Podcasts about Susquehanna

Benjamin is the Founder of cap.In this episode, we dive into how Cap aims to unlock a new era of scalable stablecoin yield generation on Ethereum and MegaETH, by tapping into competitive markets and institutional players like Susquehanna, Franklin Templeton, and potentially DeFi powerhouses like Ethena and Maker.------

No, there isn't a salmon run on the Susquehanna, but you CAN get really fresh (frozen) salmon in central PA!  A couple episodes back, we talked about the five pound box of frozen haddock. This time, I talked to the people who actually catch sockeye salmon (and rockfish, and cod, and the big king salmon) up in Alaska, fillet and freeze them, and bring them back to us, wild-caught, and next best to fresh. I interviewed Captain Steve Kurian of Bloomsburg's Wild For Salmon and also talked to two other area fishermen, Captain Dan Brigham of Capt'n Dan's Wild Caught Alaskan Salmon, and Ron Rovansek of Bellefonte's Kodiak Rush. Bring your weather gear, this interview is like being out on the boat! What else? With a story like this, I had to cook some salmon! And I did, on my new soapstone insert for my Kamado Joe grill. It worked like a charm, and I cooked Wild For Salmon sockeye portions and fresh asparagus on it, and baked two local potatoes on the grill. Great meal!  'That's great,' I hear you say, 'But what about the drinks!' I sampled Elk Creek Cafe's new Valley Vista Cream Ale, and I also got in a plug for my friend John Holl's podcast This Week in Rauchbier, the world's most important podcast about smoked beer. Listen to it, I beseech you! Next episode? Got a lot of choices for a change -- got four interviews in the can, doing another one tomorrow night! -- but I think we're going to go with a food producer who's way back in the Pennsylvania Wilds. You've probably seen their stuff. See you again in two weeks! Until then? TELL YOUR FRIENDS ABOUT THE PODCAST! Seen Through A Glass is sponsored by the Happy Valley Adventure Bureau. Come visit Centre County!   This episode uses these sounds under the following license: Creative Commons CC BY 4.0 https://creativecommons.org/licenses/by/4.0/ "Champ de tournesol" by Komiku at https://www.chosic.com/free-music/all/ arrow-impact-87260 Sound Effect found on Pixabay (https://pixabay.com) "Glow" by Scott Buckley | www.scottbuckley.com.au Music promoted by https: //www.chosic.com/free-music/all/ All sounds sourced by STAG Music Librarian Nora Bryson, with our thanks.

Susquehanna | Son of a Boy Dad #287 -- #Ad: Go to the App Store and download the free Experian app now! -- #Ad: Go to https://vuori.com/BOYDAD for 20% off your first purchase. Exclusions apply. Visit the website for full terms and conditions. -- #Ad: Gambling problem? Call 1-800-GAMBLER (MI/NJ/PA/WV). Help is available for problem gambling, call (888) 789-7777 or visit ccpg.org (CT). 21+. Physically present in CT/MI/NJ/PA/WV only. Void in ONT. Eligibility restrictions apply. 1 per new customer. Opt-in req. Min. net loss of $5 on eligible games to earn 100% of net losses back (“Lossback”) for 24 hours following opt-in. Max. $1,000 issued in Casino Credits for select games that are non-withdrawable, single-use, have no cash value, and expire in 7 days (168 hours). Terms: casino.draftkings.com/promos. Ends 4/27/25 at 11:59 PM ET. Sponsored by DK. -- Follow us on our socials: https://linktr.ee/sonofaboydad -- Merch: https://store.barstoolsports.com/collections/son-of-a-boy-dad -- SUBSCRIBE TO THE YOUTUBE #SonOfABoyDad #BarstoolSportsYou can find every episode of this show on Apple Podcasts, Spotify or YouTube. Prime Members can listen ad-free on Amazon Music. For more, visit barstool.link/sonofaboydad

At the 40th anniversary of the TMI accident in 2019. Unit 1 in background was still in operation. This Week’s Featured Interview: Eric Epstein is the Chairman of Three Mile Island Alert, Inc., a safe-energy organization based in Harrisburg, Pennsylvania that was founded in 1977. TMIA monitors the Peach Bottom, Susquehanna, and Three Mile Island...

Former Ford CEO Mark Fields weighs in what the one-month delay in auto tariffs means for the stocks. Former Boston Fed President Eric Rosengren breaks down the Beige Book, jobs, and Fed policy after the latest economic data. Vital Knowledge's Adam Crisafulli and Wilmington Trust's Meghan Shue analyze the market landscape, and we cover key earnings from Marvell, MongoDB, Victoria's Secret, and Zscaler. Plus, Christopher Rolland of Susquehanna on Marvell's earnings. 

Welcome To the Bangin Beers! Sharing my love for the beer and spirits industry exploring the craft scene by trying new drinks and going on location to review Breweries, Bars, and more.ABJ Links:https://linktr.ee/anthonyblackwelljrhttps://www.sbcbeer.com/

Looking for a quick fix for their fast-growing electricity diets, tech giants are increasingly looking to strike deals with power plant owners to plug in directly, avoiding a long and expensive process of hooking into a fraying electric grid that serves everyone else. It's raising questions over whether diverting power to higher-paying customers will leave enough for others and whether it's fair to excuse big power users from paying for the grid. Federal regulators are trying to figure out what to do about it, and quickly. Front and center is the data center that Amazon's cloud computing subsidiary, Amazon Web Services (AWS), is building next to the Susquehanna nuclear plant in eastern Pennsylvania. The arrangement between the plant's owners and AWS is the first such to come before the Federal Energy Regulatory Commission (FERC). For now, FERC has rejected a deal that could eventually send 960 megawatts—about 40% of the plant's capacity—to the data center. That's enough to power more than a half-million homes. Big Tech also wants to stand up their centers fast. But tech's voracious appetite for energy comes at a time when the power supply is already strained by efforts to shift away from planet-warming fossil fuels. Plugging directly into a power plant would take years off their development timelines. The profit potential is one that other nuclear plant operators, in particular, are embracing after years of financial distress and frustration with how they are paid in the broader electricity markets. Many say they have been forced to compete in some markets against a flood of cheap natural gas as well as state-subsidized solar and wind energy. Power plant owners also say the arrangement benefits the wider public, by bypassing the costly buildout of long power lines and leaving more transmission capacity on the grid for everyone else. Susquehanna's owners say the data center won't be on the grid and shouldn't have to pay to maintain it. But critics contend that the power plant itself is benefiting from taxpayer subsidies and ratepayer-subsidized services, and shouldn't be able to strike deals with private customers that could increase costs for others. This article was provided by The Associated Press.

There has been a lot of information for the market to digest so far this year and rates volatility has drifted lower with the Fed on hold for now, while elevated US economic policy uncertainty has helped support VIX. In this edition of the All Options Considered podcast, BI's Chief Global Derivatives Strategist Tanvir Sandhuis joined byChris Murphy, Co-Head Derivative Strategy atSusquehanna, to discuss cross-asset volatility and flows. 

On this episode of Bet Your Ash, friend of the podcast and consummate Philadelphia sports fan Chris Rodgers returns to talk with Magee about the Eagles season and the Super Bowl run and his plans for the parade, and of course they check in with all the other Philly sports topics while he's on the show.  Tell us on IG, FB, and X.  Also, please check out all of the fine offerings available right now in the BYAPN SHOP.

In this episode, Matt welcomes Willson Cross, the co-founder and CEO of Borderless AI, to discuss how AI is transforming the global HR and payroll industry. Willson shares his entrepreneurial journey, from founding and selling GoFetch to launching Borderless AI. They explore how AI-driven compliance, payroll, and onboarding are solving key challenges in hiring global teams. Willson also talks about the company's $35M funding, its partnership with Cohere, and how they differentiate from major competitors like Deel and Rippling.About Willson Cross:Willson Cross is the Co-Founder and CEO of Borderless AI, a global payroll platform that uses generative AI to streamline hiring, managing, and paying international employees. Since launching in 2023, the company has raised $27 million from top investors, including Susquehanna and Bernard Arnault. Based in Toronto, Willson leads the team in building AI-powered solutions for the future of work.Before Borderless AI, Willson co-founded GoFetch, Canada's leading pet services marketplace. Starting from his basement in 2015, he grew the company to seven markets, raised $3.5 million, and led a team of 45 before selling the business in 2018. Earlier, he launched UBC Bitcoin Jobs, an online job board that connected university students with cryptocurrency startups, matching over 80 students to 20 companies.Originally from Vancouver, Willson studied economics at New York University before leaving after his third year to pursue startups full-time.⏱ Topics* (1:26) – Willson's background & founding GoFetch* (2:59) – Key lessons from running a bootstrapped startup* (4:55) – The transition to Borderless AI & identifying HR's biggest challenges* (6:33) – Payroll & benefits: The first major opportunities* (6:52) – Building real-time global payroll infrastructure* (7:50) – Meeting co-founder Sean Agarwal & forming a strong partnership* (9:45) – AI's role in HR compliance, payroll & automation* (12:04) – How Cohere's AI models enhance HRGPT* (15:48) – Competing with Deel & Rippling as an AI-native company* (18:19) – Pricing strategy & product differentiation* (19:13) – How AI is transforming HR roles* (20:47) – The shift toward larger early-stage funding rounds* (24:30) – Target customers: Startups & large enterprises* (27:41) – Why Borderless AI chose a full in-office model

The Susquehanna Art Museum is a non-collecting art museum. They also have multiple shows, and world class art that travel through Harrisburg. “We're located in Midtown, in the new Harrisburg Arts Corridor, and we are near the Broad Street Market and the Midtown Scholar. We are, as a non-collecting entity, we're always bringing something new, lots of something new, “said Alice Anne Schwab, Executive Director of the Susquehanna Art Museum. There are two exhibits that are opening on February 6. “One is called Wall Power. It's spectacular quilts from the American Folk Art Museum, which is located in New York City. We are bringing that show to Harrisburg. Additionally, we are bringing a show called There, like T -H -E -R -E, by Jordan Nasser, who is an artist who is really making quite a name for himself. He works in embroidery. He does cross -stitch, which sounds not necessarily like what you would think of as a major New York artist. He is Palestinian by his heritage, but he is actually making cross -stitch pieces using the skills and talents of some people who are living in Hebron, living in the Middle East, and he brings that sense of community together with a community building of embroidery. We have one piece that is 20 feet long. Think of that, an embroidery that's 20 feet long, “said Schwab. The exhibit will be available at the museum until May 11. According to Rachel Barron, Director of Education at the Susquehanna Art Museum, art education is important. “I believe that arts education is crucial for a well-rounded education. I often like to boil it down to creative problem-solving skills. Creating art really means constantly asking yourself questions and searching for solutions. And art also connects to so many other topics and subjects. For example, with Wall Power, the exciting quilt exhibition that we have opening today. The kids are going to be able to connect the quilts with geometry, with symmetrical, and pattern. And they're also going to have the opportunity to learn about Pennsylvania history, as well as local history, “said Barron.Support WITF: https://www.witf.org/support/give-now/See omnystudio.com/listener for privacy information.

A high-stakes earnings day with deep dives into major tech and consumer names. Sand Hill Global Advisors CIO Brenda Vingiello joins alongside CNBC's Mike Santoli to break down the market reaction. Alphabet, Snap, and AMD are in the spotlight, with expert analysis from Roth MKM's Rohit Kulkarni and Susquehanna's Christopher Rolland. Plus, a key conversation on the U.S. approach to digital assets with White House AI & Crypto Czar David Sacks. Also on the docket: Jon Fortt's exclusive sound from IBM's CEO. 

