Podcasts about Tinker

In this powerful exclusive interview, Bogdan Zaslavsky, father of Brayden Zaslavsky, breaks his silence after his son was viciously beaten by a violent anti-ICE mob at Olathe Northwest High School simply for holding a Trump flag.What started as student-led walk-outs quickly turned into chaos and violence — and instead of protecting students, Olathe Schools Superintendent Dr. Brent Yeager sent a letter to parents claiming these walk-outs are “protected free speech.”He is dead wrong.On this episode of The Right Side, Bogdan shares the horrifying details of the attack on Brayden, how school officials responded (or failed to respond), and why this must never happen again.We also break down the Tinker v. Des Moines Supreme Court ruling that proves disruptive walk-outs that lead to violence are NOT protected speech — and why Dr. Yeager and Principal Mr. Chris Zuck have a duty to ban them immediately.This is raw, emotional, and unfiltered truth from a father fighting for his son and for every child in the Olathe school district.✅ Timestamps:0:00 – Bogdan Zaslavsky shares what really happened to Brayden4:15 – The moment his son was attacked for holding the Trump flag8:40 – Dr. Brent Yeager's “free speech” letter exposed12:20 – Principal Chris Zuck's response (or lack of it)16:30 – What parents must do now – Call to ActionIf you live in Olathe, call Superintendent Dr. Yeager and the school board TODAY and demand real leadership and safety for our kids.Share this interview with every parent and teacher you know.The Right Side with Doug Billings — Unapologetic. Uncensored. America First.SUBSCRIBE and turn on notifications so you never miss an episode.Follow me:X: @DougBillingsRumble: The Right Side with Doug Billings#OlatheSchools #OlatheWalkOut #BraydenZaslavsky #BogdanZaslavsky #TrumpFlag #OlatheNorthwest #AntiICERiot #SchoolViolence #DrBrentYeager #ChrisZuck #FreeSpeechLie #ProtectOurKids #OlatheKS #AmericaFirst #Trump #America #KansasSupport the show

The median gym owner brings home $61,000 per year, but the owners on Two-Brain's latest leaderboard earn between $189,000 and $357,000 annually. What's the difference?In this episode, Mike Warkentin sits down with top earner Ryan McStockard to find out exactly how he secured his spot on the leaderboard.In 2020, Ryan took zero income in some months just to keep the gym alive. Then, in 2021, he invested in Two-Brain mentorship and rebuilt everything.Now he consistently earns over $16,000 per month from his gym.His biggest wins came from adding high-value services, such as personal training, and focusing on improving the client journey: Personal training makes up 34% of his revenue, and his clients stick around for a whopping 42 months on average. As a Two-Brain mentor, Ryan now helps other gym owners replicate his success.He's also in the Tinker Mastermind, where he's focused on maximizing his income and his lifestyle. His primary goal today is simply “to not miss family dinners.”Interested in becoming a Tinker? Email Joleen Bingham (leader of Tinker North America) or Lisa Palmer (leader of Tinker Europe) to learn more: joleen.bingham@twobrainbusiness.com or lisa.palmer@twobrainbusiness.comLinksGym Owners UnitedBook a Call1:07 - Gym overview & low point5:02 - Revenue breakdown7:24 - Finding Two-Brain20:52 - Additions to Ryan's NOB31:13 - Retention secret

In this hard-hitting 11-minute episode of The Right Side, Doug Billings reads Olathe (O-lay-thu) Kansas Public Schools Superintendent Dr. Brent Yeager's own parent letter back to him — word for word — and finishes the Supreme Court ruling from Tinker v. Des Moines that Dr. Yeager conveniently left out.Free speech does NOT protect mass student walkouts during class time, truancy, fights, or turning taxpayer-funded schools into political battlegrounds.Last Friday's walkout at Olathe Northwest High School ended with a juvenile arrest and injured students.Parents and taxpayers of Olathe and Johnson County: this is your moment.Demand the Olathe School Board immediately ban all mass walkouts during instructional hours.Education, NOT indoctrination.Timestamps:0:00 – Intro & The Crisis in Olathe1:45 – Reading Dr. Yeager's Letter4:20 – The FULL Tinker v. Des Moines Ruling7:10 – What the Law Actually Allows9:40 – Your Action Plan TonightCommentary & Opinion – February 24, 2026Full video version available on YouTube: @TheRightSideDougBillingsShare this episode with every parent you know.Tag Dr. Brent Yeager and the Olathe School Board.We're in this together, folks. Believe it. For the Republic!#OlatheSchools #BrentYeager #TinkerRuling #StudentWalkouts #Education #Indoctrination #Olathe #Taxpayers #KansasFirst #SchoolBoard #ParentsRights #Kansas #Students #Teachers #America #USASupport the show

