Podcasts about Algernon

The penultimate episode of Season Two finds Algernon, Beck, and Cal scattered, covered, and smothered. Support the show on Patreon. Buy some merch at the Contention General Store. Follow along on Bluesky. Find other listeners on Discord and Reddit. Join the chat on Twitch. Soundtrack by WAAAVV. Wolf the Dog played "What Kind of World Are You Living In" by Dragon Inn 3.

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

과연 이 공식은 성립하는가?영혼 = 기억 = 언어 = 행동 = 의지(P.S. pseudo-spiritual elements는 한국어로 "유사영체"로 번역됨.)---✍️ 녹취록: https://aimdreaming.imaginariumkim.com/죽은-자의-제국-유기체와-무기체-누가-살려/☕️ 한아임한테 ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠커피 사주기⁠⁠⁠⁠⁠: ⁠⁠⁠⁠⁠⁠⁠⁠https://buymeacoffee.com/ithaka⁠⁠⁠⁠⁠⁠⁠⁠

Adam and Nate get to know CHAЯLY (1968) and its episode-long Simpsons parody in “HOMЯ” (S12E9). While this movie barely exists today, when this adaptation of Daniel Keyes' short story “Flowers for Algernon” came out in the early days of New Hollywood, it pushed the boundaries of disability on film, formal experimentation… and good taste. Also in this episode:• Cliff Robertson and a brief history of the Oscar bait performance• Is this the most 1968 movie ever made?• “Multi-dynamic image technique” and other awesome film history from Expo ‘67 • Should this movie get a sequel?Plus, check out our show notes for a complete list of Simpsons references, double feature suggestions, and further readingNext time, Nate and Adam Billy Wilder's reclaimed box office flop Ace in the Hole (1951) and its extended parody in “Radio Bart” (S3E13).For more Simpsons movie parody content, check out SpringfieldGoogolplex.com, or follow us at @simpsonsfilmpod on Instagram, TikTok, Threads, YouTube, and Letterboxd. Discover more great podcasts on the That Shelf Podcast Network.

Some books are incredible experiences.They challenge us.They wreck us emotionally.They leave a permanent mark.And then… once is enough.In this episode of Fantasy for the Ages, Jim and Zach talk about fantasy, science fiction, and horror books they're genuinely glad they read, but have absolutely no desire to ever revisit. Not because they're bad. Not because they failed. But because they succeeded too well.We discuss:• Emotionally devastating reads• Intellectually exhausting masterpieces• Surprise heavyweights that hit harder than expected• Horror novels that did their job too well• Why rereadability is NOT the same thing as qualityThis is a reflective, conversation-driven episode about how we read, why we read, and how our relationship with books changes over time.

Whether you like ripping page turners, incredible characters, books that make you laugh out loud, exploring unforgettable new worlds, or literary books that will make you see the world in a new way, there's a great intro to scifi out there for everyone!Join the Hugonauts book club on discord to tell us about your favorite time travel booksOr you can watch the episode on YouTube if you prefer videoIf you want to jump around, here are the timestamps for all the books we talked about: 00:00 Intro 00:38 Incredible Characters - Vorkosigan Saga by Lois McMaster Bujold 3:07 A Long Way to a Small, Angry Planet by Becky Chambers 4:04 Flowers for Algernon by Daniel Keyes 4:52 Unforgettable Worlds - The Expanse by James S.A. Corey 6:58 Hyperion by Dan Simmons 8:24 House of Suns by Alastair Reynolds 9:20 Children of Time by Adrian Tchaikovsky 10:56 The Forever War by Joe Haldeman 12:22 Funny SF - Hitchhiker's Guide to the Galaxy by Douglas Adams 13:36 Snow Crash by Neal Stephenson 14:50 Old Man's War by John Scalzi 16:01 Page turners - Project Hail Mary by Andy Weir 17:43 Dark Matter or Recursion by Blake Crouch 18:52 All Systems Red by Martha Wells 20:01 Ender's Game by Orson Scott Card 21:35 Ready Player One by Ernest Cline 22:34 Literary SciFi - The Left Hand of Darkness by Ursula K. LeGuin 24:55 Never Let Me Go by Kazuo Ishiguro 26:26 The Road by Cormac McCarthy 27:49 Slaughterhouse-Five by Kurt Vonnegut 28:40 Starship Troopers by Robert Heinlein

Today we are feeling nostalgic...for a time long gone, when multiplayer games were only expected to last you for a few hours a week for maybe a month or two. When console wars were the most toxic spats in the gaming space. When Kevin knew a British guy with a dead son on Xbox Party Chat (unsure if this is real). MORE PLACES TO FIND USCrubscribe ► https://bit.ly/CrubcastGet the show early and get exclusive content at our Patreon ► https://www.patreon.com/crubOur Crubcasts are recorded LIVE at https://www.twitch.tv/crub_official every Tuesday at 7pm Eastern, with EXCLUSIVE Pre- and Post-ShowsJoin our Discord ► https://crub.org/joinBlueSky ► https://bsky.app/profile/crub.orgCome join our Steam group ► https://steamcommunity.com/groups/crubclubPodcasts are available on Apple, Google, Spotify, and other platforms are available at ► https://crub.orgSHOW NOTESSome information on the return of Modnation Racers:https://www.reddit.com/r/Modnation/comments/1o0i9ep/online_multiplayer_is_back_and_better_than_ever/Here's a link to The Karters 2:https://store.steampowered.com/app/2269950/The_Karters_2_Turbo_Charged/Spoilers for Flowers of Algernon are in this episode.TODAY'S CRUBCAST HOSTSBrody: https://www.youtube.com/@RACROXKevin: https://www.youtube.com/@TheGoldenBoltSean: https://www.youtube.com/@WolfkaosaunCHAPTERS00:00 God Nation Racers unite08:27 First Starhawk mention in 202510:04 First Monday Night Combat mention in 2025, also19:05 Sean misses a bygone era of vicarious experiences online27:28 ...remember party chat? Or meeting strangers online?37:16 Making our own fun in GTA IV, and the need for games to last forever42:43 Touching on fans getting too far into the weeds on the "business" of games47:04 We miss...console wars...54:15 Growing alongside the culture of gaming growing1:02:50 Pour one out for Assassin's Creed: Brotherhood's multiplayer. Literally.1:06:17 Do we lean on save states in older games, or play them as intended? (TheCrazyEven) ★ Support this podcast on Patreon ★

Algernon Health CEO Christopher Moreau joined Steve Darling from Proactive to announce that the company has entered into a significant strategic business and investment agreement with American Molecular Imaging, one of the premier radiology reading services providers in the United States. The partnership is designed to ensure that every patient visiting Algernon's planned U.S. brain-focused neuroimaging clinics receives top-tier PET scan interpretations delivered with unmatched accuracy and turnaround times. Moreau explained that Algernon's planned clinic network will introduce the first dedicated, brain-optimized PET neuroimaging centers in the United States, facilities engineered to detect early signs of Alzheimer's disease with exceptional precision. In addition to Alzheimer's diagnostics, the clinics will offer advanced PET imaging for a broad range of neurological conditions, including other dementias, epilepsy, neuro-oncology indications, and movement disorders. Under the terms of the new partnership, AMI will become the exclusive radiology reading services provider for all of Algernon's future neuroimaging clinics. To further strengthen the collaboration, AMI will make a US$250,000 strategic investment in Algernon's recently announced private placement, and an additional US$250,000 investment into Algernon USA LLC—the company's newly formed subsidiary tasked with overseeing all U.S. neuroimaging operations. Algernon USA LLC is leading efforts to open the first clinic, currently targeted for early 2026. Moreau also highlighted another key milestone: Algernon has finalized an equipment order, financing package, and consulting agreement with Catalyst MedTech, a recognized leader in medical imaging technologies. This non-dilutive arrangement, valued at over CAD $4 million, includes four FDA-cleared Oncovision CareMiBrain™ PET scanner systems that will equip the first wave of Algernon's U.S. clinics. The deal also provides for the acquisition of six additional systems at a reduced cost as the company expands its footprint across the country. #proactiveinvestors #algernonpharmaceuticalsinc #cse #agn #otcqb #agnpf #alzheimerdisease #demetia #AlgernonHealth #AlzheimersDiagnosis #PETScan #BrainImaging #MedicalTechnology #HealthcareInvestment #NeuroImaging #StrategicPartnership #RadiologyInnovation

