Podcasts about Bissell

A great ROAS can be a watermelon: green on the outside, bleeding on the inside. Antoine Deventer, Senior Integrated Performance Marketing Specialist at Bissell, joins the Shiny New Object Podcast to talk about what happens when you stop optimising to vanity metrics and start focusing on real growth. We cover Amazon's evolution into a full-funnel media powerhouse, why "tool stack navigation" is a modern marketer's superpower, and the daily discipline that turns impressions into intelligence (breakfast: budgets + KPIs; lunch: root-cause analysis with the agency; dinner:  we'll see...)   #marketingpodcast #modernmarketing #toolstackactivation #roas  

“95% of AI pilots fail. I lived that, full stop.” Craig Foldes (Founder of ChatWalrus, fmr. Global Head of AI at Crocs) and Matt Kruer (CIO at Bissell) join host Sean Frank to explore the state of AI within enterprise versus DTC brands. The conversation covers how to find + celebrate the 10% of employees who are AI power users, what it looks like when adoption works, and why this is “for the rebels.” They debate whether AI is the great equalizer or a quiet advantage, unpack which parts of the AI hype cycle are overblown, and make the case that the people who learn to master these tools now are the ones who will win, in their careers and in their companies. Craig Foldes https://www.chatwalrus.com/ https://www.linkedin.com/in/craig-foldes-1b949b96/ Matt Kruer https://x.com/matthew_kruer https://www.linkedin.com/in/matthew-kruer-9a90b716/ Powered By Fulfil https://bit.ly/3pAp2vu Aftersell https://9ops.co/4i3bb5 Richpanel https://9ops.co/richpanel Northbeam https://www.northbeam.io/ Saras Analytics https://bit.ly/9OP-Ytdesc Postscript https://9ops.co/postscript Operators Newsletter https://9operators.com/

First week of March, what'd you miss in vet med?Zoetis to acquire Neogen's Genomics DivisionGallant partners with MWI and data with AAHAMars Impact FundDuffield and Bissell Fix the FutureAKC Humane FundCutting Horse launches $75M FundBond Vet partners with ACC of NYCHelpful links:The Bird Bath substackVRCE - The Veterinary Profession's #1 CSR Development Program

The state is clawing back more than $3-million dollars from a nearly $5 million grant it awarded Cleveland for a program that would help rid old houses of lead. The Ohio Department of Development administered the grant as part of the Lead Safe Ohio Program. It would pay up to $15,000 to remove old windows and doors, a major source of lead paint that chips and flakes and exposes occupants to lead poisoning. Lead can cause permanent neurological damage in children, and Cleveland has been working for years to remove lead from its older housing stock and the city's health director says there is actually promising news: Testing has shown for the second straight year a reduction in lead levels for kids. The story begins our discussion of the week's top news on the Friday “Sound of Ideas Reporters Roundtable.” Cuyahoga County Executive Chris Ronayne wants to take control of finances for the county sheriff's department as overtime costs there soar. The sheriff has said he'll sue if that happens. Cuyahoga County prosecutors argued before the Ohio Supreme Court on Feb.11 that a murder conviction is appropriate for the man who struck and killed Cleveland Johnny Tetrick as the firefighter was responding to an accident on I-90. Leander Bissell was convicted of murder, but an appeals court reduced it to involuntary manslaughter. Bissell struck Tetrick as he drove around stopped traffic at an accident scene. A federal judge yesterday denied the Trump administration's request to pause a ruling that allows Haitians in the U.S. under Temporary Protected Status to maintain that status. Thousands of Haitians with such protection live in Springfield. The administration's appeal continues. The Trump administration announced yesterday it was ending its immigration surge in Minneapolis. Border czar Tom Homan called Operation Metro Surge a success. Two U.S. citizens were killed, and widespread protests gripped the city. Homan credited coordination with local law enforcement as a factor in the operation's success. Protests continue across the country, including locally, where Thursday students at Cleveland Heights High School staged a long-planned walk out to show solidarity with immigrant families impacted by Immigration and Customs Enforcement. Many of those participating have direct ties to immigrant communities and want schools to be safe spaces. This week, Akron became the latest city to oppose proposed bills in the Ohio legislature that would require local police to help with federal immigration enforcement. The College of Wooster is cutting staff in response to shrinking enrollment. President Anne McCall announced that the school is laying off 22 non-faculty staff. It's almost time for public schools to submit their budget forecasts to the state for approval and the districts in Cleveland and Akron say they'll need to make significant cuts over the next several years, despite already going through consolidation and collecting more money from taxpayers with levies. More than half of the public school districts in Ohio, part of a coalition called Vouchers Hurt Ohio, are suing the state over how it funds schools, diverting money to vouchers for private schools. Lawmakers who approve of the vouchers say they allow families to have education choice. A new bill introduced in Columbus would allow the state to yank funding from districts that sue. Guests: -Abigail Bottar, Reporter, Ideastream Public Media -Conor Morris, Education Reporter, Ideastream Public Media -Karen Kasler, Statehouse News Bureau Chief, Ohio Public Radio/TV

This week's New to Lou Too features the Bissell Garage Pro Wet Dry Vac! Transform your garage, vehicle, and workshop cleanup with this versatile vacuum solution for wet and dry messes. For more info, visit the YouTube HouseSmarts Channel.

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

Sorry we are late getting this up! Technical difficulties yesterday! Follow us on Instagram: @MOVE100Halifax, @ErinHopkinsFM & @PeterAtMove100

This week, we're all about dog updates, comfy clothes, and community vibes. We share Sally's recovery journey after major dental work, Scouty and Huck's commingling progress, and a deep dive into the effectiveness of gentle leaders, front-clip harnesses, and Bissell stomp pads for pet stains. Add in block party buzz and Betsy's favorite British murder mysteries, and you've got an episode you won't want to miss!