The Smarter Way To Pick Winning Stocks  Podcast: Find out more about Blueberry Markets – Click Here Find out more about my Online Video Forex Course Book a Call with Andrew or one of his team now Click Here to Attend my Free Masterclass Checkout the Tykr Platform here. #624: The Smarter Way To Pick Winning Stocks In this video: 00:14 – Sean Tepper – found of TYKR 04:55 – How does this software help? 08:50 – TFTC also helps create successful traders 12:25 – Is social media helpful? 16:20 – Multiple brokers or one? 22:18 – TFTC creating a trading bot program 28:16 – 60,000 stocks analyzed 32:45 – Contact Sean Andrew Mitchem Hello, everybody. It’s Andrew Mitchem here at The Forex Trading Coach. And today I’m really pleased to be joined by Sean Tepper, who’s the founder and the CEO of Tykr. Welcome along. Sean. Sean Tepper Andrew. Good to be here. Andrew Mitchem Awesome to have you. Sean, could you introduce yourselves to everybody and let us know who you are and what you do and what we’re going to talk about? Sean Tepper – found of TYKR Sean Tepper Sure. Yeah. My name is Sean Tepper. I’m the founder of TYKR, as Andrew said. And long story short, TYKRs a platform that helps people buy and sell stocks with confidence prior to that. My background is about 20 years in tech, 15 years investing, and I kind of created TYKR as a solution to a frustration in the markets. Sean Tepper And we could dive into what that frustration is, if you’d like. Yeah. But yeah, I had to create a solution because it was very hard to make decisions when I first got started. And that’s where really TYKR came from. And, but yeah, fast forward to today. We’ve got a little over, 13,000 customers in about 50 countries, including where you’re based. Sean Tepper New Zealand. Andrew Mitchem Oh that’s good. Yeah. So you had 50 countries. That’s a that’s an awesome effort. And, and Sean, I was reading about, you know, you started, on your website says, in, you know, 2011 to 2015, you were trying to figure out what wasn’t there to help you. What did you find back then? Was the biggest frustration that led to TYKR happening? Sean Tepper Yeah. So when I first got started, you know, I think I joined E-Trade. And, you know, there’s so many brokers these days, it’s hard to keep track of. But as soon as I joined, I had no idea what to do next. So I started going on YouTube researching where do you go to invest? Like looking up different investing platforms? Sean Tepper I found a few of our competitors, like Seeking Alpha and Motley Fool, and they do a fine job, but it’s still very difficult to truly know the difference between a strong stock and a weak stock is is very frustrating. And for context, my background is in tech, but to go, layer deeper, it’s actually in process engineering. Sean Tepper Like I’ve worked a lot for GE and Koehler. And the rule is in process engineering, if you have 100 data points, you cannot present that to a customer or an executive. You have to roll it up to ideally a binary decision like yes or no or a traffic light. And I was complaining at that time, like, am I the only one complaining about the fact that there’s no process engineering lens layered over investing like, this is insane. Sean Tepper Like nobody’s making it easy. And that was kind of the green light I was thinking of, like, hey, if I could figure something out here, I think the big solution is a create a process engineering solution in the world of finance and apparently I’m the only one really doing that today, other than the few platforms that say buy or sell. Sean Tepper But I don’t really recommend that. But yeah, that was that was the beginning. And it took about a year to build this Excel sheets. And I give you context here, I found a lot of inspiration from Phil Towne. He wrote a few books on value investing. Do you know Phil Towne? Andrew Mitchem No, I don’t know. No. Okay. Sean Tepper Your your audience may be interested. He wrote a book. One of them is rule one. The other one is payback time. I really provided some. Yeah, yeah. You know, rule one investing, Warren Buffett. We can talk about that. But, yeah, I, I found some of the calculus in his books, put it into Excel, and I ended up coming up with about 50 data points to analyze the stock. Sean Tepper And then on top of that, I created a traffic like rating system where stocks are either on sale, watch or overpriced. That’s green, gray or red. And I used it the next 4 or 5 years on my own, making returns between 15 and 50%, and my returns still fall in that range today. Our customers actually fall in that range as well. Sean Tepper But yeah, I, I wanted to make sure I’m using my own money testing it to make sure it works, not just like four weeks or four months. I went like that over four years. And then it was 2019 was the inflection point when I’m like, I think I’ve got a solution here, but let’s just confirm. Sent the sheet to a few of the retail investors and everybody’s like, I’m not going to use this Excel sheet. Sean Tepper This is insane. You got to create a software. So that right. That was the green light. Let’s go create a SaaS platform. And took a year to build the first version. And the first version was not pretty. But yeah, fast forward to today. That’s where we’re at. But yeah. Andrew Mitchem They Nimrod when you look back on them. Sean Tepper Yeah, right. It was like the, the metaphor I use is it felt like I was building a physical prototype made of like, and duct tape and cardboard. It was not pretty videos. It’s pretty ugly. But you get feedback from your customers and you just keep making it better, and it actually turns into something. How does this software help? Andrew Mitchem So, yeah, awesome. That’s brilliant. So fast forward then to today. Why would someone come and use what you have and I suppose in a practical basis, how does it help them? What are they. What do they input? What do they use to make decisions for them? Sean Tepper Sure. Yeah. So I’ll give you some of the the subjective reasons and then we’ll get into the objective and why that’s actually important to our, our broker partners. But our rating system again process engineering, it doesn’t sound very glamorous, but the concept of making decisions very easy for people, it is very true in most industries. So we we use the process engineering lens. Sean Tepper Plus we take a lot of inspiration from Duolingo for language learning in our opinion. Like what? They’ve got over 600 million users. They’re doing something right. We’re teaching people how to learn a language with these micro learning modules. And I’m like, we need to do the same thing in our platform, but it’s got to be investing focused. So we’ve got these modules peppered around that quickly teaches people how to invest in you put the two together, the rating system, plus the simplified education that helps people. Sean Tepper And it’s not our guarantee, but it’s it’s something we let people know upfront that 90% of customers is actually over 90. But we say 90% of customers that use TYKR are able to go from a beginner to confident an investor in 14 days or less. It’s very quick. Wow. And what does that mean from an objective standpoint? And this is what matters most to brokers, which is most brokers we’re talking to have two big problems. Sean Tepper And number one, very little transaction volumes, like somebody will join on day one and they’ll wait three months or six months or nine months, and then make another trade. And the other issue is the average account size is less than 5000. While with TYKR after five years. Now we’re we track like a lot of data points to see our, investors behavior. Sean Tepper And typically people make 30% more transactions after joining TYKR. And their average account size is about $180,000. So what that tells us is and it tells. Right. So these people are their confidence is skyrocketing and they’re adding more money from their checking account or their savings. So it’s not sitting in a low interest vehicle. So so there you go. Sean Tepper That’s how we’re different. I’ll give you one more way where different in your audience may appreciate this is TYKRs. Calculations are actually open source for personal use. And the SEC really likes that. Like we had an audit done to make sure we fall in that publisher exclusion category. We could talk about that in a minute, but making sure we’re not we’re not giving financial advice, but this firm we’re talking to and we had another we’re actually had two firms. Sean Tepper Take a look. They were both very impressed that we we put those calculations out and I’m like, I’m, I’m actually not concerned anybody’s going to take it because it’s even though it’s relatively simple math, it’s a lot of it. And try to put together in a software what would take you a really long time. So fortunately nobody’s tried to duplicate it. Sean Tepper But the calculations are out there. Andrew Mitchem Yeah, well, for the sake, I was looking on your your purchase, page. Your pricing page. For the sake of $50 a month, you just use it. Wouldn’t you? Rather than trying to reinvent it or. Sean Tepper It exact right at the base price is like, you’re saying 15, 15 bucks a month or 99 a year? You’re right. It’s like, oh, okay. So here’s the here’s the calculations. Yeah. I’m not going to reiterate. That’s where it. Andrew Mitchem Is. I mean in in lifetime working it out will spend $100 a year same. Sean Tepper Same prices Netflix their. Andrew Mitchem Data. Exactly. Yeah a lot more educational. Yes. Sean Tepper Yes. TFTC also helps create successful traders Andrew Mitchem Thank you. So it it sounds like although we’re in, slightly different markets within the overall similar markets now, we have something very similar going on, which is amazing is we’ve never met obviously, before, you know, 20 minutes ago, and that we find that our clients would be very similar to yours. The average forex person’s out there, small account, scared to trade, or they do the opposite and they do silly things and they make us even money and then lose it all, which inevitably happens. Andrew Mitchem And then they blame the break on the market. And that’s where we find our clients are different as well. You know, they have confidence that low risk approach. They they know what they’re doing, what to look for, when to do it. And therefore when they go to a broker brokers out there because, you know, the client’s got a hugely, bigger account and trading more often. Andrew Mitchem So it’s incredible how education and lack of it can affect so many people in this. Seriously. Yeah. It’s crazy. Yeah. Now, Sean, you mentioned, about the no financial advice, you know, situation. And again, coming back, that’s where we’re similar, you know, what’s your take on the no financial advice? Sean Tepper Yeah. So with the SEC, there’s I don’t have the exact, it’s like rule 102-5 or whatever. I’m making that up. But yeah, they’re essentially three rules you have to follow with staying in the publisher exclusion category. And there are companies and there are guys out there, some women as well, that they they get into some some shaky ground or gray areas where they push the envelope and they can get into some some big legal trouble. Sean Tepper So the three rules really go as follows. Number one is all information has to be factual. Like we can’t say like, hey, because I like x, y, z CEO, I think the share price is going to $2,000 a share. That’s crazy. We have to present the data like everything we do is really based off the fundamentals. We don’t cook any books. Sean Tepper We don’t skew the financials. It’s like, hey, here’s the EPS, here’s the revenue, here’s the net income, here’s the debt. Bam, roll it up to our calculations. And there’s your score. Keep it very simple right. Number two is and this is actually pretty easy to follow is we can’t ask our customers their age their risk level when they want to retire and then give them recommendations based on that criteria. Sean Tepper That is described as personalized financial advice. So very easy. Like okay, so don’t ask those personal questions. And number three everything has to be regular. And what does regular mean. It means all information we we put out has to be like every day or every week, which it’s we update our data every day. We can’t do and this is a common problem with a lot of discord and WhatsApp groups. Sean Tepper And so I’ve been told from the SEC, which is pump and dumps, is like, hey, go buy as much of GameStop by Tuesday. And then the very next day, without telling anyone, they’ll go sell a bunch of GameStop or whatever stock they they can come up with. And that is actually a common issue because you can make a lot of money in short order. Sean Tepper So, yeah, no, no irregular posting. It has to be regular posting. So yeah, those are the three rules with the publisher exclusion. And to be honest with you, but actually pretty easy to follow. Is social media helpful? Andrew Mitchem Yeah, yeah. That’s good. Do you find you mentioned on social media type of apps? Do you find that those, causing problems generally for people because they just think they’re going to find something that’s going to solve all their life’s financial problems? Sean Tepper You mean like our customer is going on social media and reading comments. Andrew Mitchem To make sure customers, but just general people out there and in general isn’t there going to find some app and follow something and it’s suddenly going to give them all the magical answers? Sean Tepper No. In general, I think most people are skeptical, which I think is good. They’re not going to like, you know, like, for example, they’re not going to come to tinker right away and be like, oh, this is this is my savior. That’s that’s not the case. We want people to be skeptical. And we always tell people like, don’t like, I’ll talk about Tinker all day, but don’t even take my word for it. Sean Tepper I always say, go to Trustpilot, see what our customers have to say first before you even think about it. And then our model is, it’s a trial 14 day trial. And then we also have a 30 day money back guarantee. So even when your credit card is charged, if you want to refund, we’re not going to fight you on it. Sean Tepper It’s like it’s 15 bucks. That’s right, that’s right. It’s like we’re not going to split hairs on this, but it’s like you want to create a platform that it’s very easy to join is very easy to learn about. You can see what your customers are saying. It’s easy to test drive. Those are kind of the boxes I like to check when I join a platform because I’m using other software to build TYKR, whether it’s a marketing software or analytics or email marketing or whatever, right. Sean Tepper I want those things. So I’m like, I’m going to do the same thing with my own platform. But coming back to the skepticism, I think it’s good. It’s good to have a healthy amount, and it’s good for people to not only, like join TYKR, but go have like join our competitors, see what they have to say. And sometimes you’ll get things to line up like let’s say it’s a stock you really like and you’ve got, you know, TYKR, Motley Fool and Seeking Alpha are all like, hey, this is this is a strong stock, not a buy stock, but its financials are strong. Sean Tepper That creates layers of confidence is how we phrase it. Yeah. Creating those layers of confidence gives people more confidence to move forward. Andrew Mitchem Yeah yeah that’s good. And I noticed also on your on your offer there that you talk about cryptos as well Matt. Obviously it’s the, the big thing that people want to talk about and we’ll see more recently we’ve seen some big drops as well. Yeah. How, how do people finding using your software or on cryptos. Andrew Mitchem Because it’s, it’s like one of the markets that we kind of cross over on. Sean Tepper Yeah. So with crypto we weren’t originally going to add it to the platform, but a few people were like, hey, can you add crypto from a tracking perspective? Now for context, we have three assets in TYKR. We have stocks, ETFs and crypto ETFs. It’s easy to analyze because it’s really just a bundle of stocks. So we analyze each individual stock. Sean Tepper We roll them all up. If it’s let’s say 500 stocks within an ETF. You can create you can calculate what is the average score within come to that on sale watch over priced. But when it comes to crypto as you know there’s no income statement cash flow statement A balance sheet is not a business, it’s just a digital asset. Sean Tepper But again, we had customers that were like, hey, you got a lot of good tracking tools, like you can set alerts on my dates and prices and really anything you want within TYKR. And so they’re saying like, can you add crypto within so we can keep track of all of our favorite assets in one clean location. And my response to that was, oh yeah, no problem. Sean Tepper We’ll add crypto to this tool. But there’s not a lot of analysis you can do there because again, it’s not a business. Multiple brokers or one? Andrew Mitchem Yeah, yeah. Fair enough. And also I noticed that you said about the broker connection. So one of your pricing models, that’s one broker three and five. Correct. What would be the reasons around someone needing, say, three brokers or five brokers as opposed to one. Sean Tepper Yeah. So the reason is typically your employer is going to issue you A41 like here in the states, of course, we get A41KI don’t know, in New Zealand you call it a pension like they do in, Europe. Andrew Mitchem Yeah. Kiwisavers called but yeah it’s that has is our name. Yeah. Sean Tepper Okay. Exactly. So you’re going to have that is going to be one retirement vehicle. And that’s typically set up with like here in the States. The two big ones are typically fidelity and Empower. There’s also Schwab. But then you’re probably going to want to do some trading on your own. So then here in the States some of the popular choices are Robinhood. Sean Tepper You’ve got E-Trade, you know. So there’s your second one. And then sometimes you’re going to have like an inherited account from a family member, you know, that could be on a different account. And if you don’t roll it over to your current broker, well, guess what? You’ve got a third broker sitting in place. But I get this. I’ve talked to people that have they’ve had more than five different brokers on my response. Sean Tepper So that is why. Yeah. So. Right. It’s it’s it seems unorganized. But we created the three tiers the premium premium plus an advanced premium. You get one broker premium Plus you get three in advance. You get five. We usually like 99.9% of the time. We don’t see people with more than five brokers. But like for example, between my wife and I, we have like we have three. Sean Tepper So yeah. Andrew Mitchem Okay. So with this allows someone to make their analysis and then connect directly through to that broker via your software. Is that how it works. Sean Tepper Yeah. Yeah. So yeah when when you join your broker and we’re really good complement to a broker will never replace it. We don’t want to be a broker dealer. That’s a legal name for their business model because we don’t hold any assets. We don’t hold people’s money. We’re just analytics. So yeah, when people join, you can sync up with your broker. Sean Tepper And what that does is it automatically updates your portfolio in TYKR every day. And it’s a much cleaner interface than most brokers out there. I, I’m never going to talk down about brokers, but it’s like their job is to protect people’s money. But when it comes to analytics dashboards or giving, like education or analytics, it’s that’s not their specialty, nor will it really ever be. Sean Tepper So we fill that gap, we complement and we make it easy to see because some people are like, I don’t I don’t actually know how much money I have because the dashboards in my broker’s so hard to use them, like just sync up your account TYKR and it’s going to kind of summarize it for you. Yeah, yeah. Andrew Mitchem That’s interesting. That makes a lot of sense. Makes life easy for people. And also I see that you have a mobile app. So can someone get the exact same information on the app. But they can all the desktop. Sean Tepper It’s pretty much the same experience. We try to release our features, if not the same day within the next week or two. Like if we need to deploy something to web or web app, we try to do the same thing to the mobile, that allows people to write. They can kind of analyze stocks and the gold or standing in line somewhere at Starbucks, whatever. Sean Tepper The mobile app, I will say this has an additional feature, which is the Duolingo inspired learning modules that kind of like swipe right, swipe left type feel. We don’t have that in the web app today, but we’ve had a few people say, hey, can you also add that to web? Well, that’ll come soon. But yeah, it’s pretty much the same experience. Andrew Mitchem And what’s the AI investing helper that’s not like yeah, humming live. Sean Tepper Oh, that could be going live. Well, recording this video is, February 9th. That could go live on the 11th. Okay. So that’s a feature where you can, like, interact with where you’re going to be the first to hear about it here. So it’s it’s an AI tool where you can ask questions like how do I get started? Sean Tepper Or what should I do with my first thousand dollars? Or, what when is the best time to buy or best to sell? You can interact with AI and it’s actually connected with TYKRs, data set, but also the the globe and it’s put a lot of rigor, rigor into place to make sure it’s not giving you financial advice, but it’s really leaning into giving you the data and TYKR. Sean Tepper So it’s for example, if you were to ask it, hey, can you tell me how to value a stock? It’s going to first go to TYKRs data set. And with the education and give you that information. And then some general information. You know that makes it sound nicer. And then kind of spit it out. So yeah, eventually we’ll release in multiple phases. Sean Tepper So the first phase we call the helper, the second phase is the portfolio builder in a will build hypothetical like for example, build me a portfolio of ten strong tech stocks or buy food stocks or car stocks, something like that. Yeah. And of course it’ll say this is not financial advice. This is a hypothetical portfolio. But yes. And then the third phase will be an analyzer. Sean Tepper So analyze my current portfolio. Like what changes would you recommend. And that that’s going to be really, really cool. So with I will say this and then I’ll stop talking. It’s a powerful tool because it can analyze large data sets in a short amount of time. But as we say at TYKR. And this is why when I become self-aware like Skynet, I’m going to be the first one to be targeted. Sean Tepper Right? It’s, it’s smart, but it’s not that smart. So you have to put a lot of rigor in a place, a lot of guardrails, because it can, as you know, hallucinate. Yeah. So we are bouncing AI up against logic and mathematics to make sure it does not say something stupid to our customers. TFTC creating a trading bot program Andrew Mitchem That’s interesting. We’re in the middle of all we’re saying in the middle. We’ve been testing this live for over a year of getting AI to create trading bots for us, and what it’s doing is it’s spitting at a heap of bots and going through, sort of live trading on, on, you know, that are not real money. We’re trading on the money. Andrew Mitchem And then each week, we’re using the human aspect, the common sense and the knowledge that we look at as technical traders to pick which bots we’re going to be running live for subscribers for the upcoming week. And, and we’re finding that that combination of using the AI for that speed and, you know, doing the, the hard work. Andrew Mitchem Yeah. And giving us some information. But like you said, the guardrail becomes the human input in the common sense of what we’re seeing as technically on a chart. There’s no point in, let’s say, say Bitcoin over the last few weeks has been, you know, crashing. So nicely. There’s no point in us selecting bullish, crypto bots for the upcoming week when there’s technical traders. Andrew Mitchem We’re looking at it dropping. So I find that adding a bit of human common sense and knowledge, along with the AI at this stage is a really nice combination. Sean Tepper You got to do it right, and you probably seen the, the bad choices some people have made. If you let I make all the decisions, you can pull yourself into a, really bad situation. Especially. I like what you’re describing with your bots or those bots actually executing trades. Andrew Mitchem They they can, but we are more trying to set it up so the individual gets the alert and still needs to manually go yes or no as well. Good call. Because I don’t want to get into that situation where it’s completely, you know, automated, although a lot of people are want it all automated. My job as someone who teaches people is you still have to have that knowledge first to understand how to run the bots and to make a commonsense decision. Andrew Mitchem Is it making a good call or not? Sean Tepper Yeah, I’m good answer there, because the other hour I was talking to one company that was have was looking to have AI execute trades automatically. I’m like, whoa, what if they just run with the line and it’s like, go right? Like if rapid fire trades for an hour or two, it’s like, yeah, put some people in a bad situation. Sean Tepper So yeah. Andrew Mitchem Anyway, yeah, we’ll avoid that. We’re both avoid that. Yep. Yeah, exactly. I use it for the hard work and still use the brain. And that’s the thing, isn’t it? You know, what you created and what we’ve created. We’re about educating people, empowering people to use their common sense. Because I still think, after all, it comes down to it, there’s nothing better as a human, as an individual to have that, that how and that it’s almost like that feelgood factor that I know I can analyze these markets and make sound decisions and do well, you know, that’s you, you. Sean Tepper You, yeah. You just hit on the, the number one thing our customers care about like in and this will give you and your audience a little moment for me when I first created TYKR, especially the Excel sheet, I was all about getting better returns. I’m like, well, if Warren and Charlie can do it, I can do it. Sean Tepper Well, when I went live, that was my focus. But then after talking to a few customers, I’m like, they don’t agree with that. There’s actually something more important. And fast forward, I probably talked to a few thousand customers by this point over five years, and the number one thing they care about is confidence. Now, having confidence to literally do it on your own. Sean Tepper That is the home run. Feeling that supersedes, you know, getting good returns any day. Like people sleep better at night. Just knowing that, Shawn, I, I can do this on my own. That is what I’m looking for. I’m like home. So we even though the returns in tech are good, like, we actually lean into confidence. Like how do we give people more confidence is actually the bigger priority now. Andrew Mitchem Yeah, yeah, I, I fully get it. You know, we’ve been operating since 2009. Come on, Ryan, the Ryan run around the world in 111 countries and the same thing we we asked people, we, of course, you know, want to know why people join. And then we follow up after three months, six months, year, two years and keep asking people it’s the community and that knowledge of knowing what you’re doing for yourself, to have that control with low risk and, you know, really good outcomes. Andrew Mitchem But up here and then I say to people, trade any trading into, investments is emotion, isn’t it? Your head in your heart. You have to control those two. And what we’re doing is providing platforms or education platforms to allow people to fulfill that, that dream successfully and safely. Sean Tepper Yep, yep. Andrew Mitchem So it’s huge. Yeah. We can have all the AI and all the risks, all the all these flash gadgets, but ultimately it still comes back to that human wanting to have confidence in what they’re doing with their own money. Sean Tepper That’s it. Yeah. Andrew Mitchem And no. And also not just handing it over to someone as well. I think it’s important. Sean Tepper They add it and it’s actually you’re kind of alluding to this. It’s in people’s best interest to let’s say AI does 90% of the work. You want to be the person you want the human being finishing that process? Yeah. Because they, they ultimately it’s it’s better for them from an educational standpoint and from an, confidence standpoint, like they should know what was done. Sean Tepper But now, I control things. I get to execute the trade. Yes. You know, that’s right, that you want people to have that power at the end of the day. 60,000 stocks analyzed Andrew Mitchem Absolutely. And the, your software obviously does a lot of analysis just to give myself and viewers and listeners a ballpark figure. What kind of number of stocks is it kind of looking at and analyzing? Sean Tepper Sure. Okay. Yeah. So we’ve got about 60,000 stocks in TYKR around the world’s. We are up. Yeah. We’re upgrading. They’ll get this in the next month or two. We’re switching our data provider. So we’re going to have in the states real time pricing. You will have 15 minute delay. But then we’re going to have actually I can’t guarantee all stocks around the world, but most that’ll bring us closer to about 75,000 stocks around the world. Sean Tepper And then we’ll also have most ETFs around the world, which I think is closer to about 10,000. I could following in that Bow Wow. Yeah. No wonder. Andrew Mitchem They need analysis software that. Sean Tepper Yeah, right, right. It’s what we do. We run into circumstances when people, you know, they’ll join from a smaller country and they’ll be like, hey, you don’t have any stocks from our country. Winner may arriving. So it’s a lot of those requests and it’s like we knew we had to get to this point eventually. Yeah. But yeah. But then you just give transparency. Sean Tepper We’re looking at Finn Hub is, the data provider that will help us get, the more stocks and ETFs around the world. Andrew Mitchem Wow. So when you see your clients in 50 countries, if, for example, someone was here in New Zealand and they don’t want to be, and 2:00 in the morning to trade the US markets, they could be trading like the Australasian markets. Yeah. So your software. Sean Tepper Absolutely. Yep. Andrew Mitchem Oh, fantastic. That’s really good. Yeah. That, that’s blowing my way. That number. One thing as a currency trader, there’s like about eight main currencies. And so that makes, hence why there’s nothing like this for the forex market. I’m guessing because we can look at charts and read a bit of news and kind of make your analysis voice your, the information. Andrew Mitchem Someone out there with that. Your software is almost got an impossible task. Sean Tepper Yeah. We I was just checking here in tick or how many stocks from New Zealand. We’ve got a little over 187. So, do you know I like the I assume it’s the new New Zealand Stock Exchange. Andrew Mitchem Yes. In Wellington. Nice. Sean Tepper Got it. Do you know how many stocks they have? Andrew Mitchem No. I’m not, I’m purely forex. I honestly don’t know. Sean Tepper Okay. No no worries. But we’ll hopefully fin Hub will be able to get us most from from your exchange. Yeah. But that’s just a good example of like absolutely. You know we again we get a lot of people from random countries like, hey, can you add more stocks from our country? It’s like, yeah, absolutely. We’re we’re on it. Andrew Mitchem Yeah. Well, and also it’s purely that time of day thing, isn’t it. Because the you know, I suppose I get used to forex which is 24 hours a day. It doesn’t matter where you live in your world, you can trade it in cryptos obviously seven days a week now as well. But when you’re talking US stocks, they are, you know, for someone on my side of the world, some quite awkward trading hours. Andrew Mitchem So what you’re providing now would allow me to trade some of the the Japanese stocks, I’m guessing. Oh, and then the Australian ones using the ones now that you mentioned. So you really do open up your product to being truly a global, tool for people. Sean Tepper Exactly. Yeah. Yeah. Andrew Mitchem That’s awesome. Sean, anything else you want to add about what we’ve not covered, about what you can help people with? Sean Tepper Yeah. Knowing that you’re more in the trading world and we’re more investing, I have to say this one detail, which is we do have about 10% of our customers are traders, give or take, and they’ll use TYKR as their starting points. You’re like, hey, let’s see. You’ve got like 100 ideas out there. Well, they’ll use TYKR to narrow it down from 100 down to ten. Sean Tepper Yeah. So that’s one main use case. It’s kind of like the short AI, as it’s been described to me. Is the short list creator TYKRs, the short list for like for traders. So so yeah, I want to add that tidbit as some people are like, well I’m not really into best thing. It’s like, you don’t have to be. Sean Tepper You can just use the tool to, narrow down your search. So I’ve selected one use case. Andrew Mitchem Yeah, that makes a lot of sense. That’s kind of how I was thinking about potentially using it as well. It’s like, makes a lot of sense to do all that, that work and get it down to something more manageable. Right? Yeah. Contact Sean Andrew Mitchem And what’s the best way that someone can contact you to find out more, about what you offer? Andrew Mitchem Sure. Well, how would. Sean Tepper They add, two ways to get in touch with, TYKR or myself? You can just go to tykr.com. That’s TYKR, tykr.com. And then, I’m really active on LinkedIn. Sean Tepper, Sean is spelled the Sean Connery way. Andrew Mitchem Yes. This with the voice. Sean Tepper Yeah. I wish I had strong Scottish voice. Yes. Andrew Mitchem Awesome. Hey, Sean, we’ll put links, of course, up here as well. And we will be sharing this in around the website and social media as well, so people can contact you finding a link here as well. It’s been awesome talking to you. I’ve learned a lot about the market. I don’t know a huge amount, and it’s fascinating to hear what you do and how, you know, you going to make it from when you mentioned 60, it still blew me away. Andrew Mitchem That number, from a ridiculous number of, stocks to help to analyze something in a, in a more simplified way. So, awesome to speak to you. Thank you. Your product looks amazing. I will be trying it. And, Yeah, look forward to it as well. Sean Tepper Thanks, Andrew. This is great. Andrew Mitchem Awesome. Thanks, Sean. Bye for now. Episode Title: #624: The Smarter Way To Pick Winning Stocks Find out more about Blueberry Markets – Click Here Find out more about my Online Video Forex Course Book a Call with Andrew or one of his team now Click Here to Attend my Free Masterclass Checkout the Tykr Platform here.

When your gym is stable and the fires are out, what's next?Two-Brain's Tinker Mastermind provides an elite level of mentorship for gym owners who are ready to build wealth, scale their businesses, learn to lead and create lasting legacies.This is the fun part of entrepreneurship—the part where you have choices: build investment portfolios, acquire real estate, franchise your concept, create new businesses or simply pick your kids up from school every day. The possibilities are endless.In this episode of “Run a Profitable Gym,” Mike Warkentin sits down with Tinker leaders Joleen Bingham and Lisa Palmer to find out exactly what the program is and who it's for.Tinker-level gym owners have reliable cash flow, available time and a growth mindset. They focus on four main pillars to build their Perfect Day: lifestyle, wealth, scaling and leadership.Tinkers join weekly breakout calls with elite entrepreneurs from around the world and attend quarterly in-person meetups in places such as Florida, Arizona, Portugal and Ireland.The results speak for themselves: Two-Brain has certified over 70 millionaire gym owners through Tinker, with 17 certified in the last year alone.One Canadian Tinker took home $300,000 in net owner benefit, became a certified millionaire, invested in three syndications and opened a second gym that's hitting $30,000-$35,000 months. A U.K. Tinker spent three months in South Africa with his family while his gym ran without him.Are you Tinker ready? Email Joleen (North America) or Lisa (Europe) to find out: joleen.bingham@twobrainbusiness.com or lisa.palmer@twobrainbusiness.comLinksGym Owners UnitedBook a Call0:44 - Who is Tinker for?5:10 - Problems Tinker solves11:59 - Tinker program structure21:40 - Tinker Toolkit preview23:47 - 70+ millionaire gym owners

Episode 183 February 12, 2026 On the Needles 1:22 ALL KNITTING LINKS GO TO RAVELRY UNLESS OTHERWISE NOTED.  Please visit our Instagram page @craftcookreadrepeat for non-Rav photos and info     Melt the ICE hat by YarnCultMN, Knit Picks Stroll Fingering in Hollyberry DONE!!   Mountain Mist Hat by tincanknits, Knit Picks Brava Worsted in brindle, black, caution, currant DONE!!   Jane Marple dishcloth by Kitchen Sink Shop, Knit Picks Dishie in Blue DONE!!   Tinker by Wooly Wormhead, Knit Picks Stroll Tweed in Dalmation DONE!!   Secret Olympic Sweater Project   On the Easel 9:12 100-Day Compositions Olympic Sketchbooking!   Daffodils are blooming! On the Table 13:34 Peanut Butter Oat Fudge Bars - Yossy Arefi   RANCHO GordoChristmas Lima Bean and Cabbage soup    January cookbook: Dinner by Meera Sodha: Mango paneer curry Green pasta with zhoug Coconut braised winter greens   Sweet potatoes with gr. Turkey, leek, and onion with dijon. Cookie boxes for the college kids On the Nightstand 25:02 We are now a Bookshop.org affiliate!  You can visit our shop to find books we've talked about or click on the links below.  The books are supplied by local independent bookstores and a percentage goes to us at no cost to you! Seeing Other People by Emily Wibberley & Austin Siegemund-Broka (audio) The Unquiet Grave by Dervla McTiernan Through Gates of Garnet and Gold by Seanan McGuire Labyrinth's Heart by M.A. Carrick Startlement by Ada Limón Mona's Eyes by Thomas Schlesser

When can a public university punish a student for speech that includes violent references, and that frightens some people, but is not a clear threat? Eugene Volokh and Jane Bambauer unpack two recent court cases, one that upholds such punishment and another that says it violates the First Amendment: Damsky v. University of Florida and Christensen v. Ohio State University. Volokh and Bambauer explore how courts are applying the “substantial disruption” standard from Tinker v. Des Moines, and why speech by public university students that alludes in an ambiguous way to violence creates hard First Amendment questions. Subscribe for the latest on free speech, censorship, social media, AI, and the evolving role of the First Amendment in today's proverbial town square. 