This show has been flagged as Explicit by the host. New hosts Welcome to our new hosts: Kirbotica, Thibaut, candycanearter. Last Month's Shows Id Day Date Title Host 4478 Wed 2025-10-01 YouTube Subscriptions 2025 #6 Ahuka 4479 Thu 2025-10-02 Who is the Algernon for Whom are the Flowers? Antoine 4480 Fri 2025-10-03 Arthur C. Clarke Becomes Successful Ahuka 4481 Mon 2025-10-06 HPR Community News for September 2025 HPR Volunteers 4482 Tue 2025-10-07 doodoo 4 the double deuce Jezra 4483 Wed 2025-10-08 HPR Beer Garden 3 - Porters Kevie 4484 Thu 2025-10-09 When Your Dentist Uses ChatControl Logic Trollercoaster 4485 Fri 2025-10-10 Git for Github and Gitlab Archer72 4486 Mon 2025-10-13 A code off my mind Lee 4487 Tue 2025-10-14 Is AI autistic? Antoine 4488 Wed 2025-10-15 Cheap Yellow Display Project Part 2: What is the problem? Trey 4489 Thu 2025-10-16 Hacks Poetic - Pilot Episode Kirbotica 4490 Fri 2025-10-17 Playing Civilization V, Part 4 Ahuka 4491 Mon 2025-10-20 Thibaut and Ken Interview David Revoy Thibaut 4492 Tue 2025-10-21 How to do a distribution upgrade of an Ubuntu LTS on a Digital Ocean droplet Rho`n 4493 Wed 2025-10-22 HPR Beer Garden 4 - Weissbier Kevie 4494 Thu 2025-10-23 Exploring FUTO Keyboard Antoine 4495 Fri 2025-10-24 An introduction to Taskwarrior candycanearter 4496 Mon 2025-10-27 Stroopwafel Lee 4497 Tue 2025-10-28 fixing 328eforth Brian-in-Ohio 4498 Wed 2025-10-29 Living the Tux Life Episode 1 Al 4499 Thu 2025-10-30 Greg Farough and Zoë Kooyman of the FSF interview Librephone lead developer Rob Savoye Ken Fallon 4500 Fri 2025-10-31 Arthur C. Clarke: 2001 and Sequels Ahuka Comments this month These are comments which have been made during the past month, either to shows released during the month or to past shows. There are 41 comments in total. Past shows There are 12 comments on 7 previous shows: hpr4238 (2024-10-30) "Snaps are better than flatpaks" by Some Guy On The Internet. Comment 4: BA on 2025-10-05: "Not a fan of any of them." hpr4453 (2025-08-27) "IPv6 for Luddites" by beni. Comment 7: Beni on 2025-10-22: "Link to the mentioned IPv6 talk on EuroBSDcon 2025" hpr4470 (2025-09-19) "HPR is twenty years old today. " by Lee. Comment 3: Steve Barnes on 2025-10-12: "Les petites félicites!" hpr4474 (2025-09-25) "Hacker Poetry - 001" by Major_Ursa. Comment 1: candycanearter07 on 2025-10-01: "love it" hpr4475 (2025-09-26) "The true audio file for walking tune to(wards) a friend" by FredBlack. Comment 1: brian-in-ohio on 2025-10-14: "Why fret about frets?" Comment 2: Folky on 2025-10-15: "Frets?" hpr4476 (2025-09-29) "Does AI cause brain damage?" by Trollercoaster. Comment 3: enistello on 2025-10-01: "Wonderful episode" Comment 4: Trollercoaster on 2025-10-02: "Re: Wondeful episode" hpr4477 (2025-09-30) "doodoo 3 a deuce plus 1" by Jezra. Comment 1: candycanearter07 on 2025-10-02: "cool app but" Comment 2: Archer72 on 2025-10-05: "Re: cool app" Comment 3: candycanearter07 on 2025-10-06: "Re: Re: cool app" Comment 4: أحمد المحمودي on 2025-10-07: "I use todoman" This month's shows There are 29 comments on 12 of this month's shows: hpr4478 (2025-10-01) "YouTube Subscriptions 2025 #6" by Ahuka. Comment 1: Anonymous 27 on 2025-10-02: "Excellent recommendations" hpr4479 (2025-10-02) "Who is the Algernon for Whom are the Flowers?" by Antoine. Comment 1: Trey on 2025-10-02: "Very interesting"Comment 2: Anonymous 27 on 2025-10-06: "Required Futurama reference" hpr4480 (2025-10-03) "Arthur C. Clarke Becomes Successful" by Ahuka. Comment 1: Archer72 on 2025-10-13: "Great show... and may the force be with you"Comment 2: Kevin O'Brien on 2025-10-13: "Thank you" hpr4483 (2025-10-08) "HPR Beer Garden 3 - Porters" by Kevie. Comment 1: Archer72 on 2025-10-16: "History of beer" hpr4484 (2025-10-09) "When Your Dentist Uses ChatControl Logic" by Trollercoaster. Comment 1: Trollercoaster on 2025-10-09: "Voting has been delayed"Comment 2: candycanearter07 on 2025-10-12: "Satire as a tool"Comment 3: Trollercoaster on 2025-10-14: "Re: Satire as a tool"Comment 4: operat0r on 2025-10-16: "Lol"Comment 5: Trollercoaster on 2025-10-20: "Re: Lol" hpr4485 (2025-10-10) "Git for Github and Gitlab" by Archer72. Comment 1: candycanearter07 on 2025-10-21: "useful introduction"Comment 2: Sayaci on 2025-10-21: "The content of the Archer72" hpr4486 (2025-10-13) "A code off my mind" by Lee. Comment 1: Trey on 2025-10-13: "Excellent perspectives " hpr4489 (2025-10-16) "Hacks Poetic - Pilot Episode" by Kirbotica. Comment 1: Ken Fallon on 2025-10-16: "What a waste !"Comment 2: Trey on 2025-10-16: "Thought provoking..."Comment 3: Claudio on 2025-10-16: "A Refreshing HPR Episode!"Comment 4: Alexander on 2025-10-17: "Just threw my iPhone in the ocean..."Comment 5: Kevin O'Brien on 2025-10-17: "I loved the show"Comment 6: Tori on 2025-10-21: "When Nostalgia Meets the Digital Age"Comment 7: brian-in-ohio on 2025-10-22: "Don't burn out" hpr4491 (2025-10-20) "Thibaut and Ken Interview David Revoy" by Thibaut. Comment 1: brian-in-ohio on 2025-10-22: "Great show"Comment 2: Henrik Hemrin on 2025-10-26: "Inspiring" hpr4493 (2025-10-22) "HPR Beer Garden 4 - Weissbier" by Kevie. Comment 1: folky on 2025-10-22: "Hefeweizen is best ;-) "Comment 2: paulj on 2025-10-22: "Great Episode!"Comment 3: Claudio on 2025-10-23: "Great Episode I Can Relate To!"Comment 4: Gan Ainm on 2025-10-26: "Scottish-Bavarian IPW" hpr4495 (2025-10-24) "An introduction to Taskwarrior" by candycanearter. Comment 1: Archer72 on 2025-10-15: "First show: Good explanation" hpr4500 (2025-10-31) "Arthur C. Clarke: 2001 and Sequels" by Ahuka. Comment 1: Archer72 on 2025-10-16: "Deep dive" Mailing List discussions Policy decisions surrounding HPR are taken by the community as a whole. This discussion takes place on the Mailing List which is open to all HPR listeners and contributors. The discussions are open and available on the HPR server under Mailman. The threaded discussions this month can be found here: https://lists.hackerpublicradio.com/pipermail/hpr/2025-October/thread.html Events Calendar With the kind permission of LWN.net we are linking to The LWN.net Community Calendar. Quoting the site: This is the LWN.net community event calendar, where we track events of interest to people using and developing Linux and free software. Clicking on individual events will take you to the appropriate web page.Provide feedback on this episode.

Charlie Gordon has an IQ of 68 and wants nothing more than to be smart. When scientists offer him an experimental surgery that has already transformed a laboratory mouse named Algernon into a genius, Charlie sees his chance—but becoming intelligent means finally understanding the cruel truth about the world around him.Support our Halloween “Overcoming the Darkness” campaign to help people with depression: https://weirddarkness.com/HOPEIN THIS EPISODE: The short story by Daniel Keyes, “Flowers for Algernon” became so popular it was later turned into a full novel, and then eventually made its way to movie screens. The short story was written in 1958 and first published in the April 1959 issue of The Magazine of Fantasy & Science Fiction, and was so loved that it won the Hugo Award for Best Short Story in 1960.SOURCES:BOOK: “The Science Fiction Hall of Fame: Volume One, 1929-1964”, https://amzn.to/3SePNlh=====(Over time links may become invalid, disappear, or have different content. I always make sure to give authors credit for the material I use whenever possible. If I somehow overlooked doing so for a story, or if a credit is incorrect, please let me know and I will rectify it in these show notes immediately. Some links included above may benefit me financially through qualifying purchases.)= = = = ="I have come into the world as a light, so that no one who believes in me should stay in darkness." — John 12:46= = = = =WeirdDarkness® is a registered trademark. Copyright ©2025, Weird Darkness.=====Originally aired: October 12, 2023EPISODE PAGE (includes sources): https://weirddarkness.com/FlowersForAlgernonABOUT WEIRD DARKNESS: Weird Darkness is a true crime and paranormal podcast narrated by professional award-winning voice actor, Darren Marlar. Seven days per week, Weird Darkness focuses on all thing strange and macabre such as haunted locations, unsolved mysteries, true ghost stories, supernatural manifestations, urban legends, unsolved or cold case murders, conspiracy theories, and more. On Thursdays, this scary stories podcast features horror fiction along with the occasional creepypasta. Weird Darkness has been named one of the “Best 20 Storytellers in Podcasting” by Podcast Business Journal. Listeners have described the show as a cross between “Coast to Coast” with Art Bell, “The Twilight Zone” with Rod Serling, “Unsolved Mysteries” with Robert Stack, and “In Search Of” with Leonard Nimoy.DISCLAIMER: Ads heard during the podcast that are not in my voice are placed by third party agencies outside of my control and should not imply an endorsement by Weird Darkness or myself. *** Stories and content in Weird Darkness can be disturbing for some listeners and intended for mature audiences only. Parental discretion is strongly advised.#WeirdDarkness #FlowersForAlgernon #ClassicSciFi #ScienceFiction #DanielKeyes #AudioDrama #SciFiStory #LiteraryFiction #HeartbreakingStory #ClassicLiterature

At long last...! So, one thing after another happened in our lives this summer, and the hiatus lasted longer than we anticipated or intended. But! We are back for another handful of episodes to round out the Season, kicking off today with a readthrough of Lords of Summer. This volume for Changeling: the Lost's first edition explored the concept of freeholds and provided a wealth of information for the four main Courts, giving us a much-needed look at the politics and society of the fae. We also get some fascinating new Entitlements for the Lost who needs some added purpose in their life. As with the other books in the game's first wave, this one is dense with material, and a lot of our discussion has been cut or condensed to fit into the episode. But equally, we hope as always that it's informative and sheds some light on the lore of the 'lings. You can snag a copy of the volume at https://www.storytellersvault.com/en/product/56375?affiliate_id=3063731, and note that it's currently 40% off for the Month of Darkness sale on the Storytellers' Vault. (Maybe fill out your collection with some other discounted books while you're at it, especially the homebrew Changeling stuff created by the community...!) Apart from that, if you'd like to reach out and bother us politely, feel free to do so via the following: Discord: https://discord.me/ctp Email: podcast@changelingthepodcast.com Facebook: https://www.facebook.com/profile.php?id=100082973960699 Mastodon: https://dice.camp/@ChangelingPod Patreon: https://www.patreon.com/changelingthepodcast YouTube: https://www.youtube.com/@ChangelingThePodcast your hosts Pooka G (any pronoun/they) qualified for an Autumn Court Scrivener position thanks to some fiercely effective bullet journaling. Amelia Fetch (she/her) would rather the Winter Court specialized in the Contracts of the Blanket-Wrapped Hot Chocolate Book Club. Never speak disrespectfully of Society, Algernon. Only people who can't get into it do that. —Oscar Wilde, The Importance of Being Earnest