One last Gold sponsor slot is available for the AI Engineer Summit in NYC. Our last round of invites is going out soon - apply here - If you are building AI agents or AI eng teams, this will be the single highest-signal conference of the year for you!While the world melts down over DeepSeek, few are talking about the OTHER notable group of former hedge fund traders who pivoted into AI and built a remarkably profitable consumer AI business with a tiny team with incredibly cracked engineering team — Chai Research. In short order they have:* Started a Chat AI company well before Noam Shazeer started Character AI, and outlasted his departure.* Crossed 1m DAU in 2.5 years - William updates us on the pod that they've hit 1.4m DAU now, another +40% from a few months ago. Revenue crossed >$22m. * Launched the Chaiverse model crowdsourcing platform - taking 3-4 week A/B testing cycles down to 3-4 hours, and deploying >100 models a week.While they're not paying million dollar salaries, you can tell they're doing pretty well for an 11 person startup:The Chai Recipe: Building infra for rapid evalsRemember how the central thesis of LMarena (formerly LMsys) is that the only comprehensive way to evaluate LLMs is to let users try them out and pick winners?At the core of Chai is a mobile app that looks like Character AI, but is actually the largest LLM A/B testing arena in the world, specialized on retaining chat users for Chai's usecases (therapy, assistant, roleplay, etc). It's basically what LMArena would be if taken very, very seriously at one company (with $1m in prizes to boot):Chai publishes occasional research on how they think about this, including talks at their Palo Alto office:William expands upon this in today's podcast (34 mins in):Fundamentally, the way I would describe it is when you're building anything in life, you need to be able to evaluate it. And through evaluation, you can iterate, we can look at benchmarks, and we can say the issues with benchmarks and why they may not generalize as well as one would hope in the challenges of working with them. But something that works incredibly well is getting feedback from humans. And so we built this thing where anyone can submit a model to our developer backend, and it gets put in front of 5000 users, and the users can rate it. And we can then have a really accurate ranking of like which model, or users finding more engaging or more entertaining. And it gets, you know, it's at this point now, where every day we're able to, I mean, we evaluate between 20 and 50 models, LLMs, every single day, right. So even though we've got only got a team of, say, five AI researchers, they're able to iterate a huge quantity of LLMs, right. So our team ships, let's just say minimum 100 LLMs a week is what we're able to iterate through. Now, before that moment in time, we might iterate through three a week, we might, you know, there was a time when even doing like five a month was a challenge, right? By being able to change the feedback loops to the point where it's not, let's launch these three models, let's do an A-B test, let's assign, let's do different cohorts, let's wait 30 days to see what the day 30 retention is, which is the kind of the, if you're doing an app, that's like A-B testing 101 would be, do a 30-day retention test, assign different treatments to different cohorts and come back in 30 days. So that's insanely slow. That's just, it's too slow. And so we were able to get that 30-day feedback loop all the way down to something like three hours.In Crowdsourcing the leap to Ten Trillion-Parameter AGI, William describes Chai's routing as a recommender system, which makes a lot more sense to us than previous pitches for model routing startups:William is notably counter-consensus in a lot of his AI product principles:* No streaming: Chats appear all at once to allow rejection sampling* No voice: Chai actually beat Character AI to introducing voice - but removed it after finding that it was far from a killer feature.* Blending: “Something that we love to do at Chai is blending, which is, you know, it's the simplest way to think about it is you're going to end up, and you're going to pretty quickly see you've got one model that's really smart, one model that's really funny. How do you get the user an experience that is both smart and funny? Well, just 50% of the requests, you can serve them the smart model, 50% of the requests, you serve them the funny model.” (that's it!)But chief above all is the recommender system.We also referenced Exa CEO Will Bryk's concept of SuperKnowlege:Full Video versionOn YouTube. please like and subscribe!Timestamps* 00:00:04 Introductions and background of William Beauchamp* 00:01:19 Origin story of Chai AI* 00:04:40 Transition from finance to AI* 00:11:36 Initial product development and idea maze for Chai* 00:16:29 User psychology and engagement with AI companions* 00:20:00 Origin of the Chai name* 00:22:01 Comparison with Character AI and funding challenges* 00:25:59 Chai's growth and user numbers* 00:34:53 Key inflection points in Chai's growth* 00:42:10 Multi-modality in AI companions and focus on user-generated content* 00:46:49 Chaiverse developer platform and model evaluation* 00:51:58 Views on AGI and the nature of AI intelligence* 00:57:14 Evaluation methods and human feedback in AI development* 01:02:01 Content creation and user experience in Chai* 01:04:49 Chai Grant program and company culture* 01:07:20 Inference optimization and compute costs* 01:09:37 Rejection sampling and reward models in AI generation* 01:11:48 Closing thoughts and recruitmentTranscriptAlessio [00:00:04]: Hey everyone, welcome to the Latent Space podcast. This is Alessio, partner and CTO at Decibel, and today we're in the Chai AI office with my usual co-host, Swyx.swyx [00:00:14]: Hey, thanks for having us. It's rare that we get to get out of the office, so thanks for inviting us to your home. We're in the office of Chai with William Beauchamp. Yeah, that's right. You're founder of Chai AI, but previously, I think you're concurrently also running your fund?William [00:00:29]: Yep, so I was simultaneously running an algorithmic trading company, but I fortunately was able to kind of exit from that, I think just in Q3 last year. Yeah, congrats. Yeah, thanks.swyx [00:00:43]: So Chai has always been on my radar because, well, first of all, you do a lot of advertising, I guess, in the Bay Area, so it's working. Yep. And second of all, the reason I reached out to a mutual friend, Joyce, was because I'm just generally interested in the... ...consumer AI space, chat platforms in general. I think there's a lot of inference insights that we can get from that, as well as human psychology insights, kind of a weird blend of the two. And we also share a bit of a history as former finance people crossing over. I guess we can just kind of start it off with the origin story of Chai.William [00:01:19]: Why decide working on a consumer AI platform rather than B2B SaaS? So just quickly touching on the background in finance. Sure. Originally, I'm from... I'm from the UK, born in London. And I was fortunate enough to go study economics at Cambridge. And I graduated in 2012. And at that time, everyone in the UK and everyone on my course, HFT, quant trading was really the big thing. It was like the big wave that was happening. So there was a lot of opportunity in that space. And throughout college, I'd sort of played poker. So I'd, you know, I dabbled as a professional poker player. And I was able to accumulate this sort of, you know, say $100,000 through playing poker. And at the time, as my friends would go work at companies like ChangeStreet or Citadel, I kind of did the maths. And I just thought, well, maybe if I traded my own capital, I'd probably come out ahead. I'd make more money than just going to work at ChangeStreet.swyx [00:02:20]: With 100k base as capital?William [00:02:22]: Yes, yes. That's not a lot. Well, it depends what strategies you're doing. And, you know, there is an advantage. There's an advantage to being small, right? Because there are, if you have a 10... Strategies that don't work in size. Exactly, exactly. So if you have a fund of $10 million, if you find a little anomaly in the market that you might be able to make 100k a year from, that's a 1% return on your 10 million fund. If your fund is 100k, that's 100% return, right? So being small, in some sense, was an advantage. So started off, and the, taught myself Python, and machine learning was like the big thing as well. Machine learning had really, it was the first, you know, big time machine learning was being used for image recognition, neural networks come out, you get dropout. And, you know, so this, this was the big thing that's going on at the time. So I probably spent my first three years out of Cambridge, just building neural networks, building random forests to try and predict asset prices, right, and then trade that using my own money. And that went well. And, you know, if you if you start something, and it goes well, you You try and hire more people. And the first people that came to mind was the talented people I went to college with. And so I hired some friends. And that went well and hired some more. And eventually, I kind of ran out of friends to hire. And so that was when I formed the company. And from that point on, we had our ups and we had our downs. And that was a whole long story and journey in itself. But after doing that for about eight or nine years, on my 30th birthday, which was four years ago now, I kind of took a step back to just evaluate my life, right? This is what one does when one turns 30. You know, I just heard it. I hear you. And, you know, I looked at my 20s and I loved it. It was a really special time. I was really lucky and fortunate to have worked with this amazing team, been successful, had a lot of hard times. And through the hard times, learned wisdom and then a lot of success and, you know, was able to enjoy it. And so the company was making about five million pounds a year. And it was just me and a team of, say, 15, like, Oxford and Cambridge educated mathematicians and physicists. It was like the real dream that you'd have if you wanted to start a quant trading firm. It was like...swyx [00:04:40]: Your own, all your own money?William [00:04:41]: Yeah, exactly. It was all the team's own money. We had no customers complaining to us about issues. There's no investors, you know, saying, you know, they don't like the risk that we're taking. We could. We could really run the thing exactly as we wanted it. It's like Susquehanna or like Rintec. Yeah, exactly. Yeah. And they're the companies that we would kind of look towards as we were building that thing out. But on my 30th birthday, I look and I say, OK, great. This thing is making as much money as kind of anyone would really need. And I thought, well, what's going to happen if we keep going in this direction? And it was clear that we would never have a kind of a big, big impact on the world. We can enrich ourselves. We can make really good money. Everyone on the team would be paid very, very well. Presumably, I can make enough money to buy a yacht or something. But this stuff wasn't that important to me. And so I felt a sort of obligation that if you have this much talent and if you have a talented team, especially as a founder, you want to be putting all that talent towards a good use. I looked at the time of like getting into crypto and I had a really strong view on crypto, which was that as far as a gambling device. This is like the most fun form of gambling invented in like ever super fun, I thought as a way to evade monetary regulations and banking restrictions. I think it's also absolutely amazing. So it has two like killer use cases, not so much banking the unbanked, but everything else, but everything else to do with like the blockchain and, and you know, web, was it web 3.0 or web, you know, that I, that didn't, it didn't really make much sense. And so instead of going into crypto, which I thought, even if I was successful, I'd end up in a lot of trouble. I thought maybe it'd be better to build something that governments wouldn't have a problem with. I knew that LLMs were like a thing. I think opening. I had said they hadn't released GPT-3 yet, but they'd said GPT-3 is so powerful. We can't release it to the world or something. Was it GPT-2? And then I started interacting with, I think Google had open source, some language models. They weren't necessarily LLMs, but they, but they were. But yeah, exactly. So I was able to play around with, but nowadays so many people have interacted with the chat GPT, they get it, but it's like the first time you, you can just talk to a computer and it talks back. It's kind of a special moment and you know, everyone who's done that goes like, wow, this is how it should be. Right. It should be like, rather than having to type on Google and search, you should just be able to ask Google a question. When I saw that I read the literature, I kind of came across the scaling laws and I think even four years ago. All the pieces of the puzzle were there, right? Google had done this amazing research and published, you know, a lot of it. Open AI was still open. And so they'd published a lot of their research. And so you really could be fully informed on, on the state of AI and where it was going. And so at that point I was confident enough, it was worth a shot. I think LLMs are going to be the next big thing. And so that's the thing I want to be building in, in that space. And I thought what's the most impactful product I can possibly build. And I thought it should be a platform. So I myself love platforms. I think they're fantastic because they open up an ecosystem where anyone can contribute to it. Right. So if you think of a platform like a YouTube, instead of it being like a Hollywood situation where you have to, if you want to make a TV show, you have to convince Disney to give you the money to produce it instead, anyone in the world can post any content they want to YouTube. And if people want to view it, the algorithm is going to promote it. Nowadays. You can look at creators like Mr. Beast or Joe Rogan. They would have never have had that opportunity unless it was for this platform. Other ones like Twitter's a great one, right? But I would consider Wikipedia to be a platform where instead of the Britannica encyclopedia, which is this, it's like a monolithic, you get all the, the researchers together, you get all the data together and you combine it in this, in this one monolithic source. Instead. You have this distributed thing. You can say anyone can host their content on Wikipedia. Anyone can contribute to it. And anyone can maybe their contribution is they delete stuff. When I was hearing like the kind of the Sam Altman and kind of the, the Muskian perspective of AI, it was a very kind of monolithic thing. It was all about AI is basically a single thing, which is intelligence. Yeah. Yeah. The more intelligent, the more compute, the more intelligent, and the more and better AI researchers, the more intelligent, right? They would speak about it as a kind of erased, like who can get the most data, the most compute and the most researchers. And that would end up with the most intelligent AI. But I didn't believe in any of that. I thought that's like the total, like I thought that perspective is the perspective of someone who's never actually done machine learning. Because with machine learning, first of all, you see that the performance of the models follows an S curve. So it's not like it just goes off to infinity, right? And the, the S curve, it kind of plateaus around human level performance. And you can look at all the, all the machine learning that was going on in the 2010s, everything kind of plateaued around the human level performance. And we can think about the self-driving car promises, you know, how Elon Musk kept saying the self-driving car is going to happen next year, it's going to happen next, next year. Or you can look at the image recognition, the speech recognition. You can look at. All of these things, there was almost nothing that went superhuman, except for something like AlphaGo. And we can speak about why AlphaGo was able to go like super superhuman. So I thought the most likely thing was going to be this, I thought it's not going to be a monolithic thing. That's like an encyclopedia Britannica. I thought it must be a distributed thing. And I actually liked to look at the world of finance for what I think a mature machine learning ecosystem would look like. So, yeah. So finance is a machine learning ecosystem because all of these quant trading firms are running machine learning algorithms, but they're running it on a centralized platform like a marketplace. And it's not the case that there's one giant quant trading company of all the data and all the quant researchers and all the algorithms and compute, but instead they all specialize. So one will specialize on high frequency training. Another will specialize on mid frequency. Another one will specialize on equity. Another one will specialize. And I thought that's the way the world works. That's how it is. And so there must exist a platform where a small team can produce an AI for a unique purpose. And they can iterate and build the best thing for that, right? And so that was the vision for Chai. So we wanted to build a platform for LLMs.Alessio [00:11:36]: That's kind of the maybe inside versus contrarian view that led you to start the company. Yeah. And then what was maybe the initial idea maze? Because if somebody told you that was the Hugging Face founding story, people might believe it. It's kind of like a similar ethos behind it. How did you land on the product feature today? And maybe what were some of the ideas that you discarded that initially you thought about?William [00:11:58]: So the first thing we built, it was fundamentally an API. So nowadays people would describe it as like agents, right? But anyone could write a Python script. They could submit it to an API. They could send it to the Chai backend and we would then host this code and execute it. So that's like the developer side of the platform. On their Python script, the interface was essentially text in and text out. An example would be the very first bot that I created. I think it was a Reddit news bot. And so it would first, it would pull the popular news. Then it would prompt whatever, like I just use some external API for like Burr or GPT-2 or whatever. Like it was a very, very small thing. And then the user could talk to it. So you could say to the bot, hi bot, what's the news today? And it would say, this is the top stories. And you could chat with it. Now four years later, that's like perplexity or something. That's like the, right? But back then the models were first of all, like really, really dumb. You know, they had an IQ of like a four year old. And users, there really wasn't any demand or any PMF for interacting with the news. So then I was like, okay. Um. So let's make another one. And I made a bot, which was like, you could talk to it about a recipe. So you could say, I'm making eggs. Like I've got eggs in my fridge. What should I cook? And it'll say, you should make an omelet. Right. There was no PMF for that. No one used it. And so I just kept creating bots. And so every single night after work, I'd be like, okay, I like, we have AI, we have this platform. I can create any text in textile sort of agent and put it on the platform. And so we just create stuff night after night. And then all the coders I knew, I would say, yeah, this is what we're going to do. And then I would say to them, look, there's this platform. You can create any like chat AI. You should put it on. And you know, everyone's like, well, chatbots are super lame. We want absolutely nothing to do with your chatbot app. No one who knew Python wanted to build on it. I'm like trying to build all these bots and no consumers want to talk to any of them. And then my sister who at the time was like just finishing college or something, I said to her, I was like, if you want to learn Python, you should just submit a bot for my platform. And she, she built a therapy for me. And I was like, okay, cool. I'm going to build a therapist bot. And then the next day I checked the performance of the app and I'm like, oh my God, we've got 20 active users. And they spent, they spent like an average of 20 minutes on the app. I was like, oh my God, what, what bot were they speaking to for an average of 20 minutes? And I looked and it was the therapist bot. And I went, oh, this is where the PMF is. There was no demand for, for recipe help. There was no demand for news. There was no demand for dad jokes or pub quiz or fun facts or what they wanted was they wanted the therapist bot. the time I kind of reflected on that and I thought, well, if I want to consume news, the most fun thing, most fun way to consume news is like Twitter. It's not like the value of there being a back and forth, wasn't that high. Right. And I thought if I need help with a recipe, I actually just go like the New York times has a good recipe section, right? It's not actually that hard. And so I just thought the thing that AI is 10 X better at is a sort of a conversation right. That's not intrinsically informative, but it's more about an opportunity. You can say whatever you want. You're not going to get judged. If it's 3am, you don't have to wait for your friend to text back. It's like, it's immediate. They're going to reply immediately. You can say whatever you want. It's judgment-free and it's much more like a