From Palantir and Two Sigma to building Goodfire into the poster-child for actionable mechanistic interpretability, Mark Bissell (Member of Technical Staff) and Myra Deng (Head of Product) are trying to turn “peeking inside the model” into a repeatable production workflow by shipping APIs, landing real enterprise deployments, and now scaling the bet with a recent $150M Series B funding round at a $1.25B valuation.In this episode, we go far beyond the usual “SAEs are cool” take. We talk about Goodfire's core bet: that the AI lifecycle is still fundamentally broken because the only reliable control we have is data and we post-train, RLHF, and fine-tune by “slurping supervision through a straw,” hoping the model picks up the right behaviors while quietly absorbing the wrong ones. Goodfire's answer is to build a bi-directional interface between humans and models: read what's happening inside, edit it surgically, and eventually use interpretability during training so customization isn't just brute-force guesswork.Mark and Myra walk through what that looks like when you stop treating interpretability like a lab demo and start treating it like infrastructure: lightweight probes that add near-zero latency, token-level safety filters that can run at inference time, and interpretability workflows that survive messy constraints (multilingual inputs, synthetic→real transfer, regulated domains, no access to sensitive data). We also get a live window into what “frontier-scale interp” means operationally (i.e. steering a trillion-parameter model in real time by targeting internal features) plus why the same tooling generalizes cleanly from language models to genomics, medical imaging, and “pixel-space” world models.We discuss:* Myra + Mark's path: Palantir (health systems, forward-deployed engineering) → Goodfire early team; Two Sigma → Head of Product, translating frontier interpretability research into a platform and real-world deployments* What “interpretability” actually means in practice: not just post-hoc poking, but a broader “science of deep learning” approach across the full AI lifecycle (data curation → post-training → internal representations → model design)* Why post-training is the first big wedge: “surgical edits” for unintended behaviors likereward hacking, sycophancy, noise learned during customization plus the dream of targeted unlearning and bias removal without wrecking capabilities* SAEs vs probes in the real world: why SAE feature spaces sometimes underperform classifiers trained on raw activations for downstream detection tasks (hallucination, harmful intent, PII), and what that implies about “clean concept spaces”* Rakuten in production: deploying interpretability-based token-level PII detection at inference time to prevent routing private data to downstream providers plus the gnarly constraints: no training on real customer PII, synthetic→real transfer, English + Japanese, and tokenization quirks* Why interp can be operationally cheaper than LLM-judge guardrails: probes are lightweight, low-latency, and don't require hosting a second large model in the loop* Real-time steering at frontier scale: a demo of steering Kimi K2 (~1T params) live and finding features via SAE pipelines, auto-labeling via LLMs, and toggling a “Gen-Z slang” feature across multiple layers without breaking tool use* Hallucinations as an internal signal: the case that models have latent uncertainty / “user-pleasing” circuitry you can detect and potentially mitigate more directly than black-box methods* Steering vs prompting: the emerging view that activation steering and in-context learning are more closely connected than people think, including work mapping between the two (even for jailbreak-style behaviors)* Interpretability for science: using the same tooling across domains (genomics, medical imaging, materials) to debug spurious correlations and extract new knowledge up to and including early biomarker discovery work with major partners* World models + “pixel-space” interpretability: why vision/video models make concepts easier to see, how that accelerates the feedback loop, and why robotics/world-model partners are especially interesting design partners* The north star: moving from “data in, weights out” to intentional model design where experts can impart goals and constraints directly, not just via reward signals and brute-force post-training—Goodfire AI* Website: https://goodfire.ai* LinkedIn: https://www.linkedin.com/company/goodfire-ai/* X: https://x.com/GoodfireAIMyra Deng* Website: https://myradeng.com/* LinkedIn: https://www.linkedin.com/in/myra-deng/* X: https://x.com/myra_dengMark Bissell* LinkedIn: https://www.linkedin.com/in/mark-bissell/* X: https://x.com/MarkMBissellFull Video EpisodeTimestamps00:00:00 Introduction00:00:05 Introduction to the Latent Space Podcast and Guests from Goodfire00:00:29 What is Goodfire? Mission and Focus on Interpretability00:01:01 Goodfire's Practical Approach to Interpretability00:01:37 Goodfire's Series B Fundraise Announcement00:02:04 Backgrounds of Mark and Myra from Goodfire00:02:51 Team Structure and Roles at Goodfire00:05:13 What is Interpretability? Definitions and Techniques00:05:30 Understanding Errors00:07:29 Post-training vs. Pre-training Interpretability Applications00:08:51 Using Interpretability to Remove Unwanted Behaviors00:10:09 Grokking, Double Descent, and Generalization in Models00:10:15 404 Not Found Explained00:12:06 Subliminal Learning and Hidden Biases in Models00:14:07 How Goodfire Chooses Research Directions and Projects00:15:00 Troubleshooting Errors00:16:04 Limitations of SAEs and Probes in Interpretability00:18:14 Rakuten Case Study: Production Deployment of Interpretability00:20:45 Conclusion00:21:12 Efficiency Benefits of Interpretability Techniques00:21:26 Live Demo: Real-Time Steering in a Trillion Parameter Model00:25:15 How Steering Features are Identified and Labeled00:26:51 Detecting and Mitigating Hallucinations Using Interpretability00:31:20 Equivalence of Activation Steering and Prompting00:34:06 Comparing Steering with Fine-Tuning and LoRA Techniques00:36:04 Model Design and the Future of Intentional AI Development00:38:09 Getting Started in Mechinterp: Resources, Programs, and Open Problems00:40:51 Industry Applications and the Rise of Mechinterp in Practice00:41:39 Interpretability for Code Models and Real-World Usage00:43:07 Making Steering Useful for More Than Stylistic Edits00:46:17 Applying Interpretability to Healthcare and Scientific Discovery00:49:15 Why Interpretability is Crucial in High-Stakes Domains like Healthcare00:52:03 Call for Design Partners Across Domains00:54:18 Interest in World Models and Visual Interpretability00:57:22 Sci-Fi Inspiration: Ted Chiang and Interpretability01:00:14 Interpretability, Safety, and Alignment Perspectives01:04:27 Weak-to-Strong Generalization and Future Alignment Challenges01:05:38 Final Thoughts and Hiring/Collaboration Opportunities at GoodfireTranscriptShawn Wang [00:00:05]: So welcome to the Latent Space pod. We're back in the studio with our special MechInterp co-host, Vibhu. Welcome. Mochi, Mochi's special co-host. And Mochi, the mechanistic interpretability doggo. We have with us Mark and Myra from Goodfire. Welcome. Thanks for having us on. Maybe we can sort of introduce Goodfire and then introduce you guys. How do you introduce Goodfire today?Myra Deng [00:00:29]: Yeah, it's a great question. So Goodfire, we like to say, is an AI research lab that focuses on using interpretability to understand, learn from, and design AI models. And we really believe that interpretability will unlock the new generation, next frontier of safe and powerful AI models. That's our description right now, and I'm excited to dive more into the work we're doing to make that happen.Shawn Wang [00:00:55]: Yeah. And there's always like the official description. Is there an understatement? Is there an unofficial one that sort of resonates more with a different audience?Mark Bissell [00:01:01]: Well, being an AI research lab that's focused on interpretability, there's obviously a lot of people have a lot that they think about when they think of interpretability. And I think we have a pretty broad definition of what that means and the types of places that can be applied. And in particular, applying it in production scenarios, in high stakes industries, and really taking it sort of from the research world into the real world. Which, you know. It's a new field, so that hasn't been done all that much. And we're excited about actually seeing that sort of put into practice.Shawn Wang [00:01:37]: Yeah, I would say it wasn't too long ago that Anthopic was like still putting out like toy models or superposition and that kind of stuff. And I wouldn't have pegged it to be this far along. When you and I talked at NeurIPS, you were talking a little bit about your production use cases and your customers. And then not to bury the lead, today we're also announcing the fundraise, your Series B. $150 million. $150 million at a 1.25B valuation. Congrats, Unicorn.Mark Bissell [00:02:02]: Thank you. Yeah, no, things move fast.Shawn Wang [00:02:04]: We were talking to you in December and already some big updates since then. Let's dive, I guess, into a bit of your backgrounds as well. Mark, you were at Palantir working on health stuff, which is really interesting because the Goodfire has some interesting like health use cases. I don't know how related they are in practice.Mark Bissell [00:02:22]: Yeah, not super related, but I don't know. It was helpful context to know what it's like. Just to work. Just to work with health systems and generally in that domain. Yeah.Shawn Wang [00:02:32]: And Mara, you were at Two Sigma, which actually I was also at Two Sigma back in the day. Wow, nice.Myra Deng [00:02:37]: Did we overlap at all?Shawn Wang [00:02:38]: No, this is when I was briefly a software engineer before I became a sort of developer relations person. And now you're head of product. What are your sort of respective roles, just to introduce people to like what all gets done in Goodfire?Mark Bissell [00:02:51]: Yeah, prior to Goodfire, I was at Palantir for about three years as a forward deployed engineer, now a hot term. Wasn't always that way. And as a technical lead on the health care team and at Goodfire, I'm a member of the technical staff. And honestly, that I think is about as specific as like as as I could describe myself because I've worked on a range of things. And, you know, it's it's a fun time to be at a team that's still reasonably small. I think when I joined one of the first like ten employees, now we're above 40, but still, it looks like there's always a mix of research and engineering and product and all of the above. That needs to get done. And I think everyone across the team is, you know, pretty, pretty switch hitter in the roles they do. So I think you've seen some of the stuff that I worked on related to image models, which was sort of like a research demo. More recently, I've been working on our scientific discovery team with some of our life sciences partners, but then also building out our core platform for more of like flexing some of the kind of MLE and developer skills as well.Shawn Wang [00:03:53]: Very generalist. And you also had like a very like a founding engineer type role.Myra Deng [00:03:58]: Yeah, yeah.Shawn Wang [00:03:59]: So I also started as I still am a member of technical staff, did a wide range of things from the very beginning, including like finding our office space and all of this, which is we both we both visited when you had that open house thing. It was really nice.Myra Deng [00:04:13]: Thank you. Thank you. Yeah. Plug to come visit our office.Shawn Wang [00:04:15]: It looked like it was like 200 people. It has room for 200 people. But you guys are like 10.Myra Deng [00:04:22]: For a while, it was very empty. But yeah, like like Mark, I spend. A lot of my time as as head of product, I think product is a bit of a weird role these days, but a lot of it is thinking about how do we take our frontier research and really apply it to the most important real world problems and how does that then translate into a platform that's repeatable or a product and working across, you know, the engineering and research teams to make that happen and also communicating to the world? Like, what is interpretability? What is it used for? What is it good for? Why is it so important? All of these things are part of my day-to-day as well.Shawn Wang [00:05:01]: I love like what is things because that's a very crisp like starting point for people like coming to a field. They all do a fun thing. Vibhu, why don't you want to try tackling what is interpretability and then they can correct us.Vibhu Sapra [00:05:13]: Okay, great. So I think like one, just to kick off, it's a very interesting role to be head of product, right? Because you guys, at least as a lab, you're more of an applied interp lab, right? Which is pretty different than just normal interp, like a lot of background research. But yeah. You guys actually ship an API to try these things. You have Ember, you have products around it, which not many do. Okay. What is interp? So basically you're trying to have an understanding of what's going on in model, like in the model, in the internal. So different approaches to do that. You can do probing, SAEs, transcoders, all this stuff. But basically you have an, you have a hypothesis. You have something that you want to learn about what's happening in a model internals. And then you're trying to solve that from there. You can do stuff like you can, you know, you can do activation mapping. You can try to do steering. There's a lot of stuff that you can do, but the key question is, you know, from input to output, we want to have a better understanding of what's happening and, you know, how can we, how can we adjust what's happening on the model internals? How'd I do?Mark Bissell [00:06:12]: That was really good. I think that was great. I think it's also a, it's kind of a minefield of a, if you ask 50 people who quote unquote work in interp, like what is interpretability, you'll probably get 50 different answers. And. Yeah. To some extent also like where, where good fire sits in the space. I think that we're an AI research company above all else. And interpretability is a, is a set of methods that we think are really useful and worth kind of specializing in, in order to accomplish the goals we want to accomplish. But I think we also sort of see some of the goals as even more broader as, as almost like the science of deep learning and just taking a not black box approach to kind of any part of the like AI development life cycle, whether that. That means using interp for like data curation while you're training your model or for understanding what happened during post-training or for the, you know, understanding activations and sort of internal representations, what is in there semantically. And then a lot of sort of exciting updates that were, you know, are sort of also part of the, the fundraise around bringing interpretability to training, which I don't think has been done all that much before. A lot of this stuff is sort of post-talk poking at models as opposed to. To actually using this to intentionally design them.Shawn Wang [00:07:29]: Is this post-training or pre-training or is that not a useful.Myra Deng [00:07:33]: Currently focused on post-training, but there's no reason the techniques wouldn't also work in pre-training.Shawn Wang [00:07:38]: Yeah. It seems like it would be more active, applicable post-training because basically I'm thinking like rollouts or like, you know, having different variations of a model that you can tweak with the, with your steering. Yeah.Myra Deng [00:07:50]: And I think in a lot of the news that you've seen in, in, on like Twitter or whatever, you've seen a lot of unintended. Side effects come out of post-training processes, you know, overly sycophantic models or models that exhibit strange reward hacking behavior. I think these are like extreme examples. There's also, you know, very, uh, mundane, more mundane, like enterprise use cases where, you know, they try to customize or post-train a model to do something and it learns some noise or it doesn't appropriately learn the target task. And a big question that we've always had is like, how do you use your understanding of what the model knows and what it's doing to actually guide the learning process?Shawn Wang [00:08:26]: Yeah, I mean, uh, you know, just to anchor this for people, uh, one of the biggest controversies of last year was 4.0 GlazeGate. I've never heard of GlazeGate. I didn't know that was what it was called. The other one, they called it that on the blog post and I was like, well, how did OpenAI call it? Like officially use that term. And I'm like, that's funny, but like, yeah, I guess it's the pitch that if they had worked a good fire, they wouldn't have avoided it. Like, you know what I'm saying?Myra Deng [00:08:51]: I think so. Yeah. Yeah.Mark Bissell [00:08:53]: I think that's certainly one of the use cases. I think. Yeah. Yeah. I think the reason why post-training is a place where this makes a lot of sense is a lot of what we're talking about is surgical edits. You know, you want to be able to have expert feedback, very surgically change how your model is doing, whether that is, you know, removing a certain behavior that it has. So, you know, one of the things that we've been looking at or is, is another like common area where you would want to make a somewhat surgical edit is some of the models that have say political bias. Like you look at Quen or, um, R1 and they have sort of like this CCP bias.Shawn Wang [00:09:27]: Is there a CCP vector?Mark Bissell [00:09:29]: Well, there's, there are certainly internal, yeah. Parts of the representation space where you can sort of see where that lives. Yeah. Um, and you want to kind of, you know, extract that piece out.Shawn Wang [00:09:40]: Well, I always say, you know, whenever you find a vector, a fun exercise is just like, make it very negative to see what the opposite of CCP is.Mark Bissell [00:09:47]: The super America, bald eagles flying everywhere. But yeah. So in general, like lots of post-training tasks where you'd want to be able to, to do that. Whether it's unlearning a certain behavior or, you know, some of the other kind of cases where this comes up is, are you familiar with like the, the grokking behavior? I mean, I know the machine learning term of grokking.Shawn Wang [00:10:09]: Yeah.Mark Bissell [00:10:09]: Sort of this like double descent idea of, of having a model that is able to learn a generalizing, a generalizing solution, as opposed to even if memorization of some task would suffice, you want it to learn the more general way of doing a thing. And so, you know, another. A way that you can think about having surgical access to a model's internals would be learn from this data, but learn in the right way. If there are many possible, you know, ways to, to do that. Can make interp solve the double descent problem?Shawn Wang [00:10:41]: Depends, I guess, on how you. Okay. So I, I, I viewed that double descent as a problem because then you're like, well, if the loss curves level out, then you're done, but maybe you're not done. Right. Right. But like, if you actually can interpret what is a generalizing or what you're doing. What is, what is still changing, even though the loss is not changing, then maybe you, you can actually not view it as a double descent problem. And actually you're just sort of translating the space in which you view loss and like, and then you have a smooth curve. Yeah.Mark Bissell [00:11:11]: I think that's certainly like the domain of, of problems that we're, that we're looking to get.Shawn Wang [00:11:15]: Yeah. To me, like double descent is like the biggest thing to like ML research where like, if you believe in scaling, then you don't need, you need to know where to scale. And. But if you believe in double descent, then you don't, you don't believe in anything where like anything levels off, like.Vibhu Sapra [00:11:30]: I mean, also tendentially there's like, okay, when you talk about the China vector, right. There's the subliminal learning work. It was from the anthropic fellows program where basically you can have hidden biases in a model. And as you distill down or, you know, as you train on distilled data, those biases always show up, even if like you explicitly try to not train on them. So, you know, it's just like another use case of. Okay. If we can interpret what's happening in post-training, you know, can we clear some of this? Can we even determine what's there? Because yeah, it's just like some worrying research that's out there that shows, you know, we really don't know what's going on.Mark Bissell [00:12:06]: That is. Yeah. I think that's the biggest sentiment that we're sort of hoping to tackle. Nobody knows what's going on. Right. Like subliminal learning is just an insane concept when you think about it. Right. Train a model on not even the logits, literally the output text of a bunch of random numbers. And now your model loves owls. And you see behaviors like that, that are just, they defy, they defy intuition. And, and there are mathematical explanations that you can get into, but. I mean.Shawn Wang [00:12:34]: It feels so early days. Objectively, there are a sequence of numbers that are more owl-like than others. There, there should be.Mark Bissell [00:12:40]: According to, according to certain models. Right. It's interesting. I think it only applies to models that were initialized from the same starting Z. Usually, yes.Shawn Wang [00:12:49]: But I mean, I think that's a, that's a cheat code because there's not enough compute. But like if you believe in like platonic representation, like probably it will transfer across different models as well. Oh, you think so?Mark Bissell [00:13:00]: I think of it more as a statistical artifact of models initialized from the same seed sort of. There's something that is like path dependent from that seed that might cause certain overlaps in the latent space and then sort of doing this distillation. Yeah. Like it pushes it towards having certain other tendencies.Vibhu Sapra [00:13:24]: Got it. I think there's like a bunch of these open-ended questions, right? Like you can't train in new stuff during the RL phase, right? RL only reorganizes weights and you can only do stuff that's somewhat there in your base model. You're not learning new stuff. You're just reordering chains and stuff. But okay. My broader question is when you guys work at an interp lab, how do you decide what to work on and what's kind of the thought process? Right. Because we can ramble for hours. Okay. I want to know this. I want to know that. But like, how do you concretely like, you know, what's the workflow? Okay. There's like approaches towards solving a problem, right? I can try prompting. I can look at chain of thought. I can train probes, SAEs. But how do you determine, you know, like, okay, is this going anywhere? Like, do we have set stuff? Just, you know, if you can help me with all that. Yeah.Myra Deng [00:14:07]: It's a really good question. I feel like we've always at the very beginning of the company thought about like, let's go and try to learn what isn't working in machine learning today. Whether that's talking to customers or talking to researchers at other labs, trying to understand both where the frontier is going and where things are really not falling apart today. And then developing a perspective on how we can push the frontier using interpretability methods. And so, you know, even our chief scientist, Tom, spends a lot of time talking to customers and trying to understand what real world problems are and then taking that back and trying to apply the current state of the art to those problems and then seeing where they fall down basically. And then using those failures or those shortcomings to understand what hills to climb when it comes to interpretability research. So like on the fundamental side, for instance, when we have done some work applying SAEs and probes, we've encountered, you know, some shortcomings in SAEs that we found a little bit surprising. And so have gone back to the drawing board and done work on that. And then, you know, we've done some work on better foundational interpreter models. And a lot of our team's research is focused on what is the next evolution beyond SAEs, for instance. And then when it comes to like control and design of models, you know, we tried steering with our first API and realized that it still fell short of black box techniques like prompting or fine tuning. And so went back to the drawing board and we're like, how do we make that not the case and how do we improve it beyond that? And one of our researchers, Ekdeep, who just joined is actually Ekdeep and Atticus are like steering experts and have spent a lot of time trying to figure out like, what is the research that enables us to actually do this in a much more powerful, robust way? So yeah, the answer is like, look at real world problems, try to translate that into a research agenda and then like hill climb on both of those at the same time.Shawn Wang [00:16:04]: Yeah. Mark has the steering CLI demo queued up, which we're going to go into in a sec. But I always want to double click on when you drop hints, like we found some problems with SAEs. Okay. What are they? You know, and then we can go into the demo. Yeah.Myra Deng [00:16:19]: I mean, I'm curious if you have more thoughts here as well, because you've done it in the healthcare domain. But I think like, for instance, when we do things like trying to detect behaviors within models that are harmful or like behaviors that a user might not want to have in their model. So hallucinations, for instance, harmful intent, PII, all of these things. We first tried using SAE probes for a lot of these tasks. So taking the feature activation space from SAEs and then training classifiers on top of that, and then seeing how well we can detect the properties that we might want to detect in model behavior. And we've seen in many cases that probes just trained on raw activations seem to perform better than SAE probes, which is a bit surprising if you think that SAEs are actually also capturing the concepts that you would want to capture cleanly and more surgically. And so that is an interesting observation. I don't think that is like, I'm not down on SAEs at all. I think there are many, many things they're useful for, but we have definitely run into cases where I think the concept space described by SAEs is not as clean and accurate as we would expect it to be for actual like real world downstream performance metrics.Mark Bissell [00:17:34]: Fair enough. Yeah. It's the blessing and the curse of unsupervised methods where you get to peek into the AI's mind. But sometimes you wish that you saw other things when you walked inside there. Although in the PII instance, I think weren't an SAE based approach actually did prove to be the most generalizable?Myra Deng [00:17:53]: It did work well in the case that we published with Rakuten. And I think a lot of the reasons it worked well was because we had a noisier data set. And so actually the blessing of unsupervised learning is that we actually got to get more meaningful, generalizable signal from SAEs when the data was noisy. But in other cases where we've had like good data sets, it hasn't been the case.Shawn Wang [00:18:14]: And just because you named Rakuten and I don't know if we'll get it another chance, like what is the overall, like what is Rakuten's usage or production usage? Yeah.Myra Deng [00:18:25]: So they are using us to essentially guardrail and inference time monitor their language model usage and their agent usage to detect things like PII so that they don't route private user information.Myra Deng [00:18:41]: And so that's, you know, going through all of their user queries every day. And that's something that we deployed with them a few months ago. And now we are actually exploring very early partnerships, not just with Rakuten, but with other people around how we can help with potentially training and customization use cases as well. Yeah.Shawn Wang [00:19:03]: And for those who don't know, like it's Rakuten is like, I think number one or number two e-commerce store in Japan. Yes. Yeah.Mark Bissell [00:19:10]: And I think that use case actually highlights a lot of like what it looks like to deploy things in practice that you don't always think about when you're doing sort of research tasks. So when you think about some of the stuff that came up there that's more complex than your idealized version of a problem, they were encountering things like synthetic to real transfer of methods. So they couldn't train probes, classifiers, things like that on actual customer data of PII. So what they had to do is use synthetic data sets. And then hope that that transfer is out of domain to real data sets. And so we can evaluate performance on the real data sets, but not train on customer PII. So that right off the bat is like a big challenge. You have multilingual requirements. So this needed to work for both English and Japanese text. Japanese text has all sorts of quirks, including tokenization behaviors that caused lots of bugs that caused us to be pulling our hair out. And then also a lot of tasks you'll see. You might make simplifying assumptions if you're sort of treating it as like the easiest version of the problem to just sort of get like general results where maybe you say you're classifying a sentence to say, does this contain PII? But the need that Rakuten had was token level classification so that you could precisely scrub out the PII. So as we learned more about the problem, you're sort of speaking about what that looks like in practice. Yeah. A lot of assumptions end up breaking. And that was just one instance where you. A problem that seems simple right off the bat ends up being more complex as you keep diving into it.Vibhu Sapra [00:20:41]: Excellent. One of the things that's also interesting with Interp is a lot of these methods are very efficient, right? So where you're just looking at a model's internals itself compared to a separate like guardrail, LLM as a judge, a separate model. One, you have to host it. Two, there's like a whole latency. So if you use like a big model, you have a second call. Some of the work around like self detection of hallucination, it's also deployed for efficiency, right? So if you have someone like Rakuten doing it in production live, you know, that's just another thing people should consider.Mark Bissell [00:21:12]: Yeah. And something like a probe is super lightweight. Yeah. It's no extra latency really. Excellent.Shawn Wang [00:21:17]: You have the steering demos lined up. So we were just kind of see what you got. I don't, I don't actually know if this is like the latest, latest or like alpha thing.Mark Bissell [00:21:26]: No, this is a pretty hacky demo from from a presentation that someone else on the team recently gave. So this will give a sense for, for technology. So you can see the steering and action. Honestly, I think the biggest thing that this highlights is that as we've been growing as a company and taking on kind of more and more ambitious versions of interpretability related problems, a lot of that comes to scaling up in various different forms. And so here you're going to see steering on a 1 trillion parameter model. This is Kimi K2. And so it's sort of fun that in addition to the research challenges, there are engineering challenges that we're now tackling. Cause for any of this to be sort of useful in production, you need to be thinking about what it looks like when you're using these methods on frontier models as opposed to sort of like toy kind of model organisms. So yeah, this was thrown together hastily, pretty fragile behind the scenes, but I think it's quite a fun demo. So screen sharing is on. So I've got two terminal sessions pulled up here. On the left is a forked version that we have of the Kimi CLI that we've got running to point at our custom hosted Kimi model. And then on the right is a set up that will allow us to steer on certain concepts. So I should be able to chat with Kimi over here. Tell it hello. This is running locally. So the CLI is running locally, but the Kimi server is running back to the office. Well, hopefully