Paul Shapiro: [00:00:00] Noa, welcome to the business for good podcast.

Noa Weiss: Thanks, Paul. It's great to be

Paul Shapiro: here. I, I have to say, out of, of more than 125 interviews, aside from the interviews that I've done with my wife, Tony, you are the only guest on this show with whom I have ever danced in person with .

Noa Weiss: So Well, it's an honor

Paul Shapiro: I, I was very psyched at the Good food conference in San Francisco a few months ago. We had the great pleasure of, learning that, you are an excellent swing dancer. I'm a mediocre swing dancer, but we still got to do like. Less than one song, but still better than nothing. And so, I appreciate that.

did your love of swing dancing predate your love of AI? Which, which came first. That's a

Noa Weiss: good question. I did start doing AI before I started swing dancing, but I feel like my love for jazz music was kind of always there. So, you know, it depends how you count.

Paul Shapiro: Yeah. Okay. I, for people who [00:01:00] don't know what swing dancing is, it is as Noah has indicated a type of, dance to jazz, but it's not like a soft jazz.

Normally it's like more of like. What do you say, like 1920s kind of swing type jazz, am I describing this accurately? Yeah, so

Noa Weiss: 1920s would be like the Charleston and then I think Lindy Hop, closer to the 50s, etc. But yeah, like faster, fun jazz songs, kind of upbeat.

Paul Shapiro: Okay, well, it was an honor to get a chance to dance with you.

And, we had planned on going out dancing, in Israel during food tech Israel, which was supposed to happen in November. sadly and horrifically, it got postponed because of the October 7th massacre and the subsequent war. But when the conference is rescheduled, I can assure you I'm going to take you up on that and we'll, go out in Israel.

It'll be fun. Fantastic. Okay, so let me ask you, Noah, like, you know, a lot of people are thinking [00:02:00] about the negative headlines relating to plant based meat these days. Sales are down. Companies are having a hard time getting funding. Layoffs are nearly ubiquitous. Some companies are going out of business altogether.

What do you think is the problem? Why do you think that campus meat is struggling so much right now?

Noa Weiss: Yeah, so what I really see and what different research has shown that it's really a lot of it goes down to the mouthfeel and to the price. So when you say mouthfeel, of course, it means a lot of things.

I'm going to focus on texture. I think it's, really the, the majority of it, of what we mean when we talk about mouthfeel. And as you know, plant based foods, plant based meats specifically, they're usually texturized with a process called extrusion, which is a process that While it is the best technology that we have today for plant based foods, for texturizing them, there's, [00:03:00] there's a lot of unknowns about it.

a lot of people will talk about it as, as, as a black box, really. And it's also a very expensive process to use, which means that, a lot of the, sorry, I'm going to stop for a second. sorry for starting out that way. Would you mind asking the question again? I think I went too deep too, too fast. All right.

Paul Shapiro: That's okay. Don't worry about it. Okay, no, there's a lot of doom and gloom surrounding the plant based meat industry right now. just to be blunt to be blunt. I don't want to sugarcoat it. so, you know, look, demand is down. Companies are doing layoffs virtually ubiquitously in the space. Several companies in the plant based meat space have just gone out of business altogether.

Or they have been acquired for pennies on the dollar and there are a lot of people who have theories about why this is like demand for plant based meat was really skyrocketing, during like 2021 and even part [00:04:00] of 2022, but now demand is down. What happened? What do you think is the issue that led to a spike in demand and now a decrease in demand?

Noa Weiss: Yeah, so I think a lot of people were curious and were willing to try plant based. I think most people in Western countries are interested, in at least partially, in choosing the, choosing the food that makes more sense both for their health and for the climate, as well as for some of them for animal welfare.

But I think that the products that we have today are just. As far as meat eaters would say, they're just not good enough. where research and surveys show that the main thing holding us back is texture. just a texture being not quite what they're looking for, as well as the price, you know, prices, like plant based meats are still more expensive [00:05:00] than animal meats.

and that's something that, you know, when you're not, I mean, for most meat eaters, they wouldn't pay more, just to get something that, in their opinion, is not as good, as the so called real deal.

Paul Shapiro: Yeah, not as good tasting that is. And so. I have also wondered whether price is the main factor. I mean, you know, there is a key difference between now and 2021, which is that we have a lot of inflation and things cost more.

And so the question is, are people willing to pay more for something that, as you said, maybe they don't see a compelling enough reason to get it. I wish that more people bought food based on its climate impact. I think very few people do that. Even the personal health is not usually a major compelling factor for most food purchases.

