interesting. It’s an incredibly cool algorithm. He was a compiler theorist anyway, an algorithmist, at Thinking Machines. So, he always wondered where the info came from. And I sat there and said, hey, we should find a way. And I remember the stunt I wanted was like, to figure out if they were aliens. And he’s like, what do you mean? It’s like, well, who started that rumor? Like, where did it happen? Right? So, imagine you could take any rumor, and I can tell you how it started. Pablos: That’s so cool. Ash: Wouldn’t that be the coolest thing ever? Pablos: So important. Ash: Yeah, and we need that. Pablos: That is super important. I’ve seen somewhere, a map that somebody made of where are all the UFO sightings reported? And like 98 percent of them are in the United States. I think the rest of the world doesn’t even have UFO as like a notion. it’s not even a, thing for them. Ash: It’s cause we have no healthcare. Look, all I know is, years ago, we just didn’t have enough data. Years ago, we couldn’t. We were like, looking at the Wayback Machine, and we were like, I was like, well, who can we go to to get all the data? Can we get the entire web? Today, large language models have already stolen all the data. They already have it. So if you have enough of the data, we could definitely help you figure out the algorithm to go backwards and it’s complicated. Pablos: That’s super exciting. Ash: He actually patented it himself because he was trying to figure out if he didn’t need a patent attorney. So that was his project, can I make a patent? And his patents on provenance. So I think it’s a big coup if they could pull it off. Can you imagine you could just type in who started, where did this first start? Pablos: Dude, that’s crazy cool. Ash: It’s super cool. Pablos: I’m kind of always on a rant about this, but we need a variety of models. Like LLM is the beginning, not It’s a thing that you need, like the way we’re doing it now actually kind of sucks and requires a lot of brute force, but there’s so many things that it’s not good for. Ash: And it’s so susceptible to the thing that, what did I do in my life? Psych warfare is all about information corruption. Dude, you corrupt a large language model, that thing is convinced that the sky is red at that point. Pablos: Exactly, well, I’ve been thinking about that. Why don’t I just.. Ash: Corrupt it?. We’re bad hackers. Pablos: I can fire up, 100,000, blogs written by an LLM that all just talk about my, prowess with the ladies. Ash: Exactly. Pablos: And the next thing you know, all the future LLMs will be trained on a massive amount of data that indicates that, Pablos is the man. Why wouldn’t we do that? Ash: At the end of the day, the LLMs are basically superstition. There you go. I’ve just said it. Pablos: Right. They’re superstition. There you go. Ash: LLMs are superstition. They’re based on some concept of something that it derived because it took a whole lot of information from a lot of grandmothers. Pablos: And that’s the thing, Like what’s posted on the internet is all that they know. It’s driving me crazy. Ash: Worse, it’s only the people who have given them permission, so the quality sources are going to start cutting them off. So, all they’ve got, all you’ve got are the people who are generating rumors that they’ve seen UFOs. Pablos: Well, that’s all true for the LLMs made in America. Ash: Yeah, so the American LLMs know where the UFOs are. Pablos: Japan decided that copyright doesn’t apply to training LLMs. So the most powerful LLMs, for now, are gonna be in Japan. Sign me up. Ash: Even better, that means Japanese information… Pablos: That’s probably true, learn Japanese. Ash: Which, think of it, if I wanted to build, my 100,000 LLMs generating your prowess, I’m gonna do it all in Japanese. I’ll do kanji, hiragana, and katakana. I’ll give it to them in all three formats. You could crush it. I I would love to see any of these. I think that’s, that should be our ask for everyone. Pablos: Yeah. Ash: if someone, someone wants to run with it, go build it. Pablos: Yeah, people, build this shit. Ash: Tell us. We can help you commercialize. We will find you. Recorded on January 8, 2024The post LLMs are Superstition – ØF appeared first on .

Part of what I love about getting to create a podcast like this is sharing conversations I’ve had with some of these extraordinary people that you just never hear about otherwise or never get to meet. They’re working behind the scenes, inventing new technologies that become part of our lives. And they’re out of the spotlight. I’ve been lucky enough to get to know Richard Chuang, who’s with us today, because we both served as board members at the University of Silicon Valley, where he is still a trustee. Richard is a pioneer in computer graphics. He’s been there since the beginning, since the moment we turned pixels into images on a computer screen and turned those images into animations. What has later become, everything you see coming out of Hollywood now. He’s a real pioneer in computer graphics, having built some of the animation systems at PDI, 30 years ago, that ultimately became DreamWorks Animation, where the pioneering feature films animated on computers. Ants, Shrek, those kinds of things were first done. Look, Richard, it makes me want to cry. How humble he is, the wisdom he has in this conversation. He’s sharing so much with us and, going back to, the seventies when he first learned about computers. there’s some computer history in here. His encounters with Steve Jobs over the years, in both working in animation with computers, his experience with, some of the other pioneers in the, in the industry. Richard doesn’t take credit personally for anything, but the truth is he’s behind a lot of these things that change the world, and I’m so thrilled to be able to share him with all of you guys. Recorded on June 20, 2018The post Pioneering Computer Graphics & Animation – Richard Chuang appeared first on .

Pablos: Here’s one of the things I think is a critical area of invention that remains unsolved, but it’s definitely a part of the future. So if you’re using an iPhone anywhere in the world, cultures vary. I’ve been working with this guy in Venezuela on a project. I text him on WhatsApp and then he replies with a voice memo like every time and so his, culture and worldview is just like talking to the phone and probably because I know Venezuelans do a lot more talking or something. Whereas I never use voice memo. I’m texting, but a lot of that is like, I’m in public around other people and I don’t want to disturb them and, disturbing people is considered uncool where I come from, but in Venezuela, like everybody’s chattering all the time, probably because they’re all Latinos. Talking to your computer will become more and more common. And you can see that some people are more comfortable with it than others. I see it a lot more in people from other countries than I do in Americans. Right now, talking to Siri kind of sucks, and Alexa. These things are kind of stunted because, they’re very one shot oriented. If you take your iPhone and start using the voice interface for ChatGPT, wow, it gets pretty exciting. Because now you’re having this, two way, audible conversation that builds on itself over time. And if you haven’t done that, I think everybody should try it because that will give you a sense of where these things are going. Once you get that going and realize, oh, I can just do this while I’m driving or walking, and I don’t have to be staring at my phone. It starts to get compelling. And so it’s not hard to imagine being, a few years down the road where ChatGPT is just listening all the time and piping in when it has the answers for you . So that’s just laying the groundwork, hopefully all that makes sense. But where I think this goes is that we need to solve one really big problem that remains, which is sub vocal input. Ash: Okay. Pablos: And what that means is, right now, if I’m talking, I don’t want to talk to my phone, I don’t even want to dictate text messages or do voice memo, because there’s people around listening, I don’t want them here in my business. We’re in this situation where the eavesdropping potential, even if you’re not talking about something super secret, it could be private or whatever. I don’t want to play a message from you out loud and I want other people hearing things that I haven’t screened yet, who knows what you’re talking about. So, what sub vocal input would do is give you the ability to just essentially whisper and have your phone pick it up. People around you wouldn’t hear you, wouldn’t understand you but you would still use the same machinery that you have and we all have the ability to whisper, and and quietly. If you’re trying to whisper for someone else to hear you, maybe it gets kind of loud, but if you’re just trying to whisper to yourself, it can be super quiet. We know that this should be possible, and we know that because deaf people are able to train themselves to do lip reading pretty well. So a deaf person who’s, got nothing, bothering them audibly can sometimes, apply enough focus to the task of learning how to read lips that they can do a really good job of it. So there’s enough of a signal in what your phone could see. So you know with Face ID there’s a tiny little LiDAR sensor that’s doing depth, and it can see your face. It can see the, minute details about your face. That’s why it can tell, the difference between your face and a photo of you and your twin brother or sister, whatever. So it might be possible right now. With the hardware that’s in an iPhone, even though you probably don’t have access to the right APIs for this to work, but maybe in a equivalent Android phone or something, maybe this could be prototyped. Where you could just use that machinery, train a giant, model, just a machine learning model on, lip reading. Ash: Yeah. Pablos: And so you would be able to just look at your phone and whisper, and it would transcribe. Ash: There’s a couple of things on this. Three GSM world, before GSM, 2000 or so. So we’ll go back in time. One of the big conversations that we would have was, I was a proponent saying that we just don’t have enough bandwidth and People are like, “yeah, but we’re going to have 3G & 4G & 5G & 6G.” And I said, “no, no, you’re missing the point.” The bandwidth to your device is not the issue, it’s between the device and the human. It’s your conversation. It’s, this is where we’re stuck. We’re stuck because we type, we could try Dvorak, we could try QWERTY, we can pick the keyboard, we can have sideways keyboards, we can speak to it, but I still think all of these are terrible. Whispering, could be very interesting. There was a MIT headset, Alter Ego. So Alter Ego, if you look at this thing up, it’s a mind reading, reading device. Sub vocalization signals through EEG, brain activity. He can actually make it work. Pablos: Well, I’ve played with some of these things. I have NeuroSky headset emotive, but I think what you have to do with them… Ash: This one you wear. It’s bone conducting. It’s wild. You just put it on and say, Pablos: Oh, it’s bone conducting. So it’s picking up speech, it’s not EEG. Ash: No, no, no. The bone conducting is how it tells you things back. So it even whispers it back. Like, into your head. Pablos: Oh, but you could just do that with headphones. Ash: No, that’s how it whispers back. You think it and then it tells you things. Anyway, it’s called alter ego, we’ll link to Alter Ego. To me, it goes back to what you’re saying, which is, is there a way? Otherwise, we just look like, we’re murmuring to ourselves, right? We’ll just look completely crazy. Like sometimes I get a little bit annoyed with people on conversations with AirPods. You just have no idea what’s going on, right? There’s a little hairdryer sticking out of their head, and they’re like, just walking around, and we just are fully, we’re already like, isolating ourselves and now we’re, we’re conversing. I think what you’re saying though is that the sub vocalization