should be, um, that's too much to run on that Mac. Yeah. I think it's, uh, it takes a full, like each 100 node. I think it's like, you can. You can run it on eight GPUs, eight 100. So, so yeah, Kimi's running. We can ask it a prompt. It's got a forked version of our, uh, of the SG line code base that we've been working on. So I'm going to tell it, Hey, this SG line code base is slow. I think there's a bug. Can you try to figure it out? There's a big code base, so it'll, it'll spend some time doing this. And then on the right here, I'm going to initialize in real time. Some steering. Let's see here.Mark Bissell [00:23:33]: searching for any. Bugs. Feature ID 43205.Shawn Wang [00:23:38]: Yeah.Mark Bissell [00:23:38]: 20, 30, 40. So let me, uh, this is basically a feature that we found that inside Kimi seems to cause it to speak in Gen Z slang. And so on the left, it's still sort of thinking normally it might take, I don't know, 15 seconds for this to kick in, but then we're going to start hopefully seeing him do this code base is massive for real. So we're going to start. We're going to start seeing Kimi transition as the steering kicks in from normal Kimi to Gen Z Kimi and both in its chain of thought and its actual outputs.Mark Bissell [00:24:19]: And interestingly, you can see, you know, it's still able to call tools, uh, and stuff. It's um, it's purely sort of it's it's demeanor. And there are other features that we found for interesting things like concision. So that's more of a practical one. You can make it more concise. Um, the types of programs, uh, programming languages that uses, but yeah, as we're seeing it come in. Pretty good. Outputs.Shawn Wang [00:24:43]: Scheduler code is actually wild.Vibhu Sapra [00:24:46]: Yo, this code is actually insane, bro.Vibhu Sapra [00:24:53]: What's the process of training in SAE on this, or, you know, how do you label features? I know you guys put out a pretty cool blog post about, um, finding this like autonomous interp. Um, something. Something about how agents for interp is different than like coding agents. I don't know while this is spewing up, but how, how do we find feature 43, two Oh five. Yeah.Mark Bissell [00:25:15]: So in this case, um, we, our platform that we've been building out for a long time now supports all the sort of classic out of the box interp techniques that you might want to have like SAE training, probing things of that kind, I'd say the techniques for like vanilla SAEs are pretty well established now where. You take your model that you're interpreting, run a whole bunch of data through it, gather activations, and then yeah, pretty straightforward pipeline to train an SAE. There are a lot of different varieties. There's top KSAEs, batch top KSAEs, um, normal ReLU SAEs. And then once you have your sparse features to your point, assigning labels to them to actually understand that this is a gen Z feature, that's actually where a lot of the kind of magic happens. Yeah. And the most basic standard technique is look at all of your d input data set examples that cause this feature to fire most highly. And then you can usually pick out a pattern. So for this feature, If I've run a diverse enough data set through my model feature 43, two Oh five. Probably tends to fire on all the tokens that sounds like gen Z slang. You know, that's the, that's the time of year to be like, Oh, I'm in this, I'm in this Um, and, um, so, you know, you could have a human go through all 43,000 concepts andVibhu Sapra [00:26:34]: And I've got to ask the basic question, you know, can we get examples where it hallucinates, pass it through, see what feature activates for hallucinations? Can I just, you know, turn hallucination down?Myra Deng [00:26:51]: Oh, wow. You really predicted a project we're already working on right now, which is detecting hallucinations using interpretability techniques. And this is interesting because hallucinations is something that's very hard to detect. And it's like a kind of a hairy problem and something that black box methods really struggle with. Whereas like Gen Z, you could always train a simple classifier to detect that hallucinations is harder. But we've seen that models internally have some... Awareness of like uncertainty or some sort of like user pleasing behavior that leads to hallucinatory behavior. And so, yeah, we have a project that's trying to detect that accurately. And then also working on mitigating the hallucinatory behavior in the model itself as well.Shawn Wang [00:27:39]: Yeah, I would say most people are still at the level of like, oh, I would just turn temperature to zero and that turns off hallucination. And I'm like, well, that's a fundamental misunderstanding of how this works. Yeah.Mark Bissell [00:27:51]: Although, so part of what I like about that question is you, there are SAE based approaches that might like help you get at that. But oftentimes the beauty of SAEs and like we said, the curse is that they're unsupervised. So when you have a behavior that you deliberately would like to remove, and that's more of like a supervised task, often it is better to use something like probes and specifically target the thing that you're interested in reducing as opposed to sort of like hoping that when you fragment the latent space, one of the vectors that pops out.Vibhu Sapra [00:28:20]: And as much as we're training an autoencoder to be sparse, we're not like for sure certain that, you know, we will get something that just correlates to hallucination. You'll probably split that up into 20 other things and who knows what they'll be.Mark Bissell [00:28:36]: Of course. Right. Yeah. So there's no sort of problems with like feature splitting and feature absorption. And then there's the off target effects, right? Ideally, you would want to be very precise where if you reduce the hallucination feature, suddenly maybe your model can't write. Creatively anymore. And maybe you don't like that, but you want to still stop it from hallucinating facts and figures.Shawn Wang [00:28:55]: Good. So Vibhu has a paper to recommend there that we'll put in the show notes. But yeah, I mean, I guess just because your demo is done, any any other things that you want to highlight or any other interesting features you want to show?Mark Bissell [00:29:07]: I don't think so. Yeah. Like I said, this is a pretty small snippet. I think the main sort of point here that I think is exciting is that there's not a whole lot of inter being applied to models quite at this scale. You know, Anthropic certainly has some some. Research and yeah, other other teams as well. But it's it's nice to see these techniques, you know, being put into practice. I think not that long ago, the idea of real time steering of a trillion parameter model would have sounded.Shawn Wang [00:29:33]: Yeah. The fact that it's real time, like you started the thing and then you edited the steering vector.Vibhu Sapra [00:29:38]: I think it's it's an interesting one TBD of what the actual like production use case would be on that, like the real time editing. It's like that's the fun part of the demo, right? You can kind of see how this could be served behind an API, right? Like, yes, you're you only have so many knobs and you can just tweak it a bit more. And I don't know how it plays in. Like people haven't done that much with like, how does this work with or without prompting? Right. How does this work with fine tuning? Like, there's a whole hype of continual learning, right? So there's just so much to see. Like, is this another parameter? Like, is it like parameter? We just kind of leave it as a default. We don't use it. So I don't know. Maybe someone here wants to put out a guide on like how to use this with prompting when to do what?Mark Bissell [00:30:18]: Oh, well, I have a paper recommendation. I think you would love from Act Deep on our team, who is an amazing researcher, just can't say enough amazing things about Act Deep. But he actually has a paper that as well as some others from the team and elsewhere that go into the essentially equivalence of activation steering and in context learning and how those are from a he thinks of everything in a cognitive neuroscience Bayesian framework, but basically how you can precisely show how. Prompting in context, learning and steering exhibit similar behaviors and even like get quantitative about the like magnitude of steering you would need to do to induce a certain amount of behavior similar to certain prompting, even for things like jailbreaks and stuff. It's a really cool paper. Are you saying steering is less powerful than prompting? More like you can almost write a formula that tells you how to convert between the two of them.Myra Deng [00:31:20]: And so like formally equivalent actually in the in the limit. Right.Mark Bissell [00:31:24]: So like one case study of this is for jailbreaks there. I don't know. Have you seen the stuff where you can do like many shot jailbreaking? You like flood the context with examples of the behavior. And the topic put out that paper.Shawn Wang [00:31:38]: A lot of people were like, yeah, we've been doing this, guys.Mark Bissell [00:31:40]: Like, yeah, what's in this in context learning and activation steering equivalence paper is you can like predict the number. Number of examples that you will need to put in there in order to jailbreak the model. That's cool. By doing steering experiments and using this sort of like equivalence mapping. That's cool. That's really cool. It's very neat. Yeah.Shawn Wang [00:32:02]: I was going to say, like, you know, I can like back rationalize that this makes sense because, you know, what context is, is basically just, you know, it updates the KV cache kind of and like and then every next token inference is still like, you know, the sheer sum of everything all the way. It's plus all the context. It's up to date. And you could, I guess, theoretically steer that with you probably replace that with your steering. The only problem is steering typically is on one layer, maybe three layers like like you did. So it's like not exactly equivalent.Mark Bissell [00:32:33]: Right, right. There's sort of you need to get precise about, yeah, like how you sort of define steering and like what how you're modeling the setup. But yeah, I've got the paper pulled up here. Belief dynamics reveal the dual nature. Yeah. The title is Belief Dynamics Reveal the Dual Nature of Incompetence. And it's an exhibition of the practical context learning and activation steering. So Eric Bigelow, Dan Urgraft on the who are doing fellowships at Goodfire, Ekt Deep's the final author there.Myra Deng [00:32:59]: I think actually to your question of like, what is the production use case of steering? I think maybe if you just think like one level beyond steering as it is today. Like imagine if you could adapt your model to be, you know, an expert legal reasoner. Like in almost real time, like very quickly. efficiently using human feedback or using like your semantic understanding of what the model knows and where it knows that behavior. I think that while it's not clear what the product is at the end of the day, it's clearly very valuable. Thinking about like what's the next interface for model customization and adaptation is a really interesting problem for us. Like we have heard a lot of people actually interested in fine-tuning an RL for open weight models in production. And so people are using things like Tinker or kind of like open source libraries to do that, but it's still very difficult to get models fine-tuned and RL'd for exactly what you want them to do unless you're an expert at model training. And so that's like something we'reShawn Wang [00:34:06]: looking into. Yeah. I never thought so. Tinker from Thinking Machines famously uses rank one LoRa. Is that basically the same as steering? Like, you know, what's the comparison there?Mark Bissell [00:34:19]: Well, so in that case, you are still applying updates to the parameters, right?Shawn Wang [00:34:25]: Yeah. You're not touching a base model. You're touching an adapter. It's kind of, yeah.Mark Bissell [00:34:30]: Right. But I guess it still is like more in parameter space then. I guess it's maybe like, are you modifying the pipes or are you modifying the water flowing through the pipes to get what you're after? Yeah. Just maybe one way.Mark Bissell [00:34:44]: I like that analogy. That's my mental map of it at least, but it gets at this idea of model design and intentional design, which is something that we're, that we're very focused on. And just the fact that like, I hope that we look back at how we're currently training models and post-training models and just think what a primitive way of doing that right now. Like there's no intentionalityShawn Wang [00:35:06]: really in... It's just data, right? The only thing in control is what data we feed in.Mark Bissell [00:35:11]: So, so Dan from Goodfire likes to use this analogy of, you know, he has a couple of young kids and he talks about like, what if I could only teach my kids how to be good people by giving them cookies or like, you know, giving them a slap on the wrist if they do something wrong, like not telling them why it was wrong or like what they should have done differently or something like that. Just figure it out. Right. Exactly. So that's RL. Yeah. Right. And, and, you know, it's sample inefficient. There's, you know, what do they say? It's like slurping feedback. It's like, slurping supervision. Right. And so you'd like to get to the point where you can have experts giving feedback to their models that are, uh, internalized and, and, you know, steering is an inference time way of sort of getting that idea. But ideally you're moving to a world whereVibhu Sapra [00:36:04]: it is much more intentional design in perpetuity for these models. Okay. This is one of the questions we asked Emmanuel from Anthropic on the podcast a few months ago. Basically the question, was you're at a research lab that does model training, foundation models, and you're on an interp team. How does it tie back? Right? Like, does this, do ideas come from the pre-training team? Do they go back? Um, you know, so for those interested, you can, you can watch that. There wasn't too much of a connect there, but it's still something, you know, it's something they want toMark Bissell [00:36:33]: push for down the line. It can be useful for all of the above. Like there are certainly post-hocVibhu Sapra [00:36:39]: use cases where it doesn't need to touch that. I think the other thing a lot of people forget is this stuff isn't too computationally expensive, right? Like I would say, if you're interested in getting into research, MechInterp is one of the most approachable fields, right? A lot of this train an essay, train a probe, this stuff, like the budget for this one, there's already a lot done. There's a lot of open source work. You guys have done some too. Um, you know,Shawn Wang [00:37:04]: There's like notebooks from the Gemini team for Neil Nanda or like, this is how you do it. Just step through the notebook.Vibhu Sapra [00:37:09]: Even if you're like, not even technical with any of this, you can still make like progress. There, you can look at different activations, but, uh, if you do want to get into training, you know, training this stuff, correct me if I'm wrong is like in the thousands of dollars, not even like, it's not that high scale. And then same with like, you know, applying it, doing it for post-training or all this stuff is fairly cheap in scale of, okay. I want to get into like model training. I don't have compute for like, you know, pre-training stuff. So it's, it's a very nice field to get into. And also there's a lot of like open questions, right? Um, some of them have to go with, okay, I want a product. I want to solve this. Like there's also just a lot of open-ended stuff that people could work on. That's interesting. Right. I don't know if you guys have any calls for like, what's open questions, what's open work that you either open collaboration with, or like, you'd just like to see solved or just, you know, for people listening that want to get into McInturk because people always talk about it. What are, what are the things they should check out? Start, of course, you know, join you guys as well. I'm sure you're hiring.Myra Deng [00:38:09]: There's a paper, I think from, was it Lee, uh, Sharky? It's open problems and, uh, it's, it's a bit of interpretability, which I recommend everyone who's interested in the field. Read. I'm just like a really comprehensive overview of what are the things that experts in the field think are the most important problems to be solved. I also think to your point, it's been really, really inspiring to see, I think a lot of young people getting interested in interpretability, actually not just young people also like scientists to have been, you know, experts in physics for many years and in biology or things like this, um, transitioning into interp, because the barrier of, of what's now interp. So it's really cool to see a number to entry is, you know, in some ways low and there's a lot of information out there and ways to get started. There's this anecdote of like professors at universities saying that all of a sudden every incoming PhD student wants to study interpretability, which was not the case a few years ago. So it just goes to show how, I guess, like exciting the field is, how fast it's moving, how quick it is to get started and things like that.Mark Bissell [00:39:10]: And also just a very welcoming community. You know, there's an open source McInturk Slack channel. There are people are always posting questions and just folks in the space are always responsive if you ask things on various forums and stuff. But yeah, the open paper, open problems paper is a really good one.Myra Deng [00:39:28]: For other people who want to get started, I think, you know, MATS is a great program. What's the acronym for? Machine Learning and Alignment Theory Scholars? It's like the...Vibhu Sapra [00:39:40]: Normally summer internship style.Myra Deng [00:39:42]: Yeah, but they've been doing it year round now. And actually a lot of our full-time staff have come through that program or gone through that program. And it's great for anyone who is transitioning into interpretability. There's a couple other fellows programs. We do one as well as Anthropic. And so those are great places to get started if anyone is interested.Mark Bissell [00:40:03]: Also, I think been seen as a research field for a very long time. But I think engineering... I think engineers are sorely wanted for interpretability as well, especially at Goodfire, but elsewhere, as it does scale up.Shawn Wang [00:40:18]: I should mention that Lee actually works with you guys, right? And in the London office and I'm adding our first ever McInturk track at AI Europe because I see this industry applications now emerging. And I'm pretty excited to, you know, help push that along. Yeah, I was looking forward to that. It'll effectively be the first industry McInturk conference. Yeah. I'm so glad you added that. You know, it's still a little bit of a bet. It's not that widespread, but I can definitely see this is the time to really get into it. We want to be early on things.Mark Bissell [00:40:51]: For sure. And I think the field understands this, right? So at ICML, I think the title of the McInturk workshop this year was actionable interpretability. And there was a lot of discussion around bringing it to various domains. Everyone's adding pragmatic, actionable, whatever.Shawn Wang [00:41:10]: It's like, okay, well, we weren't actionable before, I guess. I don't know.Vibhu Sapra [00:41:13]: And I mean, like, just, you know, being in Europe, you see the Interp room. One, like old school conferences, like, I think they had a very tiny room till they got lucky and they got it doubled. But there's definitely a lot of interest, a lot of niche research. So you see a lot of research coming out of universities, students. We covered the paper last week. It's like two unknown authors, not many citations. But, you know, you can make a lot of meaningful work there. Yeah. Yeah. Yeah.Shawn Wang [00:41:39]: Yeah. I think people haven't really mentioned this yet. It's just Interp for code. I think it's like an abnormally important field. We haven't mentioned this yet. The conspiracy theory last two years ago was when the first SAE work came out of Anthropic was they would do like, oh, we just used SAEs to turn the bad code vector down and then turn up the good code. And I think like, isn't that the dream? Like, you know, like, but basically, I guess maybe, why is it funny? Like, it's... If it was realistic, it would not be funny. It would be like, no, actually, we should do this. But it's funny because we know there's like, we feel there's some limitations to what steering can do. And I think a lot of the public image of steering is like the Gen Z stuff. Like, oh, you can make it really love the Golden Gate Bridge, or you can make it speak like Gen Z. To like be a legal reasoner seems like a huge stretch. Yeah. And I don't know if that will get there this way. Yeah.Myra Deng [00:42:36]: I think, um, I will say we are announcing. Something very soon that I will not speak too much about. Um, but I think, yeah, this is like what we've run into again and again is like, we, we don't want to be in the world where steering is only useful for like stylistic things. That's definitely not, not what we're aiming for. But I think the types of interventions that you need to do to get to things like legal reasoning, um, are much more sophisticated and require breakthroughs in, in learning algorithms. And that's, um...Shawn Wang [00:43:07]: And is this an emergent property of scale as well?Myra Deng [00:43:10]: I think so. Yeah. I mean, I think scale definitely helps. I think scale allows you to learn a lot of information and, and reduce noise across, you know, large amounts of data. But I also think we think that there's ways to do things much more effectively, um, even, even at scale. So like actually learning exactly what you want from the data and not learning things that you do that you don't want exhibited in the data. So we're not like anti-scale, but we are also realizing that scale is not going to get us anywhere. It's not going to get us to the type of AI development that we want to be at in, in the future as these models get more powerful and get deployed in all these sorts of like mission critical contexts. Current life cycle of training and deploying and evaluations is, is to us like deeply broken and has opportunities to, to improve. So, um, more to come on that very, very soon.Mark Bissell [00:44:02]: And I think that that's a use basically, or maybe just like a proof point that these concepts do exist. Like if you can manipulate them in the precise best way, you can get the ideal combination of them that you desire. And steering is maybe the most coarse grained sort of peek at what that looks like. But I think it's evocative of what you could do if you had total surgical control over every concept, every parameter. Yeah, exactly.Myra Deng [00:44:30]: There were like bad code features. I've got it pulled up.Vibhu Sapra [00:44:33]: Yeah. Just coincidentally, as you guys are talking.Shawn Wang [00:44:35]: This is like, this is exactly.Vibhu Sapra [00:44:38]: There's like specifically a code error feature that activates and they show, you know, it's not, it's not typo detection. It's like, it's, it's typos in code. It's not typical typos. And, you know, you can, you can see it clearly activates where there's something wrong in code. And they have like malicious code, code error. They have a whole bunch of sub, you know, sub broken down little grain features. Yeah.Shawn Wang [00:45:02]: Yeah. So, so the, the rough intuition for me, the, why I talked about post-training was that, well, you just, you know, have a few different rollouts with all these things turned off and on and whatever. And then, you know, you can, that's, that's synthetic data you can kind of post-train on. Yeah.Vibhu Sapra [00:45:13]: And I think we make it sound easier than it is just saying, you know, they do the real hard work.Myra Deng [00:45:19]: I mean, you guys, you guys have the right idea. Exactly. Yeah. We replicated a lot of these features in, in our Lama models as well. I remember there was like.Vibhu Sapra [00:45:26]: And I think a lot of this stuff is open, right? Like, yeah, you guys opened yours. DeepMind has opened a lot of essays on Gemma. Even Anthropic has opened a lot of this. There's, there's a lot of resources that, you know, we can probably share of people that want to get involved.Shawn Wang [00:45:41]: Yeah. And special shout out to like Neuronpedia as well. Yes. Like, yeah, amazing piece of work to visualize those things.Myra Deng [00:45:49]: Yeah, exactly.Shawn Wang [00:45:50]: I guess I wanted to pivot a little bit on, onto the healthcare side, because I think that's a big use case for you guys. We haven't really talked about it yet. This is a bit of a crossover for me because we are, we are, we do have a separate science pod that we're starting up for AI, for AI for science, just because like, it's such a huge investment category and also I'm like less qualified to do it, but we actually have bio PhDs to cover that, which is great, but I need to just kind of recover, recap your work, maybe on the evil two stuff, but then, and then building forward.Mark Bissell [00:46:17]: Yeah, for sure. And maybe to frame up the conversation, I think another kind of interesting just lens on interpretability in general is a lot of the techniques that were described. are ways to solve the AI human interface problem. And it's sort of like bidirectional communication is the goal there. So what we've been talking about with intentional design of models and, you know, steering, but also more advanced techniques is having humans impart our desires and control into models and over models. And the reverse is also very interesting, especially as you get to superhuman models, whether that's narrow superintelligence, like these scientific models that work on genomics, data, medical imaging, things like that. But down the line, you know, superintelligence of other forms as well. What knowledge can the AIs teach us as sort of that, that the other direction in that? And so some of our life science work to date has been getting at exactly that question, which is, well, some of it does look like debugging these various life sciences models, understanding if they're actually performing well, on tasks, or if they're picking up on spurious correlations, for instance, genomics models, you would like to know whether they are sort of focusing on the biologically relevant things that you care about, or if it's using some simpler correlate, like the ancestry of the person that it's looking at. But then also in the instances where they are superhuman, and maybe they are understanding elements of the human genome that we don't have names for or specific, you know, yeah, discoveries that they've made that that we don't know about, that's, that's a big goal. And so we're already seeing that, right, we are partnered with organizations like Mayo Clinic, leading research health system in the United States, our Institute, as well as a startup called Prima Menta, which focuses on neurodegenerative disease. And in our partnership with them, we've used foundation models, they've been training and applied our interpretability techniques to find novel biomarkers for Alzheimer's disease. So I think this is just the tip of the iceberg. But it's, that's like a flavor of some of the things that we're working on.Shawn Wang [00:48:36]: Yeah, I think that's really fantastic. Obviously, we did the Chad Zuckerberg pod last year as well. And like, there's a plethora of these models coming out, because there's so much potential and research. And it's like, very interesting how it's basically the same as language models, but just with a different underlying data set. But it's like, it's the same exact techniques. Like, there's no change, basically.Mark Bissell [00:48:59]: Yeah. Well, and even in like other domains, right? Like, you know, robotics, I know, like a lot of the companies just use Gemma as like the like backbone, and then they like make it into a VLA that like takes these actions. It's, it's, it's transformers all the way down. So yeah.Vibhu Sapra [00:49:15]: Like we have Med Gemma now, right? Like this week, even there was Med Gemma 1.5. And they're training it on this stuff, like 3d scans, medical domain knowledge, and all that stuff, too. So there's a push from both sides. But I think the thing that, you know, one of the things about McInturpp is like, you're a little bit more cautious in some domains, right? So healthcare, mainly being one, like guardrails, understanding, you know, we're more risk adverse to something going wrong there. So even just from a basic understanding, like, if we're trusting these systems to make claims, we want to know why and what's going on.Myra Deng [00:49:51]: Yeah, I think there's totally a kind of like deployment bottleneck to actually using. foundation models for real patient usage or things like that. Like, say you're using a model for rare disease prediction, you probably want some explanation as to why your model predicted a certain outcome, and an interpretable explanation at that. So that's definitely a use case. But I also think like, being able to extract scientific information that no human knows to accelerate drug discovery and disease treatment and things like that actually is a really, really big unlock for science, like scientific discovery. And you've seen a lot of startups, like say that they're going to accelerate scientific discovery. And I feel like we actually are doing that through our interp techniques. And kind of like, almost by accident, like, I think we got reached out to very, very early on from these healthcare institutions. And none of us had healthcare.Shawn Wang [00:50:49]: How did they even hear of you? A podcast.Myra Deng [00:50:51]: Oh, okay. Yeah, podcast.Vibhu Sapra [00:50:53]: Okay, well, now's that time, you know.Myra Deng [00:50:55]: Everyone can call us.Shawn Wang [00:50:56]: Podcasts are the most important thing. Everyone should listen to podcasts.Myra Deng [00:50:59]: Yeah, they reached out. They were like, you know, we have these really smart models that we've trained, and we want to know what they're doing. And we were like, really early that time, like three months old, and it was a few of us. And we were like, oh, my God, we've never used these models. Let's figure it out. But it's also like, great proof that interp techniques scale pretty well across domains. We didn't really have to learn too much about.Shawn Wang [00:51:21]: Interp is a machine learning technique, machine learning skills everywhere, right? Yeah. And it's obviously, it's just like a general insight. Yeah. Probably to finance too, I think, which would be fun for our history. I don't know if you have anything to say there.Mark Bissell [00:51:34]: Yeah, well, just across the science. Like, we've also done work on material science. Yeah, it really runs the gamut.Vibhu Sapra [00:51:40]: Yeah. Awesome. And, you know, for those that should reach out, like, you're obviously experts in this, but like, is there a call out for people that you're looking to partner with, design partners, people to use your stuff outside of just, you know, the general developer that wants to. Plug and play steering stuff, like on the research side more so, like, are there ideal design partners, customers, stuff like that?Myra Deng [00:52:03]: Yeah, I can talk about maybe non-life sciences, and then I'm curious to hear from you on the life sciences side. But we're looking for design partners across many domains, language, anyone who's customizing language models or trying to push the frontier of code or reasoning models is really interesting to us. And then also interested in the frontier of modeling. There's a lot of models that work in, like, pixel space, as we call it. So if you're doing world models, video models, even robotics, where there's not a very clean natural language interface to interact with, I think we think that Interp can really help and are looking for a few partners in that space.Shawn Wang [00:52:43]: Just because you mentioned the keyword