playground. It's much more like a fun experience. And you could see that if the AI gave a person a compliment, they would love it. It's much easier to get the AI to give you a compliment than a human. From that day on, I said, okay, I get it. Humans want to speak to like humans or human like entities and they want to have fun. And that was when I started to look less at platforms like Google. And I started to look more at platforms like Instagram. And I was trying to think about why do people use Instagram? And I could see that I think Chai was, was filling the same desire or the same drive. If you go on Instagram, typically you want to look at the faces of other humans, or you want to hear about other people's lives. So if it's like the rock is making himself pancakes on a cheese plate. You kind of feel a little bit like you're the rock's friend, or you're like having pancakes with him or something, right? But if you do it too much, you feel like you're sad and like a lonely person, but with AI, you can talk to it and tell it stories and tell you stories, and you can play with it for as long as you want. And you don't feel like you're like a sad, lonely person. You feel like you actually have a friend.Alessio [00:16:29]: And what, why is that? Do you have any insight on that from using it?William [00:16:33]: I think it's just the human psychology. I think it's just the idea that, with old school social media. You're just consuming passively, right? So you'll just swipe. If I'm watching TikTok, just like swipe and swipe and swipe. And even though I'm getting the dopamine of like watching an engaging video, there's this other thing that's building my head, which is like, I'm feeling lazier and lazier and lazier. And after a certain period of time, I'm like, man, I just wasted 40 minutes. I achieved nothing. But with AI, because you're interacting, you feel like you're, it's not like work, but you feel like you're participating and contributing to the thing. You don't feel like you're just. Consuming. So you don't have a sense of remorse basically. And you know, I think on the whole people, the way people talk about, try and interact with the AI, they speak about it in an incredibly positive sense. Like we get people who say they have eating disorders saying that the AI helps them with their eating disorders. People who say they're depressed, it helps them through like the rough patches. So I think there's something intrinsically healthy about interacting that TikTok and Instagram and YouTube doesn't quite tick. From that point on, it was about building more and more kind of like human centric AI for people to interact with. And I was like, okay, let's make a Kanye West bot, right? And then no one wanted to talk to the Kanye West bot. And I was like, ah, who's like a cool persona for teenagers to want to interact with. And I was like, I was trying to find the influencers and stuff like that, but no one cared. Like they didn't want to interact with the, yeah. And instead it was really just the special moment was when we said the realization that developers and software engineers aren't interested in building this sort of AI, but the consumers are right. And rather than me trying to guess every day, like what's the right bot to submit to the platform, why don't we just create the tools for the users to build it themselves? And so nowadays this is like the most obvious thing in the world, but when Chai first did it, it was not an obvious thing at all. Right. Right. So we took the API for let's just say it was, I think it was GPTJ, which was this 6 billion parameter open source transformer style LLM. We took GPTJ. We let users create the prompt. We let users select the image and we let users choose the name. And then that was the bot. And through that, they could shape the experience, right? So if they said this bot's going to be really mean, and it's going to be called like bully in the playground, right? That was like a whole category that I never would have guessed. Right. People love to fight. They love to have a disagreement, right? And then they would create, there'd be all these romantic archetypes that I didn't know existed. And so as the users could create the content that they wanted, that was when Chai was able to, to get this huge variety of content and rather than appealing to, you know, 1% of the population that I'd figured out what they wanted, you could appeal to a much, much broader thing. And so from that moment on, it was very, very crystal clear. It's like Chai, just as Instagram is this social media platform that lets people create images and upload images, videos and upload that, Chai was really about how can we let the users create this experience in AI and then share it and interact and search. So it's really, you know, I say it's like a platform for social AI.Alessio [00:20:00]: Where did the Chai name come from? Because you started the same path. I was like, is it character AI shortened? You started at the same time, so I was curious. The UK origin was like the second, the Chai.William [00:20:15]: We started way before character AI. And there's an interesting story that Chai's numbers were very, very strong, right? So I think in even 20, I think late 2022, was it late 2022 or maybe early 2023? Chai was like the number one AI app in the app store. So we would have something like 100,000 daily active users. And then one day we kind of saw there was this website. And we were like, oh, this website looks just like Chai. And it was the character AI website. And I think that nowadays it's, I think it's much more common knowledge that when they left Google with the funding, I think they knew what was the most trending, the number one app. And I think they sort of built that. Oh, you found the people.swyx [00:21:03]: You found the PMF for them.William [00:21:04]: We found the PMF for them. Exactly. Yeah. So I worked a year very, very hard. And then they, and then that was when I learned a lesson, which is that if you're VC backed and if, you know, so Chai, we'd kind of ran, we'd got to this point, I was the only person who'd invested. I'd invested maybe 2 million pounds in the business. And you know, from that, we were able to build this thing, get to say a hundred thousand daily active users. And then when character AI came along, the first version, we sort of laughed. We were like, oh man, this thing sucks. Like they don't know what they're building. They're building the wrong thing anyway, but then I saw, oh, they've raised a hundred million dollars. Oh, they've raised another hundred million dollars. And then our users started saying, oh guys, your AI sucks. Cause we were serving a 6 billion parameter model, right? How big was the model that character AI could afford to serve, right? So we would be spending, let's say we would spend a dollar per per user, right? Over the, the, you know, the entire lifetime.swyx [00:22:01]: A dollar per session, per chat, per month? No, no, no, no.William [00:22:04]: Let's say we'd get over the course of the year, we'd have a million users and we'd spend a million dollars on the AI throughout the year. Right. Like aggregated. Exactly. Exactly. Right. They could spend a hundred times that. So people would say, why is your AI much dumber than character AIs? And then I was like, oh, okay, I get it. This is like the Silicon Valley style, um, hyper scale business. And so, yeah, we moved to Silicon Valley and, uh, got some funding and iterated and built the flywheels. And, um, yeah, I, I'm very proud that we were able to compete with that. Right. So, and I think the reason we were able to do it was just customer obsession. And it's similar, I guess, to how deep seek have been able to produce such a compelling model when compared to someone like an open AI, right? So deep seek, you know, their latest, um, V2, yeah, they claim to have spent 5 million training it.swyx [00:22:57]: It may be a bit more, but, um, like, why are you making it? Why are you making such a big deal out of this? Yeah. There's an agenda there. Yeah. You brought up deep seek. So we have to ask you had a call with them.William [00:23:07]: We did. We did. We did. Um, let me think what to say about that. I think for one, they have an amazing story, right? So their background is again in finance.swyx [00:23:16]: They're the Chinese version of you. Exactly.William [00:23:18]: Well, there's a lot of similarities. Yes. Yes. I have a great affinity for companies which are like, um, founder led, customer obsessed and just try and build something great. And I think what deep seek have achieved. There's quite special is they've got this amazing inference engine. They've been able to reduce the size of the KV cash significantly. And then by being able to do that, they're able to significantly reduce their inference costs. And I think with kind of with AI, people get really focused on like the kind of the foundation model or like the model itself. And they sort of don't pay much attention to the inference. To give you an example with Chai, let's say a typical user session is 90 minutes, which is like, you know, is very, very long for comparison. Let's say the average session length on TikTok is 70 minutes. So people are spending a lot of time. And in that time they're able to send say 150 messages. That's a lot of completions, right? It's quite different from an open AI scenario where people might come in, they'll have a particular question in mind. And they'll ask like one question. And a few follow up questions, right? So because they're consuming, say 30 times as many requests for a chat, or a conversational experience, you've got to figure out how to how to get the right balance between the cost of that and the quality. And so, you know, I think with AI, it's always been the case that if you want a better experience, you can throw compute at the problem, right? So if you want a better model, you can just make it bigger. If you want it to remember better, give it a longer context. And now, what open AI is doing to great fanfare is with projection sampling, you can generate many candidates, right? And then with some sort of reward model or some sort of scoring system, you can serve the most promising of these many candidates. And so that's kind of scaling up on the inference time compute side of things. And so for us, it doesn't make sense to think of AI is just the absolute performance. So. But what we're seeing, it's like the MML you score or the, you know, any of these benchmarks that people like to look at, if you just get that score, it doesn't really tell tell you anything. Because it's really like progress is made by improving the performance per dollar. And so I think that's an area where deep seek have been able to form very, very well, surprisingly so. And so I'm very interested in what Lama four is going to look like. And if they're able to sort of match what deep seek have been able to achieve with this performance per dollar gain.Alessio [00:25:59]: Before we go into the inference, some of the deeper stuff, can you give people an overview of like some of the numbers? So I think last I checked, you have like 1.4 million daily active now. It's like over 22 million of revenue. So it's quite a business.William [00:26:12]: Yeah, I think we grew by a factor of, you know, users grew by a factor of three last year. Revenue over doubled. You know, it's very exciting. We're competing with some really big, really well funded companies. Character AI got this, I think it was almost a $3 billion valuation. And they have 5 million DAU is a number that I last heard. Torquay, which is a Chinese built app owned by a company called Minimax. They're incredibly well funded. And these companies didn't grow by a factor of three last year. Right. And so when you've got this company and this team that's able to keep building something that gets users excited, and they want to tell their friend about it, and then they want to come and they want to stick on the platform. I think that's very special. And so last year was a great year for the team. And yeah, I think the numbers reflect the hard work that we put in. And then fundamentally, the quality of the app, the quality of the content, the quality of the content, the quality of the content, the quality of the content, the quality of the content. AI is the quality of the experience that you have. You actually published your DAU growth chart, which is unusual. And I see some inflections. Like, it's not just a straight line. There's some things that actually inflect. Yes. What were the big ones? Cool. That's a great, great, great question. Let me think of a good answer. I'm basically looking to annotate this chart, which doesn't have annotations on it. Cool. The first thing I would say is this is, I think the most important thing to know about success is that success is born out of failures. Right? Through failures that we learn. You know, if you think something's a good idea, and you do and it works, great, but you didn't actually learn anything, because everything went exactly as you imagined. But if you have an idea, you think it's going to be good, you try it, and it fails. There's a gap between the reality and expectation. And that's an opportunity to learn. The flat periods, that's us learning. And then the up periods is that's us reaping the rewards of that. So I think the big, of the growth shot of just 2024, I think the first thing that really kind of put a dent in our growth was our backend. So we just reached this scale. So we'd, from day one, we'd built on top of Google's GCP, which is Google's cloud platform. And they were fantastic. We used them when we had one daily active user, and they worked pretty good all the way up till we had about 500,000. It was never the cheapest, but from an engineering perspective, man, that thing scaled insanely good. Like, not Vertex? Not Vertex. Like GKE, that kind of stuff? We use Firebase. So we use Firebase. I'm pretty sure we're the biggest user ever on Firebase. That's expensive. Yeah, we had calls with engineers, and they're like, we wouldn't recommend using this product beyond this point, and you're 3x over that. So we pushed Google to their absolute limits. You know, it was fantastic for us, because we could focus on the AI. We could focus on just adding as much value as possible. But then what happened was, after 500,000, just the thing, the way we were using it, and it would just, it wouldn't scale any further. And so we had a really, really painful, at least three-month period, as we kind of migrated between different services, figuring out, like, what requests do we want to keep on Firebase, and what ones do we want to move on to something else? And then, you know, making mistakes. And learning things the hard way. And then after about three months, we got that right. So that, we would then be able to scale to the 1.5 million DAE without any further issues from the GCP. But what happens is, if you have an outage, new users who go on your app experience a dysfunctional app, and then they're going to exit. And so your next day, the key metrics that the app stores track are going to be something like retention rates. And so your next day, the key metrics that the app stores track are going to be something like retention rates. Money spent, and the star, like, the rating that they give you. In the app store. In the app store, yeah. Tyranny. So if you're ranked top 50 in entertainment, you're going to acquire a certain rate of users organically. If you go in and have a bad experience, it's going to tank where you're positioned in the algorithm. And then it can take a long time to kind of earn your way back up, at least if you wanted to do it organically. If you throw money at it, you can jump to the top. And I could talk about that. But broadly speaking, if we look at 2024, the first kink in the graph was outages due to hitting 500k DAU. The backend didn't want to scale past that. So then we just had to do the engineering and build through it. Okay, so we built through that, and then we get a little bit of growth. And so, okay, that's feeling a little bit good. I think the next thing, I think it's, I'm not going to lie, I have a feeling that when Character AI got... I was thinking. I think so. I think... So the Character AI team fundamentally got acquired by Google. And I don't know what they changed in their business. I don't know if they dialed down that ad spend. Products don't change, right? Products just what it is. I don't think so. Yeah, I think the product is what it is. It's like maintenance mode. Yes. I think the issue that people, you know, some people may think this is an obvious fact, but running a business can be very competitive, right? Because other businesses can see what you're doing, and they can imitate you. And then there's this... There's this question of, if you've got one company that's spending $100,000 a day on advertising, and you've got another company that's spending zero, if you consider market share, and if you're considering new users which are entering the market, the guy that's spending $100,000 a day is going to be getting 90% of those new users. And so I have a suspicion that when the founders of Character AI left, they dialed down their spending on user acquisition. And I think that kind of gave oxygen to like the other apps. And so Chai was able to then start growing again in a really healthy fashion. I think that's kind of like the second thing. I think a third thing is we've really built a great data flywheel. Like the AI team sort of perfected their flywheel, I would say, in end of Q2. And I could speak about that at length. But fundamentally, the way I would describe it is when you're building anything in life, you need to be able to evaluate it. And through evaluation, you can iterate, we can look at benchmarks, and we can say the issues with benchmarks and why they may not generalize as well as one would hope in the challenges of working with them. But something that works incredibly well is getting feedback from humans. And so we built this thing where anyone can submit a model to our developer backend, and it gets put in front of 5000 users, and the users can rate it. And we can then have a really accurate ranking of like which model, or users finding more engaging or more entertaining. And it gets, you know, it's at this point now, where every day we're able to, I mean, we evaluate between 20 and 50 models, LLMs, every single day, right. So even though we've got only got a team of, say, five AI researchers, they're able to iterate a huge quantity of LLMs, right. So our team ships, let's just say minimum 100 LLMs a week is what we're able to iterate through. Now, before that moment in time, we might iterate through three a week, we might, you know, there was a time when even doing like five a month was a challenge, right? By being able to change the feedback loops to the point where it's not, let's launch these three models, let's do an A-B test, let's assign, let's do different cohorts, let's wait 30 days to see what the day 30 retention is, which is the kind of the, if you're doing an app, that's like A-B testing 101 would be, do a 30-day retention test, assign different treatments to different cohorts and come back in 30 days. So that's insanely slow. That's just, it's too slow. And so we were able to get that 30-day feedback loop all the way down to something like three hours. And when we did that, we could really, really, really perfect techniques like DPO, fine tuning, prompt engineering, blending, rejection sampling, training a reward model, right, really successfully, like boom, boom, boom, boom, boom. And so I think in Q3 and Q4, we got, the amount of AI improvements we got was like astounding. It was getting to the point, I thought like how much more, how much more edge is there to be had here? But the team just could keep going and going and going. That was like number three for the inflection point.swyx [00:34:53]: There's a fourth?William [00:34:54]: The important thing about the third one is if you go on our Reddit or you talk to users of AI, there's like a clear date. It's like somewhere in October or something. The users, they flipped. Before October, the users... The users would say character AI is better than you, for the most part. Then from October onwards, they would say, wow, you guys are better than character AI. And that was like a really clear positive signal that we'd sort of done it. And I think people, you can't cheat consumers. You can't trick them. You can't b******t them. They know, right? If you're going to spend 90 minutes on a platform, and with apps, there's the barriers to switching is pretty low. Like you can try character AI, you can't cheat consumers. You can't cheat them. You can't cheat them. You can't cheat AI for a day. If you get bored, you can try Chai. If you get bored of Chai, you can go back to character. So the users, the loyalty is not strong, right? What keeps them on the app is the experience. If you deliver a better experience, they're going to stay and they can tell. So that was the fourth one was we were fortunate enough to get this hire. He was hired one really talented engineer. And then they said, oh, at my last company, we had a head of growth. He was really, really good. And he was the head of growth for ByteDance for two years. Would you like to speak to him? And I was like, yes. Yes, I think I would. And so I spoke to him. And he just blew me away with what he knew about user acquisition. You know, it was like a 3D chessswyx [00:36:21]: sort of thing. You know, as much as, as I know about AI. Like ByteDance as in TikTok US. Yes.William [00:36:26]: Not ByteDance as other stuff. Yep. He was interviewing us as we were interviewing him. Right. And so pick up options. Yeah, exactly. And so he was kind of looking at our metrics. And he was like, I saw him get really excited when he said, guys, you've got a million daily active users and you've done no advertising. I said, correct. And he was like, that's unheard of. He's like, I've never heard of anyone doing that. And then he started looking at our metrics. And he was like, if you've got all of this organically, if you start spending money, this is going to be very exciting. I was like, let's give it a go. So then he came in, we've just started ramping up the user acquisition. So that looks like spending, you know, let's say we're spending, we started spending $20,000 a day, it looked very promising than 20,000. Right now we're spending $40,000 a day on user acquisition. That's still only half of what like character AI or talkie may be spending. But from that, it's sort of, we were growing at a rate of maybe say, 2x a year. And that got us growing at a rate of 3x a year. So I'm growing, I'm evolving more and more to like a Silicon Valley style hyper growth, like, you know, you build something decent, and then you canswyx [00:37:33]: slap on a huge... You did the important thing, you did the product first.William [00:37:36]: Of course, but then you can slap on like, like the rocket or the jet engine or something, which is just this cash in, you pour in as much cash, you buy a lot of ads, and your growth is faster.swyx [00:37:48]: Not to, you know, I'm just kind of curious what's working right now versus what surprisinglyWilliam [00:37:52]: doesn't work. Oh, there's a long, long list of surprising stuff that doesn't work. Yeah. The surprising thing, like the most surprising thing, what doesn't work is almost everything doesn't work. That's what's surprising. And I'll give you an example. So like a year and a half ago, I was working at a company, we were super excited by audio. I was like, audio is going to be the next killer feature, we have to get in the app. And I want to be the first. So everything Chai does, I want us to be the first. We may not be the company that's strongest at execution, but we can always be theswyx [00:38:22]: most innovative. Interesting. Right? So we can... You're pretty strong at execution.William [00:38:26]: We're much stronger, we're much stronger. A lot of the reason we're here is because we were first. If we launched today, it'd be so hard to get the traction. Because it's like to get the flywheel, to get the users, to build a product people are excited about. If you're first, people are naturally excited about it. But if you're fifth or 10th, man, you've got to beswyx [00:38:46]: insanely good at execution. So you were first with voice? We were first. We were first. I only knowWilliam [00:38:51]: when character launched voice. They launched it, I think they launched it at least nine months after us. Okay. Okay. But the team worked so hard for it. At the time we did it, latency is a huge problem. Cost is a huge problem. Getting the right quality of the voice is a huge problem. Right? Then there's this user interface and getting the right user experience. Because you don't just want it to start blurting out. Right? You want to kind of activate it. But then you don't have to keep pressing a button every single time. There's a lot that goes into getting a really smooth audio experience. So we went ahead, we invested the three months, we built it all. And then when we did the A-B test, there was like, no change in any of the numbers. And I was like, this can't be right, there must be a bug. And we spent like a week just checking everything, checking again, checking again. And it was like, the users just did not care. And it was something like only 10 or 15% of users even click the button to like, they wanted to engage the audio. And they would only use it for 10 or 15% of the time. So if you do the math, if it's just like something that one in seven people use it for one seventh of their time. You've changed like 2% of the experience. So even if that that 2% of the time is like insanely good, it doesn't translate much when you look at the retention, when you look at the engagement, and when you look at the monetization rates. So audio did not have a big impact. I'm pretty big on audio. But yeah, I like it too. But it's, you know, so a lot of the stuff which I do, I'm a big, you can have a theory. And you resist. Yeah. Exactly, exactly. So I think if you want to make audio work, it has to be a unique, compelling, exciting experience that they can't have anywhere else.swyx [00:40:37]: It could be your models, which just weren't good enough.William [00:40:39]: No, no, no, they were great. Oh, yeah, they were very good. it was like, it was kind of like just the, you know, if you listen to like an audible or Kindle, or something like, you just hear this voice. And it's like, you don't go like, wow, this is this is special, right? It's like a convenience thing. But the idea is that if you can, if Chai is the only platform, like, let's say you have a Mr. Beast, and YouTube is the only platform you can use to make audio work, then you can watch a Mr. Beast video. And it's the most engaging, fun video that you want to watch, you'll go to a YouTube. And so it's like for audio, you can't just put the audio on there. And people go, oh, yeah, it's like 2% better. Or like, 5% of users think it's 20% better, right? It has to be something that the majority of people, for the majority of the experience, go like, wow, this is a big deal. That's the features you need to be shipping. If it's not going to appeal to the majority of people, for the majority of the experience, and it's not a big deal, it's not going to move you. Cool. So you killed it. I don't see it anymore. Yep. So I love this. The longer, it's kind of cheesy, I guess, but the longer I've been working at Chai, and I think the team agrees with this, all the platitudes, at least I thought they were platitudes, that you would get from like the Steve Jobs, which is like, build something insanely great, right? Or be maniacally focused, or, you know, the most important thing is saying no to, not to work on. All of these sort of lessons, they just are like painfully true. They're painfully true. So now I'm just like, everything I say, I'm either quoting Steve Jobs or Zuckerberg. I'm like, guys, move fast and break free.swyx [00:42:10]: You've jumped the Apollo to cool it now.William [00:42:12]: Yeah, it's just so, everything they said is so, so true. The turtle neck. Yeah, yeah, yeah. Everything is so true.swyx [00:42:18]: This last question on my side, and I want to pass this to Alessio, is on just, just multi-modality in general. This actually comes from Justine Moore from A16Z, who's a friend of ours. And a lot of people are trying to do voice image video for AI companions. Yes. You just said voice didn't work. Yep. What would make you revisit?William [00:42:36]: So Steve Jobs, he was very, listen, he was very, very clear on this. There's a habit of engineers who, once they've got some cool technology, they want to find a way to package up the cool technology and sell it to consumers, right? That does not work. So you're free to try and build a startup where you've got your cool tech and you want to find someone to sell it to. That's not what we do at Chai. At Chai, we start with the consumer. What does the consumer want? What is their problem? And how do we solve it? So right now, the number one problems for the users, it's not the audio. That's not the number one problem. It's not the image generation either. That's not their problem either. The number one problem for users in AI is this. All the AI is being generated by middle-aged men in Silicon Valley, right? That's all the content. You're interacting with this AI. You're speaking to it for 90 minutes on average. It's being trained by middle-aged men. The guys out there, they're out there. They're talking to you. They're talking to you. They're like, oh, what should the AI say in this situation, right? What's funny, right? What's cool? What's boring? What's entertaining? That's not the way it should be. The way it should be is that the users should be creating the AI, right? And so the way I speak about it is this. Chai, we have this AI engine in which sits atop a thin layer of UGC. So the thin layer of UGC is absolutely essential, right? It's just prompts. But it's just prompts. It's just an image. It's just a name. It's like we've done 1% of what we could do. So we need to keep thickening up that layer of UGC. It must be the case that the users can train the AI. And if reinforcement learning is powerful and important, they have to be able to do that. And so it's got to be the case that there exists, you know, I say to the team, just as Mr. Beast is able to spend 100 million a year or whatever it is on his production company, and he's got a team building the content, the Mr. Beast company is able to spend 100 million a year on his production company. And he's got a team building the content, which then he shares on the YouTube platform. Until there's a team that's earning 100 million a year or spending 100 million on the content that they're producing for the Chai platform, we're not finished, right? So that's the problem. That's what we're excited to build. And getting too caught up in the tech, I think is a fool's errand. It does not work.Alessio [00:44:52]: As an aside, I saw the Beast Games thing on Amazon Prime. It's not doing well. And I'mswyx [00:44:56]: curious. It's kind of like, I mean, the audience reading is high. The run-to-meet-all sucks, but the audience reading is high.Alessio [00:45:02]: But it's not like in the top 10. I saw it dropped off of like the... Oh, okay. Yeah, that one I don't know. I'm curious, like, you know, it's kind of like similar content, but different platform. And then going back to like, some of what you were saying is like, you know, people come to ChaiWilliam [00:45:13]: expecting some type of content. Yeah, I think it's something that's interesting to discuss is like, is moats. And what is the moat? And so, you know, if you look at a platform like YouTube, the moat, I think is in first is really is in the ecosystem. And the ecosystem, is comprised of you have the content creators, you have the users, the consumers, and then you have the algorithms. And so this, this creates a sort of a flywheel where the algorithms are able to be trained on the users, and the users data, the recommend systems can then feed information to the content creators. So Mr. Beast, he knows which thumbnail does the best. He knows the first 10 seconds of the video has to be this particular way. And so his content is super optimized for the YouTube platform. So that's why it doesn't do well on Amazon. If he wants to do well on Amazon, how many videos has he created on the YouTube platform? By thousands, 10s of 1000s, I guess, he needs to get those iterations in on the Amazon. So at Chai, I think it's all about how can we get the most compelling, rich user generated content, stick that on top of the AI engine, the recommender systems, in such that we get this beautiful data flywheel, more users, better recommendations, more creative, more content, more users.Alessio [00:46:34]: You mentioned the algorithm, you have this idea of the Chaiverse on Chai, and you have your own kind of like LMSYS-like ELO system. Yeah, what are things that your models optimize for, like your users optimize for, and maybe talk about how you build it, how people submit models?William [00:46:49]: So Chaiverse is what I would describe as a developer platform. More often when we're speaking about Chai, we're thinking about the Chai app. And the Chai app is really this product for consumers. And so consumers can come on the Chai app, they can come on the Chai app, they can come on the Chai app, they can interact with our AI, and they can interact with other UGC. And it's really just these kind of bots. And it's a thin layer of UGC. Okay. Our mission is not to just have a very thin layer of UGC. Our mission is to have as much UGC as possible. So we must have, I don't want people at Chai training the AI. I want people, not middle aged men, building AI. I want everyone building the AI, as many people building the AI as possible. Okay, so what we built was we built Chaiverse. And Chaiverse is kind of, it's kind of like a prototype, is the way to think about it. And it started with this, this observation that, well, how many models get submitted into Hugging Face a day? It's hundreds, it's hundreds, right? So there's hundreds of LLMs submitted each day. Now consider that, what does it take to build an LLM? It takes a lot of work, actually. It's like someone devoted several hours of compute, several hours of their time, prepared a data set, launched it, ran it, evaluated it, submitted it, right? So there's a lot of, there's a lot of, there's a lot of work that's going into that. So what we did was we said, well, why can't we host their models for them and serve them to users? And then what would that look like? The first issue is, well, how do you know if a model is good or not? Like, we don't want to serve users the crappy models, right? So what we would do is we would, I love the LMSYS style. I think it's really cool. It's really simple. It's a very intuitive thing, which is you simply present the users with two completions. You can say, look, this is from model one. This is from model two. This is from model three. This is from model A. This is from model B, which is better. And so if someone submits a model to Chaiverse, what we do is we spin up a GPU. We download the model. We're going to now host that model on this GPU. And we're going to start routing traffic to it. And we're going to send, we think it takes about 5,000 completions to get an accurate signal. That's roughly what LMSYS does. And from that, we're able to get an accurate ranking. And we're able to get an accurate ranking. And we're able to get an accurate ranking of which models are people finding entertaining and which models are not entertaining. If you look at the bottom 80%, they'll suck. You can just disregard them. They totally suck. Then when you get the top 20%, you know you've got a decent model, but you can break it down into more nuance. There might be one that's really descriptive. There might be one that's got a lot of personality to it. There might be one that's really illogical. Then the question is, well, what do you do with these top models? From that, you can do more sophisticated things. You can try and do like a routing thing where you say for a given user request, we're going to try and predict which of these end models that users enjoy the most. That turns out to be pretty expensive and not a huge source of like edge or improvement. Something that we love to do at Chai is blending, which is, you know, it's the simplest way to think about it is you're going to end up, and you're going to pretty quickly see you've got one model that's really smart, one model that's really funny. How do you get the user an experience that is both smart and funny? Well, just 50% of the requests, you can serve them the smart model, 50% of the requests, you serve them the funny model. Just a random 50%? Just a random, yeah. And then... That's blending? That's blending. You can do more sophisticated things on top of that, as in all things in life, but the 80-20 solution, if you just do that, you get a pretty powerful effect out of the gate. Random number generator. I think it's like the robustness of randomness. Random is a very powerful optimization technique, and it's a very robust thing. So you can explore a lot of the space very efficiently. There's one thing that's really, really important to share, and this is the most exciting thing for me, is after you do the ranking, you get an ELO score, and you can track a user's first join date, the first date they submit a model to Chaiverse, they almost always get a terrible ELO, right? So let's say the first submission they get an ELO of 1,100 or 1,000 or something, and you can see that they iterate and they iterate and iterate, and it will be like, no improvement, no improvement, no improvement, and then boom. Do you give them any data, or do you have to come up with this themselves? We do, we do, we do, we do. We try and strike a balance between giving them data that's very useful, you've got to be compliant with GDPR, which is like, you have to work very hard to preserve the privacy of users of your app. So we try to give them as much signal as possible, to be helpful. The minimum is we're just going to give you a score, right? That's the minimum. But that alone is people can optimize a score pretty well, because they're able to come up with theories, submit it, does it work? No. A new theory, does it work? No. And then boom, as soon as they figure something out, they keep it, and then they iterate, and then boom,Alessio [00:51:46]: they figure something out, and they keep it. Last year, you had this post on your blog, cross-sourcing the lead to the 10 trillion parameter, AGI, and you call it a mixture of experts, recommenders. Yep. Any insights?William [00:51:58]: Updated thoughts, 12 months later? I think the odds, the timeline for AGI has certainly been pushed out, right? Now, this is in, I'm a controversial person, I don't know, like, I just think... You don't believe in scaling laws, you think AGI is further away. I think it's an S-curve. I think everything's an S-curve. And I think that the models have proven to just be far worse at reasoning than people sort of thought. And I think whenever I hear people talk about LLMs as reasoning engines, I sort of cringe a bit. I don't think that's what they are. I think of them more as like a simulator. I think of them as like a, right? So they get trained to predict the next most likely token. It's like a physics simulation engine. So you get these like games where you can like construct a bridge, and you drop a car down, and then it predicts what should happen. And that's really what LLMs are doing. It's not so much that they're reasoning, it's more that they're just doing the most likely thing. So fundamentally, the ability for people to add in intelligence, I think is very limited. What most people would consider intelligence, I think the AI is not a crowdsourcing problem, right? Now with Wikipedia, Wikipedia crowdsources knowledge. It doesn't crowdsource intelligence. So it's a subtle distinction. AI is fantastic at knowledge. I think it's weak at intelligence. And a lot, it's easy to conflate the two because if you ask it a question and it gives you, you know, if you said, who was the seventh president of the United States, and it gives you the correct answer, I'd say, well, I don't know the answer to that. And you can conflate that with intelligence. But really, that's a question of knowledge. And knowledge is really this thing about saying, how can I store all of this information? And then how can I retrieve something that's relevant? Okay, they're fantastic at that. They're fantastic at storing knowledge and retrieving the relevant knowledge. They're superior to humans in that regard. And so I think we need to come up for a new word. How does one describe AI should contain more knowledge than any individual human? It should be more accessible than any individual human. That's a very powerful thing. That's superswyx [00:54:07]: powerful. But what words do we use to describe that? We had a previous guest on Exa AI that does search. And he tried to coin super knowledge as the opposite of super intelligence.William [00:54:20]: Exactly. I think super knowledge is a more accurate word for it.swyx [00:54:24]: You can store more things than any human can.William [00:54:26]: And you can retrieve it better than any human can as well. And I think it's those two things combined that's special. I think that thing will exist. That thing can be built. And I think you can start with something that's entertaining and fun. And I think, I often think it's like, look, it's going to be a 20 year journey. And we're in like, year four, or it's like the web. And this is like 1998 or something. You know, you've got a long, long way to go before the Amazon.coms are like these huge, multi trillion dollar businesses that every single person uses every day. And so AI today is very simplistic. And it's fundamentally the way we're using it, the flywheels, and this ability for how can everyone contribute to it to really magnify the value that it brings. Right now, like, I think it's a bit sad. It's like, right now you have big labs, I'm going to pick on open AI. And they kind of go to like these human labelers. And they say, we're going to pay you to just label this like subset of questions that we want to get a really high quality data set, then we're going to get like our own computers that are really powerful. And that's kind of like the thing. For me, it's so much like Encyclopedia Britannica. It's like insane. All the people that were interested in blockchain, it's like, well, this is this is what needs to be decentralized, you need to decentralize that thing. Because if you distribute it, people can generate way more data in a distributed fashion, way more, right? You need the incentive. Yeah, of course. Yeah. But I mean, the, the, that's kind of the exciting thing about Wikipedia was it's this understanding, like the incentives, you don't need money to incentivize people. You don't need dog coins. No. Sometimes, sometimes people get the satisfaction fro

