Podcast appearances and mentions of hayes valley

The Dutch art of Niksen. Niksen translates to "doing nothing." That's what the act is all about - relaxing, lounging around, and not doing anything. It's not even about meditating - that's doing something. It's about zoning out in complete stillness and simply existing.Everything we know about kids and phones is wrong. A study out of the University of South Florida assessed 1500 kids 11-13 and found smartphone ownership and usage, social media use, gaming, cyber-bullying, relationships, their mental health offline and more. And it turns out, kids who have their own phone scored better than kids who don't on just about every measure of well-being assessed.Things you should never share with ChatGPT. It's pretty common sense, but avoid personal info, business secrets, financial information, etc.Second Date Update: Tony and Haley met for drinks in Hayes Valley. The date went so well, he spent the night. So, why is she ghosting?

Tony and Haley met for drinks in Hayes Valley. The date went so well, he spent the night. So, why is she ghosting?

Oakland-based graphic artist Hugh D'Andrade, author of the graphic novel “The Murder Next Door,” talks about: His first graphic novel, The Murder Next Door, including what led him to finally making a graphic novel after being a big fan of them for a long time; studying fine art at the California College of Arts and Crafts back in the 1980s, and then going back to the same school, now called simply California College of the Arts, to get a masters in graphic novels; graphic novelists who have been influential to Hugh, including Adrian Tomine from nearby Berkeley, Chris Ware, who he refers to as both a giant and a genius in the field, as well Art Spiegelman, Thi Bui (whom he had as one of his graphic novel professors), Marjane Satrapi, and Phoebe Glockner; how the graphic novelists he's met have generally been very talkative and have quirky sensibilities, but also have introverted streaks which are necessary for long stretches alone that are necessary for producing their work; how he worked on the beginning of his graphic novel while in grad school, where the crits were very nurturing and supportive, unlike crits from back in the day (undergrad); where graphic novel reading falls in our attention economy; the value he puts on the hand-drawn in comics, with modest digital intervention; and how Vipassana meditation, the first chapter of the book, played a big role in Hugh's healing journey…. [the Conversation continues for another hour in the BONUS episode for Patreon supporters] In the 2nd half of the full conversation (available to Patreon supporters), Hugh talks about: the distinction between cartooning and illustration, and how challenging it is to render a person from multiple views in that style; what feedback he's gotten so far, with at least one reader saying that it was ‘very unique,' probably meaning they found it too dark; the roll his parents played (or didn't play) in healing from his trauma (the murder the book is focused on); his trolling of conspiracy theorists on social media (which is described in the book), which came out of his reaction to people making things up about who was responsible for the murder, along with the pros and cons of engaging with a conspiracy theorist; his description of 3 or 4 major career trajectory paths for artists in big art capitals, inspired by his nephew and students and their impending career paths- the A path/A-train: rock star; B path/B train: you have a partner who has a job/supports you financially;  C path/train: artist with a day job;  D-train: you live just outside of a major city, or in a college town, or rural areas; housing in the U.S., particularly in the art capitals (a sort of passion of both of ours) and how he bought a house in East Oakland, a part of the city he had never been in and he'd been living in the East Bay for decades; how he's in a ‘coffee dessert,' meaning he needs to drive at least 10 minutes to get to a good coffee spot, leading to a beautiful paradox: as a participant in gentrifying his neighborhood, he realizes that as soon as that fancy coffee place pops up in his neighborhood, the gentrification will essentially be complete; the neighborhoods Hugh lived in in San Francisco, particularly the Mission, Hayes Valley and the Tenderloin, and their respective reputations and what he experienced living there as an older young person going to punk shows and the like; his friend Rebecca Solnit's book Hollow City, about how gentrification displaces people of color as well as creative communities; we dig quite a bit into the weeds of the housing crisis, and how he lived on the cheap in the Bay Area for years, including getting around by bike up until 10 years ago; and finally he talks about his music show highlights over the years, including his changing relationship to the Grateful Dead over the decades. 