A baffled Sir Chucklenugget arrives at Wizzlethorp's tower with a strange report: a "mad-gnome" is loose in Snaggleton!

Welcome to Dev Game Club, where this week we begin a series on 1985's Ultima IV. After talking about the recent Defeating Games for Charity, we set the game in its time, talk about our encounters in the past with the series, and then dive into the manuals and the start of the game. Dev Game Club looks at classic video games and plays through them over several episodes, providing commentary. Sections played: The first couple of hours and the manuals  Issues covered: Defeating Games for Charity, the first pancake, our experiences with this series, an opaque franchise, mainlining a game, opacity being part of the point, performance characteristics of the PCs of the time, the importance of the manuals, entering the world as yourself, using the manual to reinforce the role-play, not requiring graphics, priming the player, describing the geography of different areas, imposing importance on a handful of pixels, the quest of the game, sublimating the quest of the game, a less traditional RPG experience, after reading the manual, the deep questions/dilemmas, tournament structure, choosing your most important virtue, getting the bard, series characters who can join your party, reflecting your beliefs, getting different dilemmas, the Venn diagram of virtues, the Tinker profession, symmetry in design, Buddhism and the Eightfold Path, countering the cultural zeitgeist, the Avatar and Hinduism, a deity's manifestation on Earth, finding your way into swamps, both hosts being poisoned and dying, death and rebirth, being unable to recruit early. Games, people, and influences mentioned or discussed: Dwarf Fortress, BioStats, KyleAndError13, Silksong, GreyFiery, Hollow Knight, Untitled Goose Game, Kaeon, Hitman, N0isses, Hades, Phil Salvador, MYST, RobotSpacer, Shadowgate, Unpacking, Kendrama, CalamityNolan, Splatoon 2, Typing of the Dead, Dark Souls 2, Nitro, Metal Gear Solid, Resident Evil, LostLake, Minecraft, Super Mario Bros Shuffler, Devil May Cry, MegaMan X, Belmont, NES, Atari 2600, Ultima Underworld, A Bard's Tale, Eye of the Beholder, Magic: The Gathering, LucasArts, Super Mario 64, Space Harrier, Gauntlet, Ghosts n' Goblins, Gradius, Super Mario Bros, Tetris, Where in the World Is Carmen Sandiego, Spy vs Spy (series), Oregon Trail, King's Quest II, The Goonies, Gremlins, A View to a Kill, Rambo, Temple of Doom, The Empire Strikes Back, SEGA Master System, Sonic (series), Wizardry, Apple ][, Commodore 64, Civilization III, The Sims, Bill Roper, Warcraft, The Elder Scrolls: Morrowind, Reed Knight, Pool of Radiance, Dungeons & Dragons, Warren Spector, Ultima Adventures, Outcast, Fallout, Wasteland, A Connecticut Yankee in King Arthur's Court, Harley Baldwin, Richard Garriott, the Ramayana, Ed Fries, Benimanjaro, Kirk Hamilton, Aaron Evers, Mark Garcia.  Note: Because Ultima IV has very little music to speak of, I will be substituting music from later in the series in the openings to these episodes TTDS: 06:25 Next time: More Ultima IV Twitch: timlongojr and twinsunscorp YouTube Discord DevGameClub@gmail.com