Barbara Doran of BD8 Capital Partners and Crossmark Global Investments' Bob Doll give their playbook for the market as earnings ramp up. Earnings from CSX and Texas Instruments. Susquehanna's Christopher Rolland joins to dissect TXN earnings and the chip sector, while Sheila Kahyaoglu from Jefferies on Boeing Q4 preannouncement.Jon Fortt sits down exclusively with Twilio CEO Khozema Shipchandler on the company's new growth targets. Keith Rabois of Khosla Ventures on the Trump economy, Musk vs. Altman, and the future of Stargate. 

Straight From The Admissions Office: Insider Strategies For College ApplicationsIf you're looking for helpful tips and insights for the college admissions process, check out my book by clicking the links below:

We're down to the best two teams in Division III football, both of whom are playing their best games at the right time. Mount Union is certainly firing on all cylinders now on offense after some struggles during the regular season, and you'd be hard-pressed to find more than one thing that went wrong for North Central as they absolutely demolished Susquehanna. How did they get here? What do we do with the two weeks off? Who benefits more from that extra nine days? Soccer stadium for the Stagg Bowl -- is that really OK? We talk about all the key moments of the semifinals, plus take your questions in this edition of the podcast. We talk about the depth of the North Central running backs. We discuss the two-quarterback system for Mount Union and how it worked in key spots. And more. Plus, we can't forget that Cortland coach Curt Fitzpatrick is leaving D-III, and we talk about that move plus another, possibly bigger move, with one of the top defensive players in Division III this season going into the portal and coming out as a scholarship player with the University of Wisconsin. You know, UW-Madison. The one in the Big 10. And what has been our favorite semifinal games to cover/attend/watch?

The River Hawks coach Tom Perkovich joins us to talk Saturday's win in the NCAA Division III quarters over Bethel; the character of the River Hawks with two wins in the final seconds in the last two weeks; the 5th year guys coming back; what Drew Robinson means to the team; we talk a bit about Saturday's opponent North Central. The River Hawks face North Central at 3:30 est on Saturday.

Touchdown or no touchdown? Hold or no hold? Should the game have been over?  So many questions, and not the ones we would prefer to be asking about a game in the Division III football national quarterfinals. And yes, there were many questions about the final moments of the Bethel-Susquehanna game, and whether they should have been the final moments, so to break it all down, we talk to someone who was there on the sidelines taking it all in. Frank Rossi will have opinions, which shouldn't surprise anyone, but they may not be the opinions that others share. He'll talk us through the questions from the closing plays of Susquehanna's 24-21 win, one which sent the program back to the national semifinals for the first time since 1991. Plus, how hard-hitting was that North Central-Springfield game? Not just who got thrown out, but who got knocked out? How quickly can one adjust to seeing the spread option or triple option offenses up close and person like that, compared to in practice, and how did Mount Union practice and prepare for seeing it in Salisbury? And we welcome Keith McMillan back into the podcast as he went to Johns Hopkins and chatted with coach Dan Wodicka and some of the key players afterward.  Plus, we hand out game balls as we go through all four games and give our thoughts on three questions from listeners. three reader questions. Including the NESCAC, team GPAs, and more.

Steve talks about Beau Pribula into transfer portal, then we talk with Pro Football Hall of Famer Ray Didinger about the Eagles vs. Steelers game and Susquehanna linebacker Drew Robinson about the River Hawks' win in the Division III quarterfinals.

Drew joins Steve to talk about Saturday's win over Bethel (Mn.) in the Division III football playoffs. Drew tells about the last play; winning on the final play in each of the last two weeks; the group of graduate students that opted to return for this season.