And so, because people are buying, because they like the way that the of the experience, right? The taste and the texture and so on of the product, they might be willing to do that, [00:06:00] but not if it's going to cost 200 or 300 or even 400 percent more than the incumbent animal based product. And so the question then is like, you know, how do we overcome those 2 barriers, right?

Like, how do we overcome price and the actual experience, the mouthfeel, the flavor, everything that you need to get there? And do you need to make it identical to animal meat? Do you think, or can you just have something that tastes really good, but isn't identical to animal meat? Yeah.

Noa Weiss: So I think I'll start with your last question.

if it were up to me, we wouldn't need to replicate animal meat at all. I feel that the plant based, food world is infinite and has a lot of exciting, variety. But I think that for people that are used to meat, to animal based meat, they are looking for something similar to switch to that. so it doesn't have to be exactly the same, but [00:07:00] It should be very similar, and in a plant based food, so we mentioned texture and, I don't know if you know that, and I assume most of your listeners don't, but, in plant based meats, the process that is usually used for texturization, it's called extrusion.

Extruders are basically these huge machines, I mean, they come in different scales, but the big ones can take up a room, And you put ingredients on the one end and you press a few buttons, choose a few parameters and then on the other end, you basically, let's put it simply, you get to be on meat. of course it's, it's not, yeah, it's not that easy, but just a simplified process to make it something a bit more.

Paul Shapiro: Yeah. It's kind of like, it's a lot of pressure and a lot of heat, let's put it that way. It changes the molecular structure of the protein to make it less like a plant and more like an animal. And so that's how you transform, you know, something like pea protein into something like a Beyond Burger.

Noa Weiss: Yeah.

Make it more [00:08:00] fibrous and yeah, just make it, make the texture more similar to animal proteins. and that's a process that, I mean, even though it's been with us for a long time, it's still very little understood, especially when it comes to protein extrusion. I'm saying that because extrusion is also, it's used in plastics, it's used for cereal, but specifically for protein extrusion.

It's very unreliable and inaccurate, so just creating the formulations for most food companies when they want to create a new product or to improve an existing product, it's much more, trial and error than something that's more, evidence based, let's say, of course, you have the experts, the ones that are like, you know, the main experts that know a bit more,They do exist, they still have to run some trial and error, but they're better than others, but they're also a very limited resource or most plant based [00:09:00] food startups, wouldn't be able to hire someone like that.

And that means that they do need to go through a lot of trial and error, get really suboptimal results a lot of the times because they can't really explore all of the options. since extruders are also very, very expensive and running extruders is very expensive. so smaller startups, you know, they have a limited budget.

There's only so much trials that they could run. so they kind of guess their way there. They find a formula. Whether it's good enough or not, it will have to do. and they spend a lot of money on that. And even later when they, like, when they try to scale up and you switch from a smaller extruder to a bigger extruder that there's also, you kind of need to go through the process again.

When you change ingredients, it's just, it's really a pain point for, plant based food manufacturers.

Paul Shapiro: And so your proposal then, Noah, is that you're going to take this pain point, which is extrusion, which is basically how [00:10:00] 99 percent of plant based meat gets made today, and you're going to make extrusion great again, right?

You're going to do something better. You're essentially saying, well, you know, if you're able to get into data science and artificial intelligence that you can do extrusion in a much more efficient and economical way. Is that accurate? Is that an accurate way of putting words in your mouth?

Noa Weiss: yeah, though, I would say that I'm a bit more, I don't want to say realistic, but just coming from the world of AI and data, so I do see, I mean, I think AI has incredible potential for a lot of things, and as you know, I worked for, I mean, I've been working with AI and data in general for 13 years, and for the past 3 or 4 years is,I've been working as a senior consultant working with companies to help them figure out how they could use A.

I. to solve their biomechs. So when I saw, like, when I [00:11:00] learned about this problem with extrusion, and how major it is for plants based food startups, I really sought a potential there, whether it will solve. Oh, sorry. Let's

Paul Shapiro: go ahead. That's okay. it may not solve everything, but let me ask you. You know, your, academic studies were in psychology, right?

You did an undergrad and master's in psychology. Presumably this

Noa Weiss: is also, yeah, sorry. Computational neuroscience too, as well.

Paul Shapiro: Computational neuroscience. So these are on, you know, looking at human minds, right. Looking at biological minds and trying to understand them. And at some point in your life, you started getting more interested in artificial minds and trying to understand them.