stuff needs to be in a way where it’s, Almost so discreet that it is a relationship between you and a listening device, right? It’s almost like the pixie on your shoulder. Pablos: Yes. Ash: It’s like the little angel devils whatever the animated version was. Pablos: Yeah, and I think there could be other technologies. I don’t know if you could fit it in something like an AirPod. Maybe like a Compton backscatter detector, one of these terahertz imagers, like the thing at the airport that you do the HOVA signal to, and then it’s you. Without a lot of radiation, you know, those things are low impact. You could do something like that to see the tongue through the side of the mouth. Ash: My belief is closer to the way that you were trying to tackle this problem, which is, hey, it listens in and jumps in. But what if I could prompt it to jump in, right? So for example, let’s assume that instead of having to build anything new, it’s now just listening to me. Constant in real time. Imagine a natural language parsing system with a, engine underneath. We used to call these things While Aware. This was actually the name of our company from years ago. And While Aware was intercepting SMS messages in real time on the SMSC. And the idea was that, it would detect what the conversation was, but because it knows who you are, it would evoke different things at different moments, right? So let’s pick, for example, Bitcoin share price, Bitcoin’s falling as a price. And that message was coming to you or that data was somehow coming to you. It might say, do you want to open up, your trading account and you can go sell it. And for me, it might, immediately tell me, do you want to book, tickets to Belize in a non extradition country, because my capital call is too high,. Whatever it is, if I have a margin call, because it knows what’s happening. It’s contextual, understanding. And I think one of the big things that we’re missing in all of these little support things that you allude to that ChatGPT brings to the table is contextual. We fail because It doesn’t understand us. Siri doesn’t know. Pablos: This is a separate conversation. Fundamentally, you are right. The whole future of AI requires that it know you, it needs to know you, it needs to know every conversation you’ve had, not only every SMS but text message and email, it needs to have 100 percent of that so it understands you. It knows what you know, it knows what you care about, it sees what you do, it sees what you say, it has to have all that and I want the AI to have all that. We need to architect for that and right now we’re not doing that because we’re building giant centralized AI’s. Ash: That’s when you’re, different technologies, whether it’s the backscatter or it’s the, lip reader or the whisper detector. All of those become a lot easier when you have context. I don’t know if you remember Google’s evolution, 2009, 2010, Google suddenly, not as creepy as Facebook, but its searches were just better, its searches were just better. Why were they better? Oh, you’re standing in New York city. So obviously maybe it’s contextual to what’s around you. Maybe the weather is cold. So Google’s original cookie, which they’re now getting rid of, was so laden with data. If you could mine that sucker, you won. It knew all of the signals. And I used to call it, signal gathering in terms of the more signal you had, the more accurate you became. And the more you look like sort of a savant. So our AI, like you said, isn’t really smart and Siri’s terrible because it doesn’t know much. It doesn’t even know intent. So as humans, why is it that we can speak with somebody with a very heavy accent sometimes? Because we know the context of what’s happening and why we got there. It’s not just lip reading. It’s because when we’re with them, we do our own interpretive dance. I think that if you tie the two together, what you just said about, you know, these other little signal things, you could pull it off. Pablos: I assume we’re gonna get the latter for free. That’s gonna happen. AIs will be stunted until they start to have access to everything and know everything about me and my context in real time. So that’s all gonna happen anyway, and there’s such momentum around that. So I think we get that for free and even if you didn’t, having a conversation with ChatGPT right now will probably convince you that it’s, like, good enough that we’re going this direction one way or another. Ash: The reason I bring all this up is, can you imagine if, instead of having to whisper, what if all I have to do is have my phone out, and I just say yes or no, or I say more? Go back to my Starship Trooper obsession of, “would you like to know more?” What’s interesting is, imagine in your scenario, you’re having this sub vocal conversation, but instead of you having to have any conversation, ChatGPT has heard you and it’s like, ” oh, alter ego, Pablos: No, no, I get it. One of my friends, figured out that you could get through life with only four words, fuck, man, dude, and totally. If you just have those four words, you can get through life because you can express a multitude of things with just those four words. Totally. Ash: Totally. Your response, totally. Funny enough though, right? That may solve some of your problems because you could whisper a little Pablos: Yeah, yeah. Ash: And not have to do long things. Pablos: Yeah. Right. Exactly. No, you’re totally right. And that’s what you do with your friends. And the closer you are to your friends, like if you’re just hanging out with somebody you’ve known for a long time, you can have a lot of communication with very little actual content. If I watch my daughter and her best friend hanging out, they’re incomprehensible because they have like, shortcodes for memes, everything they see or talk about or discuss is related to some other thing that I wasn’t part of and like they’re foreign objects to me. I think that is kind of what you’re describing. Like at some point, Ash: So go back to your Venezuelan, right? If you go back to that conversation and they’re sending you a voice note. Now, let’s say that voice notes processed and parsed and read by our GPT friend, and it comes back and gives you a summary, five sentence. So you don’t even have to look. It just whispers it in your head. Like he wants to know, should he edit the podcast? I don’t know, whatever it is. And you could just go back and be like, just hit the yes button, right? I mean, you could go back and say, totally. You could do one of your four words. Pablos: Yeah, totally. No, you got to try it. I tried it. You can go for days without using any other words. But yeah, I think that gets more possible. Like with a human, the more shared experience you have, the more shared context, shared vocabulary, the more concise you can be in your interactions. And so it stands to reason that an AI that knows you really well could get to the point where. All you gotta do is nod or wink and you’re done, on a lot of things cause it knows how to set you up to make a quick decision. Ash: If it can formulate the outbound response in long form, and all you have to say is totally… Pablos: Mm hmm, yep. Ash: Then you’re good, right? That’s usually the problem with these voices, with getting those voices. I’ve got those too, where people, it is the Latin America thing. They just love, like, I don’t know what’s going on. It was Brazil too, just, people just go off. And they have a recording. I’m like, you do understand, if I could listen to this, I wouldn’t be texting you. That’s like, I would pick up the phone and just phone you if I can, if I could have a dialogue, I would have one. When I saw that, I was like, well, can you just tell me like what’s in the voice recording? That’s what we’re looking for. The other thing to think of, and I thought this is where you were going before, you were talking about the sub vocal thing, It’s almost like the Babelfish thing, for all the fans of Hitchhiker’s Guide. I just had this crazy problem happen, which was, I’d ordered an Uber, and I’m sending information to the Uber driver in English, and the Uber driver is replying in Spanish, but I have a little translate button, but I don’t think they had a translate button. And at some point they just simply just said, no hable ingles. I tried to give the directions to my house, finally, I had to run into the street. I sent my daughter out into the street, like someone went out and we’re trying to tell them like, go to the yellow house. And I’m like, does anyone remember the word yellow? I realized that I was getting translate and they just didn’t speak English. I think that maybe there’s this universal input concept. If someone sends you a voice message, it not just transcribes it, but maybe it automatically just dumps it into like concise format. Or to the other person, it reads it to them. So you pick your poison of consumption, like the way you like to consume it, and you just build a proxy in the sky that just It just takes care of all this. There’s like a universal proxy, like a little babble bot that sits in the world. And I think you could get pretty far with that. And then you use that to feed ChatGPT. And then you use that to go with the totally man, dude, fuck, right? That’s your sequence to that. And then you add your sort of exotic input mechanisms for your sub vocal and everything else. So I could like, you know. Whisper. Pablos: So job one is all the people making AIs need to figure out how to make them mine so that I have my own that I can love and trust and have for life. Job two is they need to make that thing know everything about me, I’m not just a lowest common denominator, I’m me and I need, I need my AI to really know me. Job three is we’ve got to come up with some clever hardware for doing sub vocal input and it could be something that you wear like a headset that just see through the side of your face and see what’s going on in your mouth and your tongue and your embouchure Ash: Well, it could be like a body cam, just clip it on. Pablos: It could be something like that, something that looks up at you. I don’t know, it’s hard to mount something that sees the front of your face very well, a phone does, though. And even if you had to just aim the phone at your face for it to work. That would be a good start. And I think you could do that today without making any hardware. Ash: Yeah, well, you could put it into your Apple watch. Just hold it up. it’s like Dick Tracy. Pablos: There’s no camera yet, but next apple Watch will. Ash: Yeah, next Apple will have a little camera, so you just hold that up. It doesn’t even have to, you just have, you don’t even have to hold it up because if you’re using your little radar or LIDAR thing, you just have to have your hand out a little bit. Gesture control on steroids. Pablos: Did you see they put like a gesture control in the new Apple Watch, but it only knows one gesture, which is you pinch your fingers together and it can detect that. I haven’t tried it yet. Ash: The other thing I was going to say is I wanted to add what you said about your daughter’s thing is that if the AI becomes your buddy, then the total bandwidth between your AI and you will start to decrease. The requirement will decrease because you’ll just be able to speak in your own code. You’ll be able to be like, yeah, that thing that we worked on last week, dude. Pablos: Mm hmm. Ash: And then it’ll just know, Pablos: Exactly. Right. Ash: the other way that it’s going to help. So it all starts with that first step, though. It’s got to twin you a little bit. Little little scary on the privacy side. Pablos: That’s where, some of these, some of these folks working on OpenAI competitors have certainly, gotten onto that notion. Allegedly Apple is trying to figure out how to make the LLM’s local, so they run on your device and presumably that’s part of the rationale beyond just, justifying you having to buy a faster device and also, make it low latency. Recorded on January 8, 2024The post Whisp Subvocal Input – ØF appeared first on .