Applications close Monday for the NYC AI Engineer Summit focusing on AI Leadership and Agent Engineering! If you applied, invites should be rolling out shortly.The search landscape is experiencing a fundamental shift. Google built a >$2T company with the “10 blue links” experience, driven by PageRank as the core innovation for ranking. This was a big improvement from the previous directory-based experiences of AltaVista and Yahoo. Almost 4 decades later, Google is now stuck in this links-based experience, especially from a business model perspective. This legacy architecture creates fundamental constraints:* Must return results in ~400 milliseconds* Required to maintain comprehensive web coverage* Tied to keyword-based matching algorithms* Cost structures optimized for traditional indexingAs we move from the era of links to the era of answers, the way search works is changing. You're not showing a user links, but the goal is to provide context to an LLM. This means moving from keyword based search to more semantic understanding of the content:The link prediction objective can be seen as like a neural PageRank because what you're doing is you're predicting the links people share... but it's more powerful than PageRank. It's strictly more powerful because people might refer to that Paul Graham fundraising essay in like a thousand different ways. And so our model learns all the different ways.All of this is now powered by a $5M cluster with 144 H200s:This architectural choice enables entirely new search capabilities:* Comprehensive result sets instead of approximations* Deep semantic understanding of queries* Ability to process complex, natural language requestsAs search becomes more complex, time to results becomes a variable:People think of searches as like, oh, it takes 500 milliseconds because we've been conditioned... But what if searches can take like a minute or 10 minutes or a whole day, what can you then do?Unlike traditional search engines' fixed-cost indexing, Exa employs a hybrid approach:* Front-loaded compute for indexing and embeddings* Variable inference costs based on query complexity* Mix of owned infrastructure ($5M H200 cluster) and cloud resourcesExa sees a lot of competition from products like Perplexity and ChatGPT Search which layer AI on top of traditional search backends, but Exa is betting that true innovation requires rethinking search from the ground up. For example, the recently launched Websets, a way to turn searches into structured output in grid format, allowing you to create lists and databases out of web pages. The company raised a $17M Series A to build towards this mission, so keep an eye out for them in 2025. Chapters* 00:00:00 Introductions* 00:01:12 ExaAI's initial pitch and concept* 00:02:33 Will's background at SpaceX and Zoox* 00:03:45 Evolution of ExaAI (formerly Metaphor Systems)* 00:05:38 Exa's link prediction technology* 00:09:20 Meaning of the name "Exa"* 00:10:36 ExaAI's new product launch and capabilities* 00:13:33 Compute budgets and variable compute products* 00:14:43 Websets as a B2B offering* 00:19:28 How do you build a search engine?* 00:22:43 What is Neural PageRank?* 00:27:58 Exa use cases * 00:35:00 Auto-prompting* 00:38:42 Building agentic search* 00:44:19 Is o1 on the path to AGI?* 00:49:59 Company culture and nap pods* 00:54:52 Economics of AI search and the future of search technologyFull YouTube TranscriptPlease like and subscribe!Show Notes* ExaAI* Web Search Product* Websets* Series A Announcement* Exa Nap Pods* Perplexity AI* Character.AITranscriptAlessio [00:00:00]: Hey, everyone. Welcome to the Latent Space podcast. This is Alessio, partner and CTO at Decibel Partners, and I'm joined by my co-host Swyx, founder of Smol.ai.Swyx [00:00:10]: Hey, and today we're in the studio with my good friend and former landlord, Will Bryk. Roommate. How you doing? Will, you're now CEO co-founder of ExaAI, used to be Metaphor Systems. What's your background, your story?Will [00:00:30]: Yeah, sure. So, yeah, I'm CEO of Exa. I've been doing it for three years. I guess I've always been interested in search, whether I knew it or not. Like, since I was a kid, I've always been interested in, like, high-quality information. And, like, you know, even in high school, wanted to improve the way we get information from news. And then in college, built a mini search engine. And then with Exa, like, you know, it's kind of like fulfilling the dream of actually being able to solve all the information needs I wanted as a kid. Yeah, I guess. I would say my entire life has kind of been rotating around this problem, which is pretty cool. Yeah.Swyx [00:00:50]: What'd you enter YC with?Will [00:00:53]: We entered YC with, uh, we are better than Google. Like, Google 2.0.Swyx [00:01:12]: What makes you say that? Like, that's so audacious to come out of the box with.Will [00:01:16]: Yeah, okay, so you have to remember the time. This was summer 2021. And, uh, GPT-3 had come out. Like, here was this magical thing that you could talk to, you could enter a whole paragraph, and it understands what you mean, understands the subtlety of your language. And then there was Google. Uh, which felt like it hadn't changed in a decade, uh, because it really hadn't. And it, like, you would give it a simple query, like, I don't know, uh, shirts without stripes, and it would give you a bunch of results for the shirts with stripes. And so, like, Google could barely understand you, and GBD3 could. And the theory was, what if you could make a search engine that actually understood you? What if you could apply the insights from LLMs to a search engine? And it's really been the same idea ever since. And we're actually a lot closer now, uh, to doing that. Yeah.Alessio [00:01:55]: Did you have any trouble making people believe? Obviously, there's the same element. I mean, YC overlap, was YC pretty AI forward, even 2021, or?Will [00:02:03]: It's nothing like it is today. But, um, uh, there were a few AI companies, but, uh, we were definitely, like, bold. And I think people, VCs generally like boldness, and we definitely had some AI background, and we had a working demo. So there was evidence that we could build something that was going to work. But yeah, I think, like, the fundamentals were there. I think people at the time were talking about how, you know, Google was failing in a lot of ways. And so there was a bit of conversation about it, but AI was not a big, big thing at the time. Yeah. Yeah.Alessio [00:02:33]: Before we jump into Exa, any fun background stories? I know you interned at SpaceX, any Elon, uh, stories? I know you were at Zoox as well, you know, kind of like robotics at Harvard. Any stuff that you saw early that you thought was going to get solved that maybe it's not solved today?Will [00:02:48]: Oh yeah. I mean, lots of things like that. Like, uh, I never really learned how to drive because I believed Elon that self-driving cars would happen. It did happen. And I take them every night to get home. But it took like 10 more years than I thought. Do you still not know how to drive? I know how to drive now. I learned it like two years ago. That would have been great to like, just, you know, Yeah, yeah, yeah. You know? Um, I was obsessed with Elon. Yeah. I mean, I worked at SpaceX because I really just wanted to work at one of his companies. And I remember they had a rule, like interns cannot touch Elon. And, um, that rule actually influenced my actions.Swyx [00:03:18]: Is it, can Elon touch interns? Ooh, like physically?Will [00:03:22]: Or like talk? Physically, physically, yeah, yeah, yeah, yeah. Okay, interesting. He's changed a lot, but, um, I mean, his companies are amazing. Um,Swyx [00:03:28]: What if you beat him at Diablo 2, Diablo 4, you know, like, Ah, maybe.Alessio [00:03:34]: I want to jump into, I know there's a lot of backstory used to be called metaphor system. So, um, and it, you've always been kind of like a prominent company, maybe at least RAI circles in the NSF.Swyx [00:03:45]: I'm actually curious how Metaphor got its initial aura. You launched with like, very little. We launched very little. Like there was, there was this like big splash image of like, this is Aurora or something. Yeah. Right. And then I was like, okay, what this thing, like the vibes are good, but I don't know what it is. And I think, I think it was much more sort of maybe consumer facing than what you are today. Would you say that's true?Will [00:04:06]: No, it's always been about building a better search algorithm, like search, like, just like the vision has always been perfect search. And if you do that, uh, we will figure out the downstream use cases later. It started on this fundamental belief that you could have perfect search over the web and we could talk about what that means. And like the initial thing we released was really just like our first search engine, like trying to get it out there. Kind of like, you know, an open source. So when OpenAI released, uh, ChachBt, like they didn't, I don't know how, how much of a game plan they had. They kind of just wanted to get something out there.Swyx [00:04:33]: Spooky research preview.Will [00:04:34]: Yeah, exactly. And it kind of morphed from a research company to a product company at that point. And I think similarly for us, like we were research, we started as a research endeavor with a, you know, clear eyes that like, if we succeed, it will be a massive business to make out of it. And that's kind of basically what happened. I think there are actually a lot of parallels to, of w between Exa and OpenAI. I often say we're the OpenAI of search. Um, because. Because we're a research company, we're a research startup that does like fundamental research into, uh, making like AGI for search in a, in a way. Uh, and then we have all these like, uh, business products that come out of that.Swyx [00:05:08]: Interesting. I want to ask a little bit more about Metaforesight and then we can go full Exa. When I first met you, which was really funny, cause like literally I stayed in your house in a very historic, uh, Hayes, Hayes Valley place. You said you were building sort of like link prediction foundation model, and I think there's still a lot of foundation model work. I mean, within Exa today, but what does that even mean? I cannot be the only person confused by that because like there's a limited vocabulary or tokens you're telling me, like the tokens are the links or, you know, like it's not, it's not clear. Yeah.Will [00:05:38]: Uh, what we meant by link prediction is that you are literally predicting, like given some texts, you're predicting the links that follow. Yes. That refers to like, it's how we describe the training procedure, which is that we find links on the web. Uh, we take the text surrounding the link. And then we predict. Which link follows you, like, uh, you know, similar to transformers where, uh, you're trying to predict the next token here, you're trying to predict the next link. And so you kind of like hide the link from the transformer. So if someone writes, you know, imagine some article where someone says, Hey, check out this really cool aerospace startup. And they, they say spacex.com afterwards, uh, we hide the spacex.com and ask the model, like what link came next. And by doing that many, many times, you know, billions of times, you could actually build a search engine out of that because then, uh, at query time at search time. Uh, you type in, uh, a query that's like really cool aerospace startup and the model will then try to predict what are the most likely links. So there's a lot of analogs to transformers, but like to actually make this work, it does require like a different architecture than, but it's transformer inspired. Yeah.Alessio [00:06:41]: What's the design decision between doing that versus extracting the link and the description and then embedding the description and then using, um, yeah. What do you need to predict the URL versus like just describing, because you're kind of do a similar thing in a way. Right. It's kind of like based on this description, it was like the closest link for it. So one thing is like predicting the link. The other approach is like I extract the link and the description, and then based on the query, I searched the closest description to it more. Yeah.Will [00:07:09]: That, that, by the way, that is, that is the link refers here to a document. It's not, I think one confusing thing is it's not, you're not actually predicting the URL, the URL itself that would require like the, the system to have memorized URLs. You're actually like getting the actual document, a more accurate name could be document prediction. I see. This was the initial like base model that Exo was trained on, but we've moved beyond that similar to like how, you know, uh, to train a really good like language model, you might start with this like self-supervised objective of predicting the next token and then, uh, just from random stuff on the web. But then you, you want to, uh, add a bunch of like synthetic data and like supervised fine tuning, um, stuff like that to make it really like controllable and robust. Yeah.Alessio [00:07:48]: Yeah. We just have flow from Lindy and, uh, their Lindy started to like hallucinate recrolling YouTube links instead of like, uh, something. Yeah. Support guide. So. Oh, interesting. Yeah.Swyx [00:07:57]: So round about January, you announced your series A and renamed to Exo. I didn't like the name at the, at the initial, but it's grown on me. I liked metaphor, but apparently people can spell metaphor. What would you say are the major components of Exo today? Right? Like, I feel like it used to be very model heavy. Then at the AI engineer conference, Shreyas gave a really good talk on the vector database that you guys have. What are the other major moving parts of Exo? Okay.Will [00:08:23]: So Exo overall is a search engine. Yeah. We're trying to make it like a perfect search engine. And to do that, you have to build lots of, and we're doing it from scratch, right? So to do that, you have to build lots of different. The crawler. Yeah. You have to crawl a bunch of the web. First of all, you have to find the URLs to crawl. Uh, it's connected to the crawler, but yeah, you find URLs, you crawl those URLs. Then you have to process them with some, you know, it could be an embedding model. It could be something more complex, but you need to take, you know, or like, you know, in the past it was like a keyword inverted index. Like you would process all these documents you gather into some processed index, and then you have to serve that. Uh, you had high throughput at low latency. And so that, and that's like the vector database. And so it's like the crawling system, the AI processing system, and then the serving system. Those are all like, you know, teams of like hundreds, maybe thousands of people at Google. Um, but for us, it's like one or two people each typically, but yeah.Alessio [00:09:13]: Can you explain the meaning of, uh, Exo, just the story 10 to the 16th, uh, 18, 18.Will [00:09:20]: Yeah, yeah, yeah, sure. So. Exo means 10 to the 18th, which is in stark contrast to. To Google, which is 10 to the hundredth. Uh, we actually have these like awesome shirts that are like 10th to 18th is greater than 10th to the hundredth. Yeah, it's great. And it's great because it's provocative. It's like every engineer in Silicon Valley is like, what? No, it's not true. Um, like, yeah. And, uh, and then you, you ask them, okay, what does it actually mean? And like the creative ones will, will recognize it. But yeah, I mean, 10 to the 18th is better than 10 to the hundredth when it comes to search, because with search, you want like the actual list of, of things that match what you're asking for. You don't want like the whole web. You want to basically with search filter, the, like everything that humanity has ever created to exactly what you want. And so the idea is like smaller is better there. You want like the best 10th to the 18th and not the 10th to the hundredth. I'm like, one way to say this is like, you know how Google often says at the top, uh, like, you know, 30 million results found. And it's like crazy. Cause you're looking for like the first startups in San Francisco that work on hardware or something. And like, they're not 30 million results like that. What you want is like 325 results found. And those are all the results. That's what you really want with search. And that's, that's our vision. It's like, it just gives you. Perfectly what you asked for.Swyx [00:10:24]: We're recording this ahead of your launch. Uh, we haven't released, we haven't figured out the, the, the name of the launch yet, but what is the product that you're launching? I guess now that we're coinciding this podcast with. Yeah.Will [00:10:36]: So we've basically developed the next version of Exa, which is the ability to get a near perfect list of results of whatever you want. And what that means is you can make a complex query now to Exa, for example, startups working on hardware in SF, and then just get a huge list of all the things that match. And, you know, our goal is if there are 325 startups that match that we find you all of them. And this is just like, there's just like a new experience that's never existed before. It's really like, I don't know how you would go about that right now with current tools and you can apply this same type of like technology to anything. Like, let's say you want, uh, you want to find all the blog posts that talk about Alessio's podcast, um, that have come out in the past year. That is 30 million results. Yeah. Right.Will [00:11:24]: But that, I mean, that would, I'm sure that would be extremely useful to you guys. And like, I don't really know how you would get that full comprehensive list.Swyx [00:11:29]: I just like, how do you, well, there's so many questions with regards to how do you know it's complete, right? Cause you're saying there's only 30 million, 325, whatever. And then how do you do the semantic understanding that it might take, right? So working in hardware, like I might not use the words hardware. I might use the words robotics. I might use the words wearables. I might use like whatever. Yes. So yeah, just tell us more. Yeah. Yeah. Sure. Sure.Will [00:11:53]: So one aspect of this, it's a little subjective. So like certainly providing, you know, at some point we'll provide parameters to the user to like, you know, some sort of threshold to like, uh, gauge like, okay, like this is a cutoff. Like, this is actually not what I mean, because sometimes it's subjective and there needs to be a feedback loop. Like, oh, like it might give you like a few examples and you say, yeah, exactly. And so like, you're, you're kind of like creating a classifier on the fly, but like, that's ultimately how you solve the problem. So the subject, there's a subjectivity problem and then there's a comprehensiveness problem. Those are two different problems. So. Yeah. So you have the comprehensiveness problem. What you basically have to do is you have to put more compute into the query, into the search until you get the full comprehensiveness. Yeah. And I think there's an interesting point here, which is that not all queries are made equal. Some queries just like this blog post one might require scanning, like scavenging, like throughout the whole web in a way that just, just simply requires more compute. You know, at some point there's some amount of compute where you will just be comprehensive. You could imagine, for example, running GPT-4 over the internet. You could imagine running GPT-4 over the entire web and saying like, is this a blog post about Alessio's podcast, like, is this a blog post about Alessio's podcast? And then that would work, right? It would take, you know, a year, maybe cost like a million dollars, but, or many more, but, um, it would work. Uh, the point is that like, given sufficient compute, you can solve the query. And so it's really a question of like, how comprehensive do you want it given your compute budget? I think it's very similar to O1, by the way. And one way of thinking about what we built is like O1 for search, uh, because O1 is all about like, you know, some, some, some questions require more compute than others, and we'll put as much compute into the question as we need to solve it. So similarly with our search, we will put as much compute into the query in order to get comprehensiveness. Yeah.Swyx [00:13:33]: Does that mean you have like some kind of compute budget that I can specify? Yes. Yes. Okay. And like, what are the upper and lower bounds?Will [00:13:42]: Yeah, there's something we're still figuring out. I think like, like everyone is a new paradigm of like variable compute products. Yeah. How do you specify the amount of compute? Like what happens when you. Run out? Do you just like, ah, do you, can you like keep going with it? Like, do you just put in more credits to get more, um, for some, like this can get complex at like the really large compute queries. And like, one thing we do is we give you a preview of what you're going to get, and then you could then spin up like a much larger job, uh, to get like way more results. But yes, there is some compute limit, um, at, at least right now. Yeah. People think of searches as like, oh, it takes 500 milliseconds because we've been conditioned, uh, to have search that takes 500 milliseconds. But like search engines like Google, right. No matter how complex your query to Google, it will take like, you know, roughly 400 milliseconds. But what if searches can take like a minute or 10 minutes or a whole day, what can you then do? And you can do very powerful things. Um, you know, you can imagine, you know, writing a search, going and get a cup of coffee, coming back and you have a perfect list. Like that's okay for a lot of use cases. Yeah.Alessio [00:14:43]: Yeah. I mean, the use case closest to me is venture capital, right? So, uh, no, I mean, eight years ago, I built one of the first like data driven sourcing platforms. So we were. You look at GitHub, Twitter, Product Hunt, all these things, look at interesting things, evaluate them. If you think about some jobs that people have, it's like literally just make a list. If you're like an analyst at a venture firm, your job is to make a list of interesting companies. And then you reach out to them. How do you think about being infrastructure versus like a product you could say, Hey, this is like a product to find companies. This is a product to find things versus like offering more as a blank canvas that people can build on top of. Oh, right. Right.Will [00:15:20]: Uh, we are. We are a search infrastructure company. So we want people to build, uh, on top of us, uh, build amazing products on top of us. But with this one, we try to build something that makes it really easy for users to just log in, put a few, you know, put some credits in and just get like amazing results right away and not have to wait to build some API integration. So we're kind of doing both. Uh, we, we want, we want people to integrate this into all their applications at the same time. We want to just make it really easy to use very similar again to open AI. Like they'll have, they have an API, but they also have. Like a ChatGPT interface so that you could, it's really easy to use, but you could also build it in your applications. Yeah.Alessio [00:15:56]: I'm still trying to wrap my head around a lot of the implications. So, so many businesses run on like information arbitrage, you know, like I know this thing that you don't, especially in investment and financial services. So yeah, now all of a sudden you have these tools for like, oh, actually everybody can get the same information at the same time, the same quality level as an API call. You know, it just kind of changes a lot of things. Yeah.Will [00:16:19]: I think, I think what we're grappling with here. What, what you're just thinking about is like, what is the world like if knowledge is kind of solved, if like any knowledge request you want is just like right there on your computer, it's kind of different from when intelligence is solved. There's like a good, I've written before about like a different super intelligence, super knowledge. Yeah. Like I think that the, the distinction between intelligence and knowledge is actually a pretty good one. They're definitely connected and related in all sorts of ways, but there is a distinction. You could have a world and we are going to have this world where you have like GP five level systems and beyond that could like answer any complex request. Um, unless it requires some. Like, if you say like, uh, you know, give me a list of all the PhDs in New York city who, I don't know, have thought about search before. And even though this, this super intelligence is going to be like, I can't find it on Google, right. Which is kind of crazy. Like we're literally going to have like super intelligences that are using Google. And so if Google can't find them information, there's nothing they could do. They can't find it. So, but if you also have a super knowledge system where it's like, you know, I'm calling this term super knowledge where you just get whatever knowledge you want, then you can pair with a super intelligence system. And then the super intelligence can, we'll never. Be blocked by lack of knowledge.Alessio [00:17:23]: Yeah. You told me this, uh, when we had lunch, I forget how it came out, but we were talking about AGI and whatnot. And you were like, even AGI is going to need search. Yeah.Swyx [00:17:32]: Yeah. Right. Yeah. Um, so we're actually referencing a blog post that you wrote super intelligence and super knowledge. Uh, so I would refer people to that. And this is actually a discussion we've had on the podcast a couple of times. Um, there's so much of model weights that are just memorizing facts. Some of the, some of those might be outdated. Some of them are incomplete or not. Yeah. So like you just need search. So I do wonder, like, is there a maximum language model size that will be the intelligence layer and then the rest is just search, right? Like maybe we should just always use search. And then that sort of workhorse model is just like, and it like, like, like one B or three B parameter model that just drives everything. Yes.Will [00:18:13]: I believe this is a much more optimal system to have a smaller LM. That's really just like an intelligence module. And it makes a call to a search. Tool that's way more efficient because if, okay, I mean the, the opposite of that would be like the LM is so big that can memorize the whole web. That would be like way, but you know, it's not practical at all. I don't, it's not possible to train that at least right now. And Carpathy has actually written about this, how like he could, he could see models moving more and more towards like intelligence modules using various tools. Yeah.Swyx [00:18:39]: So for listeners, that's the, that was him on the no priors podcast. And for us, we talked about this and the, on the Shin Yu and Harrison chase podcasts. I'm doing search in my head. I told you 30 million results. I forgot about our neural link integration. Self-hosted exit.Will [00:18:54]: Yeah. Yeah. No, I do see that that is a much more, much more efficient world. Yeah. I mean, you could also have GB four level systems calling search, but it's just because of the cost of inference. It's just better to have a very efficient search tool and a very efficient LM and they're built for different things. Yeah.Swyx [00:19:09]: I'm just kind of curious. Like it is still something so audacious that I don't want to elide, which is you're, you're, you're building a search engine. Where do you start? How do you, like, are there any reference papers or implementation? That would really influence your thinking, anything like that? Because I don't even know where to start apart from just crawl a bunch of s**t, but there's gotta be more insight than that.Will [00:19:28]: I mean, yeah, there's more insight, but I'm always surprised by like, if you have a group of people who are really focused on solving a problem, um, with the tools today, like there's some in, in software, like there are all sorts of creative solutions that just haven't been thought of before, particularly in the information retrieval field. Yeah. I think a lot of the techniques are just very old, frankly. Like I know how Google and Bing work and. They're just not using new methods. There are all sorts of reasons for that. Like one, like Google has to be comprehensive over the web. So they're, and they have to return in 400 milliseconds. And those two things combined means they are kind of limit and it can't cost too much. They're kind of limited in, uh, what kinds of algorithms they could even deploy at scale. So they end up using like a limited keyword based algorithm. Also like Google was built in a time where like in, you know, in 1998, where we didn't have LMS, we didn't have embeddings. And so they never thought to build those things. And so now they have this like gigantic system that is built on old technology. Yeah. And so a lot of the information retrieval field we found just like thinks in terms of that framework. Yeah. Whereas we came in as like newcomers just thinking like, okay, there here's GB three. It's magical. Obviously we're going to build search that is using that technology. And we never even thought about using keywords really ever. Uh, like we were neural all the way we're building an end to end neural search engine. And just that whole framing just makes us ask different questions, like pursue different lines of work. And there's just a lot of low hanging fruit because no one else is thinking about it. We're just on the frontier of neural search. We just are, um, for, for at web scale, um, because there's just not a lot of people thinking that way about it.Swyx [00:20:57]: Yeah. Maybe let's spell this out since, uh, we're already on this topic, elephants in the room are Perplexity and SearchGPT. That's the, I think that it's all, it's no longer called SearchGPT. I think they call it ChatGPT Search. How would you contrast your approaches to them based on what we know of how they work and yeah, just any, anything in that, in that area? Yeah.Will [00:21:15]: So these systems, there are a few of them now, uh, they basically rely on like traditional search engines like Google or Bing, and then they combine them with like LLMs at the end to, you know, output some power graphics, uh, answering your question. So they like search GPT perplexity. I think they have their own crawlers. No. So there's this important distinction between like having your own search system and like having your own cache of the web. Like for example, so you could create, you could crawl a bunch of the web. Imagine you crawl a hundred billion URLs, and then you create a key value store of like mapping from URL to the document that is technically called an index, but it's not a search algorithm. So then to actually like, when you make a query to search GPT, for example, what is it actually doing it? Let's say it's, it's, it could, it's using the Bing API, uh, getting a list of results and then it could go, it has this cache of like all the contents of those results and then could like bring in the cache, like the index cache, but it's not actually like, it's not like they've built a search engine from scratch over, you know, hundreds of billions of pages. It's like, does that distinction clear? It's like, yeah, you could have like a mapping from URL to documents, but then rely on traditional search engines to actually get the list of results because it's a very hard problem to take. It's not hard. It's not hard to use DynamoDB and, and, and map URLs to documents. It's a very hard problem to take a hundred billion or more documents and given a query, like instantly get the list of results that match. That's a much harder problem that very few entities on, in, on the planet have done. Like there's Google, there's Bing, uh, you know, there's Yandex, but you know, there are not that many companies that are, that are crazy enough to actually build their search engine from scratch when you could just use traditional search APIs.Alessio [00:22:43]: So Google had PageRank as like the big thing. Is there a LLM equivalent or like any. Stuff that you're working on that you want to highlight?Will [00:22:51]: The link prediction objective can be seen as like a neural PageRank because what you're doing is you're predicting the links people share. And so if everyone is sharing some Paul Graham essay about fundraising, then like our model is more likely to predict it. So like inherent in our training objective is this, uh, a sense of like high canonicity and like high quality, but it's more powerful than PageRank. It's strictly more powerful because people might refer to that Paul Graham fundraising essay in like a thousand different ways. And so our model learns all the different ways. That someone refers that Paul Graham, I say, while also learning how important that Paul Graham essay is. Um, so it's like, it's like PageRank on steroids kind of thing. Yeah.Alessio [00:23:26]: I think to me, that's the most interesting thing about search today, like with Google and whatnot, it's like, it's mostly like domain authority. So like if you get back playing, like if you search any AI term, you get this like SEO slop websites with like a bunch of things in them. So this is interesting, but then how do you think about more timeless maybe content? So if you think about, yeah. You know, maybe the founder mode essay, right. It gets shared by like a lot of people, but then you might have a lot of other essays that are also good, but they just don't really get a lot of traction. Even though maybe the people that share them are high quality. How do you kind of solve that thing when you don't have the people authority, so to speak of who's sharing, whether or not they're worth kind of like bumping up? Yeah.Will [00:24:10]: I mean, you do have a lot of control over the training data, so you could like make sure that the training data contains like high quality sources so that, okay. Like if you, if you're. Training data, I mean, it's very similar to like language, language model training. Like if you train on like a bunch of crap, your prediction will be crap. Our model will match the training distribution is trained on. And so we could like, there are lots of ways to tweak the training data to refer to high quality content that we want. Yeah. I would say also this, like this slop that is returned by, by traditional search engines, like Google and Bing, you have the slop is then, uh, transferred into the, these LLMs in like a search GBT or, you know, our other systems like that. Like if slop comes in, slop will go out. And so, yeah, that's another answer to how we're different is like, we're not like traditional search engines. We want to give like the highest quality results and like have full control over whatever you want. If you don't want slop, you get that. And then if you put an LM on top of that, which our customers do, then you just get higher quality results or high quality output.Alessio [00:25:06]: And I use Excel search very often and it's very good. Especially.Swyx [00:25:09]: Wave uses it too.Alessio [00:25:10]: Yeah. Yeah. Yeah. Yeah. Yeah. Like the slop is everywhere, especially when it comes to AI, when it comes to investment. When it comes to all of these things for like, it's valuable to be at the top. And this problem is only going to get worse because. Yeah, no, it's totally. What else is in the toolkit? So you have search API, you have ExaSearch, kind of like the web version. Now you have the list builder. I think you also have web scraping. Maybe just touch on that. Like, I guess maybe people, they want to search and then they want to scrape. Right. So is that kind of the use case that people have? Yeah.Will [00:25:41]: A lot of our customers, they don't just want, because they're building AI applications on top of Exa, they don't just want a list of URLs. They actually want. Like the full content, like cleans, parsed. Markdown. Markdown, maybe chunked, whatever they want, we'll give it to them. And so that's been like huge for customers. Just like getting the URLs and instantly getting the content for each URL is like, and you can do this for 10 or 100 or 1,000 URLs, wherever you want. That's very powerful.Swyx [00:26:05]: Yeah. I think this is the first thing I asked you for when I tried using Exa.Will [00:26:09]: Funny story is like when I built the first version of Exa, it's like, we just happened to store the content. Yes. Like the first 1,024 tokens. Because I just kind of like kept it because I thought of, you know, I don't know why. Really for debugging purposes. And so then when people started asking for content, it was actually pretty easy to serve it. But then, and then we did that, like Exa took off. So the computer's content was so useful. So that was kind of cool.Swyx [00:26:30]: It is. I would say there are other players like Gina, I think is in this space. Firecrawl is in this space. There's a bunch of scraper companies. And obviously scraper is just one part of your stack, but you might as well offer it since you already do it.Will [00:26:43]: Yeah, it makes sense. It's just easy to have an all-in-one solution. And like. We are, you know, building the best scraper in the world. So scraping is a hard problem and it's easy to get like, you know, a good scraper. It's very hard to get a great scraper and it's super hard to get a perfect scraper. So like, and, and scraping really matters to people. Do you have a perfect scraper? Not yet. Okay.Swyx [00:27:05]: The web is increasingly closing to the bots and the scrapers, Twitter, Reddit, Quora, Stack Overflow. I don't know what else. How are you dealing with that? How are you navigating those things? Like, you know. You know, opening your eyes, like just paying them money.Will [00:27:19]: Yeah, no, I mean, I think it definitely makes it harder for search engines. One response is just that there's so much value in the long tail of sites that are open. Okay. Um, and just like, even just searching over those well gets you most of the value. But I mean, there, there is definitely a lot of content that is increasingly not unavailable. And so you could get through that through data partnerships. The bigger we get as a company, the more, the easier it is to just like, uh, make partnerships. But I, I mean, I do see the world as like the future where the. The data, the, the data producers, the content creators will make partnerships with the entities that find that data.Alessio [00:27:53]: Any other fun use case that maybe people are not thinking about? Yeah.Will [00:27:58]: Oh, I mean, uh, there are so many customers. Yeah. What are people doing on AXA? Well, I think dating is a really interesting, uh, application of search that is completely underserved because there's a lot of profiles on the web and a lot of people who want to find love and that I'll use it. They give me. Like, you know, age boundaries, you know, education level location. Yeah. I mean, you want to, what, what do you want to do with data? You want to find like a partner who matches this education level, who like, you know, maybe has written about these types of topics before. Like if you could get a list of all the people like that, like, I think you will unblock a lot of people. I mean, there, I mean, I think this is a very Silicon Valley view of dating for sure. And I'm, I'm well aware of that, but it's just an interesting application of like, you know, I would love to meet like an intellectual partner, um, who like shares a lot of ideas. Yeah. Like if you could do that through better search and yeah.Swyx [00:28:48]: But what is it with Jeff? Jeff has already set me up with a few people. So like Jeff, I think it's my personal exit.Will [00:28:55]: my mom's actually a matchmaker and has got a lot of married. Yeah. No kidding. Yeah. Yeah. Search is built into the book. It's in your jeans. Yeah. Yeah.Swyx [00:29:02]: Yeah. Other than dating, like I know you're having quite some success in colleges. I would just love to map out some more use cases so that our listeners can just use those examples to think about use cases for XR, right? Because it's such a general technology that it's hard to. Uh, really pin down, like, what should I use it for and what kind of products can I build with it?Will [00:29:20]: Yeah, sure. So, I mean, there are so many applications of XR and we have, you know, many, many companies using us for very diverse range of use cases, but I'll just highlight some interesting ones. Like one customer, a big customer is using us to, um, basically build like a, a writing assistant for students who want to write, uh, research papers. And basically like XR will search for, uh, like a list of research papers related to what the student is writing. And then this product has. Has like an LLM that like summarizes the papers to basically it's like a next word prediction, but in, uh, you know, prompted by like, you know, 20 research papers that X has returned. It's like literally just doing their homework for them. Yeah. Yeah. the key point is like, it's, it's, uh, you know, it's, it's, you know, research is, is a really hard thing to do and you need like high quality content as input.Swyx [00:30:08]: Oh, so we've had illicit on the podcast. I think it's pretty similar. Uh, they, they do focus pretty much on just, just research papers and, and that research. Basically, I think dating, uh, research, like I just wanted to like spell out more things, like just the big verticals.Will [00:30:23]: Yeah, yeah, no, I mean, there, there are so many use cases. So finance we talked about, yeah. I mean, one big vertical is just finding a list of companies, uh, so it's useful for VCs, like you said, who want to find like a list of competitors to a specific company they're investigating or just a list of companies in some field. Like, uh, there was one VC that told me that him and his team, like we're using XR for like eight hours straight. Like, like that. For many days on end, just like, like, uh, doing like lots of different queries of different types, like, oh, like all the companies in AI for law or, uh, all the companies for AI for, uh, construction and just like getting lists of things because you just can't find this information with, with traditional search engines. And then, you know, finding companies is also useful for, for selling. If you want to find, you know, like if we want to find a list of, uh, writing assistants to sell to, then we can just, we just use XR ourselves to find that is actually how we found a lot of our customers. Ooh, you can find your own customers using XR. Oh my God. I, in the spirit of. Uh, using XR to bolster XR, like recruiting is really helpful. It is really great use case of XR, um, because we can just get like a list of, you know, people who thought about search and just get like a long list and then, you know, reach out to those people.Swyx [00:31:29]: When you say thought about, are you, are you thinking LinkedIn, Twitter, or are you thinking just blogs?Will [00:31:33]: Or they've written, I mean, it's pretty general. So in that case, like ideally XR would return like the, the really blogs written by people who have just. So if I don't blog, I don't show up to XR, right? Like I have to blog. well, I mean, you could show up. That's like an incentive for people to blog.Swyx [00:31:47]: Well, if you've written about, uh, search in on Twitter and we, we do, we do index a bunch of tweets and then we, we should be able to service that. Yeah. Um, I mean, this is something I tell people, like you have to make yourself discoverable to the web, uh, you know, it's called learning in public, but like, it's even more imperative now because otherwise you don't exist at all.Will [00:32:07]: Yeah, no, no, this is a huge, uh, thing, which is like search engines completely influence. They have downstream effects. They influence the internet itself. They influence what people. Choose to create. And so Google, because they're a keyword based search engine, people like kind of like keyword stuff. Yeah. They're, they're, they're incentivized to create things that just match a lot of keywords, which is not very high quality. Uh, whereas XR is a search algorithm that, uh, optimizes for like high quality and actually like matching what you mean. And so people are incentivized to create content that is high quality, that like the create content that they know will be found by the right person. So like, you know, if I am a search researcher and I want to be found. By XR, I should blog about search and all the things I'm building because, because now we have a search engine like XR that's powerful enough to find them. And so the search engine will influence like the downstream internet in all sorts of amazing ways. Yeah. Uh, whatever the search engine optimizes for is what the internet looks like. Yeah.Swyx [00:33:01]: Are you familiar with the term? McLuhanism? No, it's not. Uh, it's this concept that, uh, like first we shape tools and then the tools shape us. Okay. Yeah. Uh, so there's like this reflexive connection between the things we search for and the things that get searched. Yes. So like once you change the tool. The tool that searches the, the, the things that get searched also change. Yes.Will [00:33:18]: I mean, there was a clear example of that with 30 years of Google. Yeah, exactly. Google has basically trained us to think of search and Google has Google is search like in people's heads. Right. It's one, uh, hard part about XR is like, uh, ripping people away from that notion of search and expanding their sense of what search could be. Because like when people think search, they think like a few keywords, or at least they used to, they think of a few keywords and that's it. They don't think to make these like really complex paragraph long requests for information and get a perfect list. ChatGPT was an interesting like thing that expanded people's understanding of search because you start using ChatGPT for a few hours and you go back to Google and you like paste in your code and Google just doesn't work and you're like, oh, wait, it, Google doesn't do work that way. So like ChatGPT expanded our understanding of what search can be. And I think XR is, uh, is part of that. We want to expand people's notion, like, Hey, you could actually get whatever you want. Yeah.Alessio [00:34:06]: I search on XR right now, people writing about learning in public. I was like, is it gonna come out with Alessio? Am I, am I there? You're not because. Bro. It's. So, no, it's, it's so about, because it thinks about learning, like in public, like public schools and like focuses more on that. You know, it's like how, when there are like these highly overlapping things, like this is like a good result based on the query, you know, but like, how do I get to Alessio? Right. So if you're like in these subcultures, I don't think this would work in Google well either, you know, but I, I don't know if you have any learnings.Swyx [00:34:40]: No, I'm the first result on Google.Alessio [00:34:42]: People writing about learning. In public, you're not first result anymore, I guess.Swyx [00:34:48]: Just type learning public in Google.Alessio [00:34:49]: Well, yeah, yeah, yeah, yeah. But this is also like, this is in Google, it doesn't work either. That's what I'm saying. It's like how, when you have like a movement.Will [00:34:56]: There's confusion about the, like what you mean, like your intention is a little, uh. Yeah.Alessio [00:35:00]: It's like, yeah, I'm using, I'm using a term that like I didn't invent, but I'm kind of taking over, but like, they're just so much about that term already that it's hard to overcome. If that makes sense, because public schools is like, well, it's, it's hard to overcome.Will [00:35:14]: Public schools, you know, so there's the right solution to this, which is to specify more clearly what you mean. And I'm not expecting you to do that, but so the, the right interface to search is actually an LLM.Swyx [00:35:25]: Like you should be talking to an LLM about what you want and the LLM translates its knowledge of you or knowledge of what people usually mean into a query that excellent uses, which you have called auto prompts, right?Will [00:35:35]: Or, yeah, but it's like a very light version of that. And really it's just basically the right answer is it's the wrong interface and like very soon interface to search and really to everything will be LLM. And the LLM just has a full knowledge of you, right? So we're kind of building for that world. We're skating to where the puck is going to be. And so since we're moving to a world where like LLMs are interfaced to everything, you should build a search engine that can handle complex LLM queries, queries that come from LLMs. Because you're probably too lazy, I'm too lazy too, to write like a whole paragraph explaining, okay, this is what I mean by this word. But an LLM is not lazy. And so like the LLM will spit out like a paragraph or more explaining exactly what it wants. You need a search engine that can handle that. Traditional search engines like Google or Bing, they're actually... Designed for humans typing keywords. If you give a paragraph to Google or Bing, they just completely fail. And so Exa can handle paragraphs and we want to be able to handle it more and more until it's like perfect.Alessio [00:36:24]: What about opinions? Do you have lists? When you think about the list product, do you think about just finding entries? Do you think about ranking entries? I'll give you a dumb example. So on Lindy, I've been building the spot that every week gives me like the top fantasy football waiver pickups. But every website is like different opinions. I'm like, you should pick up. These five players, these five players. When you're making lists, do you want to be kind of like also ranking and like telling people what's best? Or like, are you mostly focused on just surfacing information?Will [00:36:56]: There's a really good distinction between filtering to like things that match your query and then ranking based on like what is like your preferences. And ranking is like filtering is objective. It's like, does this document match what you asked for? Whereas ranking is more subjective. It's like, what is the best? Well, it depends what you mean by best, right? So first, first table stakes is let's get the filtering into a perfect place where you actually like every document matches what you asked for. No surgeon can do that today. And then ranking, you know, there are all sorts of interesting ways to do that where like you've maybe for, you know, have the user like specify more clearly what they mean by best. You could do it. And if the user doesn't specify, you do your best, you do your best based on what people typically mean by best. But ideally, like the user can specify, oh, when I mean best, I actually mean ranked by the, you know, the number of people who visited that site. Let's say is, is one example ranking or, oh, what I mean by best, let's say you're listing companies. What I mean by best is like the ones that have, uh, you know, have the most employees or something like that. Like there are all sorts of ways to rank a list of results that are not captured by something as subjective as best. Yeah. Yeah.Alessio [00:38:00]: I mean, it's like, who are the best NBA players in the history? It's like everybody has their own. Right.Will [00:38:06]: Right. But I mean, the, the, the search engine should definitely like, even if you don't specify it, it should do as good of a job as possible. Yeah. Yeah. No, no, totally. Yeah. Yeah. Yeah. Yeah. It's a new topic to people because we're not used to a search engine that can handle like a very complex ranking system. Like you think to type in best basketball players and not something more specific because you know, that's the only thing Google could handle. But if Google could handle like, oh, basketball players ranked by like number of shots scored on average per game, then you would do that. But you know, they can't do that. So.Swyx [00:38:32]: Yeah. That's fascinating. So you haven't used the word agents, but you're kind of building a search agent. Do you believe that that is agentic in feature? Do you think that term is distracting?Will [00:38:42]: I think it's a good term. I do think everything will eventually become agentic. And so then the term will lose power, but yes, like what we're building is agentic it in a sense that it takes actions. It decides when to go deeper into something, it has a loop, right? It feels different from traditional search, which is like an algorithm, not an agent. Ours is a combination of an algorithm and an agent.Swyx [00:39:05]: I think my reflection from seeing this in the coding space where there's basically sort of classic. Framework for thinking about this stuff is the self-driving levels of autonomy, right? Level one to five, typically the level five ones all failed because there's full autonomy and we're not, we're not there yet. And people like control. People like to be in the loop. So the, the, the level ones was co-pilot first and now it's like cursor and whatever. So I feel like if it's too agentic, it's too magical, like, like a, like a one shot, I stick a, stick a paragraph into the text box and then it spits it back to me. It might feel like I'm too disconnected from the process and I don't trust it. As opposed to something where I'm more intimately involved with the research product. I see. So like, uh, wait, so the earlier versions are, so if trying to stick to the example of the basketball thing, like best basketball player, but instead of best, you, you actually get to customize it with like, whatever the metric is that you, you guys care about. Yeah. I'm still not a basketballer, but, uh, but, but, you know, like, like B people like to be in my, my thesis is that agents level five agents failed because people like to. To kind of have drive assist rather than full self-driving.Will [00:40:15]: I mean, a lot of this has to do with how good agents are. Like at some point, if agents for coding are better than humans at all tests and then humans block, yeah, we're not there yet.Swyx [00:40:25]: So like in a world where we're not there yet, what you're pitching us is like, you're, you're kind of saying you're going all the way there. Like I kind of, I think all one is also very full, full self-driving. You don't get to see the plan. You don't get to affect the plan yet. You just fire off a query and then it goes away for a couple of minutes and comes back. Right. Which is effectively what you're saying you're going to do too. And you think there's.Will [00:40:42]: There's a, there's an in-between. I saw. Okay. So in building this product, we're exploring new interfaces because what does it mean to kick off a search that goes and takes 10 minutes? Like, is that a good interface? Because what if the search is actually wrong or it's not exactly, exactly specified to what you mean, which is why you get previews. Yeah. You get previews. So it is iterative, but ultimately once you've specified exactly what you mean, then you kind of do just want to kick off a batch job. Right. So perhaps what you're getting at is like, uh, there's this barrier with agents where you have to like explain the full context of what you mean, and a lot of failure modes happen when you have, when you don't. Yeah. There's failure modes from the agent, just not being smart enough. And then there's failure modes from the agent, not understanding exactly what you mean. And there's a lot of context that is shared between humans that is like lost between like humans and, and this like new creature.Alessio [00:41:32]: Yeah. Yeah. Because people don't know what's going on. I mean, to me, the best example of like system prompts is like, why are you writing? You're a helpful assistant. Like. Of course you should be an awful, but people don't yet know, like, can I assume that, you know, that, you know, it's like, why did the, and now people write, oh, you're a very smart software engineer, but like, you never made, you never make mistakes. Like, were you going to try and make mistakes before? So I think people don't yet have an understanding, like with, with driving people know what good driving is. It's like, don't crash, stay within kind of like a certain speed range. It's like, follow the directions. It's like, I don't really have to explain all of those things. I hope. But with. AI and like models and like search, people are like, okay, what do you actually know? What are like your assumptions about how search, how you're going to do search? And like, can I trust it? You know, can I influence it? So I think that's kind of the, the middle ground, like before you go ahead and like do all the search, it's like, can I see how you're doing it? And then maybe help show your work kind of like, yeah, steer you. Yeah. Yeah.Will [00:42:32]: No, I mean, yeah. Sure. Saying, even if you've crafted a great system prompt, you want to be part of the process itself. Uh, because the system prompt doesn't, it doesn't capture everything. Right. So yeah. A system prompt is like, you get to choose the person you work with. It's like, oh, like I want, I want a software engineer who thinks this way about code. But then even once you've chosen that person, you can't just give them a high level command and they go do it perfectly. You have to be part of that process. So yeah, I agree.Swyx [00:42:58]: Just a side note for my system, my favorite system, prompt programming anecdote now is the Apple intelligence system prompt that someone, someone's a prompt injected it and seen it. And like the Apple. Intelligence has the words, like, please don't, don't hallucinate. And it's like, of course we don't want you to hallucinate. Right. Like, so it's exactly that, that what you're talking about, like we should train this behavior into the model, but somehow we still feel the need to inject into the prompt. And I still don't even think that we are very scientific about it. Like it, I think it's almost like cargo culting. Like we have this like magical, like turn around three times, throw salt over your shoulder before you do something. And like, it worked the last time. So let's just do it the same time now. And like, we do, there's no science to this.Will [00:43:35]: I do think a lot of these problems might be ironed out in future versions. Right. So, and like, they might, they might hide the details from you. So it's like, they actually, all of them have a system prompt. That's like, you are a helpful assistant. You don't actually have to include it, even though it might actually be the way they've implemented in the backend. It should be done in RLE AF.Swyx [00:43:52]: Okay. Uh, one question I was just kind of curious about this episode is I'm going to try to frame this in terms of this, the general AI search wars, you know, you're, you're one player in that, um, there's perplexity, chat, GPT, search, and Google, but there's also like the B2B side, uh, we had. Drew Houston from Dropbox on, and he's competing with Glean, who've, uh, we've also had DD from, from Glean on, is there an appetite for Exa for my company's documents?Will [00:44:19]: There is appetite, but I think we have to be disciplined, focused, disciplined. I mean, we're already taking on like perfect web search, which is a lot. Um, but I mean, ultimately we want to build a perfect search engine, which definitely for a lot of queries involves your, your personal information, your company's information. And so, yeah, I mean, the grandest vision of Exa is perfect search really over everything, every domain, you know, we're going to have an Exa satellite, uh, because, because satellites can gather information that, uh, is not available publicly. Uh, gotcha. Yeah.Alessio [00:44:51]: Can we talk about AGI? We never, we never talk about AGI, but you had, uh, this whole tweet about, oh, one being the biggest kind of like AI step function towards it. Why does it feel so important to you? I know there's kind of like always criticism and saying, Hey, it's not the smartest son is better. It's like, blah, blah, blah. What? You choose C. So you say, this is what Ilias see or Sam see what they will see.Will [00:45:13]: I've just, I've just, you know, been connecting the dots. I mean, this was the key thing that a bunch of labs were working on, which is like, can you create a reward signal? Can you teach yourself based on a reward signal? Whether you're, if you're trying to learn coding or math, if you could have one model say, uh, be a grading system that says like you have successfully solved this programming assessment and then one model, like be the generative system. That's like, here are a bunch of programming assessments. You could train on that. It's basically whenever you could create a reward signal for some task, you could just generate a bunch of tasks for yourself. See that like, oh, on two of these thousand, you did well. And then you just train on that data. It's basically like, I mean, creating your own data for yourself and like, you know, all the labs working on that opening, I built the most impressive product doing that. And it's just very, it's very easy now to see how that could like scale to just solving, like, like solving programming or solving mathematics, which sounds crazy, but everything about our world right now is crazy.Alessio [00:46:07]: Um, and so I think if you remove that whole, like, oh, that's impossible, and you just think really clearly about like, what's now possible with like what, what they've done with O1, it's easy to see how that scales. How do you think about older GPT models then? Should people still work on them? You know, if like, obviously they just had the new Haiku, like, is it even worth spending time, like making these models better versus just, you know, Sam talked about O2 at that day. So obviously they're, they're spending a lot of time in it, but then you have maybe. The GPU poor, which are still working on making Lama good. Uh, and then you have the follower labs that do not have an O1 like model out yet. Yeah.Will [00:46:47]: This kind of gets into like, uh, what will the ecosystem of, of models be like in the future? And is there room is, is everything just gonna be O1 like models? I think, well, I mean, there's definitely a question of like inference speed and if certain things like O1 takes a long time, because that's the thing. Well, I mean, O1 is, is two things. It's like one it's it's use it's bootstrapping itself. It's teaching itself. And so the base model is smarter. But then it also has this like inference time compute where it could like spend like many minutes or many hours thinking. And so even the base model, which is also fast, it doesn't have to take minutes. It could take is, is better, smarter. I believe all models will be trained with this paradigm. Like you'll want to train on the best data, but there will be many different size models from different, very many different like companies, I believe. Yeah. Because like, I don't, yeah, I mean, it's hard, hard to predict, but I don't think opening eye is going to dominate like every possible LLM for every possible. Use case. I think for a lot of things, like you just want the fastest model and that might not involve O1 methods at all.Swyx [00:47:42]: I would say if you were to take the exit being O1 for search, literally, you really need to prioritize search trajectories, like almost maybe paying a bunch of grad students to go research things. And then you kind of track what they search and what the sequence of searching is, because it seems like that is the gold mine here, like the chain of thought or the thinking trajectory. Yeah.Will [00:48:05]: When it comes to search, I've always been skeptical. I've always been skeptical of human labeled data. Okay. Yeah, please. We tried something at our company at Exa recently where me and a bunch of engineers on the team like labeled a bunch of queries and it was really hard. Like, you know, you have all these niche queries and you're looking at a bunch of results and you're trying to identify which is matched to query. It's talking about, you know, the intricacies of like some biological experiment or something. I have no idea. Like, I don't know what matches and what, what labelers like me tend to do is just match by keyword. I'm like, oh, I don't know. Oh, like this document matches a bunch of keywords, so it must be good. But then you're actually completely missing the meaning of the document. Whereas an LLM like GB4 is really good at labeling. And so I actually think like you just we get by, which we are right now doing using like LLM