So what happened? Like, how did you go from worrying about human psychology to worrying about artificial psychology?

Noa Weiss: that's a good question. I haven't been asked that before. I like it. I would say that the potential for impact, in my current line of work is much [00:12:00] greater. And that's something that, really, really speaks to me.

Paul Shapiro: Okay. And your current line of work being an interest in plant based eating or your interest in as a consultant on AI for other companies? Like, what is what do you perceive as your current line of work?

Noa Weiss: Yeah. So in that I meant, AI data, just everything you can do with that machine learning. And it is I'll mention something that, to me, it's obvious, but probably to a lot of listeners isn't that It is very, so AI today, like neural networks, which are the algorithms that are like the family of algorithms used for GPT and everything else that most people have heard of, they are based on the understanding of the human brain, at least originally.

So it is something that I, even though I also studied the human minds during my academic studies, I also studied that, So when I, once I left academia, it was kind of like a natural [00:13:00] way to go.

Paul Shapiro: Interesting, or an unnatural way to go, since you're not looking at natural minds anymore. Yeah, an

Noa Weiss: artificial way to go, some would say.

Paul Shapiro: Yeah, I actually, I kind of have a pet peeve about the fact that natural was perceived as so good and artificial was perceived as so bad, because a lot of the times things that are artificial are better than things that are natural. Not always, but you know, sometimes they are. but let me ask you then, because, you know, right now, you know, there's a boom in a I chat.

She has been the most obvious example of that, but it's led to a massive interest from the venture capital community. A lot of people joke that unless your startup is an a I, you're not going to get funding. It's not totally true, but there is some there is some truth to it that people are really interested in funding a I tech right now.

so. You have this great interest in A. I. But as you mentioned, you know, you're also really interested in plant based eating. You're a good food institute mentor. We actually met in person for the first time at a good food is to do conference. but what [00:14:00] predated what, what preceded what in your life were you interested in plant based eating before you were interested in A.

I. And how did that come to pass? Like, why are you so involved in the plant based community? Yeah, so

Noa Weiss: I've been a vegan for about a decade. really just got into it for the animal welfare perspective before it was such a

Paul Shapiro: What led to that, Noah? Why did you become a vegan a decade ago? I know you said animals, but what was the catalyst for it?

Noa Weiss: For me, I just, I got to learn more and more about what things really look like in the animal based food industry. And, the more I learned about it, the clearer it became that it's, it's not something that I want to contribute to. And ever since becoming a vegan, I really explored like something that's always been on my mind is how, how can I help promote, veganism or just, you know, the, the end of factory farming.

And recently, I mean, [00:15:00] recently, and when you're looking at a decade, it's recent, but about a year ago, when I learned on, of alternative protein, it, really, I mean, the alternative protein really strikes me as the best, the best focus we could have, to, to promote that shift towards a food system that is, plant based, plant based or again, not animal based.

Paul Shapiro: Yeah, I definitely agree with that. And I agree with the sentiment that you expressed earlier, which is it would be great if we didn't have to mimic the meat experience. I wish that people were willing to eat hummus wraps and bean and rice burritos and lentil soup. That would be wonderful. but it's kind of like saying, you know, I wish that people would walk in and bike more, but people seem to like to drive.

So we need cars that don't rely on fossil fuels and we need meat that doesn't rely on the exploitation of animals. and so for similar reasons to you, I became a vegan. sadly, I'm a bit older. So it was 30 years ago for me, but I,you know, for me, it was the same motivating factor. And I went through a number of stages in my [00:16:00] life where I thought, well, you know, maybe, you know, we just have to.

Publicize the plate of what is happening to animals, and that would be sufficient to change people. That was obviously, not true. That is not sufficient. You know, people say that if slaughterhouses had glass walls, everybody would be vegetarian. Something that's obviously false, given that most people who watch a video of a slaughterhouse don't become a vegetarian.

and I, you know, I've worked a lot in public policy on these issues and, now really am convinced that it's new technologies that we need. And so I, I really am grateful that you are working to help bring new technology to help advance the interests of animals by helping to make extrusion, much better.

So tell me about Green Protein AI, Noah, why did you start this and what's the goal of what you're actually trying to accomplish?

Noa Weiss: Yeah, so Green Protein AI, it's a non profit that I started with Food System Innovations that you, of course, know. Also a non profit based in California [00:17:00] focused on the same goal of shifting our food system to be more plant based.