Pablos: There’s this idea that was just published that you could produce concrete and make it stronger by adding charred coffee grounds to the mix. And this is some research out of Australia. So concrete, if it’s not obvious, is like the most used material on the entire planet, aside from oil, which we burn. Cement, is in everything, and it’s this like staggering scale problem. Partly because of its contribution to greenhouse gases, right? So when you make cement, you’re burning some shit to make a bunch of heat to make the cement and you need that heat and there are ideas to decarbonize cement by electrifying cement plants. But then there’s this chemical process going on, which is the bulk of the carbon emissions. And there’s just no way to get rid of that. So that’s kind of the lay of the land. Interestingly, about half of all the cement in the entire world is made in China. That country is basically made of cement. This is one of the major targets for trying to do reductions of carbon emissions. And these guys figured out how to use coffee grounds. It’s not totally clear to me that they’re using, uh, used coffee grounds, I presume that’s the case, because there’s 10 billion Kilograms of used coffee waste every year that mostly ends up as biomass rotting in landfills. So this is worth solving. I thought this was kind of interesting. You can’t just take the coffee and throw it in the cement because the oils and stuff in it will seep out and actually make the cement fall apart. They invented this pyrolyzing process where you basically heat up the coffee grounds to a specific, pretty high target temperature, around 500 C, I guess. That’ll get rid of the oils presumably, and makes it into an additive you can just throw into the cement mix and it makes it 30 percent stronger. So I got two things that are kind of interesting, related to this. We Have a company our fund backed called DMAT, and these guys figured out how to make cement that’s lower carbon, but the way they do it, is they solved this 2000 year old mystery in material science, which is, how did the Romans make cement? Ash: I was going to bring that up. Pablos: Yeah. Cause they made the, the Pantheon to like two millennia ago and it’s still there. It’s unreinforced concrete in a seismic zone. And then they, somehow got busy, watching Netflix or something and got bored and forgot all about how to make cement. And then nobody’s been able to figure it out ever since. Ash: They were just looking at the colosseum. They were like, Hey, I’d rather look at the lion. Maximus Aurelius or whomever. And then that’s it. They’re like, forget it. Pablos: Look at the cool lion. Oh shit. The lion ate the guy who knows how to make the cement. Ash: Literally probably what happened. Pablos: That is literally probably what happened. So anyway, I got this team at MIT that figured it out. Ash: It was self healing, right? Pablos: We figured that out a little while ago. It’s self healing because what happens with cement is it fractures, water seeps into the cracks and then destroys the cement from the inside out. And that’s what’s happening to our bridges and everything else we made. And so to make it stronger and handle that, we load it up with steel rebar. So it’s steel reinforced, and then it still only lasts 50 years. The Roman cements, apparently lasting at least 2000 years. And what happens is it just gets stronger because when it cracks, water seeps into the cracks and it activates these lime deposits that are trapped in there. And so then the lime fills the crack and seals it up and heals the cement. Presumably the colosseum is just getting stronger over time. Now we know how to do that. So we can make cement that lasts virtually forever, use less of it, use less steel, and the kicker is, it’s about 20 percent less CO2, out of the box without even trying. That’s pretty dramatic considering the, the scale of the problem and the lack of other practical ways of decarbonizing. So these might be compatible, right? You might be able to also use this coffee additive. What I like about this is that cement is such a big thing. Most people just take it for granted. They don’t know how. Intensive this is from a carbon emissions standpoint and the scale of it. this. You know like we can actually make things way, way better. with some of these ideas. Ash: And the way they were doing it, the Romans had volcanic rocks, so they had this ability to automatically have the little bubbles in it. But I think what’s interesting is that, some people are like, oh, can we put plastic? Isn’t that where we just got in trouble with microplastics? Let’s solve one problem and then really screw up something else. The idea I was thinking is maybe this is where the coffee ground becomes like the aeration, right? Cause the whole structure was that as the bubbles popped, that was how the lime. Seeped back in, right? The water combined. Pablos: I think that was one of the theories that was debunked. I’m not positive, but I think that was the, like the prevailing idea, or it was kind of a half baked idea of like how this happened. And I think that is not what actually, it’s nothing to do with the volcanic rock after all. Ash: It wasn’t the volcanic, right? They had a couple , right? One was like some guy was trying to do bacteria. five, six years ago. That was the other crazy one, which was like, we will just have a living organism inside. The other question is, during production, can you trap, can you use it to just trap the stuff? Like, if you look at, was it clean, right? If you look at those guys, Pablos: So that’s what DMAT solved. And they do it with this process called hot mixing. Which apparently was considered dumb for, I don’t know, centuries or something. And so nobody tried it. Apparently using hot mixing they can get the lime deposits optimally trapped in the cement. I don’t know all the details. Ash: I like it. Pablos: Yeah, so we’ll get them on the podcast sometime and have them explain all the all the ins and outs. But yeah, pretty cool stuff. Ash: The challenge with almost all of these carbon reduction technologies is scale. Oh, hey, we’re going to take carbon out of the sky. And it’s like, okay, what did, what was the impact? Well, it’s like half a car. Pablos: Right because the sky is like the most entropic source of carbon there is. Literally, the number 400 parts per million. Well, let’s see. If you had a haystack, and you had, 400 needles and, a million pieces of straw, good luck finding a needle. It’s literally, the hardest possible place to get carbon. If you want to, sequester carbon, the thing to do would be to just, leave the fucking coal in the ground. Where it’s, the highest density of carbon you could find. So yeah, it’s, it’s kind of idiotic. Most of these things kind of solve themselves if you solve energy. If you had like a shit ton of free energy, then yeah, you could go do carbon capture from the atmosphere, but, otherwise it’s pretty painful. Ash: The problem is, yeah, like you said, unless you can turn it back into like a diamond or something, like you said, put it back into coal. These magma guys are, are cranking. Maybe we can use those guys. You’ve heard of the magma guys? Pablos: What’s the magma guys? Ash: These guys were doing the near magma experiment. They’re like, we’re just going to go 6, 000 feet, like just a little over a mile. What’s a mile? 5,280 feet? So you just go a little bit into the mantle. Just tap into that hyper geothermal. Pablos: I don’t know what you’re talking about. Ash: Oh, so there’s a project, just came out a couple of days ago that they revealed that they have a timeline on 2025. They’re going to do two. One is an open magma bubble, it’s in Iceland and then they’re going to do another one on top of it. They’re going to build like a little station and they’re going to go straight down. This is poking the bear, I would say. Pablos: So they’re basically trying to do a man made volcano. Ash: Yes, yes, that’s the, that’s the way to think of it. Pablos: Iceland doesn’t have enough volcanoes. Ash: There’s not enough problems where you could just suddenly drill a hole and burst the pimple of God, right? I don’t Pablos: People are worried about AI, and here we are trying to make a cousin for Eyjafjallajökull. Ash: I like it because someone’s like, “there’s infinite heat.” And I’m like, “yeah, but it’s kind of down there for a reason.” Didn’t work out too well for a lot of people, right? Pablos: I don’t understand, I guess if you succeeded at drilling that hole, then I think you would have basically the same thing as the makings of a volcano. Ash: Yeah, but they’re trying to contain it, right? They somehow feel like, like they could drill in a place… Pablos: You’re going to have to cycle it because if it cools, even if the magma comes up and cools, it’s just going to plug your hole. Ash: So the point is that they have to get a turbine to magma, magma rotating. It’s wild. It’s going to be interesting. just liked the idea that, that someone’s literally poking the bear. Pablos: Oh, they definitely should try. Ash: Cause you know, we talk about fusion being risky, but this one I just feel has a lot more problems. Pablos: Yeah, I think they’re just gonna, the magma is just gonna plug the hole. Ash: No, they’ve got, they’ve got, some ideas. Yeah, well, it is pressure. It’s under pressure. That’s why I keep calling it a pimple. Pablos: Yeah, that’s why volcanoes get made, right? Ash: That’s why they gotta go to Iceland. But, the interesting thing is, if you could technically, if you could maintain pressurization all the way up to the top, right, then it can stay magmatic and you could technically build some sort of, high velocity magma drive. That’s, what they’re thinking of. And that will just keep cycling. Cooling, but just spinning this turbine. Pablos: What do you do with the magma that comes up hot? Ash: It becomes like a, a river. Pablos: You run the turbine, but then where does it go? You gonna pump it back down? Ash: Yeah, it’s as if you were in a magma flow, right? So magma continues to move. It continues, it has a lot of movement, which people don’t realize. Look, the minute I heard drill 6,000 feet into a thin crust lava magma I sort of went, Hmm, this cannot end well. That’s, that’s the way I looked at it. But who knows? Pablos: But it’s just Iceland, so you know, there’s only like 130,000 people there. They’re tough though. If anybody can handle it… Ash: Don’t you remember? Didn’t, they stop all transatlantic flights? You remember right? There’s like a little Ash: cloud and, so just Iceland, but it’s, it’s literally on the jet stream. We Have a few airplanes crossing right over Iceland. No more going to Europe or vice versa. Pablos: Yeah, well, we overdid it anyway. Europe is basically just like a suburb of the U.S. now. Ash: And Brexit. So, you know, Pablos: There’s a lot of people who are trying to figure out how to decarbonize cement and it stalls out in part because there’s like four or five thousand cement plants