Level Up 168 Forge of the Artificer Hoy Nacho desvaría con Matrix, trabajando con Seijo se dio cuenta de los patrones que suceden en la película Matrix que pueden extrapolarse al mundo rolero. A partir de ahí intenta trasladar todo este enfoque para diseñar un juego de rol. Eberron: Forge of the Artificer es un compendio de reglas para Dungeons & Dragons, ambientado en el mundo de Eberron, se publicó como una expansión de la quinta edición revisada (5.5e) el 9 de diciembre de 2025. Este suplemento se centra principalmente en la clase Artífice, conocida por su habilidad para combinar magia e invención tecnológica, ofreciendo nuevas opciones tanto para jugadores como para directores de juego (DMs). La clase Artífice revisada El Artífice regresa como un maestro de las invenciones mágicas, con una reestructuración profunda de sus capacidades para la nueva edición. Entre los cambios más destacados se incluyen: Tinker's Magic: reemplaza la antigua habilidad de Magical Tinkering. Ahora, el Artífice puede crear objetos cotidianos útiles como cuerdas, antorchas, garfios o proyecciones de gravilla con sus herramientas, que duran hasta el próximo descanso largo. La cantidad de usos por descanso depende del modificador de Inteligencia del Artífice. Replicate Magic Item: sustituye el sistema de Infuse Item. Ahora el Artífice aprende planos para crear objetos mágicos de distintos niveles y puede fabricarlos directamente, otorgando una flexibilidad sin precedentes. Puede crear escudos, varitas, botas voladoras y objetos mágicos sin depender de objetos base. Magic Item Tinker: a partir del nivel 6, el Artífice puede manipular sus objetos replicados: recargar cristales mágicos con hechizos, drenar objetos para recuperar espacios de hechizo y transformar un objeto replicado en otro conocido. Flash of Genius: mejorado para activarse tras un fallo de tirada, añadiendo a cualquier chequeo o salvación el modificador de Inteligencia del personaje. Epic Boon y Soul of Artifice: capacidades de niveles superiores que permiten sobrevivir a impactos mortales mediante la destrucción de objetos replicados y recuperar usos de Flash of Genius tras un descanso corto. Subclases y especializaciones Forge of the Artificer trae cinco subclases: Alchemist: experto en pociones y elixires, centrado en curación y buffs de manera versátil. Armorer: mejora armaduras y puede convertirse en un tanque con personalizada armadura mágica. Artillerist: especialista en daño a distancia, usando su Eldritch Cannon para ataque y apoyo. Battle Smith: acompañante mecánico llamado Steel Defender y roles defensivos para el grupo. Cartographer (nueva): esta subclase se enfoca en exploración y control del campo de batalla mediante mapas mágicos (Adventurer's Atlas), portales de teletransporte, y habilidades que permiten a los aliados moverse y atacar con mayor libertad. El Cartógrafo, en particular, enfatiza la movilidad y la inteligencia táctica, otorgando ventajas únicas al posicionamiento y a la coordinación durante combates, exploración y desafíos estratégicos. Opciones para jugadores El suplemento amplía la creación de personajes con más de 40 opciones de jugador, que incluyen: Especies jugables revisadas, como los Warforged mecanizados y los Khoravar (mitad elfos de Eberron). Trasfondos y dotes, incluyendo el rediseño de las Dragonmarks, accesibles ahora sin restricciones de especie. Hechizos, objetos mágicos innovadores y vehículos especiales que amplían la narración y la interacción del grupo con el mundo mágico-tecnológico de Eberron. Herramientas para directores de juego Forge of the Artificer proporciona modelos de campaña y herramientas creativas: Tres plantillas de aventura: fantasía negra, intriga política y aventura pulp, con capítulos de muestra, enganches narrativos y guías de encuentros. Más de 20 monstruos nuevos y estructuras de bastión para crear desafíos emocionantes. Reglas para el uso de airships y bases móviles, permitiendo escenarios espectaculares y dinámicos. Esperamos que os guste! Música de Uppbeat: License code: DSJHNLFTIRWBKXPO Música de Youtube

  Music from: Empty Hats, MadWitch, The Lost Boys, Boom Pirates, Kathleen Johnson, Marc Gunn, Langer's Ball, Nightin Gael, Dublin Harpers, The Cross Jacks, The Irish Bard, New Minstrel Revue, Maggie and the Tinker, Phillip Hole, Celtic Shores, Old Goat Skiffle Band, Queen Ann's Lace, The Musical Blades, Jesse Ferguson, Pirates Of Rogues Cove, DeCantus, Sheer Pandemonium VISIT OUR SPONSORS Bawdy Podcast https://renfestbawdypodcast.libsyn.com/ Happy To Be Coloring Pages https://happytobecoloring.justonemore.website RESCU https://RESCU.org The 23 Patrons of the Podcast https://www.patreon.com/RenFestPodcast The Ren List http://www.therenlist.com SONGS Song 01: Blind Fiddler by Empty Hats from Released www.emptyhats.com Song 02: ZigZag by MadWitch from Fablegroove https://madwitchband.com/ Song 03: The Hod Song by The Lost Boys from Heroes & Scoundrels(2008) www.facebook.com/TheLostBoys1599/ Song 04: Scallywagg by Boom Pirates from Prepare To Be Boarded www.facebook.com/boompirates/ Song 05: Drink To Me Only by Kathleen Johnson from Faire Music www.kathleen-johnson.com/ Song 06: Old Dun Cow [11] by Marc Gunn from Virtual Public House www.marcgunn.com Song 07: Whiskey From the Still by Langer's Ball from Hold Tight www.TheLangersBall.com Song 08: Rose, Rose by Nightin Gael from First Flight www.facebook.com/nightingael/ Song 09: Round About Reel by Dublin Harpers from Dublin Harpers Live www.dublinharpers.bandcamp.com Song 10: Star of the County Down [39] by The Cross Jacks from The Cross Jacks www.sites.google.com/site/thecrossjacks/ Song 11: Bog Down in the Valley [04] by The Irish Bard from The Irish Bard www.theirishbard.com/ Song 12: Tarantella [02] by New Minstrel Revue from Many Hands UNKNOW WEBSITE Song 13: The Woodcutter's Song(Trad) by Maggie and the Tinker from Huh? www.facebook.com/maggieandthetinker/ Song 14: Fiddler's Green [14] by Phillip Hole from The Singing Gravedigger UNKNOW WEBSITE Song 15: Whiskey You're the Devil [01] by Celtic Shores from Weathering The Storm www.matthughesmusic.com Song 16: Maggie May [05] by Old Goat Skiffle Band from Just Kidding www.facebook.com/OldGoatSkiffleBand Song 17: All Around My Hat [09] by Queen Ann's Lace from Moves Through the Faire www.QALace.com Song 18: Blood Red Roses [02] by The Musical Blades from Modern Day Pirate www.musicalblades.com Song 19: Blood Red Roses [01] by Jesse Ferguson from Sea Shanties and Whaling Ballads www.jessefergusonmusic.com Song 20: Roll the Old Chariot Along [04] by Pirates Of Rogues Cove from Setting Sail www.roguescove.org Song 21: The Girl I Left Behind Me [01] by DeCantus from Tonight We'll Merry Bee www.decantus.com/ Song 22: Black Velvet Doo Wop by Sheer Pandemonium from Singles Song 23: Raise Your Pistols by Beerside Scoundrels from Duel! www.reverbnation.com/thebeersidescoundrels Song 24: Parting Glass [30] by LandLoch'd from The Devil's Own Invention www.landlochd.com   HOW TO CONTACT US Please post it on Facebook https://www.facebook.com/renfestmusic Please email us at renfestpodcast@gmail.com OTHER CREDITS Thee Bawdy Verson https://renfestbawdypodcast.libsyn.com/ The Minion Song by Fugli www.povera.com Valediction by Marc Gunn https://marcgunn.com/ HOW TO LISTEN Patreon https://www.patreon.com/RenFestPodcast Apple https://podcasts.apple.com/us/podcast/renaissance-festival-podcast/id74073024 Spotify https://open.spotify.com/show/76uzuG0lRulhdjDCeufK15?si=obnUk_sUQnyzvvs3E_MV1g Listennotes http://www.listennotes.com/podcasts/renaissance-festival-podcast-minions-1Xd3YjQ7fWx/

In 1965, John and Mary Beth Tinker protested the Vietnam War by wearing black arm bands to school. The incident led to a landmark Supreme Court decision that guaranteed free speech rights for public school students. The Tinkers reflect on this history and present day threats to the First Amendment. Later, a new play from playwright Megan Gogerty works through her complicated feelings about her father and family's history as a sixth generation Iowan.

Stjärnregissören Tomas Alfredson är bioaktuell med Lek med Alfons Åberg. P1 Kulturs Lisa Bergström undersöker vad som är hans egen relation till Alfons? Och till Gunilla Bergström? Lyssna på alla avsnitt i Sveriges Radios app. Tomas Alfredson är mest känd för filmer som dramaskräckisen ”Låt den rätte komma in”, Killinggängets ”Fyra nyanser av brunt” och spionthrillern ”Tinker, Tailor, Soilder, Spy”.Förra året gjorde han tv-serien ”Trolösa” i SVT. Men dessförinnan släppte sin första Bokfilm: "Aja baja, Alfons Åberg" (2022) - nu som då med Jonas Karlsson som berättare.Varför dras han till Alfons Åberg? Och vad är egentligen en ”bokfilm”?Dessutom, efter intervjun följer ett kritiksamtal om ”Lek med Alfons Åberg” med kulturredaktionens filmkritiker Nina Asarnoj.

USA fortsätter att sätta tryck på Danmark angående kontrollen av Grönland. Sveriges Radios Norden-korrespondent David Rasmusson gästar P1 Kultur och vår reporter Emma Engström har ringt runt till grönländska kulturinstitutioner Lyssna på alla avsnitt i Sveriges Radios app. ADAM PRICE (”BORGEN”) OM NÄR VERKLIGHETEN SPRANG OM FIKTIONEN PÅ GRÖNLANDManusförfattaren Adam Price skildrade den geopolitiska krutdurken som är Grönland för en bred publik i fjärde säsongen av den danska tv-serien ”Borgen” på Netflix. Det var fyra år sedan. Nu har verkligheten sprungit om hans egen fiktion. Vår reporter Emma Engström ringde upp honom.HÄR ÄR DE NOMINERADE TILL SVERIGES RADIOS ROMANPRIS!Sveriges Radios litteraturredaktör Lina Kalmteg och Romanprisets producent Anna Tullberg gästar P1 Kultur för att berätta mer om de fyra nominerade romanerna: ”17 juni” av Alex Schulman, ”Våran pojke” av Mikael Yvesand, ”Döden i trakten / Kvinnor i revolt” av Monika Fagerholm och ”Förlorad mark” av Frans Wachtmeister. Vad utmärker de nominerade romanerna? Och hur och när kommer vinnaren att utses?ALFONS ÅBERG GÖR COMEBACK PÅ BIO – SOM BOKFILMStjärnregissören Tomas Alfredson (”Låt den rätte komma in”, ”Tinker, Tailor, Soldier, Spy”, ”Fyra nyanser av brunt”) är bioaktuell med ”Lek med Alfons Åberg” – P1 Kulturs Lisa Bergström undersöker vad som är Alfredsons egen relation till Alfons Åberg? Och till Alfons-skaparen Gunilla Bergström? Dessutom diskuterar vi den nya ”bokfilmen” med vår filmkritiker Nina Asarnoj.Programledare: Lisa BergströmProducent: Henrik Arvidsson

Write. Tinker. Win.From Hip Hop to EntrepreneurshipRoss Simmonds grew up learning lessons from hip hop that would later shape his entire career. From Jay-Z and Lupe Fiasco to Kendrick Lamar, the messages of hunger, excellence, and humility built the foundation for how he approaches business. In this episode of Just Keep Learning, Ross explains how those same principles helped him turn curiosity and writing into a multi-business empire.Building Businesses From CuriosityRoss didn't start with a blueprint,he started with experiments. From selling jerseys and durags out of his locker to creating blogs and digital guides, he learned that curiosity compounds into skills. Each project taught him something new about sales, storytelling, and community,skills he now uses to run his B2B marketing agency and e-commerce brand.Personal Branding and the “CEO of You”Ross breaks down his framework for personal branding: think of yourself as a company. Be your own CEO, marketing director, finance officer, and HR department. Decide what you want to be known for, and act accordingly. A personal brand isn't about pretending; it's about doing real things, then sharing them.Hip Hop, Hustle, and Staying HumbleHip hop taught Ross that ambition and gratitude can coexist. At his agency, Foundation, the mantra “Stand up. Be humble.” serves as a daily reminder to celebrate wins without getting complacent. Like a great verse, every project deserves your best performance,treat your first like your last and your last like your first.B2B vs. B2C and Making Money OnlineRoss demystifies the world of business models. Whether it's selling to consumers or companies, he says the key is finding what excites you. For some, that's making merch or art; for others, it's helping organizations grow. Both can work if you stay focused and learn to sell. He explains how digital skills,writing, design, communication,can turn into income fast through freelancing, affiliate marketing, or online products.Lessons For Aspiring CreatorsTreat every project like your firstLearn from hip hop: stay hungry, stay humbleThink like a CEO,build your personal brand with intentionUse the internet as your equalizer; the opportunities are endlessBuild skills before income; curiosity compounds into cash flowExperiment. Tinker. Keep learning.Memorable Quotes“Treat your first like your last, and your last like your first.”“The internet is the greatest equalizer.”“Be the CEO of you.”“There's no one too unskilled to make money online.”“Find joy in tinkering,the play is the path.”Final Advice For CreatorsBe willing to experiment. Don't chase perfection,chase curiosity. Build something, learn from it, and keep evolving. That's how you win in business and in life.Guest BioRoss Simmonds is an entrepreneur, speaker, and the founder of Foundation, a B2B content marketing agency helping global brands scale through strategy and storytelling. He's also behind Hustle & Grind, a lifestyle brand for creators. Known for blending hip hop culture with business insight, Ross teaches creators and marketers how to turn ideas into impact.CHECK OUT THE JKL STORE FOR HELP MAKING YOUR BOOK, PODCAST AND BUSINESS DREAMS COME TRUE!FOLLOW JustinInstagram – @JustKeepLearning.CaYouTube –@justkeeplearningpodcastTwitter – @JustinNolan_JKLTiktok – @justkeeplearning.caPinterest – JustKeepLearningcaFacebook – JustKeepLearningLinkedIn – Justin I'm so happy you found this podcast. I am here to serve you, the creative solopreneur & aspiring content creator to get clarity on building your publishing business. Write a book, create a podcast, share content, and build a business, design the life of your dreams.Let's make it happen. You got this! See how we can work together. https://stan.store/justkeeplearning

Why do most gyms plateau at 122 members? The answer: leadership.In this episode of "Run a Profitable Gym," Two-Brain CEO Chris Cooper explains how your leadership skills determine whether your gym grows, stalls or shrinks.Your gym will rise to the level of your leadership and fall to the level of your worst staff members. To take your gym to increasingly higher levels, you must evolve as a leader. Chris presents the four phases of leadership for gym owners and lists the skills required to climb the ladder:✅ Founder—Master self-leadership with focus and discipline.✅ Farmer—Build team leadership through clarity and systemized delegation.✅ Tinker—Develop peer leadership by collaborating and mentoring.✅ Chief—Become a better storyteller and improve your ability to create and inspire new leaders.To avoid outpacing your leadership development, Chris recommends you build your gym business plan with 150 members as your first target—not 300. If you try to go big too soon, you'll always slide back to 120-150 members. But if you learn to serve 150 people in a rock-solid business and develop your CEO skills, you can acquire as many members as you want or move on to the next legacy-building project.Watch this episode to get clarity on your current leadership phase and learn exactly which skills you need to break through to the next level.LinksGym Owners UnitedBook a Call2:17 - Why gyms plateau at 122 members9:02 - Founder: self-leadership11:35 - Farmer: team leadership14:43 - Tinker: peer leadership18:20 - Chief: tribe leadership

Discover the "Gold Standard" of the Great Plains. In this episode of the Only in OK Show, Brett and Harley take you to the furthest corner of the Panhandle to celebrate a historic milestone: Black Mesa State Park has officially become Oklahoma's first International Dark Sky Park. We dive into what it took to achieve this prestigious designation from DarkSky International and why "nocturnal heritage" is the next big thing for Oklahoma tourism. From removing "islands of light" to protecting the biological rhythms of bighorn sheep and mountain lions, we explore why Black Mesa is now a premier global destination for astrotourism. In this episode, we discuss: The 5-Year Transformation: How the park retrofitted lighting to eliminate light pollution. Where the Rockies Meet the Prairie: The unique geology of the 30-million-year-old black lava rock. The High Point Trail: Navigating the nature preserve and the famous Okie-Tex Star Party. Astrotourism's Economic Impact: How the village of Kenton and the OKC Astronomy Club put Oklahoma on the celestial map. Stick around after the break: We're heading to Midwest City because Tinker Air Force Base is getting a "Glow Up." Learn about the latest developments and what it means for the community. Plan your visit:  https://www.travelok.com/state-parks/black-mesa-state-park-nature-preserve Also discussed:  Chickasha Christmas Lights, Yukon Christmas Lights, Ralphie's Restaurant, Tinker AFB and Midwest City #OnlyInOK #BlackMesa #DarkSkyPark #Stargazing #OklahomaTravel #ExploreOK #Astrotourism #TinkerAFB #OklahomaStateParks #KeepTheDark

This episode of the Pipeliners Podcast features a thoughtful conversation with Scott Tinker on the realities of the global energy landscape and the often-misunderstood narrative surrounding the energy transition. The discussion explores energy demand, economic development, and the continued role of both traditional and emerging energy sources, offering a fact-based perspective on what the future may realistically hold. Listeners are also introduced to Scott's education-focused initiatives aimed at improving global energy literacy and addressing energy poverty.   Visit PipelinePodcastNetwork.com for a full episode transcript, as well as detailed show notes with relevant links and insider term definitions.