A road trip to Connecticut to confront the Billionaires reveals their evil casino plans: What are the odds?! And now the future of Arconia hangs in the balance! ONLY MURDERS IN THE BUILDING Season 5, Episode 7 "Silver Alert" sees Oliver dressed as Cowboy Carter, Mabel and Charles winning at Game Night and Bash's creepy kid! 00:00 Intro 00:02 Paying for the Finger 00:46 Let's Solve Only Murders in the Building 02:07 Credit Clue Easter Eggs 02:33 Top Suspect Talk 09:59 Victim Profile: Nicky 'the Neck' 10:17 Victim Profile: The Finger 10:36 Mayor Tillman 11:22 Romy 11:45 The Billionaires 12:18 Camila White 13:02 Algernon 13:19 Bash Steed 14:29 Jay Pflug 14:52 Oliver 15:07 Charles 15:14 Bloody Mabel 15:19 Tin-Foil Hat Theory 17:47 Spoilers from new Teasers 19:34 Feedback The murder mystery/true crime podcast spoof with Steve Martin, Martin Short and Selena Gomez! Upper West Side neighbors Charles, Oliver and Mabel bond over a shared love of true crime. The mayor warns the trio about the billionaires, sending them to investigate further at a villainous lair upstate - as Oliver boots it in an attempted escape. Spoiler Videos discussed:  https://www.youtube.com/watch?v=vnUSZT6mZbo  https://www.instagram.com/onlymurdershulu/?hl=en Do you watch on Disney+, Hulu or Star+? Did we miss any clues? Twitter/Instagram/Threads: @DoublePHQ http://facebook.com/doublephq #onlymurdersinthebuilding #omitb #bloodymabel #OnlyMurders #ONLYMURDERS IN THE BUILDING Explained ONLY MURDERS IN THE BUILDING Recap ONLY MURDERS IN THE BUILDING Review ONLY MURDERS IN THE BUILDING Theory Theories s5e7 s05e07 s5e07 #selenagomez #stevemartin #martinshort Directed by Jessica Yu Writing Credits Steve Martin ... (created by) & John Hoffman ... (created by) Taylor Cox ... (written by) & Pete Swanson ... (written by) & Cast (in credits order) Steve Martin ... Charles-Haden Savage Martin Short ... Oliver Putnam Selena Gomez ... Mabel Mora Michael Cyril Creighton ... Howard Morris Meryl Streep ... Loretta Durkin Téa Leoni ... Sofia Caccimelio Logan Lerman ... Jay Pfluig Christoph Waltz ... Bash Steed Dianne Wiest ... Lorraine Coluca Renée Zellweger ... Camila White Keegan-Michael Key ... Mayor Tillman Bobby Cannavale ... Nicky Caccimelio David Patrick Kelly ... Miller Amy Ryan ... Jan Bellows Ryan Broussard ... Will Putnam Vanessa Aspillaga ... Ursula Tina Fey ... Cindy Canning Ryan Broussard ... Will Jackie Hoffman ... Uma Da'Vine Joy Randolph ... Detective Williams James Caverly ... Theo Dimas Teddy Coluca ... Lester Richard Kind ... Vince Fish Anthony Ruiz ... José the Super Jane Lynch ... Sazz Pataki Jason Veasey ... Jonathan Julian Cihi ... Tim Kono Emory Cohen ... Young Lester Siobhan Fallon Hogan ... Mrs. Morris Adriane Lenox ... Roberta Putnam Madison Wray ... Young Rainey Isabella Aparicio ... Young Mabel Shea Buckner ... Tony Caccimelio James Ciccone ... Doorman Joaquin Simone Recasner ... Wondify Executive Dane DiLiegro ... Caccimelio Aaron Dean Eisenberg ... Braden Caccimelio Beanie Feldstein ... Althea Jermaine Fowler ... Randall Siobhan Fallon Hogan ... Mrs. Morris Jacob MacKinnon ... Young Howard Evan Mulrooney ... Johnny Caccimelio Joshua Iverson ... Young Artful Dodger John Leone ... Realtor Hayes McCracken ... Young Oliver Jim O'Hare ... Al Ivy Schur ... Tween Girl Ian Unterman ... Fagin Produced by Dan Fogelman ... executive producer Selena Gomez ... executive producer John Hoffman ... executive producer Steve Martin ... executive producer Jess Rosenthal ... executive producer Martin Short ... executive producer Music by Siddhartha Khosla ... (music by) Consulting Producers Benj Pasek and Justin Paul

This show has been flagged as Clean by the host. What is it? Flowers for Algernon is a short science fiction story. Originally that. It was later developed as a novel. How did I come unto it? I know I have heard the title years before. So, when I saw it recently at the entrance on the bookstore, in a beautiful hardcover, I gave it a view. I did not decided to buy, but it stayed with me, specially for having few pages. I knew nothing of the plot, I only recognized the title, vaguely, as something I heard before as a praised work — and Isaac Asimov, who handed Keyes the Hugo Award for this short story, in 1960, as Best Novelette of 1959, "praised it lavishly" (source: Arthur Bruce Evans, of DePauw University. Daniel Keyes's Works ). I then, weeks or months later, searched about.and discovered it was originally a short story. And available online. In the moment of the interest aroused (soon before producing this.HPR episode), I was more than happy with the immediate possibility of reading, instead of having to wait to buy the book or letting it stay until the next visit to the Public Library of Paraná (that is, of my state in Brazil), that might have a copy. The first lines won me, so I kept reading, in two "seats", two moments, on the phone. It is 26 pages long. Now, to the story. The plot (Here starts a full revelation of the plot, if you want to stop listening.) (No personal written notes here, comment made directly to audio — so, more stuttered as I tried to find the ideas and words; thanks for the patience!) Curiosity: The Simpsons "As well as cinematic and stage adaptations, the book inspired a musical, starring Michael Crawford, and an episode of The Simpsons. In the episode, called Homr, Homer Simpson discovers that a crayon lodged in his brain has been responsible for his stupidity. On its removal, Homer becomes clever, only to have the crayon re-inserted after becoming distanced from family and friends. Aired in 2001, the episode won an Emmy for outstanding animated programme." (Source: BBC. Flowers for Algernon writer Daniel Keyes dies at 86 . June 18, 2014.) Ending... the author The author, Daniel Keyes, died on June 15, 2014, aged 86, from complications of pneumonia, at his home in Boca Raton (Florida, USA). His only wife, Aurea Georgina Vazquez, whom he married in 1952, had died one year, one month and one day before, on May 14, 2013.They had two daughters. Links: Wikipedia page for the story Flowers for Algernon: https://en.m.wikipedia.org/wiki/Flowers_for_Algernon Only that. Thanks for the opportunity to share! Provide feedback on this episode.

Algernon Cadwallader is a midwest emo band originally from Pennsylvania. They took a hiatus back in 2012, and now they’re officially back with their first full-length album in more than a decade, Trying Not to Have a Thought. KEXP’s Meerah Powell spoke with some of the members about the band’s revival, their newfound connections to the Pacific Northwest, and how their lyrics leave little room for ambiguity. “I think we’re at a point where there needs to be a little more ‘get pissed’ in everything that people are making,” drummer Nick Tazza says in the interview. “Everyone feels it, and I think we need to stop shying away from it.” On this record, Algernon Cadwallader directly confronts complicated events in America’s political history, from the 1985 bombing of the Philadelphia organization MOVE to the more recent placement of boulders under freeway bridges in Portland to deter homeless people from camping there. “We used to spend so much time in between songs talking about [political issues],” vocalist Peter Helmis says. “Well, now, it just comes along with the music. Anytime someone plays it, they’re hearing the message.” Tazza adds: “We’ve all put a record together that stands for something and it means something. All the bands we loved growing up were super political, and that’s what we cut our teeth on, so to see it come full circle is kind of cool.” Support the show: kexp.org/deeper Photo credit: Scott TroyanSupport the show: https://www.kexp.org/sound/See omnystudio.com/listener for privacy information.

This week Jeremy welcomes Peter Helmis of Algernon Cadwallader On this episode, Jeremy and Peter talk Saddle Creek Records, Kriss Kross, the parental advisory sticker, Hot Topic, Dippin Dotz, Stone Temple Pilots, learning guitar, Joshua Fit For Battle, apprehension to sing, his prolific output, Halfway to Holland's first tour starting the day high school ended, the paper atlas, their new album "Trying to Not Have a Thought", and so much more!! SUBSCRIBE TO THE PATREON for a bonus episode where Peter answered questions that were submitted by subscribers!

Algernon, Beck, Cal, Diggory, and Stevie make their way down to Daddy's. Support the show on Patreon. Buy some merch at the Contention General Store. Follow along on Bluesky. Find other listeners on Discord and Reddit. Join the chat on Twitch. Soundtrack by WAAAVV. Wolf the Dog played "My Life is Great and It's All My Fault" by Altar Girl.

Episode: 3329 Cognitive Decline as We Age.  Today, a well-tempered mind.