This episode took me a while to get to!  We actually recorded this in July of 2024, but it was a beast to edit, so it had been on my to-do list for a long long time.  I hope it is worth the wait! Elaine, Mandy, Ben, Alexa, and I drove around SF for 3 hours trying some of San Francisco's most famous Asian to-go foods.  And they did not disappoint! 1) We started in Chinatown at Golden Gate Bakery for their famous daan taats which were flakey and creamy.  2) Next we went to the Tenderloin for a Saigon Sandwich banh mi, which is the best value meal in San Francisco. 3) Our third stop was Dumpling Home in Hayes Valley, for some sheng jian baos, that had the perfect combination of crispy, pillowy, salty, fatty, and a little sweet, it's such a good bite of food! 4) From there we headed into the fog of the Inner Sunset, for some Rose Indian Cuisine vegetarian samosas.  The crunchy exterior and favorable soft interior was such a great afternoon snack. 5) We headed back towards my hometown and ended our journey at Fil-Am in Daly City for some perfect lumpia Shanghai and some lumpia turon (banana lumpia).  Talk about a strong finish!  I hope you enjoy our ASMR lumpia experience! All in all a fantastic day.  We kept it under $60 for this tasting adventure, and believe it or not, all 5 of us got pretty full off of that small expenditure!  Special thanks to Ben who dropped us off and picked us up at each location! There's no way we would have made it if we had to park each time.  Also special thanks to ALEXA!  Alexa did some fantastic research and presented her facts like an absolute pro!  Mandy did our photography, and Elaine did a lot of the ordering (and paying) for us!  It was truly a team effort!!! I hope you enjoy this episode.  Let me know if you want us to try any restaurants in the Bay Area, the team is definitely ready to head out again! As I always mention, you can write to us at: ⁠infatuasianpodcast@gmail.com⁠, and please follow us on Instagram and Facebook @infatuasianpodcast  Our Theme: “Super Happy J-Pop Fun-Time” by Prismic Studios was arranged and performed by All Arms Around  Cover Art and Logo designed by Justin Chuan @w.a.h.w (We Are Half the World) #sanfranciscofood #foodcrawl #asianpodcast #asian #asianamerican #infatuasian #infatuasianpodcast #aapi #veryasian  #asianamericanpodcaster #representationmatters