¿Qué tangos se escuchaban en Medellín antes de la muerte de Gardel? ¿De qué manera fue usado el bambuco como defensa conservadora de la blancura en los años 50 frente a la música tropical costeña? ¿Qué papel jugaron las emisoras locales de Medellín en la guerra de las textileras Coltejer y Fabricato? ¿Cómo suena la MEMORIA de una ciudad? La etnomusicóloga Carolina Santamaría Delgado nos cuenta sobre su investigación sobre la escucha y la música popular en Medellín a mediados del siglo XX y sobre cómo los sonidos configuraron la identidad cultural de la región. En Medellín se cruzaron ritmos del Caribe, México, Argentina y Estados Unidos. La ciudad se convirtió en un centro de la industria cultural colombiana a partir de los años 50, con el surgimiento de grandes conglomerados como RCN y Caracol. Santamaría aborda la tensión entre las visiones de músicos bogotanos como Emilio Murillo, defensor de la música como emblema nacional, y antioqueños como Gonzalo Vidal, quien priorizaba la formación académica europea. La investigadora cuestiona el mito de que la muerte de Gardel convirtió a Medellín en ciudad tanguera, señalando que ya existía una CULTURA DE ESCUCHA arraigada en mercados y espacios populares como Guayaquil antes de 1935. “La escucha no es necesariamente una cosa pasiva. Al momento de escuchar también hay una acción, hay un hacer”. CAROLINA SANTAMARÍA DELGADO Maestra en Música de la Pontificia Universidad Javeriana, MA y PhD en Etnomusicología de la Universidad de Pittsburgh. Es formada en estudios culturales y estudios latinoamericanos. Desde el 2003 colabora frecuentemente con el sello discográfico académico Smithsonian Folkways Recordings. Ha sido Tinker visiting professor en el Teresa Lozano Long Institute of Latin American Studies en la Universidad de Texas.

Chip updates on the results of his experimentation with arduino boards and organizational tricks he discovered.youtube available:https://youtu.be/D-BO8mHRPkM

On this week's episode of The Liberal Patriot Podcast, I talk with geologist and energy expert Scott Tinker about why affordable, reliable energy is the foundation of human progress. We examine energy poverty, the limits of renewables, and why many climate policies collide with physics, economics, and lived reality—especially for the world's poorest people.From 2000-2024, Tinker was Director of the Bureau of Economic Geology and State Geologist of Texas. He is currently CEO of Tinker Energy Associates and executive producer and host of PBS Energy Switch, an energy and climate talk series appearing in over 100 million households nationwide.Please listen in on a fantastic discussion and subscribe to the TLP Podcast if you don't already. A transcript is available on the website at the top of page. Get full access to The Liberal Patriot at www.liberalpatriot.com/subscribe

In this episode, I sit down with author Jill Liron to talk about Tinker & The Joy Thief, her beautiful debut children's book. Jill shares a little of her own story and the heart behind why this book wanted to be written, and together we explore a conversation that feels especially important right now — how we can support our children to protect their joy. We talk about big emotions, everyday pressures, and the simple yet powerful ways adults can help children stay connected to their light, resilience, and natural happiness in a world that can sometimes feel overwhelming. Grab your copy of Tinker & The Joy Thief Here: https://www.jillliron.com/book

Step aboard the Punky Steamer and watch everyday moments turn into portals. -> listen to the fantastic tale here! I highly recommend checking this audio play out before listening to the episode. For one it's awesome and for sure lots of what we talk about will feel deeper and make even more sense.  We sit down with Clay Hillman—once a Lutheran minister, now the imagination behind a toy-and-coffee shop and the audio adventure KC Bonker's Road to Joy—to explore how play can be both serious and sacred. Clay's world is richly built: a flying machine crewed by six archetypes of play, potions served with straight-faced wonder, and an audio play that clicks from past to present like a spell taking hold. The result is a practical philosophy of joy that you can taste, touch, and breathe.Clay introduces the Aeronaut, Cartographer, Chronaut, Philosopher, Goggle Jockey, and Tinker—personae that map how children experiment and how adults find vocation. When we keep those roles playful, work feels like meaning rather than grind. We dig into “sacred toys” too: stick, string, plane, block, wheel, and ball. Open-ended objects invite agency; they don't perform for you, they ask you to perform with them. That's why a simple paper toy can outshine a pricey gadget—it expands your world instead of prescribing one.Ritual ties it all together. In the shop, dragon blood, beetle juice, and unicorn milk layer in a glass until the final step demands your breath through a one-way straw. That small act completes the drink and inducts you into the story—breath revealing the invisible like a pinwheel turning wind into sight. We trace the same thread through vinyl records, soundscapes, and live showmanship where attention is the real currency. Presence isn't forced; it's designed through steps you choose to take.If you've ever felt a toy hold more truth than a lecture, or a performance feel like a pact kept, this ride is for you. Hear how myth, craft, and commerce meet without losing soul, and pick out your own play archetype along the way. If it moves you, subscribe, share this episode with a curious friend, and leave a review telling us the one small ritual that brings you wonder.Support the show...If you want to help support this podcast it would be tremendous if you wrote a glowing review on iTunes or Spotify.If you want to contact me about anything, including wanting me to collaborate on one of your projects you can reach me on thewayoftheshowman@gmail.comor find out more on the Way of the Showman website.you can follow the Way of Instagram where it is, not surprisingly thewayoftheshowman.If you find it in you and you have the means to do so, you can suport the podcast financially at:https://www.buymeacoffee.com/captainfrodo

*** the sound balance is a bit off on this episode and we couldn't resolve it in editing - apologies!Shopify's bi-annual Editions launch is a key industry event that generates a lot of buzz.Learn about the latest developments from Shopify's winter editions with Ben Homer, Senior Solutions Engineer at Shopify. The discussion centers around the transformative impact of AI and agentic commerce on the platform, highlighting Shopify's commitment to enhancing both user and developer experiences. Why listen:Get insights into Shopify's strategic directionUnderstand the potential of AI in commerceLearning about new tools that democratise business capabilities.Key discussion points:Shopify's AI integration: explore how Shopify is leveraging AI to enhance platform capabilities, including the rollout of agentic commerce tools like Sidekick.Catalogs API Access: learn about the new access for developers to Shopify's catalogs API, enabling innovative tooling and expanded commerce capabilities.Pulse and SimGym: discover how these tools are democratising data-driven insights and testing, making advanced capabilities accessible to businesses of all sizes.Future of Shopify Flow: understand the potential of Shopify Flow in automating complex tasks and enhancing operational efficiency. Tinker and A/B Testing: get a glimpse into upcoming tools designed to simplify content creation and enhance hardware connectivity for Shopify users.

This week we'll be running away to join the circus to find out just what these bloody clowns have done with this pesky mole. Yes, it's Tinker, Tailor, Soldier, SpyAnd joining me to be Smiley friends with a very slow horse, is Andrew O'Neill. Hosted on Acast. See acast.com/privacy for more information.

. Best coaching advice you've gotten?“What would it take to let it go?” – helped her shed self-limiting beliefs.Learned during a Georgetown fishbowl coaching session.Empowered her to define herself and step into a bigger space.2. What are you still trying to improve?Contracting with clients to avoid misalignment.Daily work on presence—removing the “static.”Asking, “Are we still in the right conversation?”3. Most outrageous/courageous thing you've done in a session?Telling a client they might need more support beyond coaching.Delivering hard truths with subtlety and courage.Felt “the clench” but leaned into trust and honesty.4. What still makes you squirm?Clients showing up with “I don't know.”Managing the pressure to “perform.”Using honesty and redirection to stay in alignment.5. Advice to new coaches?Get into supervision—it's essential support.Coaching can be lonely without intentional community.Keeps coaches anchored, self-aware, and growing.6. Something you've had to conquer?Transitioning from corporate to private practice.Proving to herself (and her husband) she could sustain independence.Leaning on referrals and relationships rather than sales.7. Are you using AI in your practice?Not directly in sessions, but useful for writing and teaching.Encourages her daughter to use it for transactional challenges.Sees AI as a supportive tool, not a threat.8. What have you learned about yourself?She can do hard things and thrive as a solopreneur.Built a sustainable practice without business development.Relationships and trust drive her long-term success.Fun Stuff: Favorite MovieRocky IV (music, energy, inspiration).Pitch Perfect 2 and The Greatest Showman.Loves movies with music and strong dialogue—even if “questionable.”

Congressional analyst Jack Pitney assesses the meaning of Marjorie Taylor Greene’s upcoming resignation from Congress, and weighs whether the Georgia Republican still has a future in politics, given her seeming banishment by President Trump. And we remember Mark Mellman, the Democratic pollster who died last month, by replaying an interview we had with him in November of 2016, when Hillary Clinton and Trump were vying for the presidency. PLUS:  A selection of favorite Trump responses to reporters’ questions at press conferences. Music in this episode: Where Is The Love by Roberta Flack and Donnie Hathaway You and I by Rick James The post Episode #426: Marjorie Tinker Taylor Q’Anon Traitor Patriot appeared first on Ken Rudin's Political Junkie.

http://copperplatemailorder.com                                   Copperplate Time 521                                presented by Alan O'Leary                             www.copperplatemailorder.com                              1. Bothy Band:  Green Groves.   After Hours 2. Open the Door For Three: Boyne Water.  The Joyful Hour3. Dezi Donnelly & Mike McGoldrick: The Walls of Liscarroll/Rooney's Jig/    ~               Connaughtman's Ramble. Dog in the Fog 4. Daoiri Farrell: A Pint of Plain. A Lifetime of Happiness 5. Garadice: The Ballintra Lasses/The Rock Reel/Silver Lining/               The Border Collie. Sanctuary6. Aidan Connolly & Bryan O'Leary:              Molly Myer's/The Humours of Glencollins. The Groves of Gneevegilla7. Brendan McAuley:  The Phaeton Carraige.                The McCartneys of Pennyburn 8. James Keane: Carmel O'Maoney Mulhaire/The Maid in the Cherry Tree/              The Kilfenora Reel. GL Compilation 9. Rita Gallagher:   The Mountain Streams.  May Morning Dew10. John & Jacinta McEvoy:  O'Flynn's Fancy/Paddy Cronin's.                    The Boyne Mist 11. Elaine Reilly:  The GalwayJig/The New Concert Flute.    Epiphany                     12. Paul Brennan/Carrig:The Pleasures of Hope/O'Donnell's HP.                Airs & Graces 13. Michael Banahan:  Finding My Way Back.  Broken Heart14. Laoise Kelly: An Londubh/Maidrin Ruadh. Ceis 15. Mick & Aoife O'Brien & Emer Mayock:  Reel 97/The Tinker's Frolic/Light Horse Reel.  Tunes from the Goodman Manuscripts 16. Ralph McTell: The Girl On The Jersey Ferry. Live in London 17. Jackie McAuley & Rod Demick:  Don't Listen to the Rich.                     Jackie McAuley & Rod Demick 18. Crosby, Stills & Nash:  Suite Judy Blue Eyes. Carry on 19. Rory McLeod:  Back to Donegal.  Travelling Home  

Music from: Three Quarter Ale, Sea Dog Slams Poems, Rowan and the Rose, Fugli, Brian Tinker Leo, Silent Lion, Bocca Musica, Whiskey Bards, Celtic Shores, Tania Opland and Mike Freeman, The Musical Blades, Dregs, Pride O' Bedlam, Faire to Middlin', Whiskey Bay Rovers, Pirates For Sail, Pirates Inc, Queen's_Gambit, Crimson Pirates, Henry Martin, Captain John Stout, Marc Gunn VISIT OUR SPONSORS Bawdy Podcast https://renfestbawdypodcast.libsyn.com/ Happy To Be Coloring Pages https://happytobecoloring.justonemore.website RESCU https://RESCU.org The 23 Patrons of the Podcast https://www.patreon.com/RenFestPodcast The Ren List http://www.therenlist.com SONGS Song 01: Shall We Gather By The Fire by Three Quarter Ale from Shall We Gather By The Fire www.facebook.com/pg/threequarterale Song 02: A Tale From the Devil's Tavern by Sea Dog Slams Poems from A Night at Devil's Tavern www.facebook.com/seadogslam/ Song 03: Arrow in the Knee by Rowan and the Rose from We Have Adventures www.rowanandtherose.com Song 04: Soup by Fugli from Fugli the Less than Unauthorized Bootleg Edition www.povera.com Song 05: The Songwriter by Brian Tinker Leo from Tinker's Rest www.facebook.com/tinkersings/ Song 06: Into the Medieval World by Silent Lion from Into the Medieval World www.silentlion.com/ Song 07: Bound for a Hangover by Bocca Musica from The Lusty Wench www.boccamusica.com Song 08: Devilish Mary by Whiskey Bards from The Recruiter...Free Rum Ain't Free www.facebook.com/whiskeybards/ Song 09: Good Drinking Weather by Celtic Shores from Let's Raise Another Pint www.matthughesmusic.com Song 10: Jack Monroe by Tania Opland and Mike Freeman from Cut To Rhythms https://opland-freeman.com/social.htm Song 11: Hollywood Pirate by The Musical Blades from Pieces of Eight www.musicalblades.com Song 12: Married to a Mermaid by Dregs from Do It Like You're Drunk www.the-dregs.net Song 13: Cheat Death by Pride O' Bedlam from Cheat Death www.prideofbedlam.com Song 14: The Wild Rover [10] by Faire to Middlin' from Kilts, Celts, & Kippers www.fairetomiddlin.com Song 15: Song for Albright by Whiskey Bay Rovers from Taverns and Tides www.facebook.com/whiskeybayrovers/ Song 16: Boatman by Pirates For Sail from Dark Side of the Lagoon www.piratesforsail.com/ Song 17: Mingulay Boat Song [21] by Pirates Inc from Drunk and Disorderly www.facebook.com/WeArePiratesInc/ Song 18: Madam Im A Darlin+ by Queen's_Gambit from Off The Board UNKNOW WEBSITE Song 19: Health to the Company [14] by Crimson Pirates from That's So Sad www.crimsonpirates.com/ Song 20: 20,000 Rubber Duckies by Henry Martin from Around the Bay UNKNOW WEBSITE Song 21: Friendship by Captain John Stout from Past, Present, & Future www.porterstout.com/ Song 22: Won't You Come With Me [03] by Marc Gunn from Happy Songs of Death www.marcgunn.com Song 23: The Mary Query by Hey Nunnie Nunnie from Hey Nunnie! Nunnie! www.heynunnienunnie.com/ Song 24: Longest Night Of The Year by Barleyjuice from This Is Why We Can't Have Nice Things www.barleyjuice.com   HOW TO CONTACT US Please post it on Facebook https://www.facebook.com/renfestmusic Please email us at renfestpodcast@gmail.com OTHER CREDITS Thee Bawdy Verson https://renfestbawdypodcast.libsyn.com/ The Minion Song by Fugli www.povera.com Valediction by Marc Gunn https://marcgunn.com/ HOW TO LISTEN Patreon https://www.patreon.com/RenFestPodcast Apple https://podcasts.apple.com/us/podcast/renaissance-festival-podcast/id74073024 Spotify https://open.spotify.com/show/76uzuG0lRulhdjDCeufK15?si=obnUk_sUQnyzvvs3E_MV1g Listennotes http://www.listennotes.com/podcasts/renaissance-festival-podcast-minions-1Xd3YjQ7fWx/

Heather is an employee engagement expert, speaker, and author of "The Tazie Effect". She has a Masters degree in Organizational Leadership. She is also the creator of a program titled PAWS for Effect. Inspired by Taz and Tinker, her adorable little 6-lb Miniature Pinschers, PAWS for Effect teaches the basic principles of employee engagement... Passion, People, and Purpose. Website: www.pentechprofessional.comBecome a supporter of this podcast: https://www.spreaker.com/podcast/the-x-zone-radio-tv-show--1078348/support.Please note that all XZBN radio and/or television shows are Copyright © REL-MAR McConnell Meda Company, Niagara, Ontario, Canada – www.rel-mar.com. For more Episodes of this show and all shows produced, broadcasted and syndicated from REL-MAR McConell Media Company and The 'X' Zone Broadcast Network and the 'X' Zone TV Channell, visit www.xzbn.net. For programming, distribution, and syndication inquiries, email programming@xzbn.net.We are proud to announce the we have launched TWATNews.com, launched in August 2025.TWATNews.com is an independent online news platform dedicated to uncovering the truth about Donald Trump and his ongoing influence in politics, business, and society. Unlike mainstream outlets that often sanitize, soften, or ignore stories that challenge Trump and his allies, TWATNews digs deeper to deliver hard-hitting articles, investigative features, and sharp commentary that mainstream media won't touch.These are stories and articles that you will not read anywhere else.Our mission is simple: to expose corruption, lies, and authoritarian tendencies while giving voice to the perspectives and evidence that are often marginalized or buried by corporate-controlled media

Josh Yohe from The Athletic makes his pilgrimage back to the podcast this week to talk about the Pittsburgh Penguins. This has been a year of new things for the Penguins. New coaching staff, new faces, new goals. One thing still remains the same. Crosby, Malkin, and Letang still dominate. How long can they keep this hot start going? Tune in now!