around the world, and they all cost $100 million to build in the first place. A lot of the ideas for decarbonizing cement require building a new plant. And even if you could build one, you’re not going to build 4,000 of them. They’re Just non starters. And that’s part of why I like DMAT is that they can integrate in any cement plant with basically zero capex. You can just go in and upgrade, turn some knobs, and make a new formula. So, that’s super cool, and hopefully this coffee based additive would have that property as well. Ash: I think what’s interesting is just the coffee part of all this conversation. Pablos: If I go back to that article, it says that there’s, 10 billion kilograms, which is 22 billion pounds of coffee waste a year. I presume this is post consumer grounds. Ash: This is probably commercial coffee grounds that they can track using, like, Starbucks. It doesn’t include what we take home. Pablos: So it’s at least something like three pounds of coffee grounds per human, for every man, woman, and child on Earth. I don’t even drink coffee. So somebody else is doing double. The other one that we, got excited about and backed is this, startup called Marvel Labs. What’s exciting there is they figured out how to use the used coffee grounds as an input material for 3D printers. That sounds like kind of a cute thing, but the truth is it’s staggering implications. And it’s because 3D printers, they’re called rapid prototypers because we used them in labs and they were very expensive and impractical for a long time. And then in 2007, one of my buddies helped start MakerBot, and I was an advisor for MakerBot, which was the first consumer 3D printer. And so we thought we were gonna eventually build farms of these things like AWS, you’d just have a data center full of MakerBots and you’d wire them up to the “buy now” button, and whenever you clicked “buy now,” a MakerBot would print your stuff and then print a box around it and then print a FedEx label on it. It would show up in the mail. Obviously that didn’t happen, and here we are 15 years later, and you don’t buy anything on Amazon that’s 3D printed. There’s two big reasons. One is they’re one pixel printers, so they’re super slow, and that makes it expensive. And then the other part of it is that the input materials are expensive, so you’ve got these high quality filaments, plastic filaments and things that are expensive. At the end of the day, you’re competing with injection molding, which is like the cheapest way of making anything on Earth. And so, it hasn’t worked out. There’s a couple of exceptions. So for example, with metals, 3d printing of metals has worked out pretty well for two reasons. One, they’re higher value parts. So you’re printing, you know, jet parts and rockets and stuff. But also the technique in the printers is it’s a powder bed, so you have this bin of powder, you run over it with a binder, like glue, from an inkjet head or a laser or something to sinter it together, and then, you pick up your part and shake it off, and you’ve got this part that was printed in a bed of dust. It’s actually a very elegant way of making a 3D printer, and it’s faster, because they’re more like layer at a time instead of pixel at a time. Anyway, so what Marvel Labs did is they adapted that style of printer, which is fast, but the input material is these used coffee grounds and what the effect of that is, is now they can print stuff out of coffee. They’re making all kinds of stuff. Sinks and light fixtures and bicycles and things. And the parts come out of the machine. They’re made of coffee and then they just powder coat them with paint or metalize them so they look like metal and you can’t even tell that it’s made of coffee. And so this whole thing works awesome, but the main reason that it’s important , and the reason that we invested, is that it flips the economics. So now, these parts that Marvel Labs is making, they’ve reshored manufacturing, they manufacture stuff in the U. S., they do it fully automated. And the parts are cheaper than doing it in Asia. That’s what’s exciting to me. They’re also printing with seaweed. They’re printing with sawdust. All the technologies they invented to make it work are about, printing with biomass in general. They’re kind of the kingpin. Now we can get this whole vision together of producing things on demand in 3D printers in the U. S. Ash: It’s interesting because several things, right? One is, like you said, it’s not just, the on demand. All of our strategic risk starts to change, right? Think of what happens when, we get to a point where we’re having another pandemic or, I don’t know, they go after Taiwan. Supply chain changes if you’re suddenly local, right? As long as we can get enough coffee into the system, we have enough of our own source material. Pablos: Ha, Ha, ha, ha. As a matter of national security, Americans are being asked to drink more coffee. Ash: It’s a national security imperative that you get a frappuccino. Pablos: Well, I found out China just surpassed the U. S. as having the most Starbucks locations. Ash: China did. Frightening. I mean, Japan, Starbucks, whole different story. I was just looking at the botanical Starbucks in Japan,  Starbucks is its own, own different conversation. But I was going to say that when you think about all of this, the implications for logistics, and one thing I wasn’t sure on, on the way that they produced, what was their binding material? Because I know they’re, one of the things they were talking about was biodegradability. Pablos: Marvel Labs has invented a variety of different binders. One of them is entirely sugar based. They use it with seaweed and they can make these biodegradable parts. Which is really cool, and then they have some top secret binders they invented that are super cool and they’re not ready to announce them yet, but it’s awesome. Ash: I saw some of the pieces. Pablos: Yeah. Oh, that’s right. Ash: I got to actually play around with it. I, I think what’s amazing to me is that the idea that you can cut production time. I don’t know if it was an experiment or if they still do it, but remember there was Amazon Now. Where like they had little trucks going around and, and they had like USB cables or like whatever you needed, like that minute. Pablos: circulating your neighborhood With, that was loaded with the things that they predicted, were going to be bought. Ash: Yeah, 100%. That’s what it was, right? They predicted that, everyone in Palo Alto needs like an extra USB cable. And they had one and you could get it like one hour delivery. Pablos: But that truck could just have a 3D printer in the back. Ash: That’s exactly it. Right? Like imagine, how big are these things? How big are the printers? Pablos: The printers are, I’d say like 80 percent of the printer is the print bed by volume. So, if you have a printer the size of a refrigerator, 20 percent of it is gantry and other crap. And that’s pretty typical of 3D printers, I guess you could say. And at least in a powder bed style printer. And the rest of the volume is printable. So, these printers are actually quite large. And one of the nice things about a powder bed printer is that you could just print a whole bunch of parts at once. You just fill up the bed with parts because they’re just floating in powder because the powder is like the support material as well. It makes it easy to do big batches of stuff. If you’re printing coffee mugs, you can print it and you got a fridge size printer. You can print, a couple hundred mugs or whatever all at the same time. And then, they just come out of there. I’d say 3D printing’s future, over the next 10 years or so will be really focused on figuring out how to make multi material printers. There’s a little bit of work on that now, especially trying to be able to do conductive materials. It’d be great to be able to print something like a game controller or a pair of headphones or something, have some of the wires printed in it. Ash: Maybe you have the recycled aluminum just like get blasted and powderized. I know of a magma plant coming up that might be able to… Pablos: Can we make a magma, printer? Ash: You take the aluminum, you feed it into the magma god and it comes out powderized. Pablos: Well, most aluminum comes from Iceland anyway. Aluminum is essentially made of electricity and they have access to cheap, clean electricity, Ash: That’s the, the, secret, right? So we have infinite power and then they’re just producing the conductive dust. One of the things I was thinking is like, how do you market this, right? Because we have to get a behavioral change on consumption. It’s so easy to go with fast fAsh:ion, fast goods. We’re addicted, I don’t know if you’ve ever seen Wish? Pablos: Oh, uh, I know what it is, but I’ve seen Temu. I signed up for Temu. I ordered some shit before I found out it was obviously Chinese spyware app. And I um, I, bought some shit Temu cause it was so cheap. They’re like paying you to take this stuff. And then it was like worse than infomercial products. Like I got these things and they’re the cheapest possible things. And they had used like trick photography. I bought this bottle of, a cleaning product, I have it right here. I’m looking at it. It’s this bottle called Foam Cleaner. I’m like, oh cool, I’ll use that to clean the shower. I don’t know what, kind of bug eye lens they must’ve used to photograph this thing. But when it showed up, the bottle itself is literally a 60 milliliter bottle, which is, that’s like the size of, it’s like a large bottle of nail polish, Ash: It’s like, It’s like, not even a perfume bottle. Pablos: And then it’s got the full size spray head that you’d have on a bottle of Windex or something on it. So this whole thing, it looks like a joke. Nobody would ever do this. I’ve never seen a bottle this small with this big, like the spray head by volume is bigger than the bottle. Ash: So basically you’ve got a bobblehead cleaner. That’s what you’re saying. Bobblehead but foam cleaner. That’s it. That’s it. We can market it. Pablos: Yeah. I mean, I’m afraid to spray it because you know, like if I pull that trigger more than three times, the bottle will be empty. Ash: I’m sure it’s not a neurotoxin or anything. Pablos: Okay. But anyway, the point being. Yeah, it’s Temu and Wish and all this bullshit. I don’t know about consumer behavior change. You would know more than me. What are the odds that we’re ever gonna be in a world where people buy less shit? Ash: It’s not that we buy less. I’m trying to figure out if we can shift them, right? Think about it. At one point, we were all obsessed around Gore Tex, it was like the magic, right? We had just left our class on osmosis and we were like, wow, it’s like osmosis in a fabric, we were excited. Pablos: Maybe explain how Gore Tex works. Ash: Gore Tex’s whole idea was about breathability, where the pores on the fabric were supposed to for air to go out, but water not to come in. Pablos: Which works because… Ash: It’s surface tension