Jeremy Mack (from The Phoenix Project, which exposes dark money in Bay Area politics) is back for a discussion about upcoming elections, TogetherSF, the billionaire-funded, "pro-moderate" astroturfing group behind SF's Prop. D, and Balaji Srinivasan's plan for "The Network State," a techbro-led New World Order complete with a walled-off Hayes Valley.   The Phoenix Project: https://www.phoenixprojectnow.com/  Instagram: @phoenixprojnow | Twitter: @phoenixprojnow   Past episodes mentioned:  -Alison Collins on being recalled from SFUSD: https://www.patreon.com/posts/project-2025-in-111973369  -Anna Kirsch on the billionaire attempt to create a billionaire's compound in Solano County, "California Forever": https://www.patreon.com/posts/video-planning-f-107097104    "The Tech Baron Seeking to Purge San Francisco of 'Blues'" (Gil Duran, The New Republic): https://newrepublic.com/article/180487/balaji-srinivasan-network-state-plutocrat   "SF Dems' sexual-misconduct inquiry puts politico Jay Cheng back in the spotlight" (Joe Rivano Barros, Mission Local): https://missionlocal.org/2024/05/sf-dems-sexual-misconduct-committee-puts-allegations-against-politico-jay-cheng-back-in-spotlight/      Support us and find links to our past episodes: patreon.com/sadfrancisco  

District 5 is one of the most diverse districts in San Francisco - spanning the Haight to the Fillmore to Hayes Valley to the Tenderloin. It's also shaping up to be a key battleground in the Board of Supervisors race this year. Bilal Mahmood, an immigrant and former Obama policy analyst is taking on incumbent Dean Preston. Join as we sit down with Bilal and chat about the drug and housing crisis, the need to rebrand “progressives”, the recent anti-incumbency wave in local SF politics and more.