"If you love cats, you should be concerned about trying to help bring those numbers down so animals don't suffer because this is why we do this. We don't want animals suffering, having unwanted litters of cats and having to have them suffer." This episode is sponsored-in-part by Maddie's Fund and 6 Degrees of Cats. In this powerful episode, host Stacy LeBaron sits down with Cathy Bissell, founder of Bissell Pet Foundation, who has revolutionized animal welfare through innovative programs reaching over 6,000 shelters across 49 states. From her unexpected entry into animal welfare during Hurricane Katrina to creating the nation's largest funded adoption event, Cathy's journey demonstrates how strategic thinking and passionate commitment can create systemic change. Her foundation has impacted nearly one million pets since 2011, but it's her latest initiative that's truly disrupting the industry. Cathy shares the incredible success of her groundbreaking "Fix the Future" program, launched in 2023 to address the veterinary care access crisis. In just under 18 months, this free spay/neuter initiative has sterilized 138,000 animals across 27 states, with an astounding 86,963 of those being cats. Through a network of 385 high-volume, high-quality relief veterinarians, the program is tackling overpopulation at its source while keeping costs remarkably low at just $35 per surgery. Cathy discusses the challenges of scaling this model, the importance of treating every animal that comes through their doors, and why she believes this "disruptor program" is essential for breaking down cost barriers that prevent people from accessing veterinary care. Whether you're working in a small grassroots rescue or leading a major shelter, this episode provides invaluable insights into creating sustainable, scalable solutions that address root causes rather than just symptoms. Cathy's emphasis on collaboration, her honest discussion about learning from mistakes (including a powerful story about declawing), and her practical advice for getting started at any age will inspire listeners to think bigger about their impact and consider how they can contribute to solving the access to care crisis in their own communities. Press play now for: Cathy's unexpected journey from Hurricane Katrina volunteer to founding a major animal welfare foundation The evolution from disaster response to adoption events to addressing systemic access to care challenges Incredible statistics: 138,000 spay/neuter surgeries in 18 months with 86,963 cats across 27 states How the Fix the Future program operates with 385 relief veterinarians at just $35 per surgery The power of MASH-style clinics and why community cat advocates should consider creating their own Why Michigan serves as a prime example with 3,000 cats out of 4,000 total surgeries at their clinic The importance of spaying/neutering before adoption and addressing kittens under six months How veterinary school limitations (graduating with only 1-3 spay/neuter surgeries) impact private practice capacity Cathy's honest story about learning from the declawing controversy and how it changed her foundation's policies Practical advice for getting involved at any age and making a difference beyond just donating money The role of Empty the Shelters adoption events in supporting shelter operations nationwide Why every animal deserves vaccination and ear-tipping as part of comprehensive TNR programs Resources mentioned: Bissell Pet Foundation website (https://www.bissellpetfoundation.org/) Empty the Shelters adoption events (https://www.bissellpetfoundation.org/programs/empty-the-shelters/) Fix the Future spay/neuter initiative (https://www.bissellpetfoundation.org/programs/fix-the-future/) Mississippi State University College of Veterinary Medicine (https://www.vetmed.msstate.edu/) MSU shelter medicine program details (https://www.vetmed.msstate.edu/about/points-of-pride) United Spay Alliance website (https://www.unitedspayalliance.org/) United Spay Alliance wet lab training programs (https://www.unitedspayalliance.org/hqhvsn-wet-labs/) BISSELL Pet Foundation grant information (https://www.bissellpetfoundation.org/grant-information/) Operation Fix the Future clinics (https://www.bissellpetfoundation.org/operation-fix-the-future/) BISSELL Pet Foundation Facebook page (https://www.facebook.com/bissellpets/) Sponsor Links: Maddie's Fund (https://www.communitycatspodcast.com/maddies623) Six Degrees of Cats (https://podcasts.apple.com/us/podcast/6-degrees-of-cats/id1669849217) Follow & Review We'd love for you to follow us if you haven't yet. Click that purple '+' in the top right corner of your Apple Podcasts app. We'd love it even more if you could drop a review or 5-star rating over on Apple Podcasts(https://podcasts.apple.com/us/podcast/the-community-cats-podcast/id1125752101?mt=2). Select “Ratings and Reviews” and “Write a Review” then share a quick line with your favorite part of the episode. It only takes a second and it helps spread the word about the podcast.

Únete a nuestra familia y descubre todo lo que tenemos para ti:•Telegram•TikTok•Facebook•Instagram•¡Mercancía y mucho más!Dale click aquí y no te pierdas de nada! https://linktr.ee/Juegodeasesinospodcast‌Puedes seguir nuestras paginas personales:❤SIGUE A MARTHA: https://www.instagram.com/mar.tham/❤SIGUE A KIKI: https://www.instagram.com/kikive72/ . PARA CONTENIDO VIP Y EPISODIOS SIN COMERCIALES ÚNETE A NUESTRA FAMILIA EXCLUSIVA EN PATREON:❤http://patreon.com/JuegodeasesinospodcastFuentes de este episodio:Gadsden Times – “Bissell pleads guilty to murder in Georgia” https://www.gadsdentimes.com/story/news/2002/02/07/bissell-pleads-guilty-to-murder-in-georgia/32361277007/ AccessWDUN – “Ohio man given life sentence in slaying, mutilation of woman” https://accesswdun.com/article/2002/2/199102 Morbid Podcast – Episode 473: “Hayward Bissell and the Murder of Patricia Booher” https://wondery.com/shows/morbid-a-true-crime-podcast/episode/10863-hayward-bissell-and-the-murder-of-patricia-booher/ Small Town Murder – Podcast Homepage https://shutupandgivememurder.com/smalltownmurder FBI Crime Statistics – 2024 Report https://www.fbi.gov/news/press-releases/fbi-releases-2024-reported-crimes-in-the-nation-statistics RAINN – Trauma-Informed Storytelling Resources https://rainn.org/consulting-services/entertainment-industry-support Transom.org – Interviewing Survivors with Empathy https://centerforhealthjournalism.org/our-work/insights/keep-these-seven-lessons-mind-when-interviewing-trauma-survivors Blood in the Snow by Tom Henderson – Book reference Amazon: https://www.amazon.com/Blood-Snow-Stay-at-Home-High-Powered-Jealousy/dp/0312948123 Goodreads: https://www.goodreads.com/book/show/9638926-blood-in-the-snow