Welcome to Captain's Pod, a Star Trek podcast presented by Ian and Deneé! Join the crew as Ian sings opera, Deneé enjoys a turd alien, and they both go deep on the android vs hologram debate.NEXT WEEK: Star Trek TNG: The Royale (S2E12)1) Ten Forward- Thoughts on the episode; what did the crew love and what can go out the airlock! (7:48) 2) The Jefferies Tubes- Bloopers and other goodies that didn't make it into the show. Don't tell Section 31! (1:29:40)Want early and ad-free access to the show PLUS other perks? Join the Tea-Flingers at the Ian and Deneé Patreon!https://www.patreon.com/iananddeneeJoin the live recording of the show! FRIDAY 11/28 at 5pm CENTRAL!YouTube: https://youtube.com/@iananddenee?si=sAmifSnfaDWnJzDATwitch: https://www.twitch.tv/deneesaysConnect with us!Email: ian@iananddenee.comDiscord: https://discord.gg/cm4nxyKd2SBluesky! The Show: @captainspod.bsky.socialIan: @whittsinned.bsky.socialDeneé: @deneesays.bsky.socialAnd live long and Podsper!Advertising Inquiries: https://redcircle.com/brandsPrivacy & Opt-Out: https://redcircle.com/privacy

Send us a textThis episode is gonna be about life, all the ups and downs, the roller coaster rides of raising a kid, having your brother live with you, new dog, marriage, and grieving Tinker.enjoy!Support the showThank you for listening. Please, download, follow, comment, rate me and share with everyone out there. I need you to continue to help me get this Podcast out in the world. Because I have a lot to say, and I want all to hear it.Please send me all your thoughts and comments to my email:laughinthroughit2021@gmail.comCheck out my Facebook for the podcast.thank you!

Tax rises! Cuts to everything! Here comes the pain! Seldom has a Budget been heralded with such dire warnings… if you believe the Toryform Press. But according to Giles Wilkes – Institute for Government fellow and former adviser to Vince Cable and Theresa May – Britain isn't in such a disastrous state after all. In a weirdly optimistic conversation he joins Andrew Harrison and Jonn Elledge to look at the real story of Britain's finances; why Brexit is an even bigger drag anchor than the Treasury will admit; and why the embattled Chancellor needs to stick to her course.   ESCAPE ROUTES  • Jonn has been watching The Celebrity Traitors, yes that again, do our panel ever watch anything else?  • Giles recommends Wellington: The Iron Duke by Richard Holmes.  • Andrew recommends the old school BBC adaptation of Tinker, Tailor, Soldier, Spy with Alec Guinness.   When you buy books through our affiliate bookshop you help fund OGWN by earning us a small commission for every sale. Bookshop.org's fees help support independent bookshops too.  www.patreon.com/ohgodwhatnow  Presented by Andrew Harrison with Jonn Elledge Audio and Video Production by Chris Jones. Art direction: James Parrett. Theme tune by Cornershop. Managing Editor: Jacob Jarvis. Group Editor: Andrew Harrison. OH GOD, WHAT NOW? is a Podmasters production.  www.podmasters.co.uk   Learn more about your ad choices. Visit podcastchoices.com/adchoices

It seems like such a dangerous world. It's what keeps you up at night as a parent—what if, what if, what if?

REWIND! This episode was originally uploaded in September, 2023. Mary Beth Tinker, along with her brother and other students, took part in a protest against the US involvement in the Vietnam War. The protest at school lead to a case which reached all the way to the Supreme Court, and would forever change the way that students view their rights. Learn more about your ad choices. Visit megaphone.fm/adchoices

Join Shane/Rayo2 as he reconnects with freedom pioneer, Greg Doud, host of The Tinker Tribe podcast. Herein, they discuss strategies for liberation, challenges with the digital technocracy, the importance of vetting & community building, and much more. Greg will be joining us a VONU PODCAST LIVE on November 29th, 8pm… The post TVP #240: Strategies To Improve Human Freedom [Guest Appearance on The Tinker Tribe Podcast] appeared first on The Vonu Podcast.

This week, I sat down with Erza Menagerie Tinker for a surprisingly deep conversation. While we talk about her experience in professional wrestling, we also delve into her dissociative identity disorder, self-expression, and how professional wrestling is art and, by proxy, for everyone. Certainly, one of the more memorable discussions I've had on the podcast.Erza Tinker can be found online at:Twitter: https://x.com/erzatinkerInstagram: https://www.instagram.com/erzatink/Facebook: https://www.facebook.com/erza.tinkerWe're on social media onFacebook: www.facebook.com/confusionwretlingpodcastTwitter, Bluesky, & Instagram: @thenovaofcass.All the other links can be found at www.linktr.ee/confusionwrestlingpodcast.If you'd like to assist monetarily, there's a tip jar at www.ko-fi.com/cassonova. For more bang for your buck, check out www.patreon.com/cassonova. For as little as $1, you can get the podcast two days early and ad free. You also get weekly exclusives and early access while helping upgrade the equipment. So be like Keith Winn, Alainya, and Alan Schroeder and check it out!Also, for all your energy drink and workout needs, head to www.reppsports.com and when you checkout, use my coupon code "CASS" at checkout and earn 15% off your order.Oh! And I'm on Cameo now at https://www.cameo.com/thenovaofcassAffiliate Links:Gevi: gevi.pxf.io/AWJxbxPrince Nana Coffee: https://princenanacoffee.com/?ref=ROBKAMERERMLW Get your Tees at: https://www.teepublic.com/user/confusionwrestlingpodcastCon-Fusion is part of the Urban Wrestling Network. You can watch their show on YouTube at Urban Wrestling Network - YouTube and you can follow them on the Twitter @UrbanWrestleNWFor business inquiries, send all messages to rzkamerer[at]comcast.net.

Episode 39: Fellers v. KelleyFellers, et al. v. Kelley, et al., argued before Circuit Judge Julie Rikelman and Senior Circuit Judges Sandra L. Lynch and Jeffrey R. Howard in the United States Court of Appeals for the First Circuit on November 5, 2025. Argued by Del Kolde (on behalf of Kyle Fellers, et al.) and Jonathan Shirley (on behalf of Marcy Kelley, et al.). Background of the case, from the Institute for Free Speech case page:A silent protest in support of girls' sports led Bow officials to censor XX wristbands, threaten arrests and ban dissenters from school grounds. Now, three parents and a grandfather are fighting back against the officials who trampled on their First Amendment rights—and the policies those officials weaponized to do it. The lawsuit, filed in the U.S. District Court for the District of New Hampshire, alleges that the defendants violated the plaintiffs' First Amendment rights by forcing them to remove “XX” wristbands, and then banning them from school grounds. The plaintiffs wore the wristbands to silently protest government officials allowing a biological male to play on the opposing girls' soccer team. School officials, along with a police officer, confronted the parents during the game, demanding that they remove the wristbands or leave. The referee also temporarily stopped the game and said that the game would be over if the remaining plaintiff did not remove his wristband. Two of the plaintiffs were later sent no-trespass notices excluding them from future games.  The plaintiffs ask the court to enjoin the school from enforcing its unconstitutional policy or practice of censoring the display of  XX wristbands or displaying signs in the parking lot in support of protecting women's sports at Bow school sporting events Statement of the Issues, from the Plaintiff-Appellants' Opening Brief:Does a blanket ban on so-called “exclusionary” speech by adults at school events open to the public discriminate against speech based on its content and viewpoint?  Do public school officials illegally discriminate against speech based on viewpoint by banning adult spectators at school sporting events from wearing XX-wristbands conveying an “exclusionary” message, when those same officials permit adult spectators to display a Pride Flag because the message is “inclusionary?”  Is the First Amendment's protection of speech by adult spectators in a limited public forum, such as a public-school extracurricular sporting event, subject to the same legal test for the protection of student speech in schools set forth in Tinker v. Des Moines and its progeny?  Can the passive display of an XX-wristband by parents watching a school sporting event in which a trans-identified student is playing “reasonably be understood as directly assaulting those who identify as transgender women?” Did the district court correctly find that the XX-wristbands' message would be likely to injure transgender students when the record lacks evidence of such phenomena?  Did the district court err by denying plaintiffs' motion for a preliminary injunction?Resources: Institute for Free Speech case page Plaintiff-Appellants' Opening Brief Defendant-Appellees' Brief The Institute for Free Speech promotes and defends the political speech rights to freely speak, assemble, publish, and petition the government guaranteed by the First Amendment. If you're enjoying the Free Speech Arguments podcast, please subscribe and leave a review on your preferred podcast platform. 

Become a supporter of this podcast: https://www.spreaker.com/podcast/the-opperman-report--1198501/support.

We're afraid they're not learning enough. We're concerned they're falling behind. Is it the school? Is there something wrong with them?

Send us a textOn the latest edition of The Brief Case, presented by Spirit Mountain Casino, Trail Blazers reporter and Insider Casey Holdahl discusses...• The Trail Blazers getting to 1-1 for the preseason by beating the Kings Friday night at Moda Center• Portland doing Friday night versus the Kings what they couldn't do Wednesday night versus the Warriors in San Francisco• Deni Avdija gets the start versus the Kings after coming off the bench versus the Warriors• Jerami Grant coming off the bench versus the Kings in the first half and the starting in the second half• Trail Blazers rookie center Yang Hansen putting on an absolute show during a six-minute stretch of the third quarter versus the Kings• Hansen's confidence seemingly growing every time he does something right• Hansen bouncing back from a lackluster debut versus the Warriors and a so-so first half versus the Kings, which will serve him well throughout his rookie season• Understanding the comparisons between Yang Hansen and Nikola Jokic• The upcoming games versus the Warriors on Tuesday and the Jazz on Wednesday• Making wild guesses about what lineups Chauncey Billups might try in the final two preseason games 

Have you every wished you could call up an experienced auto tech to diagnose your car trouble? One company is doing just that by transforming the DIY auto repair experience.   With nearly 1 million app downloads, Tinker DIY is the only platform that offers live video support with ASE-certified mechanics for auto repairs, rideshare inspections, and used car evaluations. Akin to “telehealth for your car,” Tinker eliminates the need for YouTube guesswork or costly auto shop visits by guiding users through step-by-step auto repairs in real-time.    Listen in as we sit down with Megan Han, Head of Operations, to discuss how Tinker helps connects users with expert guidance to help them diagnose and repair their vehicles on their own.    We'd love to hear from you. Share your comments, questions and ideas for future topics and guests to podcast@sae.org. Don't forget to take a moment to follow SAE Tomorrow Today — a podcast where we discuss emerging technology and trends in mobility with the leaders, innovators and strategists making it all happen—and give us a review on your preferred podcasting platform.  Follow SAE International: Facebook: https://www.facebook.com/SAEInternational/ X: https://x.com/SAEIntl LinkedIn: https://www.linkedin.com/company/sae-international/ Instagram https://www.instagram.com/saeintl/   Follow host Grayson Brulte: LinkedIn: https://www.linkedin.com/in/graysonbrulte X: https://x.com/gbrulte Instagram: https://www.instagram.com/gbrulte/  

In this episode we are talking all things colour, from what to paint a snug to make it cosy, to the best colours for greenhouses and fences. We're also diving into separate bedrooms, Jojo's latest read, what Polly is sowing, Ice rollers, Marks and Spencer and being the sandwich generation. This week we are sponsored by Tinker & Tallulah - the makers of the most joyful, handcrafted lampshades. Designed and made in Nottinghamshire by husband-and-wife duo Rach and Liam, each lampshade blends Art Deco opulence with a modern twist - think jewel-toned velvets, playful fringe and timeless design that transforms any corner into a statement. T&T also work with interior designers on residential and hospitality projects, and their custom lampshades can be seen around the world in cocktail bars and restaurants. Explore the full collection at tinkerandtallulah.co.uk and use discount code PODCAST for 20% off your first order.InstagramPodcast - @the_insandouts_Jojo - @houseninedesignPolly - @pollyanna_wilkinsonWebsitesJojo - https://www.housenine.co.uk/Polly - https://www.pollyannawilkinson.com/ Hosted on Acast. See acast.com/privacy for more information.

Returning guest Bryan Power (Head of People, Nextdoor) talk about AI workplace adoption, contrasting executives who avoid AI as time-consuming with his dedicated approach of treating AI as teammates, scheduling one-on-ones with custom GPTs, and transforming workflows.*Email us your questions or topics for Kelli & Nolan: hrheretics@turpentine.coFor coaching and advising inquire at https://kellidragovich.com/HR Heretics is a podcast from Turpentine.Support HR Heretics Sponsors:Planful empowers teams just like yours to unlock the secrets of successful workforce planning. Use data-driven insights to develop accurate forecasts, close hiring gaps, and adjust talent acquisition plans collaboratively based on costs today and into the future. ✍️ Go to https://planful.com/heretics to see how you can transform your HR strategy.Metaview is the AI platform built for recruiting. Our suite of AI agents work across your hiring process to save time, boost decision quality, and elevate the candidate experience.Learn why team builders at 3,000+ cutting-edge companies like Brex, Deel, and Quora can't live without Metaview.It only takes minutes to get up and running. Check it out!Ethena is the compliance training platform built for modern workplaces. Visit goethena.com/heretics and get 10% off your first year.KEEP UP WITH BRYAN, NOLAN + KELLI ON LINKEDINBryan: https://www.linkedin.com/in/bryanpower/Nolan: https://www.linkedin.com/in/nolan-church/Kelli: https://www.linkedin.com/in/kellidragovich/—LINKS:Nextdoor: https://nextdoor.com—TIMESTAMPS:(00:00) Intro(01:00) The Tinkerer vs. The Resisters(03:00) The AI Bubble and Workplace Resistance(05:00) Project Neighbor: Nextdoor's AI Initiative(07:00) Case Study: Building AI Training with ChatGPT(09:00) Mental Model Shift: AI as Teammate, Not Tool(10:00) Scheduling One-on-Ones with Custom GPTs(10:51) Ad Break - Athena & Planful Sponsors(14:01) Executive Offsite Planning: AI in Action(16:00) The Onboarding Problem: Context and Custom GPTs(18:00) Compensation GPT: Domain-Specific AI Applications(21:00) Output and Velocity: Gamma and Slide Creation(22:43) Ad Break - Metaview Sponsor(24:37) Optional or Essential: The Future of AI Adoption(26:00) The Mass Extinction Event for Knowledge Workers(30:00) Creating Permission to Tinker(32:00) Restructuring Executive Time for AI(34:00) Corporate Lingo Roast(44:08) Wrap This is a public episode. If you would like to discuss this with other subscribers or get access to bonus episodes, visit hrheretics.substack.com

Overwhelmed by conflicting business advice? Cut through the noise with Chris Cooper's proven system for building wealth as a gym owner. In this episode of “Run a Profitable Gym,” Chris explains how to move beyond the passion-first mentality that keeps most fitness entrepreneurs stuck and broke.He breaks down his four-phase roadmap for gym-owner wealth: Founder, Farmer, Tinker and Chief. These phases show you what to focus on right now, what to ignore and how to move toward financial freedom.Coop also shares candid stories from his early years of gym ownership, including mopping floors personally and trapping his business in Founder Phase. Everything changed when he focused on fixing the foundation first, stopped trying to market a broken gym, and started doing the right things as a CEO and business owner.Now as the CEO of Two-Brain Business, Cooper has helped thousands of fellow gym owners fix their businesses, too. He's minted more than 60 millionaire gym owners, and hundreds more are earning over $100,000 per year.It's time to break free from day-to-day operations and start building wealth. Tune in to get the full blueprint.LinksGym Owners UnitedBook a Call1:28 - Why gym owners get stuck7:44 - Founder Phase10:51 - Farmer Phase14:34 - Tinker Phase19:36 - Chief Phase

Understand—and remember—that they are where they are, are who they are. They are developing. They are experiencing. They are figuring stuff out.Give yourself the ultimate gift of parenting tools, structure, and community. Join The Daily Dad Society here: https://dailydad.com/society Tinker, create and innovate with KiwiCo! Get 50% off at KiwiCo.com with code DAILYDAD✉️ Sign up for the Daily Dad email: DailyDad.com

Ryan's back from 27 days in Greece, and he's got stories. A bee sting to the throat, a jellyfish sting, lost luggage, and a nearly missed flight… all while trying to stay calm with two young kids. In this solo episode, he shares what went wrong, what went right, and why the best parenting lessons happen when nothing goes according to plan.Give yourself the ultimate gift of parenting tools, structure, and community. Join The Daily Dad Society here: https://dailydad.com/societyPESTIE | Protect your home from bugs with Pestie. Go to pestie.com/dad for an extra 10% off your order!  Tinker, create and innovate with KiwiCo! Get up to 50% off your first crate at KiwiCo.com with code DAILYDAD✉️ Sign up for the Daily Dad email: DailyDad.com

Is our planet doomed? Probably not, it turns out. Dr. Jordan B. Peterson joins geologist Scott Tinker to dismantle the myth of energy scarcity, exposing the flawed narratives that demonize coal, oil, and natural gas. Together, they reject the false binary of renewables versus fossil fuels, arguing instead for an abundant future powered by both. This conversation confronts the culture of fear that paralyzes progress and issues a stark warning: if the West continues to undermine its own energy and technological ambitions in service of an ideological green agenda, it risks ceding global leadership to authoritarian regimes like China. Innovation, prosperity, and freedom depend on confronting reality—not retreating from it. Privacy Policy: https://www.dailywire.com/privacy This episode was filmed on May 23rd, 2025.  | Links | For Scott Tinker: Watch Scott's speech at the 2025 ARC Conference https://www.youtube.com/watch?v=N7EjhVyCHgA Switch On (Film) https://www.youtube.com/watch?v=xk75bD-C3H4   Switch Energy Alliance https://switchon.org/about/leadership/   Watch Energy Switch (Show) https://www.pbs.org/show/energy-switch/