allows the droplets to hold more together, so they’re bigger than the water vapor molecules going out, right? So, so the molecular sizes are different. So you can create this sort of barrier. Now there’s 50 versions of this to Sunday. But, Gore Tex was, was something which became a brand name, right? I don’t know if it was before Intel Inside, but it was kind of the same concept, right? Saw a little label on Gore Tex. Pablos: It’s like the Dolby of outerwear. Ash: It is. It was the Dolby of Outerwear. So I think somehow we’ve got to build that kind of reputational or brand concept, For example, if it’s the seaweed and sugar and everything nice, right? Pablos: Okay. I see. Full circle brand where it’s like “buy as much of this shit as you want. Whenever you’re done we’re just gonna turn it into the next shit you’re gonna buy.” Ash: it’s not just recyclable… Pablos: It’s like infinitely recyclable. Recycling is a is a joke. Ash: And the amount of energy and stuff that it takes is is sort of crazy, on that as well, right? So that’s that’s one of the, the sort of big, big problems that that happens with it. And I think one of the challenges is that we’ve got to figure out a way. That, something like what we’re talking about in terms of, this new product, this new mechanism, this new process can be Gore Tex’d. Or Dolby’d, and a little bit more than like this is recyclable. I think we’re kind of over it, right? Like we’ve seen the little symbol, we don’t even know what’s going on anymore. I know that in most countries they have like, at least like five bins. I think most Americans can’t figure out like. What’s up? There’s a blue box. Pablos: You could imagine a version of this where, ultimately everything is just made of, some atoms, right? They have to come from somewhere. And then the energy it costs to, move them around and stick them together. So. You know, if you sort of just take that approach, you could say, okay, this stuff is made of this much joules and, this many atoms, like you could basically measure everything that way.  Then you could say like, all right, well, the total cost of ownership in a given product could be added up that way. The cost of like mining all the shit, the cost of transporting around the world, the cost of, burning stuff to make it, whatever it takes. If you added that up for any object, it would probably be staggering. In the long run, you would, you, what you would like to do is track things that way and then be able to say, okay, this is kind of a full circle product, like an apple is probably like the closest you get maybe to a product that is low impact, it grows, we there, there’s some energy cost in transporting it from a farm to your mouth, and then you eat it, you throw out a quarter of it as biomass. Ash: When you say an Apple, not your iPhone. Pablos: Oh yeah, I’m talking about like an actual physical apple. The kind you can eat. Yeah. Not an phone. Granny Smith, not a Macintosh. Ash: But maybe that’s the score, right? Pablos: I think your Intel inside becomes… Ash: is it net negative? Is it net positive? Pablos: It’s net negative or it’s like close to the threshold of about an apple instead of being, at the threshold of like about a Tesla. Ash: That may be the interesting way to do it? So maybe a dynamic symbol is the way to think of it, right? So instead of the old Intel Inside or Dolby Atmos or whatever’s going on, or Gore Tex, maybe it’s about the level. Is there a number? Is there a score? Lasered in or 3D printed into the object itself or, or anything that you look at, it just tells you that this has a small number or a small something that people can understand that’s better or higher or whatever. Pablos: Energy star. Ash: I look at something like calories. Like years and years ago, we all started getting obsessed and that definitely the generation that grew up with cereal boxes, who had nothing better to read. And we didn’t have a iPhone to scroll. We read cereal boxes. We knew more about niacin and potassium in your cornflakes than any human should ever know. Pablos: It’s true. I read a lot of cereal boxes. Ash: That’s what you’d read. You read, you’d read the cereal box. When they changed the USDA standard for what you can see inside, the bigger format I remember that was like a big change on the packaging design. That was something where we could see the calories and then we realized, per standard serving size or whatever it was. And I think that at some point, the same thing has to happen, right? Each object that we consume or buy, can have that. There’s actually a company. That we’re looking at, called Love, like seriously called love.com. Uh, uh, I won’t go into much more about that, but they’re actually trying to change this, like specifically change this idea. They’re trying to build an Amazon. First of all, they have love.com. I sort of tossed out the idea that it’s powered by love. And that way, it can have a score, each thing you’re buying. They curate what’s allowed to be sold on there. So it’s like an Amazon, but like, we’re going to get rid of Pablos: So all you need is love. Love is all you need? Ash: It’s true. That’s their eventual goal is to go head to head with Amazon. A billionaire multi time, entrepreneur who’s kicking this off. What’s interesting, though, is I think people will start to recognize this. Pablos: Yeah, you could do some big branding campaign around, certified green or whatever, but it seems so like all these things are so gameable. I mean like calories, even like, I understand this as a kid, but now that I know what a calorie is like… Ash: It’s totally gameable. Pablos: Oh my god, that’s a totally fake thing that we made up that’s, like, barely a measure of anything. Ash: That’s why I picked it. I was going to say that with good numbers come good evil, right? Are you drinking a 12 ounce can of Coke? Was it like eight ounces? What did they do? It’s interesting how it became a complete nonsense number? It mattered. We learned later that maybe the mix matters, and it wasn’t about the sodium. And there’s a lot of little bits that didn’t matter. The question becomes, can you build something genuinely? There’s another company, we invested in, Dollar Donation Club. And what’s interesting about them is, when Seth, who’s the founder, said, “Hey, I’m going to see if we could create the world’s first super philanthropist.” The idea that if we all gave a dollar a month, technically it’s billions of dollars. You can make a lot of changes. He said,” where am I going to give the money? I don’t want to be another money place. I want to be something where I can see the impact.” So he built a giant impact map of things he wanted to do. And he said, “okay, I want to know exactly how many kilos of microplastic are removed for my donation.” Like, I don’t care that I donate $1, $2. I was like, I’m willing to go and take out a kilo. Well, it turned out he can only get to like, I forget what the number is like 11 or 20 charities. It took that long and that his professional teams, like when they vet out what the charity really does. Pablos: Yeah. Ash: Almost no one qualified. So I think this is the unfortunate thing that’s going to happen, right? So if our coffee friends bring it full circle, if Marvel can really like just crush it. Like they can demonstrate there’s an actual true cost reduction I’m talking about from Guangzhou to, Columbus. By the time it gets there, like what actually happened and then the return leg, right? Like what happens on the back if, if that’s actually a real score. That we can defend. Maybe that’s what Marvel has to do. Pablos: The way it should be done probably is kind of like, consumer reports. There ought to be, like, life cycle metrics made for, the product coming outta Marvel Labs versus its competitor that came from Guangzhou. Here’s your Samsung versus iPhone versus, Nokia or whatever and somebody does the research and figures out; this is the mining footprint; this is the shipping cost. This is how much, energy was burned. The factory is running off of a coal plant versus a nuclear reactor or whatever. Ash: Like Energy Star, but like it actually makes sense as opposed to Energy Star. Pablos: Yeah, and that could be given a score in joules that just ranks these things against each other. Ash: But we’re talking about three ideas here, right? So that one idea is to get somebody to come out there and say, look, fundamentally, product life cycle measurement is something someone should go build, like someone should, whether it’s independent of Marvel or not, somebody should do it. And then different manufacturers or, or whether it’s a 3D printer of type company or someone else should go in and say, look, let’s show you why we are the lowest score, the highest score, whatever the, whichever one’s considered the better thing. And then we have to create education and marketing on that, to say, Hey, if you’re not doing this, you, you are literally creating damage. Pablos: There must be initiatives like this that we don’t know about. An interesting thing to consider is an iPhone is made of whatever, 2000 components. Some of them are like screws that Apple sourced and didn’t manufacture. Where was the metal for the screws mined? Where’s the factory for the screws? How far are the screws traveling to get to the iPhone factory? All that kind of stuff. And so you would, eventually if this were fully played out, when you design an iPhone and CAD, it would just tell you, where your screws are coming from. We already have the environmental impact score for those screws. Pick the ones that have the lower score. Ash: So this is like an SAP thing. So go back to, Fast moving consumer goods. So in the FMCG world, one of the things that’s really interesting is something called, smart label and smart label is interesting because it said, Hey, like ingredients don’t cut it. I want to know like really what’s going on, it goes really deep, you can dive into the label, but where did you source it? Like, is it really honey from here or what was going on? I think Nestle, I think some of the biggest players all support it. Procter and Gamble, all these guys are on smart, smart label. Now that’s interesting because you’re almost already there, for those guys, you’re pretty close, but that’s for food. Hopefully that’s mostly biodegradable. Otherwise we have other problems in life. Pablos: Yeah, that’s interesting. Maybe that could be extended so that all the, the ingredients of my, headphones… Ash: Exactly. Could you extend that construct? I actually think back to another company, from years ago, it is one of my patents, from a while back. it was a company called, Black Duck Software. You were talking about, as you’re sitting there with your CAD, I was thinking of, open source. Remember it was like, “”are you using something that’s gonna infect the rest of your project?” When you’re coding in Eclipse or something and you’re like, oh, let me just grab this little… Pablos: You accidentally scoop up some GPL library… Ash: Yeah, it’s an LGPL or something. It happened to Fidelity. Their entire mortgage calculator, their entire mortgage algorithm had to be open sourced because they used a website plug in. So, they eventually invested in the company. Obviously, they invested in us. But what was good is that, when you, were able to sit down and look at the project, it would tell you immediately, like, if you put this in there, you will like, have to open source your print driver. Pablos: All that should just be in CAD. A lot of CAD software has a plug in to tell you how much it’s going to cost to machine that part that you made based on the design. And it could easily tell you how much material it’s going to take and how much material cost there’s going to be. But you could extend on that and say, you chose these screws. Here’s how much they’re going to cost. Here’s what the lead times are. All that’s in SAP already. And then it tells you, this is the environmental footprint of the screws you chose. Ash: And now you can tie that into some exchanges or B2B sourcing companies and just say, okay, give me a scenario. I want to automatically reduce my carbon or my, my total footprint. Where else could I source, right? So maybe instead of titanium screws, I have to manufacture for this new titanium iPhone from like some Russian mine where the titanium lives. Pablos: be seven Web3 companies trying to do this already. Ash: I think what they miss. And this is something that I think is an interesting part of the journey, right? That you and I also take is it sometimes great technology and great back end stuff doesn’t hit the front. The only reason calories don’t matter today because we woke up and realized that somebody paid off the cardiologists to get us to eat margarine and told us that sugar was, okay and fat was terrible. That was programming, right? That was maybe we need some good programming. I mean, we got programmed the wrong way. Maybe we need to program people. To see the right thing. And I don’t know that we could be seen as altruistic or that we’re necessarily not, not commercially motivated. I think that there’s some way that today because of information and speed of information, I think we can create some level of transparency, like you said. And then we can turn around and say, back in the day, I couldn’t tell you where my, millet was coming from for the food. Today we can, Smart Label will tell you literally where that food comes from. I think we could do something fun, fun with that. Someone should go do that. Pablos: Yeah. Someone should go do that, which is, one of the main points of doing this podcast is that hopefully we’ll come up with ideas that somebody else should go do. Recorded on January 8, 2024The post Coffee ＆ Cement – ØF appeared first on .

George Dyson, a science historian and author, shares insights from a life spent at the intersection of technology and history. He emphasizes the plight of historians in a digital age where records fade away, advocating for preserving tangible history. George reflects on his unique upbringing alongside his father, physicist Freeman Dyson, and discusses the democratization of technology. He also critiques current energy practices, contrasts SpaceX's efficiency with traditional operations, and explores innovative uses of wind power in shipping.

Here’s the dumbest thing in the world. You pull up to an intersection, the light is red, there’s no one else in sight and you have to sit there and wait for it to turn green. Traffic lights are the dumbest thing in the world. And this is insufferable because right now, if you, if you’re in a Tesla, the Tesla knows, Oh, no one’s coming from any other direction. It would totally be safe to go, but you can’t because the light is red. I think what somebody needs to do is rip the guts out of a Tesla, mount them in a traffic light and let the traffic light decide when it should be green or red. How hard is this? This is easy to do. it’s going to take years to upgrade traffic lights, but that’s at least one startup. Somebody should be able to do that. We have all the tech, it’s not that hard. We can use vision or radars or whatever. Ash: You’re not gonna believe me. So, funny enough, uh, Columbus, Ohio. Project, Pre- Razorfish, Traffic Lights. Pablos: Wait, that’s a real, that’s a real project? Ash: It’s a real thing! It’s a real Pablos: Wait, so somebody did this in Columbus? Ash: No, us! Pablos: Oh, you did this? Ash: is what we were doing! Pablos: Wait, Ash: You couldn’t have possibly known that! Pablos: No, I didn’t. No, seriously, you, you, you worked on a project like this. I didn’t know. Ash: I mean, yeah, so, yeah, so what was interesting is that project was, so I keep hired to figure out traffic light optimization and it’s, you know, it’s really, really fucking complicated. Like there’s a lot of math to, to make sure that, you know, you know, like that. To get people going in one direction and all that stuff and, that problem was being solved. And one of them was, do you start going flashy? Back then they didn’t have the little Tesla thing. Right. Pablos: What year was this? Ash: Do you start flashing? It’s gotta be like 1995, 1996. How do you, how do you optimize the sequence of lights so that, the traffic keeps flowing? What do you do with intercepts? And then Palle, this is even, this is even better. So Palle Peterson, like my partner, Palle’s dad was a crazy, mad genius inventor, he was in the Western part of, of Denmark. He wasn’t even in like regular Denmark. There’s like an Island that they kept him on. He had convinced them that when ambulances go, that they could start to change the lights faster, like emergency services. Of course he had the hack, but so you would just click the lights to green. Pablos: Cause he had one of those transmitters that the ambulances have? Ash: First he invented it. Pablos: Yeah, I had, the MERT. Oh, that thing. I bought one of those and put it in my car, where I was in Seattle at the time, it only worked on the emergency corridors, only on certain roads where they had, where the ambulances knew, and I didn’t know were set up for that. It’s like an infrared transmitter you put in your car and it sends infrared signal to like a TV remote to the, traffic light and they change. I could smoke it around town on certain streets. So you’re saying this guy invented the thing? Ash: Yeah, he invented, whatever the original one. I remember Palle telling me stories like, “dad had designed this thing” and then he convince them that they should all use it and then of course, like, ” I have back door.” So Columbus, the biggest problem they had was, they just had traffic lights, like each section was on its own. It didn’t live in like a, a grid or it didn’t have any understanding. So the ripple effects were just fucking out of control. For example, you could have a place where you’re sitting there with a red light and then there’s no one around you.. then you could have another place where, because it was doing its own thing, you could just be in stop and go, it would just create its own eddies of, of hell. Pablos: Yeah, it feels like that still exists. Ash: It does because what the problem is, is that no one is running enough, you know, computational fluid dynamics, I mean, that’s the problem. Pablos: You’d do a simulation now. Ash: You would, and that’s, and, and, and the horsepower gets better now, right? We have more flops to like mess around with this stuff. But the problem is that we, we still haven’t figured out how to do your thing, which is now what happens when you build the emergency corridor. What happens if you’re like, all right, so the Tesla says no one’s coming from any side, but. You go through. Are you like a leaky pipe? Go back to like traffic theory, and pipe theory. One of the things that you have is that when you got a pipe, everyone thinks that, let’s, let’s call it. , the 405, let’s call the pipe, 405. What’s the best way to set up the 405, in terms of traffic, is it better to have six lanes, or is it better to have two sets of three lanes and a shoulder or two shoulders and it turns out, that the eddies are the problem. So,, we get these lame attempts of traffic light, traffic flow regulator, right? We have to go into the. Highway. So I was just thinking that when you, when you started talking about traffic lights, I was thinking problem is in theory, it sounds amazing, but the problem is when you’re inside a mesh. Pablos: So you need active feedback loops into whatever the thing is that’s running the simulations, right? Because you need to say, “okay, this guy wants to change the light to green because there’s no traffic around. We can give him 30 seconds to do that and then go back without messing up the synchronization.” Or, all this could get a lot more sophisticated. Ash: No, exactly. But I think that’s the key. Right. So I think it’s more like, can you get a brain that’s dynamic, and right now the brain is not. Pablos: I presume there’s not much of a brain and it’s not a very advanced area, Ash: It’s a non dynamic brain. Pablos: One cloud SaaS company could be making the brain for traffic and sell it to every city. Another company could be making the, Tesla traffic light that just knows how to see if there’s any cars around. Ash: That’s security problem, Pablos: Why is that? Oh, if it’s centralized, you mean? Ash: There’s a quote from a person that let’s just say I met. An agency called RAW. (https://en.wikipedia.org/wiki/Research_and_Analysis_Wing) RAW is fantastic. That said, yeah, what happens when 2 minutes before an invasion, all lights go red? An invasion or attack or whatever, all lights go red. Pablos: I don’t know, This is one of these old People have been saying, what if hackers shut down the traffic lights for, decades, and the only time it ever happened meaningfully was in the fucking movies. So, I, I don’t buy it. If all the lights go red, then people just start going the way they do in Southeast asia. Ash: Then, and suddenly we’re like in Beirut. Pablos: I kind of think that’s how they should do it anyway. I was driving in Riyadh a couple of weeks ago, in Riyadh, the lines are painted, but they’re irrelevant. Yeah. It’s a free for all. And what I realized is that it’s actually kind of better because, in the U. S. everybody’s been coddled. They got lanes for this and that, they got the turbo or not turbo lane, I wish. They have a handicap lane and HOV lane and, bus lane, all these different lanes. And then, you got to be a lawyer to read the parking signs. So everyone’s being coddled all the time. You could probably drive with your eyes closed in a lot of American cities because, everybody’s following the rules. But if someone goes out of bounds, then they’re going to cause a real problem. If you’re in Riyadh, everybody’s driving at maximum speed all the time. There are no lanes. People are swerving all the time. You got to be on the ball. You couldn’t hit somebody if you were trying. If you literally tried to hit somebody with your car, they