Agradece a este podcast tantas horas de entretenimiento y disfruta de episodios exclusivos como éste. ¡Apóyale en iVoox! Únete a nuestra familia y descubre todo lo que tenemos para ti:•Telegram•TikTok•Facebook•Instagram•¡Mercancía y mucho más!Dale click aquí y no te pierdas de nada! https://linktr.ee/Juegodeasesinospodcast‌Puedes seguir nuestras paginas personales:❤SIGUE A MARTHA: https://www.instagram.com/mar.tham/❤SIGUE A KIKI: https://www.instagram.com/kikive72/ . PARA CONTENIDO VIP Y EPISODIOS SIN COMERCIALES ÚNETE A NUESTRA FAMILIA EXCLUSIVA EN PATREON:❤http://patreon.com/JuegodeasesinospodcastFuentes de este episodio:Gadsden Times – “Bissell pleads guilty to murder in Georgia” https://www.gadsdentimes.com/story/news/2002/02/07/bissell-pleads-guilty-to-murder-in-georgia/32361277007/ AccessWDUN – “Ohio man given life sentence in slaying, mutilation of woman” https://accesswdun.com/article/2002/2/199102 Morbid Podcast – Episode 473: “Hayward Bissell and the Murder of Patricia Booher” https://wondery.com/shows/morbid-a-true-crime-podcast/episode/10863-hayward-bissell-and-the-murder-of-patricia-booher/ Small Town Murder – Podcast Homepage https://shutupandgivememurder.com/smalltownmurder FBI Crime Statistics – 2024 Report https://www.fbi.gov/news/press-releases/fbi-releases-2024-reported-crimes-in-the-nation-statistics RAINN – Trauma-Informed Storytelling Resources https://rainn.org/consulting-services/entertainment-industry-support Transom.org – Interviewing Survivors with Empathy https://centerforhealthjournalism.org/our-work/insights/keep-these-seven-lessons-mind-when-interviewing-trauma-survivors Blood in the Snow by Tom Henderson – Book reference Amazon: https://www.amazon.com/Blood-Snow-Stay-at-Home-High-Powered-Jealousy/dp/0312948123 Goodreads: https://www.goodreads.com/book/show/9638926-blood-in-the-snowEscucha este episodio completo y accede a todo el contenido exclusivo de Juego de Asesinos Podcast . Descubre antes que nadie los nuevos episodios, y participa en la comunidad exclusiva de oyentes en https://go.ivoox.com/sq/731758

Únete a nuestra familia y descubre todo lo que tenemos para ti:•Telegram•TikTok•Facebook•Instagram•¡Mercancía y mucho más!Dale click aquí y no te pierdas de nada!https://linktr.ee/Juegodeasesinospodcast‌Puedes seguir nuestras paginas personales:❤SIGUE A MARTHA: https://www.instagram.com/mar.tham/❤SIGUE A KIKI: https://www.instagram.com/kikive72/.

The humble vacuum cleaner is a household hero, but its story is far from simple. It's a fascinating saga of grit, genius, and a little bit of luck. Most people have never heard of J. Murray Spangler, the asthmatic janitor who cobbled together the first electric suction sweeper from a broom, a pillowcase, and an old fan motor. His ingenious invention, born from a need to escape a dusty, backbreaking job, was a game-changer. Yet, he hardly sold any of his machines.This podcast reveals how his cousin's husband, a savvy leather goods maker named William Hoover, saw the potential and transformed a struggling invention into a global brand so iconic that its name became a verb.But the story doesn't start or end there. We'll travel back in time to the very beginnings of civilized life and the invention of the broom, tracing its evolution from a simple bundle of leaves to the meticulously engineered sorghum broom of the 18th century. From there, we'll uncover the forgotten inventors who tried and failed to mechanize cleaning with bellows and hand cranks, paving the way for innovations like the Bissell carpet sweeper, born from a wife's frustration with sawdust on the floor of her husband's pottery shop.This deep dive into the history of home cleaning isn't just about machines—it's about the people behind them. We'll explore the perseverance of inventors like James Dyson, who battled a skeptical industry for years to prove that a bagless vacuum cleaner using cyclone technology was a superior solution. His long and difficult journey from 5,127 prototypes to market domination serves as a powerful reminder that true innovation often requires unwavering belief. Join us to discover how frustration and a touch of genius led to one of the most significant and overlooked inventions of the modern home.You can find a transcript of the story hereAnd check out my website for many other stories and other resources to help think about and manage innovation

In this special Oh Behave episode on Pet Life Radio, host Arden Moore welcomes the remarkable, resilient Cathy Bissell, the founder of the Bissell Pet Foundation. Discover how her foundation is helping to save more than one million pet lives, aid more than 6,000 animal shelters with adoption events and spay/neuter surgeries across the country. Oh, yeah. And, tune in as she playfully runs down the names and personalities of her beloved personal rescued dogs. EPISODE NOTES: Meet the Help-Animals-In-Need Champion: Cathy Bissell of the Bissell Pet FoundationBecome a supporter of this podcast: https://www.spreaker.com/podcast/oh-behave-with-arden-moore-harmony-in-the-household-with-your-pets-recommended-by-oprah--6666801/support.

  complete show notes pending... Update of the Dealey Plaza UK conference The Washington Post's Bomb on George Joannides - Article links to documents of note mentioned available at Mary Ferrell website Traces of an M.O.: Bissell's testimony on Executive Action - File: 135-10001-10297 Traces of an M.O.: Ed Lansdale's Playbook File 104-10315-10011 QJWIN - File: 135-10001-10246 The Pepe letters: file 124-10279-10068 and 124-10279-10068 Black Letters - File: 178-10004-10148 Operation Mongoose.  

Aaron Magness is the SVP of Marketing at Full Glass Wine Co., a brand acquisition and management firm focused on operating DTC wine companies with strong community roots and lasting customer value. From first-time buyers to wine club loyalists, Aaron leads marketing across a growing portfolio of brands, building distinct identities while driving collective growth at scale.With 15+ years of experience at fast-growing consumer brands, Aaron brings a sharp operator's mindset to every marketing challenge. His work centers on sustainable value creation, balancing customer acquisition with deep retention, brand storytelling with data-driven execution. Outside of Full Glass, he's also an active advisor and investor in consumer startups, with a passion for enhancing customer experience at every touchpoint.Whether unpacking how to manage marketing across multiple brands, sharing what he looks for in standout talent, or reflecting on the role of skill vs. luck in his career, Aaron offers a grounded, thoughtful take on what it really takes to lead modern marketing teams.He shares what it means to scale without shortcuts, how to build teams that compound over time, and why marketing today is more about connection than ever before.In This Conversation We Discuss:[00:41] Intro[00:59] Investing in your professional network[01:47] Navigating job loss during economic downturns[03:09] Scaling DTC through subscription experience[06:03] Building expert teams in a startup portfolio[07:04] Transferring insights across brand portfolios[08:47] Electric Eye, Social Snowball, Portless, Reach & Zamp[15:08] Specializing before expanding your skillset[18:07] Aligning teams around shared outcomes[19:41] Focusing on customer quality over quantity[23:16] Balancing tools with firsthand market knowledgeResources:Subscribe to Honest Ecommerce on YoutubeRedefining the fragmented DTC wine market by building a multi-brand platform, delivering curated wines fullglass.wine/Follow Aaron Magness linkedin.com/in/aaronmagnessSchedule an intro call with one of our experts electriceye.io/connectDrive revenue through affiliates & referrals socialsnowball.io/honestRevolutionize your inventory and fulfillment process portless.com/Level up your global sales withreach.com/honest  Fully managed sales tax solution for Ecommerce brands zamp.com/honestIf you're enjoying the show, we'd love it if you left Honest Ecommerce a review on Apple Podcasts. It makes a huge impact on the success of the podcast, and we love reading every one of your reviews!