Xebec SF in Hayes Valley, was set to have a soft opening but a break-in causes heartbreaking losses and a delay for the owner.See omnystudio.com/listener for privacy information.

We're always on the lookout for great value, and Al has found a super line of wines that pack a lot of punch for just $15 across the board.See omnystudio.com/listener for privacy information.

Holy SH*T, These two words have been said on this episode multiple times, way more than ever before I want to say, and it's because we got 2 incredible exciting breaking news announcements in a very very short amount of time (in the span of 3 hours) and the OpenAI announcement came as we were recording the space, so you'll get to hear a live reaction of ours to this insanity. We also had 3 deep-dives, which I am posting on this weeks episode, we chatted with Yi Tay and Max Bane from Reka, which trained and released a few new foundational multi modal models this week, and with Dome and Pablo from Stability who released a new diffusion model called Stable Cascade, and finally had a great time hanging with Swyx (from Latent space) and finally got a chance to turn the microphone back at him, and had a conversation about Swyx background, Latent Space, and AI Engineer. I was also very happy to be in SF today of all days, as my day is not over yet, there's still an event which we Cohost together with A16Z, folks from Nous Research, Ollama and a bunch of other great folks, just look at all these logos! Open Source FTW

Part 2 begins with how Melan thinks of herself as an artist. "Art is therapy," she says. It's how she knows herself. "If I cannot create, I cannot be myself."   She's been creative her whole life. She wanted to be a tap dancer early on, pointing to Shirley Temple as inspiration (by the way, Temple was originally from Santa Monica, but died in Woodside). Melan even did drag for a while. But she found painting around four years ago and decided then that she's not doing anything else after that.   She cites her mom's love of cooking and baking shows as another inspiration. Back in the day, before Food Network and competitive cooking shows, it was just PBS. Melan watched a lot of Julia Child, Jacques Pepin, and Martin Yan. She says that she watched these shows more than the Saturday morning cartoons most kids her age were glued to. She also loved cookbook illustrations and says they've been a big inspiration for her.   Melan talks about the "Muni Raised Me" show at SomArts last year, which she was part of. In the podcast, she describes her Muni paintings that were part of the SomArts show ... they involved dim sum, burritos, and Irish coffees. Then our conversation evolves into a discussion of Muni and what it can mean to life in The City.   Plans for 2024 include hibernating. She says she needs to paint, that travel in 2023 pulled her away from that. She's looking for new things to paint, so if you've got ideas, drop her a line.   We end the podcast with Melan riffing on our theme: "We're All in It."   Follow Melan on social media: Instagram/TikTok   We recorded this podcast in Patricia's Green in Hayes Valley in December 2023.   Photography by Jeff Hunt

Melan Allen is a third-generation San Franciscan. In this episode, we get to know this born-and-raised food artist whom I met last summer at Fillmore Jazz Festival. Melan's grandparents moved here in the Sixties and lived in San Francisco until the 2000s. Her mom's mom came to SF from Texas and was part of a mass migration west, when her mom was very young. In our conversation, Melan says that she sometimes wonders what it would have been like if she had grown up in Texas instead of The City.   Her dad was born here and raised in Western Addition/Hayes Valley. Her mom also grew up in that part of town. Perhaps naturally, when the two met and started to raise a family, they stayed in the area. Her family was there until Melan was 16, in fact. Even though she no longer lives there, Melan says that this hood is home, even though it has changed.   "It's like your first love," Melan says of her hometown. "It feels like growing up in Oz." She left The City when she found herself complaining about changes.   Rewinding a bit, Melan shares the story of her family getting evicted from her grandma's house in Ingleside when she was 19. She had wanted to move out on her own anyway, but wasn't sure how. And so, as it turns out, this unfortunate event forced her to become an adult.   She's the middle kid of three, with one older sister and one younger brother. Melan says that she and her siblings are all different, that they did their own things, and that she is the only artist among them. Her dad is a playwright and her mom's a hard-core crafter. Melan says that she has always been creative, that creativity and expression were fostered in their home.   Her mom collected/hoarded things, and Melan thinks that's where she got her own propensity to pick things up off the street. She feels like she can "McGuyver" anything.   We end Part 1 with Melan explaining that she's consistently cookie-decorating at her home in the East Bay. At the time of our recording last December, she was also making fake cookies out of clay. She rattles off some of the other projects she's currently working on, and ends by proclaiming, "I have to have a lot of space."   Follow Melan on Instagram @melanmadethat. Visit her website here.   Photography by Jeff Hunt   We recorded this podcast in Patricia's Green in Hayes Valley in December 2023.

Hayes Valley's Proxy is a cluster of boutique shops and restaurants that functions as a community gathering space, but it sits on land that has been flagged for affordable housing for decades. Now that the city wants to start development, residents are divided on whether the project should move forward. Reporter J.K. Dineen joins host Cecilia Lei to break down the controversy and the broader stakes for San Francisco's housing debate. | Unlimited Chronicle access: sfchronicle.com/pod Got a tip, comment, question? Email us: fifth@sfchronicle.com Learn more about your ad choices. Visit megaphone.fm/adchoices

Two 7-Eleven workers in California took matters into their own hands and used a stick to wallop a man who tried to steal a trash can full of cigarettes. California Democrat Governor Gavin Newsom stayed radio silent on Thursday after Florida Governor Ron Desantis accepted his debate challenge this week. San Francisco city leaders are taking heat from Hayes Valley residents who say homeless people lit warming fires in their neighborhood for months. Residents said their warnings were ignored by the city until a massive 4-alarm blaze ignited Tuesday before dawn. The cause of the blaze has not been officially released. Mexico Links Texas Border Buoys To Migrant Deaths — Abbott Says That's ‘Flat-Out Wrong'. CJ Sveen, a homeowner in California, has had his home insurance canceled based on photos of his property allegedly taken by a drone. The reasons for cancellation include the presence of a “dilapidated car” in the policyholder's yard, as well as multiple tires.See omnystudio.com/listener for privacy information.

We're always on the lookout for great values, and Al has found a super line of wines that pack a lot of punch for just $15 across the board.See omnystudio.com/listener for privacy information.

I'm pleased to announce that I'm introducing a new podcast and starting a YouTube channel. I'm calling it “Newcomer” — like this newsletter. What can I say? It's a good name.The show kicks off tomorrow with an interview with LinkedIn co-founder and Greylock partner Reid Hoffman. Hoffman just stepped off OpenAI's board of directors. We talk about that decision, AI sentience, the PayPal mafia, cloud compute spending, Joe Biden's presidency, and much more. I think you'll enjoy the episode.For the new show, I've got interviews lined up with investor and former top Tesla and Lyft executive Jon McNeill and with Lightspeed Venture Partners founder and managing director Ravi Mhatre.I'm also going to publish some of the conversations from the Cerebral Valley AI Summit on the podcast feed and YouTube channel. In that vein, I'm happy to announce that Clem Delangue, the CEO of Hugging Face, and Amjad Masad, the CEO of Replit, are scheduled to sit down with me together at the Cerebral Valley AI Summit on March 30. (Founders and CEOs can still apply this week to attend the one-day conference in Hayes Valley. We've been overwhelmed with investor interest to attend.)Newcomer, the weekly podcast, will post on Tuesdays. I'll send it to newsletter subscribers and publish it to Apple podcasts, Spotify, and YouTube. Email me with guest ideas. I'll publish summaries of the episodes here in the newsletter. Over time, I might add bonus sections for paying Newcomer subscribers. With this podcast, I'm going solo, interviewing top investors and founders. I'm bringing my sensibility as someone who understands the inside-story of Silicon Valley but who is happy to poke and prod as to why the tech world operates like it does. I want to thank automated security and compliance platform Vanta for being the launch sponsor for the Newcomer podcast. You may remember Vanta CEO Christina Cacioppo from her appearance on the second episode of my old podcast Dead Cat. She's been an early believer in my audio efforts! Excited to have Vanta on board. If you're interested in sponsoring the podcast, reach out. For fans of my old podcast Dead Cat, give the new podcast a try. It will be arriving via the same podcast feed. The Newcomer podcast shouldn't be so much a revolution as an evolution. Yes, my former co-host Tom Dotan is off skewering Marc Benioff for the Wall Street Journal. I'm on my own. It will give me more time to ask the hard questions and listen to the guests' replies. I'm going to try to talk about the media less and the business of tech more. But it will be the same probing podcast that you've come to love. To get new episodes, subscribe to this newsletter, sign up to receive the podcast on Apple, and subscribe to the Newcomer YouTube channel. I'd definitely appreciate some positive reviews as I get this thing going. Like, comment, subscribe, and all that.See you in your feeds tomorrow! Get full access to Newcomer at www.newcomer.co/subscribe

I'm pleased to announce that I'm introducing a new podcast and starting a YouTube channel. I'm calling it “Newcomer” — like this newsletter. What can I say? It's a good name.The show kicks off tomorrow with an interview with LinkedIn co-founder and Greylock partner Reid Hoffman. Hoffman just stepped off OpenAI's board of directors. We talk about that decision, AI sentience, the PayPal mafia, cloud compute spending, Joe Biden's presidency, and much more. I think you'll enjoy the episode.For the new show, I've got interviews lined up with investor and former top Tesla and Lyft executive Jon McNeill and with Lightspeed Venture Partners founder and managing director Ravi Mhatre.I'm also going to publish some of the conversations from the Cerebral Valley AI Summit on the podcast feed and YouTube channel. In that vein, I'm happy to announce that Clem Delangue, the CEO of Hugging Face, and Amjad Masad, the CEO of Replit, are scheduled to sit down with me together at the Cerebral Valley AI Summit on March 30. (Founders and CEOs can still apply this week to attend the one-day conference in Hayes Valley. We've been overwhelmed with investor interest to attend.)Newcomer, the weekly podcast, will post on Tuesdays. I'll send it to newsletter subscribers and publish it to Apple podcasts, Spotify, and YouTube. Email me with guest ideas. I'll publish summaries of the episodes here in the newsletter. Over time, I might add bonus sections for paying Newcomer subscribers. With this podcast, I'm going solo, interviewing top investors and founders. I'm bringing my sensibility as someone who understands the inside-story of Silicon Valley but who is happy to poke and prod as to why the tech world operates like it does. I want to thank automated security and compliance platform Vanta for being the launch sponsor for the Newcomer podcast. You may remember Vanta CEO Christina Cacioppo from her appearance on the second episode of my old podcast Dead Cat. She's been an early believer in my audio efforts! Excited to have Vanta on board. If you're interested in sponsoring the podcast, reach out. For fans of my old podcast Dead Cat, give the new podcast a try. It will be arriving via the same podcast feed. The Newcomer podcast shouldn't be so much a revolution as an evolution. Yes, my former co-host Tom Dotan is off skewering Marc Benioff for the Wall Street Journal. I'm on my own. It will give me more time to ask the hard questions and listen to the guests' replies. I'm going to try to talk about the media less and the business of tech more. But it will be the same probing podcast that you've come to love. To get new episodes, subscribe to this newsletter, sign up to receive the podcast on Apple, and subscribe to the Newcomer YouTube channel. I'd definitely appreciate some positive reviews as I get this thing going. Like, comment, subscribe, and all that.See you in your feeds tomorrow! Get full access to Newcomer at www.newcomer.co/subscribe

​San Francisco is about to get its first new LGBTQ bar in a long, long time, y'all. In this episode, we'll meet Malia Spanyol. Currently, Malia owns Thee Parkside. She was born in Honolulu and went to ASU in Tempe, Arizona. But she hated it and came to San Francisco in 1989 just before the big earthquake that year. Malia was already out and was here looking for her people. She worked, went to school at SF State, made friends, and explored the town on her motorcycle. It was a "great time to be gay in SF," the early 1990s. She was always going to music shows, art shows, poetry readings, and parties, mostly in the Mission. "Valencia Street was dirty" then, Malia says. She worked in a dildo factory and lived in Hayes Valley. On her way to work, she and friends would drive down Valencia in a t-top, out and proud as fuck. At her job, Malia learned bookkeeping and helped friends and small businesses do taxes. She seized an opportunity to become a business owner herself when she bought Pop's Bar with friends in 2003. Lil Tuffy, who some of you might know from this podcast and his show posters, came in and became the manager at the bar. Malia ran Pop's for 10 years, from 2003 to 2013. In 2007, she found out about an opportunity at Thee Parkside, a spot with more to offer—food, a stage, an outside area. And so she capitalized. As Malia notes, the area around Thee Parkside was very different then—more blue collar. She learned Muay Thai around 2007 and fell in love with the sport. Her coach asked her to open a new gym and she did. Check back next week to hear all about Malia's newest adventure—opening Mother, the newest queer and femme-centered bar in The City. We recorded this episode at Thee Parkside in Potrero Hill in November 2022. Photography by Michelle Kilfeather

State Senator Scott Wiener of San Francisco has asked Caltrans to study the potential costs of removing the Central Freeway. The roughly one mile elevated connector between Highway 101 and San Francisco's Hayes Valley. That in addition to an inquiry to look into the removal of two other freeways in the city. To discuss further, KCBS Radio's Bret Burkhart spoke to California Senator Scott Wiener.