The College Football Experience (@TCEonSGPN) on the Sports Gambling Podcast Network preview the upcoming college football week from the legendary Army Navy Rivalry "America's Game" to the FCS Playoffs, D2 Playoffs, D3 Playoffs and the two bowl games happening this week. Pick Dundee aka (@TheColbyD), Patty C (@PattyC831) & NC Nick (@NC__NicK) break down every single game and key in on their favorite plays for the weekend. Will Brian Newberry and the Navy Midshipmen get their first win over the Army Black Knights in three years? Will the Idaho Vandals be a live dog on Friday night against the Montana State Bobcats in Bozeman?Will Bill Belichek be the next head coach of the North Carolina Tar Heels? Will Ferris State continue to roll in the D2 ranks? Are the Jackson State Tigers and TC Taylor going to win their first Celebration Bowl against South Carolina State? Can the UC Davis Aggies and Lan Larison hit the road to Vermillion, South Dakota and grab a huge road victory for UC Davis? Are the Western Michigan Broncos and Lance Taylor going to to head into Montgomery, Alabama and upset Geo Lopez and the South Alabama Jaguars? We talk it all and more on this episode of The College Football Experience. 00:00 Introduction and Sponsorships 01:03 Opening Remarks and Banter 01:45 Football Should Never Be Played Indoors 02:08 Introducing the Hosts 03:19 Discussion on College Football Playoffs 06:02 Belichick at North Carolina Speculations 08:13 Coaching Changes and Portal Talk 12:40 Bracket Predictions and Analysis 29:42 FCS Playoff Preview 46:24 Mountain Union vs. Salisbury Showdown 47:12 Maryland Football Weekend 47:28 Salisbury's Upset Potential 48:19 Salisbury Memories and Dining Hall Critique 49:29 Betting and Predictions 50:44 Salisbury Steak Debate 51:58 Susquehanna vs. Bethel 55:46 Johns Hopkins vs. Mary Harden-Baylor 57:40 North Central vs. Springfield 59:37 Kaiser Seahawks vs. Benedictine 01:02:23 Morningside vs. Grand View 01:03:49 Army vs. Navy Classic 01:10:19 UC Davis vs. South Dakota 01:17:09 Western Michigan vs. South Alabama 01:20:17 Memphis vs. West Virginia 01:24:59 College Football Experience Wrap-Up JOIN the SGPN community #DegensOnlyExclusive Merch, Contests and Bonus Episodes ONLY on Patreon - https://sg.pn/patreonDiscuss with fellow degens on Discord - https://sg.pn/discordDownload The Free SGPN App - https://sgpn.appCheck out the Sports Gambling Podcast on YouTube - https://sg.pn/YouTubeCheck out our website - http://sportsgamblingpodcast.comSUPPORT us by supporting our partnersUnderdog Fantasy code SGPN - Up to $1000 in BONUS CASH - https://play.underdogfantasy.com/p-sgpnRithmm - Player Props and Picks - Free 7 day trial! http://sportsgamblingpodcast.com/rithmmRebet - Social sportsbook - 100% deposit match promo code SGPN in your app store! ADVERTISE with SGPNInterested in advertising? Contact sales@sgpn.io WATCH the Sports Gambling PodcastYouTube - https://sg.pn/YouTubeTwitch - https://sg.pn/TwitchFOLLOW The Sports Gambling Podcast On Social MediaTwitter - http://www.twitter.com/gamblingpodcastInstagram - http://www.instagram.com/sportsgamblingpodcastTikTok - https://www.tiktok.com/@gamblingpodcastFacebook - http://www.facebook.com/sportsgamblingpodcastFOLLOW The Hosts On Social MediaSean Green - http://www.twitter.com/seantgreenRyan Kramer - http://www.twitter.com/kramercentric Gambling problem? Call 1-800-GAMBLER CO, DC, IL, IN, LA, MD, MS, NJ, OH, PA, TN, VA, WV, WY Call 877-8-HOPENY or text HOPENY (467369) (NY) Call 1-800-327-5050 (MA)21+ to wager. Please Gamble Responsibly. Call 1-800-NEXT-STEP (AZ), 1-800-522-4700 (KS, NV), 1-800 BETS-OFF (IA), 1-800-270-7117 for confidential help (MI)

The College Football Experience (@TCEonSGPN) on the Sports Gambling Podcast Network preview the upcoming college football week from the legendary Army Navy Rivalry "America's Game" to the FCS Playoffs, D2 Playoffs, D3 Playoffs and the two bowl games happening this week. Pick Dundee aka (@TheColbyD), Patty C (@PattyC831) & NC Nick (@NC__NicK) break down every single game and key in on their favorite plays for the weekend. Will Brian Newberry and the Navy Midshipmen get their first win over the Army Black Knights in three years? Will the Idaho Vandals be a live dog on Friday night against the Montana State Bobcats in Bozeman?Will Bill Belichek be the next head coach of the North Carolina Tar Heels? Will Ferris State continue to roll in the D2 ranks? Are the Jackson State Tigers and TC Taylor going to win their first Celebration Bowl against South Carolina State? Can the UC Davis Aggies and Lan Larison hit the road to Vermillion, South Dakota and grab a huge road victory for UC Davis? Are the Western Michigan Broncos and Lance Taylor going to to head into Montgomery, Alabama and upset Geo Lopez and the South Alabama Jaguars? We talk it all and more on this episode of The College Football Experience. 00:00 Introduction and Sponsorships 01:03 Opening Remarks and Banter 01:45 Football Should Never Be Played Indoors 02:08 Introducing the Hosts 03:19 Discussion on College Football Playoffs 06:02 Belichick at North Carolina Speculations 08:13 Coaching Changes and Portal Talk 12:40 Bracket Predictions and Analysis 29:42 FCS Playoff Preview 46:24 Mountain Union vs. Salisbury Showdown 47:12 Maryland Football Weekend 47:28 Salisbury's Upset Potential 48:19 Salisbury Memories and Dining Hall Critique 49:29 Betting and Predictions 50:44 Salisbury Steak Debate 51:58 Susquehanna vs. Bethel 55:46 Johns Hopkins vs. Mary Harden-Baylor 57:40 North Central vs. Springfield 59:37 Kaiser Seahawks vs. Benedictine 01:02:23 Morningside vs. Grand View 01:03:49 Army vs. Navy Classic 01:10:19 UC Davis vs. South Dakota 01:17:09 Western Michigan vs. South Alabama 01:20:17 Memphis vs. West Virginia 01:24:59 College Football Experience Wrap-Up JOIN the SGPN community #DegensOnlyExclusive Merch, Contests and Bonus Episodes ONLY on Patreon - https://sg.pn/patreonDiscuss with fellow degens on Discord - https://sg.pn/discordDownload The Free SGPN App - https://sgpn.appCheck out the Sports Gambling Podcast on YouTube - https://sg.pn/YouTubeCheck out our website - http://sportsgamblingpodcast.comSUPPORT us by supporting our partnersUnderdog Fantasy code SGPN - Up to $1000 in BONUS CASH - https://play.underdogfantasy.com/p-sgpnRithmm - Player Props and Picks - Free 7 day trial! http://sportsgamblingpodcast.com/rithmmRebet - Social sportsbook - 100% deposit match promo code SGPN in your app store!ADVERTISE with SGPNInterested in advertising? Contact sales@sgpn.io Follow The College Experience & SGPN On Social MediaTwitter - https://twitter.com/TCEonSGPNInstagram - http://www.instagram.com/TCEonSGPNTikTok - https://www.tiktok.com/@TCEonSGPNYoutube - https://www.youtube.com/@TheCollegeExperienceFollow The Hosts On Social MediaColby Dant - http://www.twitter.com/thecolbydPatty C - https://twitter.com/PattyC831NC Nick - https://twitter.com/NC__NicK Gambling problem? Call 1-800-GAMBLER CO, DC, IL, IN, LA, MD, MS, NJ, OH, PA, TN, VA, WV, WY Call 877-8-HOPENY or text HOPENY (467369) (NY) Call 1-800-327-5050 (MA)21+ to wager. Please Gamble Responsibly. Call 1-800-NEXT-STEP (AZ), 1-800-522-4700 (KS, NV), 1-800 BETS-OFF (IA), 1-800-270-7117 for confidential help (MI)

The College Football Experience (@TCEonSGPN) on the Sports Gambling Podcast Network preview the upcoming college football week from the legendary Army Navy Rivalry "America's Game" to the FCS Playoffs, D2 Playoffs, D3 Playoffs and the two bowl games happening this week. Pick Dundee aka (@TheColbyD), Patty C (@PattyC831) & NC Nick (@NC__NicK) break down every single game and key in on their favorite plays for the weekend. Will Brian Newberry and the Navy Midshipmen get their first win over the Army Black Knights in three years? Will the Idaho Vandals be a live dog on Friday night against the Montana State Bobcats in Bozeman?Will Bill Belichek be the next head coach of the North Carolina Tar Heels? Will Ferris State continue to roll in the D2 ranks? Are the Jackson State Tigers and TC Taylor going to win their first Celebration Bowl against South Carolina State? Can the UC Davis Aggies and Lan Larison hit the road to Vermillion, South Dakota and grab a huge road victory for UC Davis? Are the Western Michigan Broncos and Lance Taylor going to to head into Montgomery, Alabama and upset Geo Lopez and the South Alabama Jaguars? We talk it all and more on this episode of The College Football Experience. 00:00 Introduction and Sponsorships 01:03 Opening Remarks and Banter 01:45 Football Should Never Be Played Indoors 02:08 Introducing the Hosts 03:19 Discussion on College Football Playoffs 06:02 Belichick at North Carolina Speculations 08:13 Coaching Changes and Portal Talk 12:40 Bracket Predictions and Analysis 29:42 FCS Playoff Preview 46:24 Mountain Union vs. Salisbury Showdown 47:12 Maryland Football Weekend 47:28 Salisbury's Upset Potential 48:19 Salisbury Memories and Dining Hall Critique 49:29 Betting and Predictions 50:44 Salisbury Steak Debate 51:58 Susquehanna vs. Bethel 55:46 Johns Hopkins vs. Mary Harden-Baylor 57:40 North Central vs. Springfield 59:37 Kaiser Seahawks vs. Benedictine 01:02:23 Morningside vs. Grand View 01:03:49 Army vs. Navy Classic 01:10:19 UC Davis vs. South Dakota 01:17:09 Western Michigan vs. South Alabama 01:20:17 Memphis vs. West Virginia 01:24:59 College Football Experience Wrap-Up JOIN the SGPN community #DegensOnlyExclusive Merch, Contests and Bonus Episodes ONLY on Patreon - https://sg.pn/patreonDiscuss with fellow degens on Discord - https://sg.pn/discordDownload The Free SGPN App - https://sgpn.appCheck out the Sports Gambling Podcast on YouTube - https://sg.pn/YouTubeCheck out our website - http://sportsgamblingpodcast.comSUPPORT us by supporting our partnersUnderdog Fantasy code SGPN - Up to $1000 in BONUS CASH - https://play.underdogfantasy.com/p-sgpnRithmm - Player Props and Picks - Free 7 day trial! http://sportsgamblingpodcast.com/rithmmRebet - Social sportsbook - 100% deposit match promo code SGPN in your app store! ADVERTISE with SGPNInterested in advertising? Contact sales@sgpn.io WATCH the Sports Gambling PodcastYouTube - https://sg.pn/YouTubeTwitch - https://sg.pn/TwitchFOLLOW The Sports Gambling Podcast On Social MediaTwitter - http://www.twitter.com/gamblingpodcastInstagram - http://www.instagram.com/sportsgamblingpodcastTikTok - https://www.tiktok.com/@gamblingpodcastFacebook - http://www.facebook.com/sportsgamblingpodcastFOLLOW The Hosts On Social MediaSean Green - http://www.twitter.com/seantgreenRyan Kramer - http://www.twitter.com/kramercentricGambling problem? Call 1-800-GAMBLER CO, DC, IL, IN, LA, MD, MS, NJ, OH, PA, TN, VA, WV, WY Call 877-8-HOPENY or text HOPENY (467369) (NY) Call 1-800-327-5050 (MA)21+ to wager. Please Gamble Responsibly. Call 1-800-NEXT-STEP (AZ), 1-800-522-4700 (KS, NV), 1-800 BETS-OFF (IA), 1-800-270-7117 for confidential help (MI)

The College Football Experience (@TCEonSGPN) on the Sports Gambling Podcast Network preview the upcoming college football week from the legendary Army Navy Rivalry "America's Game" to the FCS Playoffs, D2 Playoffs, D3 Playoffs and the two bowl games happening this week. Pick Dundee aka (@TheColbyD), Patty C (@PattyC831) & NC Nick (@NC__NicK) break down every single game and key in on their favorite plays for the weekend. Will Brian Newberry and the Navy Midshipmen get their first win over the Army Black Knights in three years? Will the Idaho Vandals be a live dog on Friday night against the Montana State Bobcats in Bozeman?Will Bill Belichek be the next head coach of the North Carolina Tar Heels? Will Ferris State continue to roll in the D2 ranks? Are the Jackson State Tigers and TC Taylor going to win their first Celebration Bowl against South Carolina State? Can the UC Davis Aggies and Lan Larison hit the road to Vermillion, South Dakota and grab a huge road victory for UC Davis? Are the Western Michigan Broncos and Lance Taylor going to to head into Montgomery, Alabama and upset Geo Lopez and the South Alabama Jaguars? We talk it all and more on this episode of The College Football Experience. 00:00 Introduction and Sponsorships 01:03 Opening Remarks and Banter 01:45 Football Should Never Be Played Indoors 02:08 Introducing the Hosts 03:19 Discussion on College Football Playoffs 06:02 Belichick at North Carolina Speculations 08:13 Coaching Changes and Portal Talk 12:40 Bracket Predictions and Analysis 29:42 FCS Playoff Preview 46:24 Mountain Union vs. Salisbury Showdown 47:12 Maryland Football Weekend 47:28 Salisbury's Upset Potential 48:19 Salisbury Memories and Dining Hall Critique 49:29 Betting and Predictions 50:44 Salisbury Steak Debate 51:58 Susquehanna vs. Bethel 55:46 Johns Hopkins vs. Mary Harden-Baylor 57:40 North Central vs. Springfield 59:37 Kaiser Seahawks vs. Benedictine 01:02:23 Morningside vs. Grand View 01:03:49 Army vs. Navy Classic 01:10:19 UC Davis vs. South Dakota 01:17:09 Western Michigan vs. South Alabama 01:20:17 Memphis vs. West Virginia 01:24:59 College Football Experience Wrap-Up JOIN the SGPN community #DegensOnlyExclusive Merch, Contests and Bonus Episodes ONLY on Patreon - https://sg.pn/patreonDiscuss with fellow degens on Discord - https://sg.pn/discordDownload The Free SGPN App - https://sgpn.appCheck out the Sports Gambling Podcast on YouTube - https://sg.pn/YouTubeCheck out our website - http://sportsgamblingpodcast.comSUPPORT us by supporting our partnersUnderdog Fantasy code SGPN - Up to $1000 in BONUS CASH - https://play.underdogfantasy.com/p-sgpnRithmm - Player Props and Picks - Free 7 day trial! http://sportsgamblingpodcast.com/rithmmRebet - Social sportsbook - 100% deposit match promo code SGPN in your app store! ADVERTISE with SGPNInterested in advertising? Contact sales@sgpn.io Follow The College Experience & SGPN On Social MediaTwitter - https://twitter.com/TCEonSGPNInstagram - http://www.instagram.com/TCEonSGPNTikTok - https://www.tiktok.com/@TCEonSGPNYoutube - https://www.youtube.com/@TheCollegeExperienceFollow The Hosts On Social MediaColby Dant - http://www.twitter.com/thecolbydPatty C - https://twitter.com/PattyC831NC Nick - https://twitter.com/NC__NicK Gambling problem? Call 1-800-GAMBLER CO, DC, IL, IN, LA, MD, MS, NJ, OH, PA, TN, VA, WV, WY Call 877-8-HOPENY or text HOPENY (467369) (NY) Call 1-800-327-5050 (MA)21+ to wager. Please Gamble Responsibly. Call 1-800-NEXT-STEP (AZ), 1-800-522-4700 (KS, NV), 1-800 BETS-OFF (IA), 1-800-270-7117 for confidential help (MI)

Susquehanna coach Tom Perkovich is back to discuss last week's win over Saint John's (Minn.) in the Division III football Round of 16 and this week's quarterfinal with Bethel (Minn.). We talk the River Hawks handling adversity last week; how they handle practice this late in the season; prepping for a playoff game at the Division III level and what to look for from Bethel. Saturday's game is at Noon at Susquehanna University in Selinsgrove. Come out and support the River Hawks: admission is $8 for adults and $4 for kids.