The Boys have a laugh filled chill show to bring everyone up. Aaron starts us off with a Delivery Downer, and some work woes. We bring out the Male Bag and read comments from Bill M, and 8-Bit.Followed up by Augie with Monster Hunter and his new PC Build. Finally Stevie gives praise to Bissell for his vacuum, streaming, and School's Out Fools.Promo @SuperMediaBros @ BeerdAlPodcastProudly Sponsored by Peace, Love, & Budhttps://www.plbud.com/Shoutouts to our Patrons; Mexi, Justin B, Kristin F ,Jeramey F ,Flaose, Todd, Jim, Flaos, Bridget F., David M., Dave A, Erin S, Donna/Colin Maggs,The GateLeapers, Kacey S., William M., Crunchie, DJ Xanthus, Crystal D., Jeff S.Free Followers on Patreon: Joáo C, Joep, Leonardo, Irsya Cahyo, Teanna Cm Lucho D.Founding Members of @OddPodsMedia https://www.patreon.com/BFYTWShow Music by @KeroseneLetter and @Mexigun Our Merch Available by contacting us.https://www.youtube.com/channel/UCyJG-PDn6su32Et_eSiC6RQwww.BFYTWpod.com

We're about to enter Vacationland Cup SZN! The pod is BACK this week to recap an INSANE night in Portland with our friends from Bissell Brothers, a preview of what's on tap for Saturday's return to Yarmouth & the road ahead to VLC '25! Today's episode is presented by Rugged Roots Trading Post - cultivator of Maine's finest recreational cannabis products! For more information or to find a location near you, visit ruggedrootstradingpost.com!

In this episode of The Pet Food Science Podcast Show, Dr. Heidi Bissell, Chief Animal Nutritionist at Disney's Animal Kingdom, shares her expertise on creative ways to feed zoo and exotic animals. She explores how replicating natural behaviors, tackling the challenges of diverse diets, and focusing on sustainability can shape the future of pet nutrition. Don't miss this fascinating discussion packed with practical insights for the pet food industry. Listen now on all major platforms!"Zoo animals need diets tailored to their natural behaviors, ensuring they meet nutritional needs while maintaining their physical and mental well-being."Meet the guest: Dr. Heidi Bissell, Chief Animal Nutritionist at Disney Animal Kingdom, holds a Ph.D. in Zoology from the University of Wisconsin-Madison and an M.S. in Animal Sciences from the University of Florida. With over 25 years in zoo and wildlife nutrition, she has advanced animal health and welfare through innovative dietary strategies.What will you learn:(00:00) Highlight(01:28) Introduction(08:13) Feeding exotic animals(12:28) Nutrition & natural behavior(19:58) Pet nutrition parallels(26:18) Diversity in diets(31:38) Nutrient needs(36:25) Final QuestionsThe Pet Food Science Podcast Show is trusted and supported by innovative companies like:* Trouw Nutrition* Kemin- Corbion- EW Nutrition- ICC- Scoular- Biorigin- Symrise

This week I talk with Cathy Bissell. Somebody pinch me. Her dedication to animal rescue and welfare is something I have admired for a long time and now we get to hear from her! We discuss how she got started and advice she has for those who may be nervous to go into their local shelter, the time it took to get the foundation up and running, and the eye-popping number of animals they have had spayed or neutered in the short time they have had the Fix the Future program running. You can learn more about Bissell Pet Foundation at www.bissellpetfoundation.org. Sponsor:LIX - check out www.lixpetwellness.com to learn more about CBD for pets. Use code Rescuepod20 for 20% off your first order!Thanks for listening! If you liked what you heard, please rate, review, and subscribe. If you have ideas for future guests please email me at theanimalrescuepodcast@gmail.com or follow me @theanimalrescuepod on Instagram. You can also learn more about the organizations I interview and how to listen/watch at www.theanimalrescuepodcast.my.canva.site

So much to unpack from WARPATH on Feb 22nd! Josh & Randy are back on the pod to breakdown a chaotic stop on the road to the Bissell Brothers Bash including B3CCA's shocking betrayal of Gabby Forza, Dijak's Championship challenge, Dezmond Cole's injury status & much more! Don't miss our return to Portland, Maine on Friday, March 21st! For more details visit LimitlessWrestling.com/tickets!

In this episode of Island Influencers, I sit down with the incredible Jason Bissell, Global AI & Data Executive, Strategic Advisor, and Chair of the UNESCO Biosphere Isle of Man Board. From a small village in Somerset to leading global AI, tech, and data companies, Jason's career path and life story are nothing short of inspiring. We talk about how his early experiences, including the influence of his stepfather, shaped his work ethic and drive. Jason shares insights from his pioneering work in AI, data analytics, and virtual reality, reflecting on the evolution of these industries and his transition from corporate leadership to strategic advising. Now based on the Isle of Man, Jason serves as Chair of the UNESCO Biosphere Isle of Man Board. He reveals what drew him to the island, his first impressions, and his vision for balancing economic growth with environmental and community well-being. If you're curious about career transitions, leadership, and sustainable innovation, this conversation is packed with inspiration. https://www.thorntonfs.com/island-influencer-jason-bissell

This week we talk to Josh Bissell.  He is an Austin-based musician who recently left his job to pursue music full-time. We talk about about how he approached taking that risk, his faith, and the modern day church. His story is sure to inspire you!Don't forget to subscribe and leave a review on the podcast so that stories like his get to as many people as possible. 

Nash Barlow & Eric Bissell, from the 2024 NCAA Champion UVM Men's Soccer Team, joins Kurt & Anthony.

Pat Bissell talks with Jill and Chris about how she found her passion and has consistently found ways to stay healthy and fit.  A long time friend of Chris's, Pat describes herself as a very active mature female. She has been active her whole life always enjoying sports, exercise classes and strength training for the past 25 years. For more info and links visit our website at BecomingElli.com