Today's episode is about #TheBear. It's on #Hulu, and so many restaurant and bar industry people have been talking about this show. I have to say I was late to The Bear. Basically, I don't trust anything on TV to get it right. There have been a few movies and a few TV shows here and there about the restaurant industry, and they miss it by a mile. You know every chef is spotless, the kitchen is super clean, no one is dirty, no spills. And that is bullshit. So, I was skeptical of the show. Then I started to see articles in the Atlantic, Bon Appetite, and the New York Times about how #TheBear showed the manic and toxic environment that restaurants can have. And I got hooked on the show and binged it one setting. That's how good I thought this show was and, more importantly, how I thought this show got so much right.  So today, I'm talking to San Francisco Chef Freedom Rains. Freedom has worked at restaurants such as Boulevard, Incanto, Flour, and Water and now is Executive chef at Amano in Hayes Valley. And we get his take on the show and restaurants in San Francisco. www.amanosf.com/chef/ www.chefchriscosentino.com www.chezpanisse.com/1/ #alicewaters www.acmebread.com www.laurachenel.com www.zunicafe.com #jeremiahtowers            

This episode features an interview with Orchid Bertelsen. Orchid is the Chief Operating Officer at Common Thread Collective, an eCommerce growth agency. In this episode, Orchid talks about the three ways to grow, developing strategic partners, and how to do it all without losing the soul of your brand.Quotes*”There's no easier audience to sell to than people who have already bought from you, know that you exist, and like the product. And so if you want to sell more to your existing customer base, you can increase their lifetime value, either through your core offering and doing a subscription service, or you can continue to launch new products that are complementary to whatever you're selling.” *”There are some products that people just want to experience in person. There is a certain way to expand into the brick and mortar experience while still utilizing and connecting the digital experience to it, whether it's something simple, like your transactions in store being tied to your account online, and you get an email receipt. I think that is the challenge, is that retail space is obviously expensive. A lot of flagship stores in major city centers are loss leaders. That retail footprint isn't actually generating a lot of revenue per square foot, but it's just another marketing expense, having a physical manifestation of what the brand is beyond the website.” *”There was a boom in e-commerce overall during COVID. When you have different partners like Shopify or Sub Stack, you can bring your business idea to life very easily. What happens then is that you have a community that's just really focused on single-channel DTC. And they probably created a solution to solve a personal problem. But at a certain stage of growth, they're like, ‘Hey, I can no longer sell to people like me with the same exact problem, because I've already reached all of them,' which is a good problem to have. So over the course of the last two years, you've seen more mature e-commerce businesses try to go omni-channel.”Time Stamps*[0:05] The Case of Scaling Up a DTC Brand*[0:32] Introducing Orchid Bertelsen, COO at Common Thread Collective*[10:45] Evidence #1: Sales are single-channel*[17:40] Evidence #2: Hasn't developed strategic sales partners*[20:44] Evidence #3: Has already saturated market*[34:16] Debrief*[35:28] HGS PubBioOrchid is the Chief Operating Officer of Common Thread Collective, an agency focused on helping ecommerce brands grow profitably, and entrepreneurs to achieve their dreams.Prior to joining CTC, Orchid Bertelsen was the Head of Consumer Experience Strategy & Innovation at Nestlé USA, where she evaluates and tests emerging technologies like artificial intelligence, voice assistance, AR/VR. She has a varied portfolio, made up of 40+ brands and includes beloved brands like Coffee-Mate, Toll House and DiGiorno. Nestlé is also a majority stakeholder in Blue Bottle Coffee and owns and operates Starbucks at Home.She lives in Hayes Valley with her husband and daughter, and loves to travel back to Taiwan, where her family is from.Thank you to our friendsThis podcast is brought to you by HGS. A global leader in optimizing the customer experience lifecycle, digital transformation, and business process management, HGS is helping its clients become more competitive every day. Learn more at hgs.cx.Links:Connect with Orchid on LinkedInFollow Orchid on TwitterCheck out Common Thread CollectiveConnect with Lyssa on LinkedInCheck out HGS

Marcia Lieberman is a long-term Buddhist practitioner who has been affiliated with San Francisco Zen Center since 1989, having resided at all three practice centers. In this podcast, we discuss her third photographic book Clean Slate—Images from Dogen’s Garden with commentaries by Dogen scholars. Clean Slate is published by ORO Editions at Goff Books and can be purchased here. Her previously published books include When Divas Confess, and Being Still. Follow Marcia on Instagram here.As an artist, Marcia’s affinity for beauty and form in ceremony has been a guiding part of her practice. She taught in the photography departments at UC Berkeley and California College of the Arts. In 2016 she completed graduate studies in Buddhist scholarship at the Institute for Buddhist Studies, UCB Graduate Theological Seminary. Marcia was the Head Student at Green Gulch Farm for the Spring 2017 Practice Period. Marcia volunteers as the librarian and beekeeper for SFZC’s City Center in Hayes Valley. Get full access to SparkZen at sparkzen.substack.com/subscribe

This episode is the second in a series we're doing with Creativity Explored. CE's mission is "to provide developmentally disabled people access to the human right of creative expression." Check back Thursday for the next episode in this series, where we meet Studio Director Paul Moshammer.​ Joseph "JD" Green lives close enough to Creativity Explored on 16th Street that he walks to get there. JD has been with Creativity Explored since just after he graduated from high school 10 years ago. He was doing art in the building where he lives, in Hayes Valley, when someone let him know about the organization serving people with developmental disabilities. He's been making art nearly his whole life, inspired by TV shows, animation, and cartoons. Nickelodeon and Disney characters made up the bulk of figures he drew, but his favorite to this day is Spider-Man. JD also does social and political art. He tells us all about a collaboration he did with other Creativity Explored artists looking at Black identity through the lens of "blackface" and flipping the script on white supremacy. In 2019, he was part of a show with other Black CE artists called "Blackiful" that looked at police violence against people of color. JD recounts his first visit to CE for us. He was in awe of the large space filled with so many people "just doing art." He immediately loved it and started meeting other artists. Today, he still draws cartoons, but his main jam is portraits. He's drawn Michael Jackson, Prince, and David Bowie, among other singers and celebrities. He also does ceramics in addition to painting and drawing. We end this episode with what JD loves about San Francisco and who his favorite artists are, including fellow Creativity Explored artist and JD's friend, Gerald Wiggins. If you missed it, Part 1 with CE's Executive Director, Linda Johnson, can be found here. We recorded this podcast at Creativity Explored in the Mission in December 2021. Photography by Jeff Hunt

This week we bring you our conversation with Rob Zaborny, long time San Francisco resident, and celebrated chef. Originally from New York, Rob moved to San Francisco in 1980 and never looked back. Although he has a great love of traveling all over the world, he especially loves to call the Bay Area home. Rob has been with the Hayes Street Grill, in Hayes Valley, for 27 years of its 40 year history! Please enjoy as we discuss with Rob the history of the Food Movement in San Francisco, and everything that makes the Bay Area such a destination for foodies everywhere. Meet Rob Zaborny!

“All of us take these things for granted, that they're always there” - Mark BaileyIn this episode our first featured voices are Mark Bailey the head of operations and Martha Martinez the head of production and training at Hayes Valley Bakeworks. We wanted to share the story of Hayes Valley Bakeworks because of its unique self-supporting social enterprise model to provide a workforce training program in the culinary arts. Hayes Valley Bakeworks trains people with disabilities, formerly homeless people and people who are at risk. Hayes Valley Bakeworks was created by Toolworks which is the parent social enterprise that is a self-supporting nonprofit agency. Toolworks is dedicated to improving the lives of people with disabilities and operates two other workforce training programs through providing janitorial services and recycling services for businesses

In this podcast, Temi picks up where she left off in Part 1, talking about founding Pembroke, her PR firm here in The City. She goes on to describe how the company transitioned during the onset of shelter-in-place earlier this year. Then Temi pivots to her own experiences with racism and her awakening to racial and social justice. She ends the podcast talking about joining Represent Collaborative, for whom this podcast was produced. REP CO is a media hub for stories about under-represented folks, and we're honored to be part of that effort.   We recorded this podcast in Hayes Valley in October 2020. Photography by Michelle Kilfeather

Temi Adamolekun moved to San Francisco sight unseen. Temi was born in Lagos, Nigeria, but raised mostly in London. Her family visited their hometown often after their move to Europe, so Temi grew up with a good sense of where she was from despite her British upbringing. After boarding school and university, she got a job at Condé Nast doing PR work. As a side hustle of sorts, she started making handbags, and through that, met the man she'd eventually marry. The young couple had a chance to move to San Francisco and seized on it, sight unseen. That was a dozen or so years ago, and today, they're raising a child here in The City. Please check back Thursday for Part 2, when Temi will talk about launching her own PR firm, her racial justice awakening, and the work she's been doing with REP CO. ​We recorded this podcast in Hayes Valley in October 2020. Photography by Michelle Kilfeather

Bay Area residents review Mamak Malaysian cuisine in Noe Valley, fresh phở in Hayward, and handmade pasta in Hayes Valley.

Today’s episode is with Kim Alter, the chef and co-owner of Nightbird and the adjoining Linden Room bar in Hayes Valley, which are currently closed to customers during the crisis. But the lights are still on as her small but mighty team is cooking hundreds of meals daily for initiatives like SF New Deal and Frontline Foods. Kim is known for her commitment to local farms and sustainability, and she’s proven to be a leader in leveraging her longtime relationships to support farmers as she sources ingredients to go into these low-cost but high-quality meals. She also shares with us a day in her extremely busy life right now—you’ll be exhausted just hearing everything she’s doing. Thanks for listening to her inspiring story. You’ll find links to Nightbird’s GoFundMe and more in the episode notes, please take a look. Thank you.Nightbird: https://www.nightbirdrestaurant.comNightbird GoFundMe: https://www.gofundme.com/f/nightbird-employee-relief-fund SF New Deal: https://www.sfnewdeal.org Frontline Foods: https://www.frontlinefoods.orgBay Area Hospitality Coalition: https://bayareahospitalitycoalition.comTwo-Top: 1. Dining Out for Life/Dining IN for Life: https://www.doflsf.org 2. La Ciccia: http://www.laciccia.com, @lacicciasfIf you’re a Bay Area business or individual and want to be featured in On the Fly, please fill out the form at bit.ly/ontheflyguest.Support the show (http://www.venmo.com/Marcia-Gagliardi)

Growing up in Laguna Beach, CA, Chef Kim Alter is a graduate of the California Culinary Academy.  She went on to work in some of the Bay Area's most notable restaurant kitchens before joining the Daniel Patterson Group where she served as Executive Chef for Haven and Plum in Oakland, CA.  Today, Kim Alter is the chef/owner of Nightbird and the adjoining cocktail concept, Linden Room, in San Francisco's Hayes Valley. Show notes… Favorite success quote or mantra: "Success isn't just about what you've accomplished, it's about what you've inspired other people to do." In this episode with Kim Alter we will discuss: You inspire others around you positively Using food to make people happy Food as acceptance Creating impactful “food memories” Mental health in the restaurant industry Tell your staff that they're doing a good job The hard work angle Ego Mentors Learning something new every single day Constantly improve your business Experiencing failure Fear of failure The inevitability of doing something wrong Thoughts on awards The importance of non-transactional relationships in the kitchen Money and waste management in the kitchen Diffusing angry guests Supporting the restaurants in your community Tasting menus Acquiring permits The importance of respect Women in the industry Culture v. Systems Working with your life partner Today's sponsor: Gusto offers modern, easy payroll, benefits, and HR to small businesses across the country — they were even named best online payroll by PCMag. And as a listener, you'll get three months free when you run your first payroll. Sign up and give it a try at Gusto.com/unstoppable.  CAKE provides an easy-to-use integrated software and hardware solution to build better dining experiences for restaurant operators and their guests. With mobile marketing and waitlist management to point of sale payment processing, the CAKErestaurant management system helps you grow your business.  Learn more at trycake.com/unstoppable EthicsSuite.com -provide a safe, secure, simple and anonymous communication channel between you and your employees to help you protect your hard-earned reputation and assets. Demonstrate to your team that you are committed to providing a workplace that operates with the highest ethical standards. Staying informed about important issues will help you resolve them internally before they spiral into larger, costly, or public problems.   Knowledge bombs Which "it factor" habit, trait, or characteristic you believe most contributes to your success? Being humble What is your biggest weakness? Too much time in the kitchen and not enough promoting What's one question you ask or thing you look for during an interview? Personality, goals, how do they treat the dishwasher? What's a current challenge? How are you dealing with it? Issues with the city impeding customer flow Share one code of conduct or behavior you teach your team Treat each other with respect What is one uncommon standard of service you teach your staff? BOH and FOH are one in the same What's one book we must read to become a better person or restaurant owner? The Art of Fermentation by Sandor Ellix Katz Setting the Table by Danny Meyer GET THIS BOOK FOR FREE AT AUDIBLE.COM  What's one piece of technology you've adopted within your four walls restaurant and how has it influence operations? Social media If you got the news that you'd be leaving this world tomorrow and all memories of you, your work, and your restaurants would be lost with your departure with the exception of 3 pieces of wisdom you could leave behind for the good of humanity, what would they be? Put your head down and work hard Treat people with respect Contact info: Night Bird website Instagram: @kimalter @nightbirdsf Thanks for listening! Thanks so much for joining today! Have some feedback you'd like to share? Leave a note in the comment section below! If you enjoyed this episode, please share it using the social media buttons you see at the top of the post. Also, please leave an honest review for the Restaurant Unstoppable Podcast on iTunes! Ratings and reviews are extremely helpful and greatly appreciated! They do matter in the rankings of the show, and I read each and every one of them. And finally, don't forget to subscribe to the show on iTunes to get automatic updates. Huge thanks to Kim Alter for joining me for another awesome episode. Until next time!   Restaurant Unstoppable is a free podcast. One of the ways I'm able to make it free is by earning a commission when sharing certain products with you. I've made it a core value to only share tools, resources, and services my guest mentors have recommend, first. If you're finding value in my podcast, please use my links!