Michael Wann takes us on a journey through paradigms, synchro-mysticism, and the enigmatic Susquehanna River. Explore how shifting perceptions influence our reality, practical strategies to stay grounded amidst life's chaos, and the deconstruction of societal constructs like time, money, and government. Michael also shares personal stories of synchronicity, transformation, and the deep mysteries of the Susquehanna River, making this an episode filled with profound insights and inspiration. For more details, links, and resources mentioned in this episode, visit our website: thewayfwrd.com/podcast/paradigms-synchro-mysticism-the-susquehanna-mystery-with-michael-wann/ The Way Forward podcast is sponsored by: BIOPTIMIZERS: Struggling with deep sleep? Magnesium deficiency might be the culprit. Try Magnesium Breakthrough with all 7 forms of magnesium for better rest. Use promo code ALEC10 at bioptimizers.com/alec for 10% off!

Susquehanna football coach Tom Perkovich joins the show to talk the River Hawks' Division III playoff game with Hobart at noon on Saturday in Selinsgrove. Tickets here: https://suriverhawks.com/sports/2022/10/31/hometown-ticketing.aspx. Then Doug from Wellsboro calls to talk Senior Day at Beaver Stadium. Then we talk some college sports.

The River Hawks' coach joins the program to tell us about Susquehanna's successes this season ahead of Susquehanna's 2nd round Division III playoff game with Hobart in Selinsgrove at noon on Saturday. You can tickets here: https://suriverhawks.com/sports/2022/10/31/hometown-ticketing.aspx Or at the game Doug Arthur Field in Selinsgrove.

It's the postseason! Ted Baker sits down with Head Coach Kevin DeWall '00 to talk about the end of the regular season, the All-Liberty League awards and the Statesmen's NCAA tournament second round opponent, Susquehanna. The Hobart Football Podcast is recorded weekly during the season.   The podcast is available on HWSAthletics.com, Amazon Music, and Spotify. To help support Hobart Football, please join the Statesmen Athletic Association. Find Hobart Football on X: @HobartFootball; Facebook: facebook.com/HobartStatesmen; and Instagram: @HobartFootball.

On this very special episode of Bet Your Ash, Magee is joined by a legend.  Great coach, great dad, great friend, and all around great human, Chris Rodgers, joins the show for the first time to reminisce about a baseball game in Oakland, CA from the summer of 2001 and to discuss the state of Philadelphia sports in the Fall of 2024.  Ever catch a game at the Coliseum?  Tell us about it on X, IG, and FB!  And the holidays are coming, get presents for all your gambling buddies at the BYAPN SHOP!

LANCASTER REPORT: DINING ALONG THE SUSQUEHANNA. JIM   JIM MCTAGUE, FORMER WASHINGTON EDITOR, BARRONS. @MCTAGUEJ.  AUTHOR OF THE "MARTIN AND TWYLA BOUNDARY SERIES."  #FRIENDSOFHISTORYDEBATINGSOCIETY 1941 Lancaster PA

GOOD EVENING:The show begins in California watching Governor Gavin Newsom prepare for a White House run in 2028... 1917 Main Street LA CBS EYE ON THE WORLD WITH JOHN BATCHELOR FIRST HOUR 9:00-9:15 CALIFORNIA RISING: Newsom & Harris for Governor 2026. Bill Whalen, Hoover 9:15-9:30 Pacific Watch/Vegas Report: Sphere must work harder. @JCBliss 9:30-9:45 Small Business America: Optimism for 2025. Gene Marks @Guardian @PhillyInquirer 9:45-10:00 Small Business America: AI at Taco Bell. Gene Marks @Guardian @PhillyInquirer SECOND HOUR 10:00-10:15 NUKES: Ukraine talks of nuclear weapons. Henry Sokolski, NPEC 10:15-10:30 NUKES: What is SMR? Henry Sokolski, NPEC 10:30-10:45 ISS: Air Leak. Bob Zimmerman, BehindtheBlack.com 10:45-11:00 NASA: Cuts at JPL. Bob Zimmerman, BehindtheBlack.com THIRD HOUR 11:00-11:15 Reagan: His Life and Legend (Part 1/8) with Max Boot 11:15-11:30 Reagan: His Life and Legend (Part 2/8) 11:30-11:45 Reagan: His Life and Legend (Part 3/8) 11:45-12:00 Reagan: His Life and Legend (Part 4/8) FOURTH HOUR 12:00-12:15 ANTISEMITISM: MSCI & what is to be done? (Part 1/2) Richard Goldberg, FDD 12:15-12:30 ANTISEMITISM: MSCI & what is to be done? (Part 2/2) Richard Goldberg, FDD 12:30-12:45 Lancaster Report: Dining Along the Susquehanna. Jim McTague, former Washington editor, Barron's. @McTagueJ, Author of the "Martin and Twyla Boundary Series" #FriendsOfHistoryDebatingSociety 12:45-1:00 CANADA: 2025 Election Preview. Conrad Black, National Post

Welcome to episode 282 of The Cloud Pod, where the forecast is always cloudy! This week Justin, Ryan, and Matthew are happy to be joining you in the clouds versus watching election information. This week we're talking nuclear energy, AI Search tools, and all things Pre:Invent. Welcome, and thanks for joining us!  Titles we almost went with this week: The Cloud Pod Would Much Rather Record This Show Than Watch the Election Results IBM Comes for Your AI Dollars AWS Goes Limitless with the PostgreSQL Possibilities It is Upon Us the Pre-Invent Period and AWS Does Not Disappoint Amazon Loses Its Nuclear Superhero A big thanks to this week's sponsor: We're sponsorless! Want to get your brand, company, or service in front of a very enthusiastic group of cloud news seekers? You've come to the right place! Send us an email or hit us up on our slack channel for more info.  Follow Up 01:13 Energy regulators scrutinizing data center use reject Amazon bid  Late Friday, the Federal Energy Regulatory Commission rejected a proposal that would have allowed an Amazon data center to co-locate with an existing nuclear power plant in Pennsylvania.   The commission voted it down 2-1  FERC chairman Willie Phillips said that the commission should encourage the development of data centers and semiconductor manufacturing as national security and economic development priorities.   Commissioners Mark Christie and Lindsay See (both R) voted to reject the proposal, while Davis Rosner and Judy Change (D) didn't vote.  Talen Energy, who signed the agreement, drew challenges from neighboring utilities AEP and Exelon – who challenged the novel arrangement, arguing it would unfairly shift costs of running the broader grid to other consumers.  FERC's order found the region’s grid operator, PJM Interconnection, failed to show why the proposal was necessary and prove such a deal would be limited to the Susquehanna plant given the widespread interest in placing data centers next to power plants.  Talen said the ruling would have a chilling effect on the region’s economic development and it is weighing its options.  Will see what happens with Microsoft/Constellation energies plan to restart 3-Mile Island.  3:21 Justin – “It’s sort of sad because I kind like the idea of nuclear power to solve a bunch of problems, but it has to be done in the right way for sure.” General News   04:12  IT'S EARNINGS TIME!   04:22 IBM revenue misses, but execs say AI will drive future growth  This week, we have an additiona

On this episode of Schiffbauer Over Rocks, host Paul Schiffbauer Jr. sits down with Glenn Smith, Owner and Founder of Brewery Tours, to discuss how he turned a passion project into a business around beer that has brought hundreds of people to Central PA to experience what our local brewing culture has to offer. Glenn shares his journey of recognizing what the community was missing and creating unique beer experiences that showcase Pennsylvania's vibrant craft beer scene. Glenn and Paul dive into the challenges of scaling a business, the importance of staying flexible, and why embracing change is essential for growth. With offerings like Walk-a-Bout tours, Brew Bus tours, and specialty experiences such as Ales on the Rails and Sips on the Susquehanna, Brewery Tours brings people closer to the craft with guided tastings, behind-the-scenes access, and local anecdotes. Whether you're a craft beer enthusiast or simply curious to learn more, Glenn's insights into Pennsylvania's brewing culture and his approach to business will inspire you to pursue your own passion. Connect with Glenn Smith and Brewery Tours at: Website: www.UltimateCraftBeerExperience.com Facebook: @BreweryTours Instagram: @ultimatecraftbeerexperience Special thanks to our sponsor, Casta Cigars, offering a luxurious experience with their rare and aged tobacco blends. Visit them online at www.castacigars.com or stop by their shop in York, PA.

Author Robert John Andrews brings the 18th-century Susquehanna Valley to life in this Catamount Press novella, A Susquehanna Tale. This period of early American history is hard, where the rifle, tomahawk, and knife rule. It is a time of hope and loss, land-hungry settlers and the Iroquois; here, two men, frontier scout Alexander Tennant and pioneer Colonel William Montgomery discuss the stories of their lives and times. A Susquehanna Tale is discussed by Robert John Andrews and Sunbury Press Books founder Lawrence Knorr in this BookSpeak Network podcast. Retired after more than 40 years of pastoral work, including nearly three decades as head of the Grove Presbyterian Church in Danville, Pennsylvania, Andrews is a popular newspaper columnist, community and church leader, and public speaker on historical and spiritual topics. His first book, Nathaniel's Call won the First Book Award from the Presbyterian Writer's Guild, the first print-on-demand book so honored.  Danville remains Andrews' home, and he says he's learned to cherish this region's rich history and love the tale of its river.

The Susquehanna Retriever Clubs AKC Fall Hunt Test - EP119-62: Molly's presents the Pitboss Podcast #podcast #duckhunting #pitbosswaterfowl #gundog #seaduckhunting #hunttest #dogtraining https://www.mymollys.com https://www.crabstogo.com https://www.duckblindbistro.com https://www.duckwaterboats..com https://www.gunnerkennels.com https://www.turtlebox.com https://www.hevishot.com https://www.pitbosswaterfowl.com https://www.patreon.com/jeffcoats https://www.instagram.com/pitbosswaterfowl Email: jeff@pitbosswaterfowl.com Text Jeff: 410-937-4034 Text Karen: 410-459-9567 Thank you for Watching & Listening!! Jeff & Karen Coats

Most years, we dedicate some space on the website or some time in our podcast to really give newcomers to Division III football a bit of a primer as to how the playoffs are structured, how at-large bids are determined, the whole 10 yards. But this year, let's face it -- we're all newbies in some manner. Nobody has ever actually put together the Division III football bracket in this manner.  So, forget what you learned last year, or any of the previous 10 or more years. All that is out the window. You've been hearing about NPI -- the NCAA Power Index? If you've been hearing angry things, well, hey, we don't love the system either, but it's what we have, so we're going to give it to you straight. Patrick and Greg spend the top of the show detailing what we know about the 40-team playoff bracket, how it will be constructed, what it means to be a Top Eight seed and more. Then Logan Hansen will talk a little more about what goes into the NPI and how it's calculated, and lastly we'll take your questions in our mailbag segment, and there were a lot of questions, so we took several more than usual. Five teams clinched automatic bids to the playoffs this week as well, and save themselves from having to worry at all about NPI. That includes Susquehanna, and we'll talk with River Hawks coach Tom Perkovich in our Fast Five conversation. And we go through our usual run of high points from Region 1 through Region 6, Greg gets put on the spot about a swing state, Patrick does weather on the 8's, and more. The D3football.com podcast is a weekly in-season podcast by Patrick Coleman and Greg Thomas, which was started in 2007. New episodes are published weekly during the season.