Send us a textWhat magic pill can help keep hundreds, indeed thousands of credit unions from vanishing over the next decade?Vim Anand, CEO of Member Support Services, says his CUSO can create operational efficiency and cost savings through economies of scale and standardization.  The focus is on backoffice technologies and, says Anand, MSS's tools deliver 20+ % cost savings.But don't take his word for all of this. Also on the show is John Bissell, CEO of $1.6 billion Greylock Federal Credit Union in Pittsfield MA. Bissell is a new MSS member-owner and he explains that the credit union took this step because he sees this as a way to stay independent and local and both of those are crucial to Bissell who believes they are a big part of the credit union special sauce.Greylock, by the way, is the biggest credit union in MSS - the two other member owners are >$400 million apiece - and MSS is actively seeking new member owners because Anand's goal is $8 to $10 billion in total assets.And the payoff, says Anand, will be helping more credit unions stay independent.As for why Bissell is set on keeping Greylock independent understand that he grew up in a Greylock family. His dad logged 30 years at GE which was the SEG that powered the birth of the credit union.Listen to the show to hear Bissell's story of how an Amherst College grad with an English degree migrated to Seattle but after 10 years he felt the call to return to western Mass, as locals call the region.Do you want more credit unions to stay independent? Listen up.Like what you are hearing? Find out how you can help sponsor this podcast here. Very affordable sponsorship packages are available. Email rjmcgarvey@gmail.comAnd like this podcast on whatever service you use to stream it. That matters.Find out more about CU2.0 and the digital transformation of credit unions here. It's a journey every credit union needs to take. Pronto

Send us a textY'all got to check out Shelton,from stories of First gig with Mickey Gilley to what he's up to now!!  A Country Sax player!!  good stuff 83 Years old and still at it!!check him and his music out at:www.sheltonbissell.comall links are thereSupport the showThe David Bradley ShowHost: David Bradleyhttps://www.facebook.com/100087472238854https://youtube.com/@thedavidbradleyshowwww.thedavidbradleyshow.com Like to be a guestContact Usjulie@thedavidbradleyshow.comRecorded at Bradley StudiosProduced by: Caitlin BackesProud Member of CMASPONSERSBottled Water and Sweet Tea provided by PURITY DairyABlaze Entertainment

Join Lori as she speaks with Cathy Bissell, Founder of the Bissell Pet Foundation, to discuss the foundation's unwavering commitment to supporting animal shelters and rescues throughout the United States. Cathy shares how the foundation raises awareness about the challenges shelter animals face and strives to give these animals a second chance at finding a loving home!   Here are the things to expect in this episode: Cathy's personal journey that changed her life and inspired her to advocate for shelter animals. What are the challenges animal shelters face, and how can people support and help? The main initiatives of the Bissel Pet Foundation. How can parents instill philanthropic values in their children from a young age? And much more! Bissell Pet Foundation Website: https://www.bissellpetfoundation.org/# Bissell Pet Foundation Instagram: https://www.instagram.com/bissellpets/ Bissell Pet Foundation Facebook: https://www.facebook.com/bissellpets Cathy's Instagram: https://www.instagram.com/cathy_bissell/ Cathy's Facebook: https://www.facebook.com/p/Cathy-Bissell-100044530445611/   Connect with Lori Kranczer! Website: https://linkphilanthropic.com Email: info@linkphilanthropic.com   

Send us a textWelcome to episode 5 of 6! Straight into some product reviews again today. Nicola is sharing her new fav store in Brisbane and Jess is Back on the Bissell train! We're also discusing:Invisalign fails and hygeineNicola's latest reel and boomer vs conscious parenting lolsOur ideas on spoon fed vs baby lead weaning and a little sweet milk tipTo leash or not to leash and crying in the coldUnsolicited advice from friends and familyWhy we don't like the concept of selling sleep- how sometimes the professionals can make you feel like you're doing it all wrong and the damaging effects of not giving options to parents.The Triple P parenting course - a little online refresher for JessLeo's bday and a last minute cake baking sesh for day-care. Look forward to catching up for our last ep (for now, who knows?) next week! If you enjoyed this episode we would really appreciate if you could leave us a rating or review, it means so much to us and it really helps us to be seen (and obviously we will love you forever for it!) Follow us at @mother_unrefined to find out more! And feel free to have a little stalk sesh... @the__unrefined  @j.oc__

On today's episode of I AM HOME, our hosts Tyler, Becca and Hilary are joined by Steve Coe, a stain specialist with Bissell, to tackle one of the most dreaded household challenges - stubborn stains on carpets and furniture. From spilled wine and pet accidents to mysterious spots that just won't budge, we break down expert-approved cleaning methods to rescue your home's soft surfaces. Join us as we explore quick fixes, DIY solutions and the best products to keep handy for every type of stain emergency. This episode will equip you with the know-how to keep your home looking spotless and fresh!  Resources Bissell Stain Removal Solutions

Diving lizards use an air bubble to breathe underwater. What can we learn from this fascinating admiral adaptation? Plus, Earth will soon have two moons…temporarily. And on 'This Day in History; the first carpet sweeper patented by Melvin Bissell also leads to the world's first female CEO – in 1889. 'Scuba-diving' lizards use bubble to breathe underwater and avoid predators Earth will soon have a temporary second moon | KTLA What you need to know about Earth's new, temporary mini-moon - Los Angeles Times (latimes.com) A Two-month Mini-moon: 2024 PT5 Captured by Earth from September to November - IOPscience The First Carpet Sweeper Contact the show - coolstuffcommute@gmail.com Learn more about your ad choices. Visit megaphone.fm/adchoices

In this episode, we explore with Megan Bissell the evolving landscape of American Christianity and how faith communities can adapt to new challenges. We begin by discussing the latest data on "nones" (those with no religious affiliation) and Gen Z, highlighting the need for a shift in thinking within American Christianity. Megan shares why she believes faith should be viewed as "a conversation" and why relationships rooted in listening are essential for churches looking to reconnect with modern society. We then introduce the concept of Sacred Listening Tools to help foster meaningful engagement. We delve into the origins of this idea, its practical applications, and its three foundational roots. Lastly, we consider the future implications for Sunday worship and discuss how the role of pastors may need to evolve to better support deeper relationships and conversations within their communities. Megan Bissell is the co-founder of Future of Faith and an applied sociologist and researcher who specializes in the lives of young people, relationships, and group dynamics. She has spent her career turning research into actionable insights that people can use to make a meaningful impact. She has extensive experience  in leading research, facilitating workshops and educational programs, and consulting with organizations who want to enhance their relational and organizational dynamics. ​Megan was previously Head of Research for both the Social Research Lab at the University of Northern Colorado and then at Springtide Research Institute. She served as the Vice President for Research at the National Catholic Educational Association. She has a B.A. and an M.A in Sociology. Megan lives in Greeley, Colorado with her family of creatives, where she has no choice but to be inspired by those around her. Video: https://youtu.be/m3lrNSEWrwI Website: www.futureoffaith.org LinkedIn: https://www.linkedin.com/in/megan-bissell-7b503713/   Presenting Sponsor: Phillips Seminary Join conversations that expose you to new ideas, deepen your commitment and give insights to how we can minister in a changing world.  Supporting Sponsors: Restore Clergy If you are clergy in need of tailored, professional support to help you manage the demands of ministry, Restore Clergy is for you! Future Christian Team: Loren Richmond Jr. – Host & Executive Producer Martha Tatarnic – Guest Host / Co-Host Paul Romig–Leavitt – Associate Producer Dennis Sanders – Producer Alexander Lang - Production Assistant

The University of Denver Division of Athletics weekly coaches' show returns on Wednesday night with updates on both Denver golf programs, featuring women's golf head coach Martha Richards in the first segment, followed by men's golf head coach Gary Bissell in the second half of the show. DU's weekly coaches show is presented by the Johnson Financial Group from Your Front Range Toyota Stores Studios.