And I say plant based, but I basically just mean not animal based. And it, what we do is we focus on that problem of extrusion, and our goal is to create, through AI and machine learning, to create. Models based simulations that will help food startups or researchers or companies, anyone using extrusion to get to a better product with less cost.

so using AI to understand the process better and. It'll be creating prediction models, so they could plan better ahead of time and also, kind of get guidance and choosing where they want to go. If. Based on what texture they're trying to imitate.

Paul Shapiro: Got it. Yeah, because, you know, the texture of different animal meats is, of course, extremely different, right?

[00:18:00] Beef, chicken, pork, turkey, fish, crab, et cetera. Those are all very different textures that you are trying to get to. And so they would require different types of extrusion experiences. But since founding the organization, have you found reception among the community of companies that are working to replace animals in the food system?

I mean, you have folks who are saying, Hey, no, I want to utilize your expertise in a I to help us make better meat.

Noa Weiss: Yeah, so there is a lot of interest. It is, we definitely hit a pain point. no question there. The, the sad thing is that a lot of them want the product now and we're still working on building it.

So right now we're in the phase of creating, a network of, we call it seed collaborators, which are mostly researchers, researchers, like research institutes or academia. That share their data with us. so we based models on that. and then once we have [00:19:00] that working MVP, MVP, a minimal viable product, then we'll be open for commercial companies.

so it's kind of, yeah, so for some of them that reach out, I need to kind of like, put, sorry, dampen their excitement, but hopefully we'll, we'll have it not, not too long from now.

Paul Shapiro: Well, hopefully we're priming the pump with this podcast to make them, even more eager to, to benefit from your services.

However, that raises the question of why nonprofit like this would be extremely valuable to any company, right? So, if a company could make a more meat like experience with their products, that's very valuable to them and they'd be willing to pay. So, first, will these companies pay to participate or is it a free service to them?

That's just funded by food systems, innovations or like, like, what, what is the way that you get paid to do this really? Yeah, so

Noa Weiss: that's a very good question. the reason that we're a nonprofit, I mean, [00:20:00] there are two major reasons. One, is just me starting this. I really wanted to be able to focus on impact and if you go to like for the startup model, that's not something you always can do once you have investors in, you need to prioritize revenue and that makes sense.

I wanted impact to be just like the, what we can direct ourselves towards. That's one thing. Another thing, is the fact that we are based on collaborations and the fact that, the first stage, for example, now is just creating these partnerships with researchers that share their data. we figured that having this as a nonprofit is a stronger signal, that we are here for the impact and for just like helping society understand extrusion better.

And that they can trust us with that. and so,

Paul Shapiro: oh, go on. I'm sorry.

Noa Weiss: I, yeah, sorry. I still have to answer your [00:21:00] other question. Once we do have a working product, those, users that will not be seed collaborators, they will pay for the service. because while we are a non profit and we are focused on impact, we do have a plan to be financially self sustainable.

so it's not something that will, I mean, we're currently working on donation money just, you know, for launching this until we get the MVP, but then, we are gonna charge for using the models.

Paul Shapiro: Got it. Okay, so let me offer a hypothetical situation. Let's say I am beyond meat and I'm thinking I want our products to have a better texture.

So I'm going to go get green protein. I'm going to pay you to help us create better extrusion models that give us more meat like texture from the peas or the fava beans or whatever we're using. You are going to do, you're going to work with us, how do I ensure that impossible foods isn't going to then just [00:22:00] get exactly what I just did, right?

Because these companies are competitors, they probably want each other both to succeed because they're both mission motivated, but they are competitors. and you know, they, you know, one's gain sometimes comes at the other's loss. So what happens there? If you find some better way to make a plant based burger and for beyond, right?

Does impossible benefit from that as well?

Noa Weiss: No, not at all. that is something that we are very careful about because as you mentioned, we we are aware, of how important that is. And there are methods for federated learning where, or in general just keeping the models separate. So each user will have a model fine tuned to their own needs and their own data.

and other like their competitors will not have access to that data.

Paul Shapiro: So the data is not going to be open source. It's not like anybody can go benefit from the experiments that were run and you found out, Hey, actually, you know, pressure X and temperature Y, you get an [00:23:00] unbelievable chicken breast, right?

You're not, that's not going to be something that's going to be, you know, made public to any company who, or to anybody who wants it. No,

Noa Weiss: I wish that I could take it all and just put it out there for everyone to use. But as you mentioned, we, we do need to keep our clients in business.