Michael Wann is back to chat about his phase of nomadic experience and his dance between driving life and accepting life on life's terms. And we chat about Hispaniola and the mystery, the starboard synchrometer, natal charts, honoring the mystery of life, subtle freedom, and our relationship with the heavens.   We also touch on his recent trip to the Dominican, the history of Haiti, Astronomia, baseline reality, and understanding patterns in the natural world.   In the last part we get further into astro physics, precession, Trump and the Haiti thing, green language, Grounding consciousness, his upcoming classes, the 400 year cycle, the story going public about Susquehanna, false time, lunar time, and Hispaniola   mkwann@comcast.net https://linktr.ee/susquehannaalchemy   To gain access to the second half of show and our Plus feed for audio and podcast please clink the link http://www.grimericaoutlawed.ca/support.   For second half of video (when applicable and audio) go to our Substack and Subscribe. https://grimericaoutlawed.substack.com/ or to our Locals  https://grimericaoutlawed.locals.com/ or Rokfin www.Rokfin.com/Grimerica Patreon https://www.patreon.com/grimericaoutlawed   Our old eps with Michael: https://grimerica.ca/2019/01/26/ep327/ https://grimericaoutlawed.ca/podcast/24-michael-wann/   Support the show directly: https://grimerica.ca/support-2/ Outlawed Canadians YouTube Channel: https://www.youtube.com/@OutlawedCanadians Our Adultbrain Audiobook Podcast and Website: www.adultbrain.ca Our Audiobook Youtube Channel:  https://www.youtube.com/@adultbrainaudiobookpublishing/videos Darren's book www.acanadianshame.ca Check out our next trip/conference/meetup - Contact at the Cabin www.contactatthecabin.com Other affiliated shows: www.grimerica.ca The OG Grimerica Show www.Rokfin.com/Grimerica Our channel on free speech Rokfin Join the chat / hangout with a bunch of fellow Grimericans  Https://t.me.grimerica https://www.guilded.gg/chat/b7af7266-771d-427f-978c-872a7962a6c2?messageId=c1e1c7cd-c6e9-4eaf-abc9-e6ec0be89ff3   Get your Magic Mushrooms delivered from: Champignon Magique  Get Psychedelics online Leave a review on iTunes and/or Stitcher: https://itunes.apple.com/ca/podcast/grimerica-outlawed http://www.stitcher.com/podcast/grimerica-outlawed Sign up for our newsletter http://www.grimerica.ca/news SPAM Graham = and send him your synchronicities, feedback, strange experiences and psychedelic trip reports!! graham@grimerica.com InstaGRAM https://www.instagram.com/the_grimerica_show_podcast/  Purchase swag, with partial proceeds donated to the show www.grimerica.ca/swag Send us a postcard or letter http://www.grimerica.ca/contact/ ART - Napolean Duheme's site http://www.lostbreadcomic.com/  MUSIC Tru Northperception, Felix's Site sirfelix.bandcamp.com 

Legendary Susquehanna River guide, Joe Raymond, joins the pod

Happy Day, Friend! In this podcast episode I'm chatting with Erik Schlimmer about trauma, mental health, and healing. Erik is an award-winning provider who's held nearly 3,000 sessions with 120 individual clients. He possesses a Master's in Social Work with a Clinical Concentration, a Bachelor's in Speech Communication with a Public Speaking Concentration, and an Associate's in Wilderness Recreation Leadership and is a Colorado Licensed Clinical Social Worker (LCSW). Beyond being an LCSW, Erik is a Livingworks Suicide Prevention Responder, Empathia Black Swan Event Responder, American Red Cross Mental Health Responder, Gottman Institute Couples Counselor, National Alliance on Mental Illness Peer Support Specialist, and National Association of Social Workers Clinical Supervisor. He particularly enjoys working with veterans and active duty personnel. Erik served as an infantryman in the Army's 82nd Airborne Division during the Gulf War Era.When he's not in the office, Erik is in the wilderness. He has hiked 17,000 miles, summitted 2,700 mountains, mountain biked across the U.S. twice, and paddled the Susquehanna and Delaware rivers from source to sea. He has worked as a backcountry ranger, trail builder, bird catcher (you read that right), and outdoor education lecturer and field instructor. He's also a photographer – all the images here are his own.Erik's passion is making the world a better place, and he feels that's best done by helping others with their mental health. I hope you find this episode valuable! You can connect with Erik on his website. BIG favor - I would so appreciate it if you could take a moment to rate and review my show, and while you're at it click the subscribe button so you're alerted when new episodes are released. Remember, take time to pause, breath, and reflect. Until next time, keep shining out there!  ~ Athea Connect with me on IG, FB, X, and LinkedIn: @atheadavis or www.atheadavis.com

MRKT Matrix - Thursday, September 26th Dow jumps more than 250 points, S&P 500 closes higher to post fresh record (CNBC) Breaking down Micron's giant rally. Why JPMorgan thinks shares can jump nearly 90% (CNBC) Super Micro shares tumble 15% after DOJ reportedly opens probe into company (CNBC) Nvidia is missing key technology and could acquire these stocks to get it, says Susquehanna analyst (CNBC) Southwest pops after executives share plan to raise profits, airlines rise in sympathy (CNBC) David Tepper says the Fed has to cut rates at least two or three more times to keep credibility (CNBC) Silver Outshines Gold This Year. Why the Rally Isn't Over. (Barron's) --- Subscribe to our newsletter: https://riskreversalmedia.beehiiv.com/subscribe MRKT Matrix by RiskReversal Media is a daily AI powered podcast bringing you the top stories moving financial markets Story curation by RiskReversal, scripts by Perplexity Pro, voice by ElevenLabs

A surprise episode drop as we recorded earlier than we usually do! It was a busy running weekend with Tom & Diana running the Susquahanna 10k by @charmcityrun, Erin running the Ocean City NJ Half Marathon and Michael did a ridiculous amount of miles as he heads into Taper time for his upcoming race! We recap it all along with getting to our usual nonsense. We read a 5 star review, tell you what we're running for and end with something good! Erin also announces a her new adventure with @runningthroughbreastcancer The @paceyourself.itsjustcancer Podcast! . Chapters 0:00 Open 15:00 Erins Announcement 26:50 Susquehanna 10k/Half 51:30 OCNJ Half 1:18:58 Something Good . Come laugh with us as we share our running experiences and talk about everything from our favorite beer runs to our chafing nightmares. Tell us what YOU run for... Email us or leave a voice memo at WillRunForPodcast@gmail.com Find us on Facebook and Instagram @WillRunForPodcast Tag your pictures and stories @WillRunForPodcast and help grow our community.

Most of the discussions on the Alpha Exchange podcast consist of guests sharing views on market risk and portfolio construction. To be sure that leads the conversations down the path of monetary policy, positioning, inflation and growth. There's a great deal of consideration around the price of optionality and the correlation of assets. But what about insights on the nitty gritty of getting into option trades, being a liquidity provider to the Street and then risk managing those positions?  Enter, Kris Abdelmessih, who spent well more than a decade doing just that. Now the author of the Moontower Substack and the founder of Moontower.ai, Kris looks back at his time on the market making front, starting with his formative experience in the renowned Susquehanna training program and ultimately trading volatility at Parallax. We talk about how he sought micro-edge by maintaining sell-side relationships, getting into positions as cleanly as possible and then having a dispassionate process for unwinding trades for which the vol profile was no longer suitable to own. We also gain his insights on perils of trading off-the-run ETFs like those on natural gas and crude oil, with the April 2020 meltdown in the latter, an important case study. I hope you enjoy this episode of the Alpha Exchange, my conversation with Kris Abdelmessih.

Send us a textThis episode is sponsored by the Keystone Trails Association.Most people never know how much volunteer work goes into their favorite hiking trail. Countless hours are spent breaking trails, cutting back brush, moving rocks, building steps, preventing water erosion and blazing trails.Then, after the trail is built, even more hours are spent maintaining it. When wind knocks down trees, they need to be cleared out. When invasive species develop, they need to be removed. When the painted blazes fade, they need to be repainted. Hundreds of hours can go into a single trail. Now imagine, being responsible for maintaining hundreds of miles of trails throughout Pennsylvania. That's what the Keystone Trails Association does. Since 1956, KTA has worked hard to provide, protect, preserve and promote recreational hiking trails and hiking opportunities in Pennsylvania. The volunteer-directed public service organization is made up of a federation of membership organizations and individuals.2024 marks the 40th year of the organization's Trail Care Program. This incredible program helps maintain Pennsylvania's extensive system of hiking trails. They maintain trails like the Mid-State Trail, Chuck Keiper Trail, Allegheny Front Trail, Loyalsock Trail, Standing Stone Trail and a portion Appalachian Trail. But KTA is much more than just a trail maintenance club, it also serves as the statewide voice of the hiking trail community and trail advocate in the state capital. KTA also hosts a number of amazing events that include trail races, hiking weekends, first aid classes, backpacking trips, webinars, guided hikes and much more. I'm most excited about their upcoming Keystone Hiking and Outdoor Weekend from Oct. 18 to 20th in the Susquehanna Riverlands. During this three-day event, participants will have the opportunity to go on hikes, take classes, tour the Susquehanna, learn from outdoor experts, backpack and so much more.This exciting weekend gives participants the chance to explore, learn and connect in a stunning landscape. I'll be hosting a trivia and smores event at 8pm on Oct. 18th at the Susquehannock State Park Ballfield Pavilion. Come test out your knowledge of Pennsylvania's parks, forests, trails and waterways or just grab a smore!Be sure to visit KTA-hike.org to register and sign up for individual events.On this episode, I speak with Brook Lenker and Haley Feaster. Brook is the executive director and Haley is the manager of communications and development at KTA. Support the showVisit our website to listen to the podcast, download free outdoor kids' activities, learn more about our public lands and to purchase merch. Follow us on Instagram and Meta to stay connected. You can support the podcast by clicking “Support this show” in the podcast description to provide a monthly donation. Hosting, production and editing: Christian AlexandersenMusic: Jon SauerGraphics: Matt Davis

Multiple suburbs are seeing more and more mail thefts. A bridge over the Susquehanna will close for three years to be rebuilt. Gas prices went down. Finally, the scientific community is abuzz with excitement.

Short-seller Hindenburg Research brought down shares of Super Micro Computer with a scathing report. Susquehanna analyst Mehdi Hosseini discusses why he turned bearish months before. Learn more about your ad choices. Visit megaphone.fm/adchoices

Hello Friends and Followers! Today we air Season 4, Episode #028, Let's chew on the topic of what makes the Susquehanna river so Special... Here we gather up some PA insiders to give us the Scoop. Join: Adam Milstead, Dain Provins, Mike Reinhold and Abby Abbondanza!!! � Facebook page: @Rustyhookpodcast � John Rapp's YouTube channel:    / @wvrapp   � John Rapp's Twitch channel:   / wvrapp  . � John Rapp's Twitter Page:   / jkrappjr   Abby Abbondanza: � Facebook page:  / abbyabbondanzaoutdoors   � Instagram channel:  / abbyabbondanzafishing   � YouTube channel:   / @abbyabbondanzafishing1161   Adam Milstead: � Facebook page:  / adam.milstead.35   � Instagram channel:  / adammilstead   � YouTube channel:   / @str8yakd   Dain Provins: � Facebook page:  / dain.provins   Mike Rienhold � Facebook page:  / mike.reinhold.7   Rusty Hook Kayak Fishing Podcast is affiliated with these fine Businesses. If you're Looking for reviews, Kayak Fishing gear, accessories or equipment, or that adventure resort vacation... go check out: Big Lake Bait Company Feelfree Kayaks Westbrook Supply Co. West Virginia Kayak Anglers ACE Adventure Resort YakGadget ZPRO Lithium DuBro Fishing We are a proud affiliate of the Paddle N' Fin Podcast Paddle Media Group. Dubro Fishing Pelican Products ZPRO Lithium #kayakbassfishing | #WVKA |#WVKAYAKANGLERS | #NRS | #RustyHookPodcast | #payneoutdoors | #johnrapp | #feelfreekayaks | #yakgadget | #zprolithium | #DubroFishing | #WestbrookSupplyCo | #bendingbranches | #hummingbird | #PaddleNFin | #biglakebaitco | #aceadventureresort Want to create live streams like this? Check out StreamYard: https://streamyard.com/pal/d/65997418... Learn more about your ad choices. Visit megaphone.fm/adchoices

Todd Simkin is an Associate Director at Susquehanna International Group, a global quantitative trading firm comprised solely of internal capital that is known for its rigorous analytical approach to decision-making. Todd is also the CEO of Susquehanna Re, his latest role in a 27-year tenure at SIG that has spanned trading, strategic initiatives, and trader education. Our conversation covers the history of SIG alongside Todd's roles, trader development, the art and science of trading, risk management, recruiting talent, competitive advantages, luck, and strategic initiatives in venture capital, prediction markets, sports gambling, and reinsurance. Learn More Follow Ted on Twitter at @tseides or LinkedIn Subscribe to the mailing list Access Transcript with Premium Membership

Ewing Minor and Kristine Fishcer go 1-2 at the Bassmaster Kayak Series Susquehanna River event. This event always lives up to the hype and it turned into a true smallmouth bass shootout. Bassmaster Kayak Series Susquehanna River Nail Biter Kayak Bass Nation is the number one live kayak bass fishing podcast. Jeff and Ryan interview tournament winners, industry leaders, and a wide variety of other guests from around KB Nation! We cover kayak bass tournament fishing from all around the country including the Bassmaster Kayak Series, Hobie Bass Open Series, All American Kayak Series, and the large regional series. #kayakfishing #bassfishing  Click here to start your own live podcast: https://streamyard.com/pal/5789067434...   Presented by:  ECO FISHING SHOP https://ecofishingshop.com/   Western Son Vodka https://westernsondistillery.com   Sponsored by:  Pro Guide Batteries  https://proguidebatteries.com/ - USE CODE KBN to save 10%

Jake Harshman joins the Bass and Brews Podcast for the third year in a row to give you all the best tips and tactics to successfully fish the Susquehanna for bass.