Brendan sat down with Josh Bissell who's a fantastic singer/songwriter but is also a worship leader in Texas. Josh tells us beginnings and all about himself in this podcast episode. #podcast #joshbissell #conversation

This interview is with Laura Brennan Bissell of Inconnu and Aitia Wines. In this interview, Laura talks about her journeys abroad and how she eventually found her way to wine. Laura shares about growing up in Virginia and some of her early memories surrounding wine. She dives into her passion for scent and how wine entwines with this passion. She goes on to talk about her travels abroad and how she found herself working in the wine industry. Later in the interview, Laura talks about getting her own vineyard and starting her two labels. She then dives into her farming and wine philosophies. Laura leaves us with her proudest accomplishment and some words of wisdom. This interview was conducted by Rich Schmidt on August 5, 2024 at Laura's home in the Columbia Gorge.

This week we chat to James Bissell.  James is the VP of Sales turned Founder. He has spent over ten years in B2B sales as a high-performing individual contributor and then VP of Sales. Tune in now!

Could you imagine slicing your finger with a hedge trimmer and still having the time of your life at a concert the next day? That's precisely what happened to Brandon, and he spills all the gory yet hilarious details before raving about the Red Hot Chili Peppers concert in St. Paul, Minnesota. Meanwhile, Nick takes us through his more relaxed weekend, filled with a double date swim party and an all-out war with some stubborn squirrels and their acorns. Their weekend tales are packed with personal stories and humor, offering a delightful peek into their lives beyond the podcast mic. Switching gears, we dive into this week's latest political drama and tech fiasco. Join us as we dissect the impact of the recent CrowdStrike incident and its eerie similarities to the Y2K scare, especially for businesses like airlines. We debate the role of insurance in covering such massive system failures and delve into a federal jury's ruling that Lockton Companies and two brokers owe USI Insurance Services around $3 million. And of course, we can't ignore the political landscape, with speculations ranging from Kamala Harris's potential run to Joe Manchin's surprising moves and Dean Phillips's unexpected presidential bid. Finally, we rank U.S. states based on business and quality of life, shedding light on the differences between California, Texas, and Minnesota in terms of regulations and public vs. private land. We also share some personal anecdotes about family outings and the joys of recreational activities like pickleball. And don't miss our discussion on Dollar General's shocking $12 million fine and the latest product recall mess involving Bissell's steam cleaners. With a mix of humor and insightful commentary, we navigate through the complexities of legal disputes, economic paradoxes, and everyday quirks. Timestamps 0:00 Introduction 1:38 Episode starts: weekend updates 5:53 Today's topics 7:12 Today's drinks: Lalo Tequila and Oban 14 Scotch 9:35 CrowdStrike failure and its effects on business and insurance 15:30 Jury awards $3M to USI in broker poaching suit against Lockton 18:09 US politics: Kamala and Gavin Newsom 22:08 Regulatory environment in California: employers now need to notify workers of their rights 28:43 Dollar General will pay $12 million in fines over workplace safety 38:05 A wholesale insurance agent's claim against a retailer 42:06 Recall of the week: Bissel steam cleaner 45:09 Today's quiz Connect with RiskCellar: Website: https://www.riskcellar.com/ Brandon Schuh: Facebook: https://www.facebook.com/profile.php?id=61552710523314 LinkedIn: https://www.linkedin.com/in/brandon-stephen-schuh/ Instagram: https://www.instagram.com/schuhpapa/ Nick Hartmann: LinkedIn: https://www.linkedin.com/in/nickjhartmann/

Persevering against all odds, and transforming through the experience is the stuff of inspiration, and makes for great stories to tell. It's the premise behind Deserts to Mountaintops, which chronicles the journey of extraordinary women overcoming monumental challenges. It's the creation of Jessica Buchanan, the woman who made headlines worldwide for her strength and tenacity, surviving a kidnapping by gunpoint by Somali pirates, being held for ransom for 93 days, forced to live outside in deplorable conditions, starved and terrorized, she was finally saved by SEAL Team VI in early 2012. After telling her own story in a book, she moved on to creating a platform to tell the stories of other women. Audrey Casey-Herrick and Wendy Casey (sisters) and their aunt Mary Casey-Bowers wrote their own story in the first volume of the series. Stacia Bissell's life was transformed on a fateful day when she flipped from her bicycle and woke up hours later in her bed, asking countless times why there was a cast on her arm. The journey has been long and winding, and has ultimately led Stacia to step forward in her greater purpose to inspire and enlighten the world through her own story. About Audrey Casey-Herrick and Wendy Casey and their aunt Mary Casey-Bowers (The Mystic Chics): We are modern day medicine women who bring a unique blend of solace and empowerment to any event with their energy healing, music, movement, and sacred ceremony. Whether it is 3 minutes or 3 hours, these intuitive women will help you feel into your own body and energy field to clear blocks and activate your true power. About Stacia Bissell After her world was turned upside down, she learned to navigate a new way of making strides in healing. With encouragement from her medical team, the Brain Injury Association of Massachusetts (BIA-MA), friends and family, she began doing speaking engagements to various audiences on the topic of brain injury. In addition to co-authoring Deserts to Mountaintops; Choosing our Healing through Radical Self-Acceptance, she is a contributor to Brain Injury HOPE magazine, a member of the Brain Injury Association of America's Brain Injury Advisory Council, council member for the Brain InInjury Alliance of Vermont, a program leader for LoveYourBrain, and a member of the BIA-USA speaker's bureau. Stacia co-founded the BIA-MA Northampton Brain Injury Support Group and the Berkshire Brain Injury Collaborative, designed to provide professional development to teachers on return-to-learn strategies after a student suffers from a concussion. --- Support this podcast: https://podcasters.spotify.com/pod/show/john-krol/support

Canadian journalist Nora Loreto reads the latest headlines for Friday, July 19, 2024.TRNN has partnered with Loreto to syndicate and share her daily news digest with our audience. Tune in every morning to the TRNN podcast feed to hear the latest important news stories from Canada and worldwide.Find more headlines from Nora at Sandy & Nora Talk Politics podcast feed.Help us continue producing radically independent news and in-depth analysis by following us and becoming a monthly sustainer.Sign up for our newsletterLike us on FacebookFollow us on TwitterDonate to support this podcastReferenced articles:Story 1 - Montreal children's hospital is seeing a spike in children injuries due to e-scooters. Story 2- Vancouver Island University is suing its own students over a Gaza solidarity encampment. Story 3 - Own a handheld steam cleaner from Bissell? It might burn you and is now under a recall notice. Story 4 - At least 17 people dead in student protests in Bangladesh over civil service hiring quotas. Story 5 - Itamar Ben-Gvir visits Al-Aqsa mosque, sparking fears that Israel has its eye on the Occupied Jerusalem site.