Paul Shapiro: yeah, and, you know, it would be good for the whole field, obviously, but at the same time, I just think of a company is paying for this.

They probably want some type of proprietary nature to the data that's being generated for them. Okay, when we're talking about extrusion, Noah, you're, you're referring to it as a black box and you think that through AI, you can maybe shine some light into that box is that you think that you can run better extrusion trials that you can plan better extrusion trials that you can make predictive outcomes about what will happen in certain extrusion trials.

Like, what is it that you think that I can actually do to improve the extrusion process for companies in the alternative space?

Noa Weiss: [00:24:00] Yeah. So basically all of the above, I think that through prediction and through planning, kind of using, machine learning and active learning for a better design of experiments, it's really enabled.

So it's about enabling the people using it, isn't it? That as, as AI, usually, as it's really about, empowering people to make better decisions. Or hopefully, that's why I, what AI usually does. so having the predict, for example, predictive models, could help food startup founders or their team, plan the trials in advance and be able to, for example, explore all of the search space.

Because that's something that you can't really do when you have to really do everything on an extruder, like, wet experiments. so that's one thing we also plan to have, probably not in the MVP stage, but hopefully straight after we plan to have modules that help, like really direct you towards, as [00:25:00] I mentioned, towards the, the best trials for you.

So you say, I want a chicken breast and that's the, like, here are my results so far, like, that's what I tried. That's what I got. And then we'll be able to tell you, or the product will be able to tell you, or you should try changing this parameter and this parameter and see

Paul Shapiro: what you get interesting.

And so the basic idea then would be that you would be informing the design of experiments that these companies can do in addition to helping them, you know, look at other forms of data. But So that rather than running a multitude of trial and error tests, you can make them a little bit smarter about what they're going to do so that they can have a shorter R& D time to get to that final product.

Noa Weiss: Yeah, shorter R& D time and also be able to explore more possibilities and hopefully get to, just some other pockets of, experiment that they wouldn't get to otherwise. [00:26:00] And in general, just using, sorry, so in a more general sense, using the models to really enhance our understanding of extrusion, as it is something that the algorithms that we're building are, ones that are easier for, like, there's the whole topic of explainability and interpretability in machine learning.

I won't go too much into it, but. it should help us to understand exclusion better.

Paul Shapiro: Are there any companies, Noah, that you think are doing a good job in this, in the alternative protein space right now? you know, NotCo has made a big deal about their AI program and that it's helped them to get to better products.

I don't know much about the claim other than that it is made, but I can't think of other companies that claim to be using AI in their product formulations other than not go. But, do you think that there are companies in the space that are doing a good job utilizing AI already? Yeah, so there

Noa Weiss: are very few on there, but I think Climax Foods, I [00:27:00] mean, they're definitely using AI and I think they're doing a good job as far as I could see.

So they, they're also, they kind of had AI from the start, I think, which really shows their commitment to it. It's not just like, something on top, it's something that's a core part of their process. I can't think of any others right now that use, that really use AI. I mean, there are ingredient companies, you know, like Imaginary, for example, but not like, end product, like packaged goods companies that I can think of.

Paul Shapiro: I have thought a lot about the idea of using it for, extrusion, which is, of course, as we noted earlier, nearly all plant based meat is made via extrusion technology. but fermentation is an up and coming technology. In some ways, it's not just up and coming. It's been used for decades by companies like corn Q U O R N.

but the premise of fermentation is that you can achieve a meat like texture through fermentation, not through extrusion. And so do you see a [00:28:00] potential for the use of AI, not just in extrusion technologies, but also in fermentation so that you could make things like mycelium or even some precision fermentation ingredients like many of the companies are trying to do to make animal proteins via microbial fermentation, with AI.

Noa Weiss: Yes, definitely. I see a lot of basically wherever you have data, you can use AI. That's a An over oversimplification, but in a way it's true. And the problem mostly with alt me, alt, protein is that a lot of times we don't have a lot of data. but we are still able to utilize what we have. With fermentation, for example, something that can be very useful as, I mentioned it earlier, using machine learning and active learning, for a more precise design of experiments.

I think that could really solve a big pain point for a lot of fermentation companies as well as cultivated meat companies. Well, as

Paul Shapiro: somebody who runs a fermentation company, the Better Meat Co., and we do a lot of [00:29:00] design experiments, I have wondered, you know, we have humans who are designing the experiments, and I wondered, could they be aided, not replaced, but could they be aided by, some AI that's helping to design the experiments?