Kim Alter’s tasting menus at Nightbird in San Francisco’s Hayes Valley tell compelling stories, like the opening “Insight” menu that was all white until the last course, when there was a burst of color. That menu reflects the journey her mother took from descending into blindness—and seeing only blurry outlines of colors—to having an experimental surgery that allowed her to see again. Thus the bright dessert. Listen in to this episode to hear how Alter has shaped her restaurant and her team to bring nuanced flavors and emotions to the table. It's HRN's annual summer fund drive, this is when we turn to our listeners and ask that you make a donation to help ensure a bright future for food radio. Help us keep broadcasting the most thought provoking, entertaining, and educational conversations happening in the world of food and beverage. Become a member today! To celebrate our 10th anniversary, we have brand new member gifts available. So snag your favorite new pizza - themed tee shirt or enamel pin today and show the world how much you love HRN, just go to heritageradionetwork.org/donate Speaking Broadly is powered by Simplecast.

In today’s episode of Escrow Out Loud, our San Francisco Real Estate podcast, we are on location at City Hall meeting with the Mayor’s Director of Housing Delivery – Judson True.[00:23] Due to the current housing crisis in San Francisco, Mayor Breed has set a goal of creating at least 5,000 new homes a year; with roughly a third of this being affordable housing. It is a lofty and crucial goal she has tasked Judson True with achieving. Judson True has an impressive background and is the first person to be appointed to this newly created position. What, exactly, is his job?[03:16] Currently, in SF there are 56,000 homes that have been approved by planning but are yet to be built. The vast majority are part of large new neighborhood projects which will transform the city. Projects like The Shipyard, Park Merced and Treasure Island. Dogpatch projects include Pier 70 and the Potrero Power Plant while Mission Rock is in Mission Bay.[05:01] Judson is working on a lot of large projects and loves them all equally. But a little more equal than the others are the waterfront projects which he is particularly excited about. It is great to see some projects moving along really quickly. Because really, the hard part (and the part that takes the longest) when building new neighborhoods, is getting all the infrastructure permitted (our favorite new phrase: "horizontal infrastructure").[06:59] Most of us realize that there is a real need for affordable housing in the city. How does funding for affordable housing work though? As you might imagine, it is complicated. Judson sheds light on how the funding for affordable housing and the building of market rate housing correlate, and where funds for affordable housing come from.[10:00] Judson is from the mid-west originally, but an opportunity at Berkeley led him to SF, where he lived in the same apartment in Hayes Valley since 1998! Hayes Valley is one of the neighborhoods that has been radically transformed over the years.[13:12] This year there are a lot of housing bills in the state legislature. Which in particular does Judson believe will have the most positive impact on housing in SF?[15:15] Finally, what are Judson’s thoughts on the CASA Compact and its impact on the housing debate so far?Thank you for listening. If you enjoyed this episode leave us a review on your favorite platform, tell your friends and don’t forget to join us again next week! See acast.com/privacy for privacy and opt-out information.

Matt Shapiro is a musician and the co-owner of the Elbo Room in Oakland. After initially working at the Elbo Room for years as its manager and booker, Matt and co-owner Erik Cantor purchased the bar in 2010.  The Elbo Room has been the home of Muni Diaries Live for many years, and just before its San Francisco location closed permanently, Matt joined Muni Diaries Live on stage to share one of the many memorable, behind-the-scenes tales from the fame club. This story involved Satan, his leather jacket, and the lengths that club owners will go to keep a promise. You can visit the Elbo Room's Jack London Square location in Oakland or find them on Elbo.com. Muni Diaries Live has a new home at Rickshaw Stop in Hayes Valley, with a new show coming up on Saturday, April 6, 2019! Go to MuniDiaries.com to get your ticket today. 

Today on Escrow Out Loud, our San Francisco Real Estate podcast, we continue the neighbourhood theme from last time with a game; let’s play Name That Neighborhood![00:21] How quickly can Britton figure out the neighborhood in question while Matt reads out descriptive sentences?We cover: Lake Street, Nob Hill, Western Addition, Clarendon Heights, Alamo Square, Twin Peaks, Anza Vista, Hayes Valley, North Panhandle, Dolores Heights, The Mission, Dogpatch, SoMa, Westwood Highlands, Miraloma, Forest Hill - throwing in some interesting facts and musings along the way.[07:49] How do freeways affect neighbourhoods? As the city evolves, old freeways are torn down and new ones are built up, but do they always make sense within a neighborhood?[14:39] The gentrification issue is a contentious one and raises an interesting question: Who does a neighborhood belong to?[22:22] There are a number of transformations planned for the city over the coming years – it will be interesting to see how these changes will further impact the city and its neighborhoods.Thank you for listening. If you enjoyed this episode leave us a review on your favourite platform, tell your friends and don’t forget to join us again next week! See acast.com/privacy for privacy and opt-out information.

It’s time for another Four Wines where we discuss four wines we tasted recently that don’t fit into an upcoming episode but we love and want to share with our listeners.    Lucien Albrecht Crémant d’Alsace Brut - priced around $23.  This wine was provided as a sample to us Nose: golden apples, bread and a hint of white flowers It’s dry with medium plus acidity, light body and flavors of really ripe pear, stonefruit and white flowers This wine is everything you want in a sparkling wine: crisp - the acidity this there but the fruit softens it, ripe fruit - the fruit is grown in a warmer pocket of Alsace You can purchase this wine here    Domaine de Pouy Côtes de Gascogne 2017 - priced around $12.  Nose - citrus mostly lemon, pineapple, white flowers and a hint herbal It’s dry, with medium plus acidity, light body with flavors of pineapple, lemon, and a hint of white flowers The nose of this wine is intoxicating and lingers This wine is light and crisp and shows that just because a wine is inexpensive and an IGP wine doesn’t mean you should discount it. This wine is definitely worth your time and money. We paired this wine with Lemon Broccoli Pasta and it paired beautifully.  Click here to learn where you can purchase this wine.   Baileyana Firepeak Pinot Noir 2016 - priced around $30. Nose: cherry cola It’s dry with medium plus acidity, light tannins, medium body and flavors of cherries and an herbal element to it like fresh fennel or arugula This wine is what we would expect from a Central Coast Pinot Noir- Cherry cola flavors and a little fuller body than pinots from Oregon or France, really tasty Food pairings: duck, salmon, turkey and chicken dishes and dishes with earthy vegetable like beets You can purchase this wine from the wineries website here   Hayes Valley 2016 Meritage Red Wine - priced around $12. Bordeaux Blend of 40% Merlot, 35% Cabernet Sauvignon, 13% Malbec, 12% Cab Franc Nose: Dark fruit like black cherries and blackberries and black pepper It’s dry with medium acidity, medium tannins, medium plus body with flavors of black plum, raspberries, black cherries and dried fennel Very juicy, fruit forward wine and the tannins are soft and smooth making this a very approachable wine that is a real crowd pleaser. Food pairings: Grilled Lamb with Goat Cheese, Mushroom Soufflé You can purchase this wine here     

In this episode, theater critic Lily Janiak talks to local actor Denmo Ibrahim as part of our Artist’s Life Series, a recurring feature that will shine a spotlight on the talent who help make up the rich tapestry of the Bay Area’s cultural life. In addition to recently playing the lead role in “A Thousand Splendid Suns” at ACT, Ibrahim is also the CEO of the Hayes Valley day spa Earthbody and the skincare line Omcali. Produced by Lily Janiak. Music by Steven Boyle. Learn more about your ad choices. Visit megaphone.fm/adchoices