Vidcast:  https://www.instagram.com/p/C9lIjq_skVo/ The Consumer Product Safety Commission and Bissell are recalling Bissell Steam Shot Handheld Steam Cleaners.  These steam cleaners tend to shoot hot water and steam unexpectedly leading to user burns. About 3.2 million  of these steam cleaners were sold in the US and about 355,000 were sold in Canada at Target, Walmart, and other department and home goods stores nationwide and online at bissell.com, amazon.com, hsn.com, and on other websites. Stop heating and using these steam cleaners.  Contact Bissell at 1-855-417-7001 for via the email RecallNA@bissell.com.  You'll receive either a $60 credit on bissell.com or a $40 refund.  You'll have to cut the power cord and email a photo of the cleaner showing the cut cord and the model number. https://www.cpsc.gov/Recalls/2024/BISSELL-Recalls-More-Than-3-Million-Steam-Shot-Handheld-Steam-Cleaners-Due-to-Burn-Hazard #bissell #steamcleaner #leaking #burns #recall

Have an episode idea or feedback? Text us here!Heather and Andy are joined in the RECAP by Jess and Bo Bissell, support raising coaches from Pioneers. Jess and Bo share their unique journey from missionaries in Japan to coaching new and seasoned workers in partnership development. They open up about their experiences, the challenges of rejuvenating fundraising efforts, and the importance of spiritual health in the process. The conversation delves into the fears and misconceptions surrounding support raising, the role of gratitude, and the necessity of community and prayer. It would be so helpful if you would take a moment to rate and review the show - thanks in advance!Have an idea for a guest or topic? WE WANT TO HEAR FROM YOU!Contact us!on Instagram @ its.not.about.the.money.podemail us: provisio at provisiofundraising.comTHANKS FOR LISTENING!

"We have now, since April, three violent crimes, all sexual in nature, and the victims seem to fit the same profile..."Between April and August of 2000, three violent crimes shook the southwestern shores of Kauai. The fourth largest of the Hawaiian islands, this was a region that rarely saw violent crime on this scope. For it to happen three times in such a short amount of time was unheard of. In response, residents began fearing that they would be next.As police struggled to ascertain who this strange attacker was, questions began to be raised about whether or not these three crimes were even related...Research, writing, hosting, and production by Micheal WhelanMusic composed and created by Micheal WhelanAdditional music includes "Unresolved Mysteries" by Ailsa Traves (podcast theme song, end credits)Learn more about this podcast at http://unresolved.meIf you would like to support this podcast, consider heading to https://www.patreon.com/unresolvedpod to become a Patron or ProducerBecome a supporter of this podcast: https://www.spreaker.com/podcast/unresolved--3266604/support.

Welcome to your Paulding County Cast! In this episode, hosts Melissa Carter and Doug Harding bring you the latest headlines from Paulding County:   Top Story: Police are searching for two suspects involved in a double shooting at Dallas Terrace Apartments. Both victims were rushed to Wellstar Kennestone Hospital, with one in critical condition. For more details and how you can help, tune in. Community Achievement: Lieutenant Tracy Brown of the Paulding County Sheriff's Office makes history as the first woman from her department to graduate from the Leadership Paulding program. Discover her significant contributions during the nine-month course. Education Spotlight: Congratulations to East Paulding High School's Mrs. Bissell and Mrs. Dupree! They were honored at the GACTE Summer Conference for achieving Marketing Industry Certification, ensuring top-tier education for EPHS students. Plus, get your weather updates for Hiram and Dallas with highs of 93 today and cooling off slightly in the coming days.   Tune in for these stories and more on the Paulding County Cast!See omnystudio.com/listener for privacy information.

Find Josh & Megan's work at Future of Faith! Summary Dr. Josh Packard and Master Megan Bissell discuss the future of faith and their work as sociologists. They emphasize the importance of applied sociology and doing work that is useful, not just interesting. They talk about how they became a team and their journey from academia to founding the Springtide Research Institute. They highlight the need for sacred listening and treating every conversation as meaningful. They also discuss the importance of relationship and understanding the spiritual practices of young people. The conversation explores the importance of understanding and guiding young people in their spiritual journeys. It highlights the need for parents and adults to have curiosity and empathy when engaging with young people's spirituality. The conversation emphasizes the role of adults as guides rather than authorities, allowing young people to explore and find their own answers. It also encourages parents to take notes and track their children's spiritual growth over time. The conversation concludes with a reminder that adults don't have to have all the answers and can rely on the Holy Spirit to guide the process. Keywords future of faith, sociology, applied sociology, sacred listening, relationship, spiritual practices, young people, spirituality, young people, guidance, curiosity, empathy, exploration, parents, adults, notes, growth, Holy Spirit Takeaways Applied sociology focuses on doing work that is useful, not just interesting. Sacred listening is treating every conversation as meaningful and finding deep listening as a sacred practice. Relationships are crucial in understanding the spiritual practices of young people. Young people are repackaging faith practices and finding spiritual moments in nature and other ways. Understanding the language and experiences of young people is essential in helping them develop meaningful faith practices. Parents and adults should approach young people's spirituality with curiosity and empathy. Adults should act as guides rather than authorities, allowing young people to explore and find their own answers. Taking notes and tracking a young person's spiritual growth over time can be valuable. Adults don't have to have all the answers and can rely on the Holy Spirit to guide the process. --- Send in a voice message: https://podcasters.spotify.com/pod/show/betterontheinside/message Support this podcast: https://podcasters.spotify.com/pod/show/betterontheinside/support

I can't say enough about how special these wines are. Her wines are a beautiful symphony, a perfect poem that captures  that moment. I'm just going to use Laura's own words here.  "Just like my life, I wish for my wines to be distilled into a poetic form, and not to have their entrails spread apart on a surgical table. There is pain and suffering, there is joy, chaos, recklessness at times, but more than anything, a quiet optimism that every day of our time here is yet another chance to experience something beautiful.https://www.inconnuwine.com/press.htmlCheck out the website: www.drinkingonthejob.com for great past episodes. Everyone from Iron Chefs, winemakers, journalist and more.