And so you've answered that question for me. It makes me very intrigued on a personal level, as opposed, in addition to the broader industry. I do want to ask you just a broader question, obviously your interest in this, as you pointed out, Noah stems back to animals and your desire to prevent animal suffering.

Are there ways that you think that I, aside from the alternative meat industry can also be used to help animals? I noticed that you're involved in some whale research that you think that maybe there is something that can be done for whales using. So I'm really eager to hear. Beyond plant based meat, what else do you think AI can do to actually make this world a little bit better for non humans?

Noa Weiss: Yeah, so the way I look at it is AI is a tool. so it's really, it's, it's [00:30:00] not the core. It's not the thing itself. It's how do you get to where you want to go? What we do with whales, you mentioned, like that's my work with the Deep Voice Foundation, which is, an, also a nonprofit, basically a research group, started in Israel.

And Just having great people working on applying their skills to help with whale research and preservation and what we do there I think is a good example because we're using AI to aid marine biologists with their work, kind of just like really boosting it and taking things that like tasks that could have results.

Like taken hundreds and hundreds of hours to the point that no one have, has the resources for that and just make it happen with a press of a button. so that's one thing that you could use.

Paul Shapiro: What's an example? So are you like recording whale sounds and that has some, light that you can shine on how the whales are, are, you know, what their welfare is [00:31:00] like, what, what is it that you're actually doing to help whales?

Noa Weiss: Yeah, so it's all about the whale sounds. You're very, very correct about that. And basically, it's working with marine biologists that, their research influences and informs regulators. so. Something that, could be, I'll just give an example, knowing what a population is in a certain area in order to decide where boats can or can't go.

it sounds trivial, but it really isn't and something that researchers like marine biologists can work a lot, without really getting definite answers on that.

Paul Shapiro: I presume that if it can be used to determine where the whales are at any given point to prevent ships from going there, those who want to harm whales could also use it right to those who want to go and hunt whales or even fishing boats who want to go find out where the fish are.

Are they using AI? Are you aware of any efforts to use AI to more efficiently [00:32:00] kill marine animals? I'm

Noa Weiss: not aware of such efforts and I really hope that they're not out there. I could say that our work as well as other, different but similar, work is out there. It's not online, so it's not real time spotting, like, there, the whale, there, like, there it is now.

Unfortunately, even without, people using it maliciously, it's still just, you know, money wins at the end of the day, so a lot of times, even if, like, ship captains know that, like, with their current I'm Rob, they're gonna just crash into a whale, which will be okay for the ship, but not okay for the whale very often.

They will not change course because that means delays. And yeah, right.

Paul Shapiro: Yeah. And you know, one of the more sobering things to recognize is that the biggest threat to whales is not whaling ships, but rather fishing ships, right? Because they're just so, [00:33:00] so, so many more of them. speaking of animals, Noah, I'm really interested whenever I talk to somebody who has thought a lot about artificial intelligence, I'm very interested in whether you first of all, let me just ask the baseline question.

Are there any artificial intelligences yet that you believe have achieved any type of consciousness, like any self awareness? No, I don't think we're there yet. Okay, not there yet. Do you have a prediction as to when, if ever that may occur?

Noa Weiss: Ah, much, people that are much smarter than me have not managed to answer that question, so I definitely don't, but I think, yeah, I, I do think it is a, a risk.

I mean, the risk of, of an AGI, I, I think it's something that we, we should be mindful of and,

Paul Shapiro: All right, and for those not initiated as artificial general intelligence, so not just something that can build paper clips, but something that actually, you know, is is like a human mind that could or or superior to a human mind.[00:34:00]

Okay, so we don't have conscious artificial intelligence yet. Have you thought about or researched where you think consciousness extends in the biological kingdom? So I presume you are convinced that mammals and birds and fish and reptiles are conscious, but there, of course, is a debate, let's say, about bees or ants or flies.

and there are smart people who I've spoken with on both sides of this topic who think so, yes, they definitely show consciousness and others who say that's absurd. what do you think? You think that consciousness goes down to that level?

Noa Weiss: So, I don't really know. And I think it also, it really differs on, you know, like we, we have those nuances in our definitions and they're very much based on our experience as humans.

and don't necessarily translate as they are to the experience of other animals. But mostly I'm less focused on that, since for me it was always not about consciousness, but [00:35:00] about the capacity to suffer. So that's really where I draw the line. Yeah.