Send us a textWoman yearns for child, adopts orangutan instead. Disaster ensues. That's the premise of Gertrude Trevelyan's wonderfully bizarre 1932 novel, Appius and Virginia. We're joined in this encore episode by guest Brad Bigelow, whose obsession with obscure books was celebrated in the 2016 New Yorker profile “The Custodian of Forgotten Books.” Discussed in this episode: Appius and Virginia by G.E. TrevelyanEvery Which Way But Loose (1978 Film)Black MirrorThe Twilight ZoneNeglectedBooks.com“The Custodian of Forgotten Books” (The New Yorker)His Monkey Wife by John CollierDorothy RichardsonMay SinclaireFlowers for Algernon by Daniel KeyesRoom by Emma DonohueBear by Marian EngelOxford's Lady Margaret HallNewdigate PrizeA Room of One's Own by Virginia Woolf Hot-House by G.E. Trevelyan“If She Was a Bloke, She'd Still Be In Print” (The Guardian)Virginia FaulknerLost Ladies of Lit Episode 41 on Edith Lewis with Melissa HomesteadSupport the showFor episodes and show notes, visit: LostLadiesofLit.comSubscribe to our substack newsletter. Follow us on instagram @lostladiesoflit. Email us: Contact — Lost Ladies of Lit Podcast

Algernon Austin, Director of Race and Economic Justice at The Center for Economic and Policy Research, is back with his take on the injustices in President Trump's ugly little tax bill.Become a supporter of this podcast: https://www.spreaker.com/podcast/tavis-smiley--6286410/support.

I overlooked getting this one posted here, so it's out of order. My apologies!Join Jim on a thrilling journey through the most iconic and influential science fiction and fantasy of the 1960s! From groundbreaking novels to works from established favorite authors, we'll explore the most beloved and enduring works of the decade that shaped the genre. From Heinlein to Clarke, LeGuin to Zelazny, we'll divine which novels rose to the top in each year of the decade through sales, awards, and reviews. So, buckle up and get ready to blast off into the fabulous world of 1960s science fiction and fantasy!#FantasyForTheAges #ReadingRecommendations #Classics #ClassicLiterature #HugoAwards #SciFi #ScienceFiction #Fantasy #FantasyFiction #SSF #BestBooks #Top3 #Top10 #booktube #booktuberWant to purchase books/media mentioned in this episode?2001: A Space Odyssey: https://t.ly/t3_m_Babel-17: https://t.ly/5Lu6xThe Ballad of Beta-2: https://t.ly/Fx0X6A Canticle for Leibowitz: https://t.ly/Nbd8gDo Androids Dream of Electric Sheep?: https://t.ly/KYKbnDorsai: https://t.ly/lqBeFDr. Bloodmoney, or How We Got Along After the Bomb: https://t.ly/t5opnThe Drowned World: https://t.ly/2QjIjDune: https://t.ly/4_w_kThe Einstein Intersection: https://t.ly/LNmEeA Fall of Moondust: https://t.ly/kro3SFarnham's Freehold: https://t.ly/PobXpFlowers for Algernon: https://t.ly/cOenOGlory Road: https://t.ly/jKIDrGraybeard: https://t.ly/PkFXQThe Left Hand of Darkness: https://t.ly/avJCxLord of Light: https://t.ly/ql0kmThe Man in the High Castle: https://t.ly/wVUUmThe Moon Is a Harsh Mistress: https://t.ly/621IcPlanet of the Apes: https://t.ly/aNdi3Slaughterhouse-Five: https://t.ly/7BINKSolaris: https://t.ly/Jth3pStranger in a Strange Land: https://t.ly/gXvOpStarship Troopers: https://t.ly/dsq75The Wanderer: https://t.ly/0v1eWWay Station: https://t.ly/Z5DumA Wizard of Earthsea: https://t.ly/KMQT4A Wrinkle in Time: https://t.ly/cAK14Ways to connect with us:Support us on Patreon: https://www.patreon.com/FantasyForTheAges Follow Jim/Father on Goodreads: https://www.goodreads.com/user/show/13848336-jim-scriven Join us on Discord: https://discord.gg/jMWyVJ6qKk Follow us on "X": @Fantasy4theAges Follow us on Blue Sky: @fantasy4theages.bsky.socialFollow us on Instagram: fantasy_for_the_ages Follow us on Mastodon: @FantasyForTheAges@nerdculture.de Email us: FantasyForTheAges@gmail.com Check out our merch: https://www.newcreationsbyjen.com/collections/fantasyfortheagesJim's Microphone: Blue Yeti https://tinyurl.com/3shpvhb4 ————————————————————————————Music and video elements licensed under Envato Elements:https://elements.envato.com/

Menù del giorno:- SNACKFLIX- 3 MOTIVI PER (non) GUARDARE LE COMMEDIE ROMANTICHE (con Nicolò Targhetta aka Non è successo niente) 1' 20''- FIORI PER ALGERNON di Daniel Keyes (con Gianluigi Bonanomi) 26' 36''- Lista dell'attesa n°97 (Weapons, The Sandman 2, Goonies + Gremlins) 42' 46''ATTENZIONE: contiene anche Woody Allen, Cassandra, tecniche di seduzioni fallimentari, 50 sfumature di grigio, la mia vita a Garden State, D&D, Q.I. e A.I.P.S. Se volete capire la battuta sull'ape dove ascoltare l'episodio 76 di Yugen

Algumas doem. Outras libertam. Umas duram uma página, outras ecoam por séculos. Neste episódio especial do 30:MIN, Arthur Marchetto, Cecilia Garcia Marcon e Vilto Reis revisitam as cenas de despedida mais memoráveis da literatura — e compartilham um anúncio.De Ariano Suassuna a Sally Rooney, de J.R.R. Tolkien a Júlio Cortázar, o trio celebra o adeus em várias formas e as despedidas que ficaram gravadas na memória: amores que se esvaem, amigos que partem, saídas de lugares de conforto e até rituais de passagem.Então aperta o play e vem se despedir conosco, mas conta pra gente: qual livro tem uma despedida que te marcou?---Links⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠Apoie o 30:MIN⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠Siga a gente nas redes⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠Já apoia? Acesse suas recompensas⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠Confira todos os títulos do clube!---Vilto Reis (Instagram)Clube de Literatura Fantástica do Vilto Reis---Livros citados no episódio1º BlocoManuscrito achado num Bolso, de CortázarMrs. Dalloway, de Virginia WoolfDois Irmãos, de Milton Hatoum2º BlocoHamnet, de Maggie O'FarrellCampo Geral, de João Guimarães RosaAuto da Compadecida, de Ariano Suassuna3º BlocoDias de abandono, de Elena FerranteSenhor dos Anéis: A sociedade do anel, de J.R.R. TolkienPessoas normais, de Sally RooneyEncerramentoOração para desaparecer, de Socorro AcioliCabeça de Santo, de Socorro AcioliFlores para Algernon de Daniel KeyesReparação, de Ian McEwan

Rebecca Davis joins John Maytham each week to reflect on just how strange the news can be. From the most important to the very strange, John and Rebecca offer their view of what is happening in our world that makes it at times infuriating, at times inspirational but always fascinating. Presenter John Maytham is an actor and author-turned-talk radio veteran and seasoned journalist. His show serves a round-up of local and international news coupled with the latest in business, sport, traffic and weather. The host’s eclectic interests mean the program often surprises the audience with intriguing book reviews and inspiring interviews profiling artists. A daily highlight is Rapid Fire, just after 5:30pm. CapeTalk fans call in, to stump the presenter with their general knowledge questions. Another firm favourite is the humorous Thursday crossing with award-winning journalist Rebecca Davis, called “Plan B”. Thank you for listening to a podcast from Afternoon Drive with John Maytham Listen live on Primedia+ weekdays from 15:00 and 18:00 (SA Time) to Afternoon Drive with John Maytham broadcast on CapeTalk https://buff.ly/NnFM3Nk For more from the show go to https://buff.ly/BSFy4Cn or find all the catch-up podcasts here https://buff.ly/n8nWt4x Subscribe to the CapeTalk Daily and Weekly Newsletters https://buff.ly/sbvVZD5 Follow us on social media: CapeTalk on Facebook: https://www.facebook.com/CapeTalk CapeTalk on TikTok: https://www.tiktok.com/@capetalk CapeTalk on Instagram: https://www.instagram.com/ CapeTalk on X: https://x.com/CapeTalk CapeTalk on YouTube: https://www.youtube.com/@CapeTalk567 See omnystudio.com/listener for privacy information.

On this episode, Austin Waters, a friend of mine from high school, describes how he has had lots of experience with many different types of reading and writing. We discuss reading plays, how we read so many good books in high school, and how competition in reading can be detrimental.    Books mentioned in this episode:    What Betsy's reading:  West With Giraffes by Lynda Rutledge  There are Rivers in the Sky by Elif Shafak    Books Highlighted by Austin: Slaughterhouse Five by Kurt Vonnegut  Peter Pan by J.M. Barrie  In Cold Blood by Truman Capote Assata: an Autobiography by Assata Shakur  Everyone's a Aliebn When Ur a Aliebn Too by Jomny Sun There are No Children Here: The Story of Two Boys Growing Up in the Other America by Alex Kotlowitz  Flowers for Algernon by Daniel Keyes  The Things They Carried by Tim O'Brien Blue Highways: A Journey into America by William Least Heat-Moon Someone Like You by Roald Dahl My Cousin, My Gastroenterologist by Mark Leyner Never Home Alone: From Microbes to Millipedes, Camel Crickets, and Honeybees, the Natural History of Where We Live by Rob Dunn    All books available on my Bookshop.org episode page.   Other books mentioned in this episode: Educated by Tara Westover  Calvin and Hobbes by Bill Watterson & GB Trudeau  A Confederacy of Dunces by John Kennedy Toole Redwall by Brian Jacques  Great Expectations by Charles Dickens Animal Farm by George Orwell  The Hobbit by J.R.R. Tolkein The Two Towers by J.R.R. Tolkein  The Brief Wondrous Life of Oscar Wao by Junot Díaz  Decoded by Jay-Z  The Great Gatsby by F. Scott Fitzgerald  The Banshees of Inisherin by Martin McDonagh  Three Billboards Outside Ebbing, Missouri by Martin McDonagh  On Earth We're Briefly Gorgeous by Ocean Vuong  The Emperor of Gladness by Ocean Vuong  Lincoln in the Bardo by George Saunders  Yellowface by R.F. Kuang  The Epic of Gilgamesh trans. Andrew George  Nothing to Be Frightened Of by Julian Barnes  The Sense of an Ending by Julian Barnes  Jesus and John Wayne by Kristin Kobes Du Mez  Let This Radicalize You by Kelly Hayes & Mariame Kaba  Galapagos by Kurt Vonnegut  To Kill a Mockingbird by Harper Lee  The Joy Luck Club by Amy Tan  The Bean Trees by Barbara Kingsolver  Hamlet by William Shakespeare  The Tempest by William Shakespeare  Macbeth by William Shakespeare  The Odyssey by Homer  No More Dead Dogs by Gordon Korman  Old Man and the Sea by Ernest Hemingway  The Amazing Adventures of Kavalier & Clay by Michael Chabon Manhood for Amateurs by Michael Chabon  Jurassic Park by Michael Crichton  On The Calculation of Volume Book I by Solvej Balle, trans. Barbara J. Haveland  House of Fury by Evelio Rosero, trans. Victor Meadowcroft  On The Clock by Claire Baglin, trans. Jordan Stump