would evade you because they’re all doing evasive driving all the time. Ash: It’s, it’s all, it’s all offensive driving. Pablos: It’s all offensive. I’d like to, I’d like to see the numbers. I don’t know if we have good data on safety. It’s Ash: interesting. So we were in Vietnam, and you go to Vietnam and it’s a sea of random mopeds. Sometimes, you have the one person in the moped, the best is when you have at least five, right? The whole family. On the moped, you have mother, father, two kids. Then the baby kind of like strapped on like a, koala bear something. That’s, that’s when, you know, it’s, it’s, it’s getting crazy. And what they were saying, it’s like, yeah, “you’re not going to get hit. Walk across the road.” I was like, “what do you mean?” “Just walk across the road.” And it’s like, it’s like you walk across. They said “we operate in a stream.” They flow around you. Pablos: Nobody wants to hit you either. Ash: Yeah, but it is also a bit slow motion.. So there is a little bit more like speed. Pablos: A few days ago, I was in Shenzhen. They have, an absurd number of electric scooters. Because they’ve outlawed gas scooters. So everything is electric scooters. You ride them on the sidewalk. So it feels a little sketchy because there’s a lot of fast moving electric scooters and not, they’re not like little Bird scooters. They look like, Honda scooters or something. They’re big, but the whole town, it’s kind of clean and quiet in that sense. Overall they still have work to do, but the scooters are mellow. It’s all quiet. It’s, it’s busy. There’s a lot of people, but it’s not noisy because today, now I’m in Bangkok and in Bangkok it’s, they got all the gas scooters that China was getting rid of. And so they’re just going full tilt on these, gas scooters with no muffler, no, no catalytic converter, nothing. And it’s just noisy as hell. It’s crazy. And I don’t know. I kind of like it. I like the entropy. Ash: I do have to say that I, if you look at it, Vietnam felt the safest. Specifically Ho Chi Minh Saigon, it was the safest of the crazy, So that, that, that felt good. I mean, Beirut was just a whole different story. Like Beirut, it definitely, and I think it was my CTO who at the time was driving me around and I was like, yeah, I’m pretty sure Antoine, this is the oncoming traffic. He goes, “yeah, that’s why there’s no one going the same way as us.” Like, “because they’re coming at us,” it was like, his logic was flawless. Right. So at that moment, I was sort of like, it’s true. We don’t have anyone going the same way as us. Cause we’re in the fucking oncoming traffic lane. He had made the fourth lane, which was go at, like, it worked, so I don’t know what to say. Yeah, I mean, they went, they went beyond lanes, the lanes were just like like you said, they’re, they’re paint on the road there. All right. So that was traffic lights for, for the last 30 minutes. Pablos: Obviously traffic lights aren’t going to work there. Okay. I have another idea, which is related. So, the fleet of deployed Teslas is massive, like in most U. S. cities anyway, maybe other places. And Teslas are driving around all the time. And they could probably figure out, like within some window of accuracy, where all the open parking spots are. Like they’re probably not looking for it now, but Teslas are just driving around. They see where the open parking spots are. And so if they were trying. They could just aggregate that data and tell you like, “Oh, you’re looking for a parking spot. Here’s the nearest one because a Tesla drove by it 12 seconds ago.” You see what I mean? Ash: Interesting. Pablos: That’d be a superpower for teslas. Ash: That’s, that’s, that’s, that would be great. I mean, that’s like, that’s like Spot Hero on crack. Pablos: Yeah. Who wouldn’t buy that car? Oh, you could buy a Kia. Or if you get a Tesla, it’ll tell you where the fucking parking spot is at. Ash: Yeah. So it’ll tell you the next, the next location. I like that. The thing that you have to figure out is how do you save it? Pablos: Well, You wouldn’t know for sure. The things could sense in any spot they have a sight line to that could see is it is it empty? Is it staying empty? Is somebody pulling into it? You could maybe make statistical probabilities for different streets. Stuff like that. Ash: It definitely helps when you’re doing the parking lot, shuffling, just going around and around and around. And then, you just hope that, that someone pulls out right. What a Tesla could do is could wait for the next Tesla. Pablos: Mm hmm. Oh, yeah. There you go. Now we’re talking. There you go. Tesla baton. They’re doing that, with their, charging stations anyway. Tesla drivers are playing a video game where they’re like, You know, waiting for a, for a charging supercharger spot so you could, you could do that. And then there’s, yeah, I like that one. I think it would be useful though, even if you just, you know, it knows where you’re trying to drive to and it could figure out like, okay, you’re going to have a real parking problem in that area. Street parking is a lost cause. Ash: But if there are four Teslas there. Pablos: It’s hard for a Tesla to know when somebody’s going to leave. Ash: It does, because the preconditions 10, 15 minutes, see, like, if you set departure time on your Tesla, because you were preconditioning or Pablos: Oh, why Would you do that? My car doesn’t know when I’m going to leave. I guess you could. You could gamify it. This guy’s got a meeting. At 3 o’clock, so he’s gonna have to leave by 2. 45, so probably there’s gonna be an empty spot here. I don’t know, maybe. Might be possible. Ash: I don’t know that you’re going to synchronize with the calendar, but I mean, that could be kind of cool, but I’m just saying that there’s definitely precondition, which, which you’re supposed to do. So if you’re plugged in at home, right. Or, but like any of these chargers, there’s like a precondition so that your car is warmer and like ready and like all that crap, right? Like they’ve been doing that for some time. Pablos: Oh, I see, oh, I see what you mean, right. I get it. I get it. So, so I don’t drive a Tesla, but what, but precondition you’re saying is like, I’m going to go. So warm up the car or cool off the car. Ash: So fancy cars do that, but also when the electric cars came in, the batteries have to have like been revved or whatever. Pablos: There’s a thermal window Ash: Or, or set them up. Pablos: I see. Ash: You got it. Right. So that’s why they want to know when you’re leaving. That way you’re not, you’re not cold driving your, your Tesla. Pablos: Yeah. Ash: So that means they know, right? So if you want maximum range, they’ve got to like do that little thermal thing inside to get the battery, like not, minus five or whatever the hell it is outside. So, so they already know. So in cold places, this would work well. Pablos: Intriguing. Okay, so there’s another idea, at least for Tesla if not a startup. Recorded on December 22, 2023The post Smart Traffic Lights – ØF appeared first on .

 This is probably the conversation I had in mind when I decided to start this podcast. Samy Kamkar is an old buddy of mine, a genius hacker. When you guys hear me praising the minds of hackers and how brilliant they can be and how they think, Samy is the example in my mind that I’m thinking of, and I always love to share him. Samy’s famous for having written a computer virus that he was using to meet girls on the internet, which is probably ill-advised. The virus he wrote took over MySpace. It was incredibly genius! What would happen is: if you looked at Samy’s page on MySpace, it would just automatically add you as his friend. MySpace is long gone, but you could imagine what that would be like on Facebook or Instagram or Snapchat nowadays. So, within 24 hour period, Samy had over a million friends on his MySpace profile, because the code not only would add you as his friend, it would copy itself to your page so that whenever anybody looked at your page, it would automatically add them as Samy’s friend too, and then do one other benign thing, which would change your profile page to list Samy as your HERO! Samy is my hero. I love him so much. He’s done a lot of amazing, beautiful work and computer hacking. He has a YouTube channel that we’ll talk about on here, but you should definitely go watch his videos. I’m not going to interview Samy. that has been done and you should listen to the Tim Ferriss interview of Samy. I think of this conversation is something you could listen to with or without having heard that, but if you want to know more about Samy and his background and all the stories, then you can go listen to Tim Ferris interviewing him. This however is a conversation between friends, it is very soulful. There’s a lot in here that I’m looking forward to sharing with you guys. Also, Samy is a co-founder of a couple of company that have been very successful and he sold his most recent company called Open Path to Motorola. This is not an ad, I’m just telling you because I’m impressed with what Samy built: Open Path is a physical door access control system that’s way better than those cards you used to have to use to get into your office. Now you can just do it with your phone and walk right in. Samy has helped build that product and the company is doing very well. And I think you should all become, customers. Oh, and I almost forgot to tell you Samy, at one point decided he wanted to become a DJ and learn how to make music. And he’s the one who created the track that we use for the podcast intro that you’re going to hear next. Please listen to this conversation with me and Samy. I’m sure you’re going to get a lot out of it. Important Links: Samy is my Hero Samy on Wikipedia Samy’s Website Samy on YouTube Tim Ferriss Podcast with Samy About Samy Kamkar Samy Kamkar is an American privacy and security researcher, computer hacker and entrepreneur. At the age of 16, he dropped out of high school.[One year later, he co-founded Fonality, a unified communications company based on open-source software, which raised over $46 million in private funding. In 2005, he created and released the fastest spreading virus of all time, the MySpace worm Samy, and was subsequently raided by the United States Secret Service under the Patriot Act. He also created SkyJack, a custom drone which hacks into any nearby Parrot drones allowing them to be controlled by its operator and created the Evercookie, which appeared in a top-secret NSA document revealed by Edward Snowden and on the front page of The New York Times. He has also worked with The Wall Street Journal, and discovered the illicit mobile phone tracking where the Apple iPhone, Google Android and Microsoft Windows Phone mobile devices transmit GPS and Wi-Fi information to their parent companies. His mobile research led to a series of class-action lawsuits against the companies and a privacy hearing on Capitol Hill. Recorded on September 17, 2021The post Samy is My Hero — Samy Kamkar appeared first on .