Paul Shapiro: Presumably one is a prerequisite for the other though, right?

If someone is not conscious, they're not capable of suffering because they're not aware that they exist. But let me ask it a different way then. Forget about consciousness. Do you think that a B is capable of suffering?

Noa Weiss: I honestly don't know. No, that's a good question. You know, like I'm a data person, so what do I would do to answer that question? I'll go and read the research on that. Like, okay, there are people that. Yeah, it's like if you, if you wanna like a nerd snipe and a data scientist or like a machine learning person, just like ask them a question where they don't have the data to answer it and that's it.

Paul Shapiro: We're gone. Interesting. All right. Well, I'm going to link in the show notes on the for this episode at business for good podcast dot com. A book that my friend Jonathan Balcom wrote. It's called Superfly. And it's about the lives of flies, and I was [00:36:00] shocked by it because I, according to Jonathan, I have underestimated the mental capacities of flies, and it made me wonder what else are we perhaps underestimating.

And, I don't know what they would, like, change how I live my life, like, it's not like something like factory farming, where you can easily change how you live, relating to it, but it does make me nervous that consciousness may be more widely distributed than I had previously thought. But, because it does have implications for, you know, how much suffering there really is in the world, even if you're not the cause of the suffering, just gives you a different view of what the world is like.

Okay, I'll include that for people who want to check it out and know you may enjoy the book as well. There's a lot of data and a lot of science in there. So it will be up your alley. Perfect. Yeah. Yes. Okay. you are obviously committed to making sure that AI permeates its way through the alternative protein space.

That's why you started Green Protein AI. And you do not [00:37:00] intend, though, to perpetually be the captain of this ship. Your goal is to start this and then move on to maybe let somebody else be the captain while you will still remain in some role. And what would you do then?

Noa Weiss: Yeah, so I'll be transitioning to be the head of the advisory board and still very much a part of the mission.

But as you mentioned, not the captain. I'm actually looking to focus my time in the for profit sector. I think there's a lot of potential, in the alt protein world, as you know, as I've talked about these past 40 minutes.

Paul Shapiro: And so presumably that means joining a company that exists to help use that use AI to advance their efforts, not starting your own new company.

Yes, exactly.

Noa Weiss: Do what I do best, which is, AI and machine learning and not founding companies, which I think I did a pretty good job. But, that's that's not where I hone my skills for 13 years, you know. [00:38:00]

Paul Shapiro: Very, very much understood. And, you know, as somebody who spent actually 13 years doing public policy lobbying and then did start a company with no entrepreneurial experience, I can assure you, you know, it looks easier from the outside than it is once you actually get started.

So, I admire that you have started the nonprofit organization. I'm very much looking forward to seeing what happens when you enter into the for profit sector and who will be benefiting from From all of your expertise and speaking of your expertise, you've accumulated a lot of it. And so I'm wondering, is there any resource out there, Noah, that you think is useful, something that helped you or that you rely on even today, that helped you to get to where you are now that you would recommend for others who want to also make a difference in the world for them to check out?

Yeah,

Noa Weiss: definitely. So, as, as you know, I do a lot of different things. I have my, my hands in a lot of, different initiatives, et cetera. and [00:39:00] one of the ways that I manage to keep on top of everything, and be really productive is, it feels like such a cliche to mention it, but like the getting things done, methodology for task, task management, It's a pretty old one.

it's like the book by David Allen came out at the 80s, I think. so I don't know if I would necessarily recommend reading the book to learn more about it just because it's a bit longer than it could have been probably. But just learning about the methodology, I really think like there's a lot of task management systems out there and it's the best one that I've seen to date.

I've been using it for about 10 years. Nice. So that's one. Yeah.

Paul Shapiro: Okay. Is there more? Is there? Because you said that's one, I wanted to make sure I wasn't cutting you off. Is there a number two also

Noa Weiss: or no? Yes, yes, there's a couple more. yes. Well, I want to give your listeners all of the advice that I can.