Get ready to have your mind blown by the most thought-provoking Science Fiction and Fantasy books out there! In this video, we'll dive into the most unforgettable SFF novels that will leave you questioning reality, morality, and the very fabric of society. From dystopian futures to magical realms, these books will haunt you long after you finish reading them. So, if you're ready to challenge your perspectives and explore the depths of human imagination, then join us on this journey into the most mind-blowing SFF books you won't stop thinking about!#FantasyForTheAges #BookRecommendations #fantasy #scifi #sciencefiction #fantasyfiction #Top10 #SFF #booktube #booktuberWant to purchase books/media mentioned in this video?Acts of Caine: https://t.ly/XCCY5Broken Earth Trilogy: https://t.ly/PPa-7Dune: https://t.ly/4_w_kEnder's Game: https://t.ly/Z62MeFirst Law Trilogy: https://t.ly/cPurjFlowers for Algernon: https://t.ly/cOenOFoundation: https://t.ly/IEoNhThe Handmaid's Tale: https://t.ly/ylLsZHyperion: https://t.ly/qhM-bThe Kingkiller Chronicle: https://t.ly/FOKzEThe MaddAddam Trilogy: https://t.ly/o5x2wThe Murderbot Diaries: https://t.ly/xvnyYPilgrims: https://t.ly/rnlMTSpeaker for the Dead: https://t.ly/ljH7AThe Three-Body Problem: https://t.ly/3OQVGTigana: https://t.ly/VVxzkThe Will of the Many: https://t.ly/O3i8iWays to connect with us:Support us on Patreon: https://www.patreon.com/FantasyForTheAges Follow Jim/Father on Goodreads: https://www.goodreads.com/user/show/13848336-jim-scriven Join us on Discord: https://discord.gg/jMWyVJ6qKk Follow us on "X": @Fantasy4theAges Follow us on Blue Sky: @fantasy4theages.bsky.socialFollow us on Instagram: fantasy_for_the_ages Follow us on Mastodon: @FantasyForTheAges@nerdculture.de Email us: FantasyForTheAges@gmail.com Check out our merch: https://www.newcreationsbyjen.com/collections/fantasyfortheagesJim's Microphone: Blue Yeti https://tinyurl.com/3shpvhb4 ————————————————————————————Music and video elements licensed under Envato Elements:https://elements.envato.com/

Introducing the Windows 11 Feature Tracker "From the 'I should have done this two years ago' files, the 'I have wasted my life' files, and the, 'great, I needed more work to do' files ... There is a need for this. So I made one. But it will evolve. Maybe into a web app/wiki/something else... like a Notion website?" - Paul Patch Tuesday brings a metric ton of new features - And what the tracker showed clearly Two seconds after posting the tracker, Microsoft changed the Copilot app yet again - proving the need for the tracker - And demonstrating why the Insider Program is so screwed up A hidden new Start menu in recent builds presents an interesting conundrum: How to handle something Microsoft has not announced? More Windows 11 Beta build for 23H2: File new tab/new window changes, Explorer context menu regression may be permanent Dev and Beta (24H2): Taskbar icon scaling is a blast from the past we all need desperately Intel is killing Unison app and service Like winter, Build is coming Build session catalog is live - mostly AI as expected. Paul and Richard are going Overview of the Windows Copilot Runtime (one year after it was announced), Windows Actions, standard Kayla Cinnamon talk on Windows productivity, using your own model with WCR, native app experiences(!), Arm64 app perf, etc. AI Final thoughts on Microsoft's 50th: Biggest accomplishment wasn't any tech, it was changing with the times. What it's best at: Democratizing tech for the commoners, an expansion on Jack Tramiel/Commodore's "computers for the masses, not the classes" schtick. And that is exactly what it is doing with AI right now Microsoft hosts a consumer AI event and announces a metric ton of new Copilot features We need a Copilot feature tracker. Copilot = every single feature other AIs have - Copilot Actions on the web, memory and personalization, Copilot Vision on mobile and Windows, AI-generated podcasts and Microsoft releases Copilot Search in Bing Is AI turning us all into Charly from Flowers for Algernon? AI is making us stupider! There are studies!! This is the argument against every single tech advance from the steam train to the ballpoint pen to this Microsoft's AI demo of vibe-coded Quake II highlights the problem nicely Sometimes it's the little things: AI recaps for book series in Kindle GitHub Copilot updated with Agent Mode, Cursor-style code overviews, more Xbox & gaming Microsoft announces new Xbox Games Showcase for June Edge Game Assist gets new features, support for new games GTA V and enhanced version for PC coming to Game Pass on April 15 - In addition to the previous Game Pass titles we discussed last week Good: Nintendo Switch 2 supports ray tracing and DLSS Bad: Nintendo delays Switch 2 to figure out the tariffs mess Tips and Picks Tip of the week: Programmers at Work App pick of the week: Apple Music RunAs Radio this week: Application Risk in Security Copilot with Ari Schorr Brown liquor pick of the week: The Heart Cut #02 These show notes have been truncated due to length. For the full show notes, visit https://twit.tv/shows/windows-weekly/episodes/927 Hosts: Leo Laporte, Paul Thurrott, and Richard Campbell

Introducing the Windows 11 Feature Tracker "From the 'I should have done this two years ago' files, the 'I have wasted my life' files, and the, 'great, I needed more work to do' files ... There is a need for this. So I made one. But it will evolve. Maybe into a web app/wiki/something else... like a Notion website?" - Paul Patch Tuesday brings a metric ton of new features - And what the tracker showed clearly Two seconds after posting the tracker, Microsoft changed the Copilot app yet again - proving the need for the tracker - And demonstrating why the Insider Program is so screwed up A hidden new Start menu in recent builds presents an interesting conundrum: How to handle something Microsoft has not announced? More Windows 11 Beta build for 23H2: File new tab/new window changes, Explorer context menu regression may be permanent Dev and Beta (24H2): Taskbar icon scaling is a blast from the past we all need desperately Intel is killing Unison app and service Like winter, Build is coming Build session catalog is live - mostly AI as expected. Paul and Richard are going Overview of the Windows Copilot Runtime (one year after it was announced), Windows Actions, standard Kayla Cinnamon talk on Windows productivity, using your own model with WCR, native app experiences(!), Arm64 app perf, etc. AI Final thoughts on Microsoft's 50th: Biggest accomplishment wasn't any tech, it was changing with the times. What it's best at: Democratizing tech for the commoners, an expansion on Jack Tramiel/Commodore's "computers for the masses, not the classes" schtick. And that is exactly what it is doing with AI right now Microsoft hosts a consumer AI event and announces a metric ton of new Copilot features We need a Copilot feature tracker. Copilot = every single feature other AIs have - Copilot Actions on the web, memory and personalization, Copilot Vision on mobile and Windows, AI-generated podcasts and Microsoft releases Copilot Search in Bing Is AI turning us all into Charly from Flowers for Algernon? AI is making us stupider! There are studies!! This is the argument against every single tech advance from the steam train to the ballpoint pen to this Microsoft's AI demo of vibe-coded Quake II highlights the problem nicely Sometimes it's the little things: AI recaps for book series in Kindle GitHub Copilot updated with Agent Mode, Cursor-style code overviews, more Xbox & gaming Microsoft announces new Xbox Games Showcase for June Edge Game Assist gets new features, support for new games GTA V and enhanced version for PC coming to Game Pass on April 15 - In addition to the previous Game Pass titles we discussed last week Good: Nintendo Switch 2 supports ray tracing and DLSS Bad: Nintendo delays Switch 2 to figure out the tariffs mess Tips and Picks Tip of the week: Programmers at Work App pick of the week: Apple Music RunAs Radio this week: Application Risk in Security Copilot with Ari Schorr Brown liquor pick of the week: The Heart Cut #02 These show notes have been truncated due to length. For the full show notes, visit https://twit.tv/shows/windows-weekly/episodes/927 Hosts: Leo Laporte, Paul Thurrott, and Richard Campbell