Today we get to hang out with my buddy Nick Touran. Nick is a nuclear engineer who’s focused on the practical deployment of clean, renewable, carbon free energy. I met Nick when we were both working at the Intellectual Ventures Lab. He is on the TerraPower team, and even though we don’t discuss the TerraPower reactor, or any of that technology on this episode, Nick and I try to dig into history of nuclear a bit. trying to explain what’s possible with nuclear reactors, so people can really understand how that fits into our future and what the pros and cons are, and really try to technically, illuminate how nuclear reactors work a little bit for people who haven’t been able to dig into that so much before. I learned a lot of what I know about nuclear reactors from Nick, and so it’s a thrill for me to get to share him with you guys and this conversation in particular is a great place to start. Nick has a website called whatisnuclear.com. If you want to learn more beyond what we cover in this episode, that’s a great place to start so go and read his writing and learn as much as you can. I believe this is one of the most miraculous technologies humans have ever invented. And it’s so frustrating for me that we haven’t put it to greater use for humanity. Important Links: Nick’s awesome website, whatisnuclear.com About Nick Touran I’m a reactor physicist working on the design of an advanced nuclear reactor for a nuclear innovation company, where I’ve been since 2009. I have a Ph.D. in nuclear engineering from the University of Michigan based on the multiobjective optimization of fast reactors using perturbation-based equilibrium cycle methods. Recorded on June 15, 2021The post Primer on Nuclear Reactors — Nick Touran appeared first on .

Short opinion piece about these helium airships and the need to preserve helium.  Back before there were memes as we know them, the meme for a disaster was the Hindenburg. The Hindenburg was this giant Zeppelin, an Airship filled with hydrogen gas that’s lighter than air. Like a helium balloon. So it would just float but it had a huge passenger compartment. This is back in. 1937, so 80 years ago, the Hindenburg famously ignited and turned into a giant flame in the sky and scared the shit out of everyone forever and these things have not gotten a lot of attention since then. I think they’re cool. But there’s a real problem with trying to make a lot of hydrogen next to actual humans and somehow imagine that it’s going to be safe. So since then, people have played around with things like blimps and things that don’t have passengers and stuff like that. But these things don’t, aren’t very popular. I have seen a little bit of news lately about this group called Lighter Than Air Research, which is trying to create air ships today. These are in part probably safer because they don’t fill them with hydrogen, they fill them with helium. So this is a massive craft. They call Pathfinder one. I’m going to link to an article in IEEE Spectrum about this and I’m just going to give you, the highlights. Pathfinder 1 is 120 meters, long, 20 meters in diameter. I think biggest Goodyear blimp right now is 75 meters. So this is like the biggest air ship ever made. I think. LTA Research staff maneuver Pathfinder 1 while the airship is under construction at the company’s Moffett Field facility, near San Francisco.  LTA RESEARCH The idea is to carry about four tons of cargo. It sounds like a lot, but if you’re not familiar with a ton, four tons is about one Humvee. Or, maybe four tons might be a good size Amazon delivery van fully loaded. That’s four tons of cargo. There’s still, also a crew, there’s what’s called water ballast, which is, water you carry for weight. So if you have a problem, descending too fast, you could drop the water and it would slow your descent to make it safe. And then fuel, cause you still need fuel in order to propel the thing. The idea is this thing would go 65 knots. So that’s about 120 kilometers an hour, which I think about 70 miles an hour. That’s about as fast as these things seem to ever really be able to go, but the, average cruising speed probably maxes out at more like two-thirds of that. This is a modern Airship probably worth revisiting it to see if it can be done better. The old ones were built with, a lot of wood. They were built with a lot of aluminum which is, good strength to weight ratio, but incendiary. In the sense that it melts at a low temperature. Modern crafts could be built with carbon fiber and titanium and all these modern materials that we can coat to make them less inflammatory, So that’s the frame and then you also have this covering and the coverings gonna be made of not cotton the way we used to do it, but we’re going to make that out of some modern polyvinyl from DuPont called Tedlar. So obviously those materials have advanced a lot in our lifetime. If you sense a little bit of a dubiousness in my voice, I’m going to tell you why that is in a little bit here. That’s the basic idea. There’s also a lot that’s advanced in weather prediction. There’s a lot that’s advanced in electric motors for propulsion. There’s a lot that’s advanced in autonomous flying and driving. And so we have lidars and we have things that can figure out how to make these things dramatically safer. I buy all that. Here’s what bothers me. The world has unlimited hydrogen on earth, more or less. We have a lot. We can make more. Hydrogen’s awesome. What the world does not have on earth is very much helium. We have very little helium. We have very little helium left. We’ve been able to find a few new helium mines in the last decade, but there’s just not much of it. And that is a super valuable element that we really need for lots of different things. We need it for making computer chips. We need it for figuring out how to make fusion reactors and things like that. We’re just running out of helium and I’m pretty disappointed in any plan that involves using a lot of helium as it’s lighter than air substance. Because of that, I’m really having a hard time getting excited about these modern airships that want to use helium. Helium is not flammable, so it won’t burn up the way that hydrogen does. If you remember your periodic table, if you look at the very beginning, the reason you’ve probably heard of hydrogen and helium is they’re numbers one and two. They are the lowest weight elements in the world. And hydrogen is a lot lighter than helium, but it also, combined with oxygen just fucking blows up, which is great, amazing amount of energy in hydrogen. We have a lot of use for that. But what’s happening with helium is, we’re just letting it go. We’re giving it away in party balloons which is a terrible disaster. It makes me practically cry when I see helium balloons, which is sad. I grew up with them. I love them. I want my kid to have them. They’re fun, but that’s a waste of good helium. We just don’t have enough and we don’t have a way of making more. And that’s the really important thing to understand. Until we get real good control of fusion reactors, and have extra ones to deploy at the job, we don’t even have any way of making helium. When you do have a fusion reactor, it makes a little bit of helium, but not much. Maybe someday fusion reactors will be able to be designed to put out a lot of helium for balloons, but right now they don’t. They don’t do anything right now, but they don’t do that. So the point is. We should be really careful about how we deplete the helium that we do have here on earth. Maybe someday we’ll get a highway to the moon and we’ll be able to go get a lot more helium. But right now this is this is a really important resource that I think we should be careful about. I don’t want to see it used on airships, which require a lot. Okay. Second thing. I tried playing with helium before, and we do use a lot of helium for weather balloons and things like that. Please use hydrogen. It’s okay if a weather balloon burns. A helium balloon that’s big, it’s just a really hard to manage. Putting a lot of lighter than air gas into a balloon to get it off the ground and float it up into the atmosphere. It’s just unwieldy. I only have a little bit of experience with this early days at Blue Origin, we tried to make some giant helium balloons just to see what potential might be in that. It’s hard cause, you gotta make the balloon out of something light and not too structural. The airships have a frame. We didn’t have frames. We just had big balloons that we made. We made them really light. But, you’ve got to bring tanks and tanks of helium to go, then fill that up to launch it wherever you are. The process of filling it up, it wants to float away while you’re filling it, and you think you could just keep loading gas into it the way that you would with a party balloon, but in practice, the more you load into it, the harder it is to tether the thing and keep the wind from blowing it away. And maybe you could do that indoors and then have a ceiling the launches, it’s pretty impractical to do. And, with travel, you want to be able to go a lot of different places, obviously with an Airship, you’d try to fill it once and then use your electric motors to move that thing around, up and down and maybe. I give up as little helium as possible, but that’s the other thing about helium. It’s really hard to contain. It leaks through almost everything. It is a very small molecule. I’m putting this out there just to let you guys know how I feel about it. From what I understand to date. I have not met or talked to the folks that are working on this at Lighter Than Air Research. If you know them, please introduce me and I’m sure that they can tell me how they think about it. I’m sure they have some other perspective and if I get that in my head, I’ll let you know if I change my mind. Recorded on December 18, 2022The post Helium Airships (Short) appeared first on .