I mean, because I think More is merrier, Noah, more is merrier. I've, I've put a lot of [00:40:00] thought and a lot of effort into the way I, really managed to get the best out of my wartime. And, you know, I see today how, for example, like our, our world is like we're constantly distracted, right? so task management is one way to deal with that, but also I really want to recommend a book, Deep Work by Cal Newport.

so also I think it's, it's quite well known, but I really, I think it gives you great tools to understand just how to use your, like, your brain power, power to the max. Thanks. And not just like the shallow work that we usually do day to day when we're constantly, like, flooded by stimuli. and the last thing is, for those, those listeners out there who, like me, believe that, a healthy body really helps you be more productive and focused.

so I really recommend anything by Dr. Michael Greger. there's the How Not to Die book, which I love. [00:41:00] And if you're a podcast fan, if you're listening to this, you probably are, then the Nutrition Facts podcast is really good. So that's also, those are my, my top recommended resources, y'all. Also,

Paul Shapiro: Very nice.

yeah, so, Michael Greger is a, longtime friend of mine for the past, 25 years or so. Is he? and I will plug his new book, which is called How Not to Age, which just came out. And I definitely recommend it. It's quite excellent. It's not about, living forever, but it is about living better into the time when you finally perish.

So it is a really great book. I highly recommend it. His other book that you mentioned, how not to die, which is a mega, mega, mega bestseller is also a bestseller for a very good reason. So. I definitely endorse, in endorses book, and I can't tell you the number of times that Bruce Friedrich from the Good Food Institute has recommended to me to read Calvin Newport's book, Deep Work, which I still haven't done.

I've listened to him on a number of interviews and so on. I've heard his talk on Ted, but I haven't actually. [00:42:00] Read the book, which I do intend to do. Maybe once I put down my phone and become less distracted, I'll, I'll, I'll,

Noa Weiss: Find an audiobook. Then you can do it when you're folding laundry. You know, that's, that's what I do for, for books, honestly.

Paul Shapiro: Very cool. Yeah, I, I, I try, you know, I, I try to maximize the efficiency of my time. And so I try to only read while walking on a treadmill. I don't like audiobooks because I can't take notes on them. Like I can't, you know, highlight or anything. And so I read digitally and I just highlight and take notes, but I like to do it on a treadmill so that I can not feel like I'm also doing something.

And then I will listen to podcasts while walking my dog Eddie. So those are those are my time efficiency recommendations. Speaking of recommendations, finally, as you know, Noah, every time I have anybody who I really admire and respect, like yourself, I want to know from them what they hope exists that doesn't exist.

Is there any company, whether for profit or non profit, that you hope somebody listening will start some initiative that they'll take on that [00:43:00] hasn't yet been done? So I

Noa Weiss: would really love to see something similar to Green Protein AI start up in the field of cultivated meat. I think there's a lot of potential there as well.

I think a lot of the cultivated meat companies, they Like their challenges are similar again, not identical, but similar, and you could work and like you could work out a mechanism in which you kind of use the data from all of them to help all of them while still keeping their IP secure. And that's something that could, could really make a dent.

Paul Shapiro: Very cool. Yeah, I would love to see that. It's so difficult. Like the, you know, trying to, work in biology as opposed to just physics is very difficult. And when you're growing cells, like there's so many variables. but the cultivated meat space still has a long way to go, and it's going to be, you know, there's no bigger cheerleader for the space than I am.

I've read a book on the topic, called Clean Meat, but, it's pretty queer to [00:44:00] me, and I think others, that it's going to be a long time before cultivated meat is making a dent in the problem of factory farming. Plant based meat has been on the market for decades, and it still is less than 1 percent of the total volume of animal meat that is being sold.

Cultivated meat is not going to be on the market in a meaningful way for years to come. the COO of upside foods was recently quoted in a, article saying that she believed that their product would be on grocery store shelves by the year 2030. and that's just on grocery store shelves, not necessarily in Walmart or Costco, right?

so. It's just, it's a very long horizon for when it's going to really start making a dent and become, let's say, even 1 percent of the total demand for meat replacement. so I'm rooting hard for the cultivated meat space, and I recognize that AI could hopefully shorten that time frame between. Now, and when it is actually going to be making a dent, in the meat, in the meat demand problem.

So I too, Noah hopes that somebody takes up, takes you up on that. And if you do, and you [00:45:00] start your own company in that space, let us know, because you would love to talk with you after you get started. And maybe you'll be on here saying how Noah Weiss inspired you to start your own company. At that point, she's going to be already deep in the extrusion or maybe even the fermentation game, making it much more efficient.

So. I'm really grateful, Noah, for everything that you're doing. Thank you for starting Green Protein AI, and I'll look forward to seeing how the organization progresses and succeeds at helping the entire field to lift all of the boats in this industry.

Noa Weiss: Thank you, Paul. It was great to be here. Thanks for having me.

Paul Shapiro: We will see each other in Israel at FoodTech Israel whenever it is rescheduled. Yes.