Introducing the Windows 11 Feature Tracker "From the 'I should have done this two years ago' files, the 'I have wasted my life' files, and the, 'great, I needed more work to do' files ... There is a need for this. So I made one. But it will evolve. Maybe into a web app/wiki/something else... like a Notion website?" - Paul Patch Tuesday brings a metric ton of new features - And what the tracker showed clearly Two seconds after posting the tracker, Microsoft changed the Copilot app yet again - proving the need for the tracker - And demonstrating why the Insider Program is so screwed up A hidden new Start menu in recent builds presents an interesting conundrum: How to handle something Microsoft has not announced? More Windows 11 Beta build for 23H2: File new tab/new window changes, Explorer context menu regression may be permanent Dev and Beta (24H2): Taskbar icon scaling is a blast from the past we all need desperately Intel is killing Unison app and service Like winter, Build is coming Build session catalog is live - mostly AI as expected. Paul and Richard are going Overview of the Windows Copilot Runtime (one year after it was announced), Windows Actions, standard Kayla Cinnamon talk on Windows productivity, using your own model with WCR, native app experiences(!), Arm64 app perf, etc. AI Final thoughts on Microsoft's 50th: Biggest accomplishment wasn't any tech, it was changing with the times. What it's best at: Democratizing tech for the commoners, an expansion on Jack Tramiel/Commodore's "computers for the masses, not the classes" schtick. And that is exactly what it is doing with AI right now Microsoft hosts a consumer AI event and announces a metric ton of new Copilot features We need a Copilot feature tracker. Copilot = every single feature other AIs have - Copilot Actions on the web, memory and personalization, Copilot Vision on mobile and Windows, AI-generated podcasts and Microsoft releases Copilot Search in Bing Is AI turning us all into Charly from Flowers for Algernon? AI is making us stupider! There are studies!! This is the argument against every single tech advance from the steam train to the ballpoint pen to this Microsoft's AI demo of vibe-coded Quake II highlights the problem nicely Sometimes it's the little things: AI recaps for book series in Kindle GitHub Copilot updated with Agent Mode, Cursor-style code overviews, more Xbox & gaming Microsoft announces new Xbox Games Showcase for June Edge Game Assist gets new features, support for new games GTA V and enhanced version for PC coming to Game Pass on April 15 - In addition to the previous Game Pass titles we discussed last week Good: Nintendo Switch 2 supports ray tracing and DLSS Bad: Nintendo delays Switch 2 to figure out the tariffs mess Tips and Picks Tip of the week: Programmers at Work App pick of the week: Apple Music RunAs Radio this week: Application Risk in Security Copilot with Ari Schorr Brown liquor pick of the week: The Heart Cut #02 These show notes have been truncated due to length. For the full show notes, visit https://twit.tv/shows/windows-weekly/episodes/927 Hosts: Leo Laporte, Paul Thurrott, and Richard Campbell

Introducing the Windows 11 Feature Tracker "From the 'I should have done this two years ago' files, the 'I have wasted my life' files, and the, 'great, I needed more work to do' files ... There is a need for this. So I made one. But it will evolve. Maybe into a web app/wiki/something else... like a Notion website?" - Paul Patch Tuesday brings a metric ton of new features - And what the tracker showed clearly Two seconds after posting the tracker, Microsoft changed the Copilot app yet again - proving the need for the tracker - And demonstrating why the Insider Program is so screwed up A hidden new Start menu in recent builds presents an interesting conundrum: How to handle something Microsoft has not announced? More Windows 11 Beta build for 23H2: File new tab/new window changes, Explorer context menu regression may be permanent Dev and Beta (24H2): Taskbar icon scaling is a blast from the past we all need desperately Intel is killing Unison app and service Like winter, Build is coming Build session catalog is live - mostly AI as expected. Paul and Richard are going Overview of the Windows Copilot Runtime (one year after it was announced), Windows Actions, standard Kayla Cinnamon talk on Windows productivity, using your own model with WCR, native app experiences(!), Arm64 app perf, etc. AI Final thoughts on Microsoft's 50th: Biggest accomplishment wasn't any tech, it was changing with the times. What it's best at: Democratizing tech for the commoners, an expansion on Jack Tramiel/Commodore's "computers for the masses, not the classes" schtick. And that is exactly what it is doing with AI right now Microsoft hosts a consumer AI event and announces a metric ton of new Copilot features We need a Copilot feature tracker. Copilot = every single feature other AIs have - Copilot Actions on the web, memory and personalization, Copilot Vision on mobile and Windows, AI-generated podcasts and Microsoft releases Copilot Search in Bing Is AI turning us all into Charly from Flowers for Algernon? AI is making us stupider! There are studies!! This is the argument against every single tech advance from the steam train to the ballpoint pen to this Microsoft's AI demo of vibe-coded Quake II highlights the problem nicely Sometimes it's the little things: AI recaps for book series in Kindle GitHub Copilot updated with Agent Mode, Cursor-style code overviews, more Xbox & gaming Microsoft announces new Xbox Games Showcase for June Edge Game Assist gets new features, support for new games GTA V and enhanced version for PC coming to Game Pass on April 15 - In addition to the previous Game Pass titles we discussed last week Good: Nintendo Switch 2 supports ray tracing and DLSS Bad: Nintendo delays Switch 2 to figure out the tariffs mess Tips and Picks Tip of the week: Programmers at Work App pick of the week: Apple Music RunAs Radio this week: Application Risk in Security Copilot with Ari Schorr Brown liquor pick of the week: The Heart Cut #02 These show notes have been truncated due to length. For the full show notes, visit https://twit.tv/shows/windows-weekly/episodes/927 Hosts: Leo Laporte, Paul Thurrott, and Richard Campbell

A huge THANK YOU to our Patrons: Michael Devries, irvin ruiz, Hoshi 127, Nora Klimek and miguel, who are supporting us on the “credited” level. www.patreon.com/bdckrThanks to the following for providing fodder for our Q&A:@HazeKasaki (BN Doomsday)@zoomingken (Blackest Night Rankings)Public Mobile referral code: VPM35ZRecommendations: Flying in Place by Susan PalwickBriar Rose by Jane YolenFlowers for Algernon by Daniel Keyes

Introducing the Windows 11 Feature Tracker "From the 'I should have done this two years ago' files, the 'I have wasted my life' files, and the, 'great, I needed more work to do' files ... There is a need for this. So I made one. But it will evolve. Maybe into a web app/wiki/something else... like a Notion website?" - Paul Patch Tuesday brings a metric ton of new features - And what the tracker showed clearly Two seconds after posting the tracker, Microsoft changed the Copilot app yet again - proving the need for the tracker - And demonstrating why the Insider Program is so screwed up A hidden new Start menu in recent builds presents an interesting conundrum: How to handle something Microsoft has not announced? More Windows 11 Beta build for 23H2: File new tab/new window changes, Explorer context menu regression may be permanent Dev and Beta (24H2): Taskbar icon scaling is a blast from the past we all need desperately Intel is killing Unison app and service Like winter, Build is coming Build session catalog is live - mostly AI as expected. Paul and Richard are going Overview of the Windows Copilot Runtime (one year after it was announced), Windows Actions, standard Kayla Cinnamon talk on Windows productivity, using your own model with WCR, native app experiences(!), Arm64 app perf, etc. AI Final thoughts on Microsoft's 50th: Biggest accomplishment wasn't any tech, it was changing with the times. What it's best at: Democratizing tech for the commoners, an expansion on Jack Tramiel/Commodore's "computers for the masses, not the classes" schtick. And that is exactly what it is doing with AI right now Microsoft hosts a consumer AI event and announces a metric ton of new Copilot features We need a Copilot feature tracker. Copilot = every single feature other AIs have - Copilot Actions on the web, memory and personalization, Copilot Vision on mobile and Windows, AI-generated podcasts and Microsoft releases Copilot Search in Bing Is AI turning us all into Charly from Flowers for Algernon? AI is making us stupider! There are studies!! This is the argument against every single tech advance from the steam train to the ballpoint pen to this Microsoft's AI demo of vibe-coded Quake II highlights the problem nicely Sometimes it's the little things: AI recaps for book series in Kindle GitHub Copilot updated with Agent Mode, Cursor-style code overviews, more Xbox & gaming Microsoft announces new Xbox Games Showcase for June Edge Game Assist gets new features, support for new games GTA V and enhanced version for PC coming to Game Pass on April 15 - In addition to the previous Game Pass titles we discussed last week Good: Nintendo Switch 2 supports ray tracing and DLSS Bad: Nintendo delays Switch 2 to figure out the tariffs mess Tips and Picks Tip of the week: Programmers at Work App pick of the week: Apple Music RunAs Radio this week: Application Risk in Security Copilot with Ari Schorr Brown liquor pick of the week: The Heart Cut #02 These show notes have been truncated due to length. For the full show notes, visit https://twit.tv/shows/windows-weekly/episodes/927 Hosts: Leo Laporte, Paul Thurrott, and Richard Campbell

Introducing the Windows 11 Feature Tracker "From the 'I should have done this two years ago' files, the 'I have wasted my life' files, and the, 'great, I needed more work to do' files ... There is a need for this. So I made one. But it will evolve. Maybe into a web app/wiki/something else... like a Notion website?" - Paul Patch Tuesday brings a metric ton of new features - And what the tracker showed clearly Two seconds after posting the tracker, Microsoft changed the Copilot app yet again - proving the need for the tracker - And demonstrating why the Insider Program is so screwed up A hidden new Start menu in recent builds presents an interesting conundrum: How to handle something Microsoft has not announced? More Windows 11 Beta build for 23H2: File new tab/new window changes, Explorer context menu regression may be permanent Dev and Beta (24H2): Taskbar icon scaling is a blast from the past we all need desperately Intel is killing Unison app and service Like winter, Build is coming Build session catalog is live - mostly AI as expected. Paul and Richard are going Overview of the Windows Copilot Runtime (one year after it was announced), Windows Actions, standard Kayla Cinnamon talk on Windows productivity, using your own model with WCR, native app experiences(!), Arm64 app perf, etc. AI Final thoughts on Microsoft's 50th: Biggest accomplishment wasn't any tech, it was changing with the times. What it's best at: Democratizing tech for the commoners, an expansion on Jack Tramiel/Commodore's "computers for the masses, not the classes" schtick. And that is exactly what it is doing with AI right now Microsoft hosts a consumer AI event and announces a metric ton of new Copilot features We need a Copilot feature tracker. Copilot = every single feature other AIs have - Copilot Actions on the web, memory and personalization, Copilot Vision on mobile and Windows, AI-generated podcasts and Microsoft releases Copilot Search in Bing Is AI turning us all into Charly from Flowers for Algernon? AI is making us stupider! There are studies!! This is the argument against every single tech advance from the steam train to the ballpoint pen to this Microsoft's AI demo of vibe-coded Quake II highlights the problem nicely Sometimes it's the little things: AI recaps for book series in Kindle GitHub Copilot updated with Agent Mode, Cursor-style code overviews, more Xbox & gaming Microsoft announces new Xbox Games Showcase for June Edge Game Assist gets new features, support for new games GTA V and enhanced version for PC coming to Game Pass on April 15 - In addition to the previous Game Pass titles we discussed last week Good: Nintendo Switch 2 supports ray tracing and DLSS Bad: Nintendo delays Switch 2 to figure out the tariffs mess Tips and Picks Tip of the week: Programmers at Work App pick of the week: Apple Music RunAs Radio this week: Application Risk in Security Copilot with Ari Schorr Brown liquor pick of the week: The Heart Cut #02 These show notes have been truncated due to length. For the full show notes, visit https://twit.tv/shows/windows-weekly/episodes/927 Hosts: Leo Laporte, Paul Thurrott, and Richard Campbell