John Bissell, co-CEO and a pivotal innovator in the chemical industry shares his insights on driving sustainable change and leveraging technology for environmental progress. With a unique blend of technological savvy and entrepreneurial spirit, Bissell has been at the forefront of developing sustainable materials, focusing on both environmental impact and commercial viability. In this episode of the Culture Leaders Podcast, John Bissell discusses the intricacies of balancing profitability with sustainability, the transformative power of technology in addressing global environmental challenges, and the critical role of leadership in navigating the complexities of modern business. He delves into the mindset required for innovative entrepreneurship and the strategic approach to fostering a culture of adaptability and growth. Join us as John Bissell takes us through his journey in the chemical industry, reflecting on the importance of making conscious decisions that benefit both humanity and the planet, and the future of sustainable practices in business.   Segmented Timestamps [00:17] John's why: Advancing human health and the planet.  [01:12] Balancing profitability with sustainability.  [04:11] The opportunity in sustainable materials and energy production.  [06:06] Capitalism as a scaling function for impactful technology.  [09:20] The benefits of a co-CEO model in handling fast growth.  [14:20] Recruiting top talent and fostering a high-performance culture.  [19:53] The challenge of maintaining alignment during rapid scaling.   Notable Quotes "We're bringing technology that is a meaningful part of the once in a planet change to sustainable materials and energy production." - John Bissell   "You have to make explicit decisions and trade-offs between making money and long-term benefit." - John Bissell   "Hacking capitalism is leveraging the system of capitalism to scale your purpose." - John Bissell   "It's all about bringing new technology and making the human species better by bringing new technology to the market." - John Bissell   "My why really is focus on the same thing as the mission of the company, Origin, which is how can I bring technologies to the world or to humanity that really advance human health, the planet. You know, it'd be nice to make some money along the way for people that are involved." - John Bissell USEFUL LINKS   Reach John at: LinkedIn: https://www.linkedin.com/in/jabissell/ Website: https://www.originmaterials.com/   GET MORE FROM THE CULTURE LEADERS PODCAST Website: https://www.jessicakriegel.com/ Jessica's LinkedIn - https://www.linkedin.com/in/jessicakriegel Culture Partners LinkedIn - https://www.linkedin.com/company/culturepartners/ Instagram: https://www.instagram.com/jess_kriegel/    Enjoyed the episode? We'd love to hear your thoughts! Please rate / review on Apple.

On today's show: 1. Ride & Roll Cycling - https://www.rideandrollcycling.com 2. Ride & Roll Cycling Instagram - https://www.instagram.com/rideandrollcycling/ 3. Holy City Sinner and MyLo Lowcountry Announce Photo Contest with Incredible Prizes - https://holycitysinner.com/lifestyle/holy-city-sinner-and-mylo-lowcountry-announces-photo-contest/ This episode's music is by Tyler Boone (tylerboonemusic.com). The episode was produced by LMC Soundsystem.

Anna Sutherland Bissell was a Canadian-American businesswoman who was the first female CEO in the United States.   Anna became a teacher at just 16 years old and then married Melville Bissell three years later. They had five children together. They moved from Wisconsin to Kalamazoo, Michigan to Grand Rapids, Michigan where they settled and had a successful crockery business.    Anna was involved in the business from the start and inspired the invention of the carpet sweeper. She was having a hard time keeping the shop clean from all the dust coming out of new cases of dishes. So, Melville stepped in determined to find a solution.   He created a rotating brush that swept the dust into an attached container, known as the first carpet sweeper. They patented the invention together and immediately began selling it to retailers.    Then, Melville passed away unexpectedly and Anna became CEO of the Bissell company. Her leadership transformed the company into a household name and led to further inventions, like the vacuum. She was also instituted policies like workman's compensation, pensions, and vacations unlike any other manufacturers or companies in the 19th century.    Get your Homance apparel: nicolebonneville.etsy.com Follow us on IG: @homance_chronicles Connect with us: linktr.ee/homance Send us a Hoe of History request: homancepodcast@gmail.com    

On January 24, 2000, sheriff's deputies in Mentone, Alabama stopped an older model Lincoln with Ohio plates that they suspected was involved in a hit-and-run accident earlier that day. The driver was thirty-seven-year-old Hayward Bissell of Norwalk, Ohio and strapped into the seat beside him was the remains of his twenty-four-year-old girlfriend, Patricia Booher. To the deputies' horror, Booher's hand and leg had been severed from her body, her eyes had been gouged out, and her heart and liver had been torn out, but were still in the car. Further investigation revealed that, in addition to Booher's murder, Bissell had also attempted to kill two other couples on what appeared to be a rampage across two states.Thank you to the ever so talented David White for research assistance :)-Schizophrenia & Psychosis Action Alliance - Website:sczaction.orgServices: Education and support groups National Alliance on Mental Illness (NAMI)Website:nami.org Services: General resources for mental health Domestic Violence: -US Hotline Number: 1(800)-799-7233-The Battered Women's Justice Project: **We donated to them, I met with them and they are amazing**Website: BWJP.org Services: Free legal help -Center For Domestic Peace Website: Centerfordomesticpeace.org Services: Support groupsReferencesActon, Andy. 2000. "Secret Service questions man in mutilation case." Birminghm Post-Herald, January 26: 23.Associated Press. 2002. "Mental illness plea accepted." Atlanta Constitution , February 8: D12.—. 2000. "Couple honors heroic Labrador retrievers." Birmingham Post-Herald, March 15: 16.—. 2001. "Man held in mutilation slaying to undergo more mental tests." Macon Telegraph, August 13: 12.—. 2000. "Police probe mutilation death of woman." The Anniston Star, Janaury 25: 8.—. 2000. "Suspect in mutilation death of woman to be sent to mental hsopital." The Anniston Star, January 26: 12.Bradley, Eric. 2000. "Manty native relates tale of terror." Manitowoc Herald-Times, Jul 7: 1.Columbus Ledger-Enquirer. 2000. "Mental tests urged for slaying suspect." Columbus Ledger-Enquirer, Janaury 27: 14.Harper, Carol. 2000. "Dismay, disbelief follow mutilation death." Sandusky Register, January 26.Johnson, Sheila. 2013. Blood Highway. New York, NY: Pinnacle Books.Nowak, Joe. 2000. "Victim's father in prison for rape." Norwalk Reflector, January 25.Nowak, Joe, and Jonathan Rickard. 2000. "Suspect has history of violent behavior." Norfolk Reflector, January 25.See Privacy Policy at https://art19.com/privacy and California Privacy Notice at https://art19.com/privacy#do-not-sell-my-info.