Rich TableBy Sarah and Evan Richwith Carolyn Alburger Intro: Welcome to the Cookery by the Book podcast with Suzy Chase. She's just a home cook in New York City, sitting at her dining room table, talking the cookbook authors.Sarah Rich: My name is Sarah Rich and my husband Evan and I have just come out with our new cookbook called Rich Table.Suzy Chase: It was so nice to meet you at High Street on Hudson, Wednesday night, and taste dishes out of this cookbook. I want to kick things off by talking about some of the incredible dishes I had. First, let's start with one of the snacks. The cranberry bean dip on page 66. Describe this dish and what are cranberry beans?Sarah Rich: Cranberry beans are a fresh shelling bean, and they're really, really delicious, and we love to use them at Rich Table. One of the things that we're really lucky to have at Rich Table is, being in San Francisco, we have these great farmers markets and we got so much great produce and we can change the menu constantly. With the cranberry bean dip, we wanted to make something that was sort of like ... similar to kind of a hummus because that's one of our favorite things to eat, but a little bit different, and we use cranberry beans instead, because they have kind of that same rich creaminess, but just something a little bit different.Suzy Chase: And then talk a little bit about the plancha bread. Is that how you pronounce it?Sarah Rich: Okay. Yeah. Yes, plancha bread. We call it that. We have something in our kitchen called a plancha, which is basically just like a flat top or a griddle. We make this bread. It's really, really easy bread to make, and we roll it out into little balls and then roll that out into a nice, long, sort of oval shape and grill it right on the plancha, so it gets ... it has a nice sort of yeasty flavor. It's got some whole wheat in it, so it's got a little nice texture to it, nice chewiness, but then cooking it right on the flattop or the griddle gives it a really wonderful flavor and a little crispness to the outside. It's kind of like a pizza dough but instead of puffing it up in the oven, we just grill it flat on the griddle. We serve the cranberry bean dip with that, and then we have some fresh wax beans or you can use runner beans or green beans or broad beans. Whatever sort of pole beans like that. Slice it up nice and thinly, dress it with a little bit of our [inaudible 00:02:35] vinaigrette and some padron peppers that we've charred, which gives it a little spiciness.Suzy Chase: Yeah. It was kind of a fresh take on the pita and Hummus.Sarah Rich: Yeah. Exactly. Exactly. A very California, Rich Table take on that.Suzy Chase: By the way, my husband said if we lived in California, we'd go here once a week. Sarah Rich: Oh, good. Well that's what we want. We do say that about Rich Table. We wanted to be the kind place where you could go for a special occasion where you could go every Tuesday night for a grilled steak and pasta.Suzy Chase: I wish you'd come back to New York City, but anyway, that's beside the point. And I digress. Next I had the sprouted quinoa cakes with summer squash and chevre on page 178. Described this dish.Sarah Rich: We really try to have a lot of vegetarian options. The way our menu is broken down, we've got our bite section, which are really tiny little things to eat, snacks to have when you start your meal, appetizers. We have pastas and then we have our main courses, of course. We always have a steak, we always have some sort of fish or something like that, but we like to also have a nice vegetarian option and we want to do something beyond just like sauteed vegetables on a plate, and so this is an example of that. You've got the sprouted quinoa. Sprouting it kind of gives it ... softens it a little bit and helps it, actually, your body digest it a little bit easier, and then we make the cakes out of that and grill them, again, on the plancha. The chev goes really nicely with that.Suzy Chase: For my main course, I ordered the buttermilk poached chicken that's on page 205. I don't think I've ever had poached chicken at a restaurant. I cannot tell you how buttery and moist it was. Describe this dish.Sarah Rich: Exactly. My husband and I met at a restaurant called Bouley, which is downtown in Tribeca, and this was actually something ... a technique that we learned there. Chicken on the menu ... even Evan's mom, she ordered the same dish. She came to the dinner as well and she said, "I never order chicken when I go out to eat.", and I think a lot of people feel that way because they're like, "Chicken. I make chicken all the time at home.", but this is a way to make chicken. It makes it, just like you said, very buttery. It's a beautiful texture. We take the breast and put it in a bag and add buttermilk, season it really nicely, and then you just poach it in a water bath really slowly and gently so that, that buttermilk, it's its own little warm bath for the chicken. It kind of permeates the meat, it gets that ... buttermilk has kind of a tangy saltiness to it, a richness to it that gets into the meat, makes it super tender. Then cooking it slowly like that just keeps it really, really nice and makes it buttery, like you said.Suzy Chase: The salted caramel panna cotta on page 240 was interesting and I thought the coffee was all the way through, but it was just the crumble that was the coffee.Sarah Rich: Yes. Yeah. I like ... with my desserts, texture is very important to me, and also I actually have a savory background. I make the desserts at Rich Table, but the majority of my training is on the savory side of things. I come to desserts from that perspective. For me, I think a lot of people make desserts that are overly sweet, really heavy and I like a little saltiness to what I do. Obviously, a little salt in the caramel panna cotta, and then the crunch from the coffee crumble, which gives ... a lot of people are afraid of bitter as a flavor, but I think bitter is a very useful tool, so I add a little bit of bitterness to kind of counter the sweetness of the caramel and then the whip cream kind of balances everything out and adds a little nice smooth texture as well.Suzy Chase: Last but not least. I don't drink coffee, I don't even like coffee, but your Rich Table coffee, knocked my socks off. The recipe's on page 278. Talk about this cup of deliciousness.Sarah Rich: When you come to San Francisco, one of the things that you do as a tourist, is you go to The Buena Vista Cafe, which is down near fisherman's wharf, and they make a classic Irish coffee and they do a fantastic job of it. We wanted to sort of put our own spin on that classic San Francisco cocktail. We use Fernet Branca, which is an Amaro, which is very, very popular out in San Francisco. In fact, when you are a line cook working in the city, that is what you drink at the end of a shift. Which, coming from New York, we had ... we didn't really know that, and so that was something that we learned being out in San Francisco. We included that in our Irish coffee and then we also add a little pistachio cream to it, which you can't .... pistachio and coffee go really wonderfully together and it's just such a sort of rich, luxurious ingredient to add that makes it really delicious. Nobody doesn't like the Rich coffee.Suzy Chase: I could literally drink this every day. It would make me a coffee drinker.Sarah Rich: Yeah, yeah. We had ... that is a common opinion. My mom is not a coffee drinker. She loves the Rich coffee. Evan's parents don't drink coffee too much. They love it. Anybody who has it loves the Rich coffee.Suzy Chase: You're traveling to a few different cities cooking out of this cookbook. How is it cooking in a different kitchen? Does it throw off your flow?Sarah Rich: For sure. That is always a difficult part of it because you're in your own kitchen, you're used to where things are you, you're used to how things are done. You don't have to run around searching for things because you know exactly what you're looking for, where to go. You've got the team that you're used to working with that ... working in a kitchen, it's kind of like being in a ballet. There's a little dance that you do in your movements and where you go and who you're dancing with, and so you don't have that sort of flow in a different kitchen. It's always challenging. We've done dinners in some of the nicest kitchens in the country and it's difficult to even in those. Yeah, it's a challenge, but it's also really fun. It's really fun to see how other people experience your food and their reaction to it and especially working with cooks, how they react to your food or the questions they have. It's fun. It's challenging, but it's fun.Suzy Chase: You learned your techniques and flavors working at some of the best restaurants in the United States. Where did you and your husband, Evan, hone your skills?Sarah Rich: We definitely, like you said, we worked in some really great restaurants here in New York and then also out in California, and that's where you really, for sure, learn those basic techniques that you need to master how to be a good cook. Then when you ... we opened our restaurant. You sort of draw from those experiences and you draw from things that you've learned in terms of flavor and texture and how to put a dish together, and then you just sort of have to break free from just doing what you're comfortable with and start to kind of develop your own perspective. I guess what I mean is, when we first opened Rich Table and we were definitely drawing from all the places we've worked. Even, for example, the buttermilk poached chicken. That was a technique that we learned at Bouley, we brought it over to Rich Table. And then, years later, you sort of evolve and start really putting your own solid perspective into things.Suzy Chase: One thing I hate about fine dining is that you have to dress up. When my husband and I want to eat out in New York City, we don't want to dress up like it's prom. I'm so happy to see that you embrace a casual atmosphere with sort of fine dining level food.Sarah Rich: Right. Yeah. That is also very important to us. I mean we have the same experience and the same feeling. In fact, being back in the city, we've been eating around town and we notice that. We leave our hotel room and we're wearing jeans and a tank top and some sandals, and let's go in anywhere in San Francisco wouldn't be a problem, but here you walk in and you're like, "Oh my gosh, I'm clearly the least properly dressed person in this restaurant.". It is kind of, on one level, just sort of a California mentality. But it's also true that we don't like dressing up. Evan hates it more than anything. He just wants to be able to go as is, a button down or whatever, but feel ... he doesn't like that feeling of feeling uncomfortable when you walk into a space, and so we don't want our guests to feel that way either. We worked in so many restaurants where our friends want to come visit us, but they feel awkward, so they don't. We want ... It was really important to us to create a space where everybody felt welcome and Rich Table is like that. It can be an event kind of dinner. You can get dressed up. You can go to the opera, wear your nice dress, wear your nice suit, stop at Rich Table, have a meal, but you can also just go into the movies that night or maybe you just want to hang out at dinner and there is no dress code.Suzy Chase: I love that. In the cookbook you wrote, "We choose ingredients and put them together based on our understanding of what makes your pallets sing.". A couple of ingredients you love, are gelatin sheets, Douglas fir powder, isomalt, and pop sorghum. Describe a few of these.Sarah Rich: Yeah. That is an interesting grouping. Yes, we do use all of those things. Douglas fir is something that we really started using when we were doing ... Before we had opened Rich Table, we started doing popups, and we were trying to figure out menus and we would take these hikes through Marin and specifically, actually one of the first hikes we ever took was when Evan was ... he was interviewing for the chef de cuisine position at a restaurant called Quince, which is one of the best restaurants in San Francisco. At this point it has three Michelin stars, four star restaurant in the chronicle, it's a fantastic restaurant. He was trying to think of dishes to put together and we're wandering through hiking Mount Tamalpais and there are all these Douglas fir trees around and they've got their fresh springs shoots with these little tiny soft feathery green shoots.And we're picking those off and smelling them. Evan was like, "I think I'll use this in something.", and put together a dish and ended up getting the job, and was there for about a year. That's how we sort of discovered this flavor of Douglas fir, and so we started incorporating it into our dishes in our popups, and then later when we opened Rich Table. It's just something that ... it's just so California. It's just, to us, the flavor, the smell, all of those things just are very so much a part of our experience in California and so we love it. We use it in our bread, we use it in cocktails, I've used it in a desert, and it's ... a little bit goes a long way. You don't want the food to taste like a Christmas tree, but just that little essence of like tiny, citrusy quality is really nice. Then isomalt. We make lot of little tuiles, kind of like a cookie, crackery sort of thing. Very crunchy. Isomalt is a ... it's kind of like a type of sugar where it has the qualities of sugar when you cook it, so you can get that brittleness, but it doesn't have all of the sweetness. It's really useful in ... if you're making a savory tuile. You want it to sort of shatter like glass, like you could do if you made caramel, but it doesn't have that sweetness. The gelatin, we use to give body to things or to set things like panna cotta. And then, what was the other one?Suzy Chase: Popped sorghum.Sarah Rich: Oh, popped sorghum. Oh, that's a great one. Popped sorghum .... sorghum is a grain and it gets used ... a grass seed, sorry. It gets used a lot of times as a syrup in the south, but it also ... it's like a little tiny seed. You can actually buy the seeds online really easily at this point, and we pop it just like you pop popcorn. We get oil really hot, throw the seeds in and they pop just like tiny ... they really ... they look exactly like tiny, tiny popcorn. And so it's a fun little way to add a little texture. I keep coming back to that because the texture is just so important to us in our food. So it's a little crunch. It's actually a little bit nuttier than popcorn. It's really fun. Everybody who sees it is like, "Oh my God, tiny popcorn.", and I make it for my kids sometimes. I'll take it back home and just pop it. They love to see tiny popcorn. We've used it all over the place.Suzy Chase: Did you know there's a region in China, and they eat things just for the texture?Sarah Rich: I believe it.Suzy Chase: They prioritize the texture over the flavor.Sarah Rich: Yeah, yeah, for sure. It's a really important part of the enjoyment of the food, I think.Suzy Chase: You also wrote in the cookbook, "You have to understand, to a girl from a small southern town, there's this fascination with New York City. It's where life happens.". And I thought the very same thing growing up in Kansas, and now I live in New York City. What was it like for you coming to the big city to go to the French Culinary Institute?Sarah Rich: Oh, it was amazing. It was like a ... I don't want to say a dream come true because that sounds so cheesy, but it was a ... I never would have thought that I would have done that. I'm a pretty ... I was saying this to somebody the other day. I'm a pretty shy kind of quiet person and not super brave about things like that, and I don't think it was something that anybody would have expected of me. There were plenty of people, when I told them I was moving to New York, they laughed at me and they said, "You'll never make it. That city's gonna eat you up.", and it was really fulfilling a dream. It really was. We used to watch these movies. Like I say in the book, Working Girl, and Melanie Griffith is on the Staten Island ferry looking into Manhattan, and it just seemed like such a vibrant, exciting place where you could make anything happen. And it was that. That's exactly what it was for me. I remember moving to the city, I lived in Hoboken at the time and was going to the French Culinary Institute in Soho and it was so exciting to take the path train and walk from the World Trade Center up to Soho. I tried to walk as much as I wanted to or could so I could see everything. Working down in Tribeca, later at Bouley. It was amazing. It was everything that I wanted it to be.Suzy Chase: I just posted something on Instagram telling about how I grew up in Prairie Village, Kansas and I would stay up late watching Saturday Night Live every weekend, and just the intro, I was like, everyone's asleep in Prairie Village, but everyone's out in New York City and was like, I'm missing something.Sarah Rich: Yes, exactly. People will sometimes have a young cook in their twenties or even early thirties, and they say, "Hey, I'm thinking about maybe moving to New York City for a while, what do you think?.", and I always say, "Do it. Do it now. Do it. Absolutely.". Because there's a point where you won't. There's a point where your life will have moved past the point where you're willing to take that leap. I 100% always encourage people to do it if it's something they want to do.Suzy Chase: Since your food is so unique, I can only imagine Rich Table, your restaurant in San Francisco, is too. Describe the space.Sarah Rich: It's actually a really lovely space. It's a corner restaurant and we have these huge windows that go floor to ceiling almost. It lets in the most wonderful lights. When ever we do photo shoots, the photographer is always just beside themselves with how great the lighting is. They almost never have to do any sort of tweaking. It's really warm and really just light and really nice. It's funny, when we first found the space, there were a number of people that were like, I don't know why you chose that space, because it's a little bit off from the main area of Hayes Valley and a little bit closer to the mission. But now people who are ... they want to know how did we find it? It's such an amazing space. They're a little jealous. But it's a corner space with big windows. You walk in and there's the host stand right there. A nice long bar over to your right, and then we've got an open kitchen. On the other side of the bar is where the pass is, where the chef stands and all the line cooks and the sous chefs are there on the hotline, cooking the food, passing it over to the chef. The service are coming up, picking up the food, taking it to tables. It's very vibrant and you feel that sort of energy throughout the entire space. We've got a banquette along one wall with long boards that go up to the ceiling that were from an old barn up in Petaluma. They were salvaged, and so those line the walls. Yeah. That's Rich Table.Suzy Chase: Now to my new segment called my last meal. If you had to place an order for your last supper on earth, what would it be?Sarah Rich: Oh, it's so easy. It would be a grilled steak with a fully loaded baked potato.Suzy Chase: Wow, that was fast. People are usually like, "Hmm.".Sarah Rich: No. You know what? Normally I would be. Normally, I'm terrible at answering questions like that because it's like, I don't know. I like this. I like that. What would it really be? But the last couple of times I have made myself a steak and a baked potato, I have thought this is just it. This is my last meal. Now I just know, that's it. There are many things to love. There are many meals to be had. There are many things that would satisfy me, but I really just think that's it.Suzy Chase: Where can we find you on the web, Social Media, and in San Francisco?Sarah Rich: We are found on Instagram @RichTable. It's just that simple. I am Sally Hurricane and Rich Table is located at 199 Gough Street, in San Francisco.Suzy Chase: And what's your website?Sarah Rich: RichTableSF.comSuzy Chase: It was so nice to meet you in person and taste food out of this glorious cookbook, and thanks for coming on cookery by the book podcast.Sarah Rich: Well, thank you so much for having me. It was fun talking to you.Suzy Chase: Subscribe in Apple podcasts, and while you're there, please take a moment to rate and review Cookery by the Book. You can also follow me on Instagram @CookerybytheBook. Twitter is IamSuzyChase and download your Kitchen Mix Tapes music to cook by, on Spotify at Cookery by the Book. Thanks for listening.

Darryl Lim grew up in San Francisco and saw first-hand the devastation that AIDS wrought on the city's gay community. In this podcast, Part 2 of Darryl's story, he talks about what it was like to watch friends and loved ones die of the disease and suffer the stigma of having it. He talks about his own experience with AIDS and what it was like, after living in a few other cities, to come back home to San Francisco. If you missed Part 1, please go back and listen. We recorded this podcast in Hayes Valley in August 2018. Film photography by Michelle Kilfeather

​Darryl Lim was born in San Francisco and raised in North Beach. In this podcast, Darryl, who is a skin care professional these days, shares the great things about his childhood, including cafes, bookstores, clubs, and the schools he went to. He talks about going to Esalen when he was 12, and the influence that hippies had on him. Check back Thursday for Part 2, when Darryl will talk about living with AIDS. We recorded this podcast in Hayes Valley in August 2018.  Film photography by Michelle Kilfeather

We'll head back to Googleville in the New Year. But first, THE INTERSECTION has a gift for you. It's the story of a San Francisco drag bar known for two things: owner Marlena (a.k.a. Gary) and her Christmas display of 1400 Santas. That is, until the bar closed in 2013. We captured the final days as fans and regulars grappled with the end of an era at this drag institution at the corner of Hayes & Octavia in the now upscale Hayes Valley neighborhood. "Marlena's Curtain Call" originally aired on KALW in June 2013.  Donate: paypal.me/THEINTERSECTION  // Hear more: www.theintersection.fm  // Twitter: @IntersectionFM // Facebook: fb.com/IntersectionFM --- Producer: David Boyer Editor: Ben Trefny Engineer: Chris Hoff and David Boyer Special thanks to Claire Schoen, who guided a newbie producer through the making of his first audio piece. 

San Francisco is full of stories. So many in fact that there is a new podcast called Storied:SF . Erin sat down at the Biergarten in the Hayes Valley neighborhood of San Francisco and talked with the creator/producer/host, Jeff Hunt who is capturing what's left of the heart and soul of the City by the bay. Download and listen in as Jeff shares a bit about his podcast as well as his own San Francisco story. #bitchplease #listensharerepeat #womanpodcaster Look at our new website! www.bitchtalkpodcast.comFollow us on Instagram, Facebook, and Twitter.........Or just shoot us an email --> therealbtpod@gmail.comSupport the showThanks for listening and for your support! We couldn't have reached 10 years, 700 episodes or Best of the Bay Best Podcast in 2022 & 2023 without your help! -- Be well, stay safe, Black Lives Matter, AAPI Lives Matter, and abortion is normal. -- Subscribe to our channel on YouTube for behind the scenes footage! Rate and review us wherever you listen to podcasts! Visit our website! www.bitchtalkpodcast.com Follow us on Instagram & Facebook Listen every Tuesday at 9 - 10 am on BFF.FM

San Francisco is full of stories. So many in fact that there is a new podcast called Storied:SF . Erin sat down at the Biergarten in the Hayes Valley neighborhood of San Francisco and talked with the creator/producer/host, Jeff Hunt who is capturing what's left of the heart and soul of the City by the bay. Download and listen in as Jeff shares a bit about his podcast as well as his own San Francisco story. #bitchplease #listensharerepeat #womanpodcaster   Look at our new website! www.bitchtalkpodcast.com Follow us on Instagram, Facebook, and Twitter......... Or just shoot us an email --> therealbtpod@gmail.com            

Shoutouts to all my listeners who called-in. Recorded from Hayes Valley, San Francisco, on the last day of my trip. I'm a little buzzed from two cups of coffee from Blue Bottle.

Episode 34 features executive chef Wilson Chan of Tsubasa Sushi, Hayes Valley's newest sushi restaurant. Subscribe to the Menu Stories podcast on menustories.com. Music provided by Ben Sound.

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Marlena's Curtain Call: a documentary remembering a Hayes Valley gay bar and community hub.

DOMA is overturned; and Marlena's Curtain Call: a documentary remembering a Hayes Valley gay bar and community hub.