Lou DiVizio shares some headlines from across the state including an update on the measles outbreak in southeastern New Mexico.Then, Albuquerque Journal reporter Algernon D'Ammassa updates us on the investigation into last month's mass shooting in Las Cruces that killed three teenagers and wounded more than a dozen other people. Executive Producer Jeff Proctor asks D'Ammassa how the people of Las Cruces and its leaders are doing following the most public, jarring act of violence seen in the city in 35 years.Host: Lou DiVizioCorrespondent: Jeff ProctorGuest: Algernon D'Ammassa, Southern New Mexico Correspondent for the Albuquerque JournalFor More Information: Algernon D'Ammassa - The Albuquerque Journal

I'm reading Ted Gioia's "Immersive Humanities Course," 52 weeks of World Classics. We continue with the Odyssey this week. I'm joined this week by my son Jack Drury. Jack is pursuing a Masters in Classics at the University of Chicago, so we are on familiar ground for him here.I'm a beginner at reading the classics, but I've decided to just "crack the book" and get started. Here are a few of my key take-aways from this week:What will I take from this week? Let's see:A deeper understanding of Greek mythology. I have a copy of Bullfinch's Mythology on my bookshelf and will probably be dipping in and out of it soon. A better view of the ancient world, its customs and habits of life. I know it's fiction, but the way the poem describes the interactions between people of different classes, between men and women, and between city-states is eye-opening. I'm tempted to carry my modern worldview into these stories, and to find fault with various people. Instead, I really have to suspend my judgement to understand what is going on and how it compares to what I already know.A richer view of the Bible, believe it or not. I've read the Bible through about ten times (maybe more). Reading other ancient works ADDS to my understanding of the world the ancient Hebrews lived in. It's one thing to understand the Old Testament, but so much richer to understand how very different the Hebrews' struggles with God were compared to the Greeks' encounters with their array of gods and goddesses.Finally, my last take-away is one that deserves its own paragraph. I am angry, honestly, that every bit of this kind of literature was erased from my education. Who did that? Why? Who decided that Flowers for Algernon was worth my attention but Odysseus and Telemachus and Pallas Athena and Penelope weren't?Jack and I also have a long discussion about the heart of the Odyssey. What is it truly about? Is it a homecoming, or a story of exiles, or a model for suffering? How can we as 21st-century Americans relate to these ancient Greeks?This is a year-long challenge! Join me next week as we head to eastward and read Confucius.CONNECTTo read more of my writing, visit my Substack - https://www.cheryldrury.substack.com.Follow me on Instagram - https://www.instagram.com/cldrury/ LISTENSpotify - https://open.spotify.com/show/5GpySInw1e8IqNQvXow7Lv?si=9ebd5508daa245bdApple Podcasts - https://podcasts.apple.com/us/podcast/crack-the-book/id1749793321 Captivate - https://crackthebook.captivate.fm

Vance is forced to endure a painful memory; the group's minder gives them a new mission; Mum comes across some very interesting information.Join us on Discord!Follow us on Twitter at @maeltopiaWant additional perks like extra lore, stories, art, and more? Check out our Patreon at: www.patreon.com/maeltopiaWant unique art and animations to go along with your Maeltopia episodes? Check out our Youtube channel at: https://www.youtube.com/channel/UCmmrdXEvkEPfQvCKT4pha4QWant to learn more about the world of Maeltopia? Check out our website!Be sure to like, comment, rate and review us on Apple Podcasts or your favorite podcast platform! We appreciate your support!Credits:Written by Steven AnzaloneEdited by Walker KornfeldSound mastering by Steven J. Anzalone--Marius voiced by Steven AnzaloneMerrick voiced by Steven AnzaloneMinder voiced by Aubrey AkersMum voice by Steven AnzaloneVance voiced by Steven Anzalone (voice mask)Felix Yarrows played by Steven AnzaloneGretchen voiced by Steven Anzalone(voice mask)Algernon viced by Steven ZivicHelena voiced by Kelly BairAngelo voiced by Steven Anzalone--The Obscuary intro music was created by Steven J. AnzaloneMusic and Sound effects are licensed from third party providers including Envato, Epidemic Sound, Artlist, Soundstripe, Music Vine, Soundcrate, Melodie, Storyblocks, Snapmuse, Slipstream and Pond 5 Hosted on Acast. See acast.com/privacy for more information.

The various cabals witness the insertion of the new puzzle piece; Felix tries to get back to the mansion.Join us on Discord!Follow us on Twitter at @maeltopiaWant additional perks like extra lore, stories, art, and more? Check out our Patreon at: www.patreon.com/maeltopiaWant unique art and animations to go along with your Maeltopia episodes? Check out our Youtube channel at: https://www.youtube.com/channel/UCmmrdXEvkEPfQvCKT4pha4QWant to learn more about the world of Maeltopia? Check out our website!Be sure to like, comment, rate and review us on Apple Podcasts or your favorite podcast platform! We appreciate your support!Credits:Written by Steven AnzaloneEdited by Walker KornfeldSound mastering by Steven J. Anzalone--Felix Yarrows played by Steven AnzaloneAnastasia voiced by Aubrey AkersEsme voiced by Aubrey AkersArkady voiced by Sam StarkThe Hare voiced by Sam StarkGretchen voiced by Steven Anzalone(modified)Algernon viced by Steven ZivicDenise voiced by Jess Van HoveHelena voiced by Kelly BairMad Man 2 voiced by Matt Van HoveMad Man 3 voiced by Matt Van Hove--The Obscuary intro music was created by Steven J. AnzaloneMusic and Sound effects are licensed from third party providers including Envato, Epidemic Sound, Artlist, Soundstripe, Music Vine, Soundcrate, Melodie, Storyblocks, Snapmuse, Slipstream and Pond 5 Hosted on Acast. See acast.com/privacy for more information.

Only 3 percent of people brave up and put pen to paper and write a book. It takes aninternal desire to push yourself to block off time and activities so you can take a book tomarket. The authors in this episode have used their drive to create breakthroughs forothers as part of their inspiration to get their books to market. Your host, Deb, asks theright questions for you to learn what to do and what not to do when writing a book that'smeant to impact in a large way.Books by our guests:“Insights and Inspirations: 300 Journal Prompts to Cultivate Joy, Mindfulness andGratitude” by Rachel Collins“The Keys To Success Are All In Your Mind” & “How to Awaken Eternal Youth” by PeterKellyYvonne Silver https://yvonnesilver.com/Cathy Holt https://catherine-holt.comRachel Collins https://passionpurpose.todayPeter Kelly https://hypnotic-energetic-healing.com“Words, Women and Wisdom” by Yvonne E. L. Silver“Outspoken Women: Finding Our Voices, Leading Change” by Cathy HoltBooks mentioned by the guests:Anne of Green Gables by Lucy Maude MontgomeryFlowers for Algernon by Daniel KeyesThe Sky's the Limit by Wayne DyerLiving in the Light by Shakti Gawain

Felix is kidnapped; Vance has an eye opening encounter with Algernon; and Helena has a tough discussion with Mum.Join us on Discord!Follow us on Twitter at @maeltopiaWant additional perks like extra lore, stories, art, and more? Check out our Patreon at: www.patreon.com/maeltopiaWant unique art and animations to go along with your Maeltopia episodes? Check out our Youtube channel at: https://www.youtube.com/channel/UCmmrdXEvkEPfQvCKT4pha4QWant to learn more about the world of Maeltopia? Check out our website!Be sure to like, comment, rate and review us on Apple Podcasts or your favorite podcast platform! We appreciate your support!Credits:Written by Steven AnzaloneEdited by Walker KornfeldSound mastering by Steven J. Anzalone--Felix Yarrows played by Steven AnzaloneAnastasia voiced by Aubrey AkersArkady voiced by Sam StarkThe Hare voiced by Sam StarkGretchen voiced by Steven Anzalone(modified)Algernon viced by Steven ZivicLuna by Jesse Van HoveHelena voiced by Kelly BairLuna's sister voiced by Steven Anzalone (modified)--The Obscuary intro music was created by Steven J. AnzaloneMusic and Sound effects are licensed from third party providers including Envato, Epidemic Sound, Artlist, Soundstripe, Music Vine, Soundcrate, Melodie, Storyblocks, Snapmuse, Slipstream and Pond 5 Hosted on Acast. See acast.com/privacy for more information.

Flowers for Algernon is a book I believe everyone should read. In this episode, I discuss the major themes of the novel and why it became my favorite read of 2024. With Dr. Martin Jacobsen's help, we examine the ethical and emotional questions the book raises and offer strategies for navigating its deeper ideas. If you're looking for a meaningful story that will leave a lasting impression, this episode is for you.Send Me a Text Message with Your QuestionsIMPORTANT LINKS:

Na discussão do último título do Clube de Leitura 30:MIN 2024, Arthur Marchetto, Cecilia Garcia Marcon e AJ Oliveira conversam sobre "Flores para Algernon", de Daniel Keyes, e convidam Luisa Geisler, escritora e tradutora do livro, para o papo. Acompanhamos a história de Charlie, um menino neurodivergente, tornando-se a cobaia de um experimento científico focado em criar gênios com alto QI. No episódio, eles discutem sobre a forma de escrita do livro, das definições de inteligência e neurodivergência e da retratação das personagens femininas do livro. Já leu, curtiu? Ainda não? Aperta o play e conta pra gente! -- Links ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠Apoie o 30:MIN⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠Siga a gente nas redes⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠Já apoia? Acesse suas recompensas⁠⁠⁠⁠

Join me on an epic adventure through the world of fantasy and science fiction as we explore AMAZING reads from A to Z! From classic novels to modern bestsellers, I'm sharing my list of some of the most captivating stories that will transport you to new worlds, introduce you to unforgettable characters, and ignite your imagination. Whether you're a fan of magic, space exploration, or dystopian futures, this episode is for you! Get ready to discover new authors, series, and genres that will keep you reading all night long. So, sit back, relax, and let's start our journey through the infinite possibilities of fantasy and science fiction! #FantasyForTheAges #readingrecommendations #scifi #sciencefiction #Fantasy #Grimdark #TBR #EpicFantasy #SFF #booktube #booktuber Want to purchase books mentioned in this episode? All Systems Red: https://t.ly/clNRv All the Weyrs of Pern: https://t.ly/N53p9 The Black Company: https://t.ly/QMwqB The Blade Itself: https://t.ly/LSDn2 The Caves of Steel: https://t.ly/uQgGq The Color of Magic: https://t.ly/0joes The Dragonbone Chair: https://t.ly/p02xZ Dune: https://t.ly/4_w_k Empire of the Vampire: https://t.ly/VPeGO Ex-Heroes: https://t.ly/XuifA The Eye of the World: https://t.ly/V-eqm Fated: https://t.ly/h3ku0 Flowers for Algernon: https://t.ly/cOenO The Gunslinger: https://t.ly/U7LP2 Gwendy's Button Box: https://t.ly/Vhn1p Hell Divers: https://t.ly/7DCoU Hyperion: https://t.ly/VYqkP In the Lives of Puppets: https://t.ly/y8J2b Interview with the Vampire: https://t.ly/oddIu Jake the Dragon Talker: https://t.ly/fMu9F Jonathan Strange & Mr. Norrell: https://t.ly/8MoJB The Kaiju Preservation Society: https://t.ly/BGopw The King Beyond the Gate: https://t.ly/wspat Leviathan Wakes: https://t.ly/muEYa The Lies of Locke Lamora: https://t.ly/1UV3h The Man in the High Castle: https://t.ly/wVUUm The Martian: https://t.ly/9Ty2E The Name of the Wind: https://t.ly/ndJbg Neuromancer: https://t.ly/lN79I Old Man's War: https://t.ly/Q3uJu The Once and Future King: https://t.ly/veIkR Perdido Street Station: https://t.ly/BMosB The Poppy War: https://t.ly/d6CIF Quarantine: https://t.ly/TpmLC The Queen of the Damned: https://t.ly/R33Rx Red Mars: https://t.ly/Qhd1H Red Rising: https://t.ly/yIHdF Snow Crash: https://t.ly/auBgE The Stand: https://t.ly/UG_4m Tigana: https://t.ly/VVxzk A Time of Dread: https://t.ly/mjcOX Under the Dome: https://t.ly/unbVA Uprooted: https://t.ly/08qm3 Valor: https://t.ly/2PagY Vicious: https://t.ly/HCmTx A Wizard of Earthsea: https://t.ly/pJ922 World War Z: https://t.ly/WYhtl Xanth: https://t.ly/eO4w7 Yumi and the Nightmare Painter: https://t.ly/_SE6e The Year of the Flood: https://t.ly/Y3V1W Zombie Fallout: https://t.ly/oLnaQ Zone One: https://t.ly/6Y9sK Ways to connect with us: Support us on Patreon: https://www.patreon.com/FantasyForTheAges Follow Jim/Father on Goodreads: https://www.goodreads.com/user/show/13848336-jim-scriven Join us on Discord: https://discord.gg/jMWyVJ6qKk Follow us on "X": @Fantasy4theAges Follow us on Blue Sky: @fantasy4theages.bsky.social Follow us on Instagram: fantasy_for_the_ages Follow us on Mastodon: @FantasyForTheAges@nerdculture.de Email us: FantasyForTheAges@gmail.com Check out our merch: https://www.newcreationsbyjen.com/collections/fantasyfortheages Jim's Microphone: Blue Yeti https://tinyurl.com/3shpvhb4 ———————————————————————————— Music and video elements licensed under Envato Elements: https://elements.envato.com/

No penúltimo episódio do Clube de Leitura 30:MIN 2024, Arthur Marchetto, Cecilia Garcia Marcon, Vilto Reis e AJ Oliveira discutem o livro "Bem-vindos ao paraíso", de Nicole Dennis-Benn. Eles falaram sobre o patoá jamaicano, a construção de línguas crioulas, a estrutura do livro e os desenvolvimentos e lutas dos personagens. Aperta o play, vem com a gente e não esqueça do próximo livro do clube: "Flores para Algernon", de Daniel Keyes. -- Links ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠Apoie o 30:MIN⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠Siga a gente nas redes⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠Já apoia? Acesse suas recompensas⁠⁠⁠⁠

After a political realignment, I explore the possibility of accepting advertising dollars from a nootropics company. But a brain enhancement pill accident involving my dog has me concerned about a "Flowers for Algernon" type situation.

The short story by Daniel Keyes, “Flowers for Algernon” became so popular it was later turned into a full novel, and then eventually made its way to movie screens. The short story was written in 1958 and first published in the April 1959 issue of The Magazine of Fantasy & Science Fiction, and was so loved that it won the Hugo Award for Best Short Story in 1960.SOURCES AND REFERENCES FROM THE EPISODE…BOOK: “The Science Fiction Hall of Fame: Volume One, 1929-1964”, https://amzn.to/3SePNlhWeird Darkness theme by Alibi Music Library. = = = = =(Over time links seen above may become invalid, disappear, or have different content. I always make sure to give authors credit for the material I use whenever possible. If I somehow overlooked doing so for a story, or if a credit is incorrect, please let me know and I will rectify it in these show notes immediately. Some links included above may benefit me financially through qualifying purchases.)= = = = ="I have come into the world as a light, so that no one who believes in me should stay in darkness." — John 12:46= = = = =WeirdDarkness® is a registered trademark. Copyright ©2024, Weird Darkness.= = = = =Originally aired: October 12, 2023CUSTOM LANDING PAGE: https://weirddarkness.com/FlowersForAlgernon

The CAN Crew (and Algernon) consider summoning Steve the Cleve. This is the penultimate episode of this arc. The ultimate episode of this arc will come out on Friday. Probs lots of announcements in that one. Stay frosty. Support the show on Patreon. Buy some merch at the Contention General Store. Follow along on Instagram, Twitter, and Facebook. Find other listeners on Discord and Reddit. Soundtrack by WAAAVV. Wolf the Dog played "My Life is Great and It's All My Fault" by Altar Girl.

Algernon Cornelius and CLYDE join us to talk about their new collaborative effort "STICK A FORK IN IT". The UK-based artists break down their writing and beat making process and discuss some of the inspiration behind the album. Then we talk about their album pick for this episode - Injury Reserve's "By the Time I Get to Phoenix". Stream and purchase "STICK A FORK IN IT" here: https://algernoncornelius.bandcamp.com/album/stick-a-fork-in-it

Esme and Algernon have a frank conversation; Zaabock performs his assessment of the Inwood Puzzle; Gretchen and Helena speak with Dr. Buchanon.Join us on Discord!Follow us on Twitter at @maeltopiaWant additional perks like extra lore, stories, art, and more? Check out our Patreon at: www.patreon.com/maeltopiaWant unique art and animations to go along with your Maeltopia episodes? Check out our Youtube channel at: https://www.youtube.com/channel/UCmmrdXEvkEPfQvCKT4pha4QWant to learn more about the world of Maeltopia? Check out our website!Be sure to like, comment, rate and review us on Apple Podcasts or your favorite podcast platform! We appreciate your support!Credits:Written by Steven AnzaloneEdited by Walker KornfeldSound mastering by Steven J. Anzalone--Helena Vespertine played by Kelly BairMarvin Mum played by Steven AnzaloneFelix Yarrows played by Steven AnzaloneEsme voiced by Aubrey AkersAlgernon voiced by Steven ZivicMiles voiced by Steven AnzaloneGretchen voiced by Steven Anzalone(modified)Vance voice by Steven Anzalone (Modified)--The Obscuary intro music was created by Steven J. AnzaloneMusic and Sound effects are licensed from third party providers including Envato, Epidemic Sound, Artlist, Soundstripe, Music Vine, Soundcrate, Melodie, Storyblocks, Snapmuse, Slipstream and Pond 5 Hosted on Acast. See acast.com/privacy for more information.

A people-centered press corps would spell out the meaning of economic “indicators” in relation to where we want to go as a society that has yet to address deep historical and structural harms.

Cal vs. Algernon. CANcakes vs. The Last Waffles. Video vs. Audio. But something just doesn't add up. Support the show on Patreon. Buy some merch at the Contention General Store. Follow along on Instagram, Twitter, and Facebook. Find other listeners on Discord and Reddit. Soundtrack by WAAAVV. Wolf played "My Life is Great and It's All My Fault" by Altar Girl.