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Brainspotting lokalizuje punkty w polu widzenia klienta, które pomagają uzyskać dostęp do nieprzetworzonego urazu w mózgu podkorowym. Brainspotting (BSP) został odkryty w 2003 roku. Dr David Grand odkrył, że „to, gdzie patrzysz, wpływa na to, jak się czujesz”. To aktywność mózgu, zwłaszcza w mózgu podkorowym, która organizuje się wokół tej pozycji oka. Na czym dokładnie polega brainspotting? Jak się nim pracuje? Rozmawiamy z dr. Roby Abeles. Brainspotting jest skuteczny w przypadku szerokiej gamy stanów emocjonalnych i somatycznych, szczególnie w sytuacjach związanych z traumą, pomagając zidentyfikować i wyleczyć ukryty uraz, który przyczynia się do lęku, depresji i innych stanów behawioralnych.Dr Roby Abeles to zatwierdzona przez PACFA międzynarodowa superwizorka, zapewniająca superwizję w obszarze traumy w różnych dziedzinach terapeutycznych. Specjalizuje się w leczeniu traumy i uzależnień. Nadzoruje sesje specjalistów zdrowia psychicznego indywidualnie lub grupowo. Praktyczka brainspottingu i międzynarodowa trenerka BSP. Konsultantka i praktyczka EMDR. Ekspertka skoncentrowana na całej osobie, ucieleśniona i zintegrowana w leczeniu i doradztwie w zakresie rozwiązywania traumy, uzależnień i zaburzeń nastroju.Terapie, które dr Abeles stosuje z klientami i superwizuje innych terapeutów, obejmują: brainspotting, Somatic Experiencing, EMDR, terapię stanu ego, archetypy jungowskie, terapię narracyjną i program MATES Resourcing – w celu opanowania regulacji emocjonalnej i zbudowania umiejętności tolerancji emocjonalnej i odporności.Odcinek został nagrany w języku angielskim. Wersję z polskimi napisami możesz obejrzeć na platformie YouTube.ENG:Brainspotting locates points in the client's field of vision that help access unprocessed trauma in the subcortical brain. Brainspotting (BSP) was discovered in 2003 by David Grand, Ph.D. Grand discovered that “Where you look affects how you feel.” It is the brain activity, especially in the subcortical brain, that organizes around that eye position.Brainspotting is effective for a wide range of emotional and somatic states. Brainspotting is particularly effective in trauma-related situations, helping to identify and heal the underlying trauma that contributes to anxiety, depression, and other behavioral states.What exactly is brainspotting? How does it work?Dr Roby Abeles is PACFA Approved Supervisor, providing Trauma-Informed Supervision in a variety of areas. Specialised is Trauma & Addiction Recovery. Supervises sessions to mental health professionals individually or in groups. Brainspotting practitioner and International BSP Trainer. Expert, Whole-Person Focused, Embodied and Integrated Treatment and Guidance for the Resolution of Trauma, Addictions, and Mood Disorders. Therapies she uses with clients and Supervise other therapists in include: Brainspotting, Somatic Experiencing, EMDR, Ego State Therapy, Jungian Archetypes, Narrative Therapy, and the MATES Resourcing Program - To Master Emotional Regulation and Build Emotional Tolerance and Resilience Skills.Podcastu „Osobiste rozmowy holistyczne” możesz posłuchać na platformach Spotify, Apple Podcasts oraz YouTube.
Episode: October 2024, with Special Guest Dr. Kate Galluzzi on Utilization of Telemedicine to Supervise Medical Students in the PALTC Setting Host: Karl Steinberg, MD, HMDC, CMD Guest(s): Katherine E. Galluzzi, DO, CMD, FACOFP *dist.*; Barbara Resnick, PhD, CRNP (Co-Editor-in-Chief, JAMDA) In This Episode: In this episode, host Dr. Karl Steinberg, MD, CMD, and co-editor-in-chief Dr. Barb Resnick, PhD, CRNP, will talk with Dr. Galluzzi about her focus on utilization of telemedicine to supervise medical students in the post-acute and long-term care setting. In addition to Dr. Galluzzi's paper, Drs. Steinberg and Resnick will review three additional articles. Articles Referenced: Utilization of Telemedicine to Supervise Medical Students in the Post-Acute/Long-Term Care Setting Understanding the Perspectives of Key Stakeholders toward Medicare's Home Health Value-Based Purchasing (HHVBP) in the US Paramedic-Assisted Community Evaluation After Discharge: The PACED Intervention A Cluster Randomized Trial: Mixed Methods Comparison of 2 Approaches to Promote Nonpharmacologic, Resident-Centered Dementia Care in Nursing Homes Date Recorded: October 21, 2024 Available Credit: The American Board of Post-Acute and Long-Term Care Medicine (ABPLM) issues CMD credits for select PALTtalk podcast episodes as follows: Claim CMD Credit
Time Stamps: 00:00:00 Community Guest Intros 00:05:00 BREAKING NEWS Halo Series Developer 343 Industries Will Only Supervise Development of Future Titles 00:40:00 Flintlock Dawn Of Siege Releases THIS Week Into Xbox Game Pass & Its Looking REALLY Good! A Solid Single Player Game For The Summer! 01:00:00 Forza Horizon 5 Surpasses 40M Player Since Launch With Continued DLC, What A Triumph For Playground Games!! 01:25:00 Panel Outros and Special Message to the Community! --- Support this podcast: https://podcasters.spotify.com/pod/show/craig-ravitch/support
Join host RS2 as he reflects and reevaluates in the good times. See if he can make the grade as he finds ways to stay ready yet enjoy the now.
Join host RS2 as he reflects and reevaluates in the good times. See if he can make the grade as he finds ways to stay ready yet enjoy the now.
Episode Date: Monday, June 3rdWelcome to Anesthesia Deconstructed!In this episode, we cover:Segment 1: Pre-CRNA Market UpdateImpact of late-stage capitalism on mentorship and professional development.Feedback from current nurse anesthesia residents/students.Questioning “Guaranteed Success” and the high cost of prep programs.Segment 2: Key Legal UpdatesSouth Carolina and Maryland Associations' successes in preventing restrictive rules.TANA's loss of the term “anesthesiology.”DC's HORA Act removing collaboration requirements for CRNAs.Segment 3: Arizona Board of Nursing UpdateNew authority for CRNAs to supervise other professionals Discussion on ensuring competence and the debate around supervision and education.Stay informed on the latest developments in anesthesia with us!Follow us at:InstagramFacebookTwitter/X
Our special guest is Brian Johnson, Managing Director of Patomak Global Partners and former CFPB Deputy Director. In Nov. 2023, the CFPB issued a proposed rule to supervise nonbank companies that qualify as larger participants in a market for “general-use digital consumer payment applications.” We first discuss the CFPB's authority to supervise nonbank entities considered to be “a larger participant of a market for other consumer financial products or services” and its previous use of that authority. We look next at how the CFPB has defined the relevant market in its current proposal and its rationale for the proposal. We then discuss the deficiencies in the CFPB's cost benefit analysis of the proposal and how the proposal reflects changes to the CFPB's approach to rulemaking under Director Chopra. We conclude with a discussion of possible litigation challenges to a final rule and issues companies likely to be covered by a final rule should be considering. Alan Kaplinsky, Senior Counsel in Ballard Spahr's Consumer Financial Services Group, leads the conversation.
Maggie, Linus, Geoffrey, and the LS crew are reuniting for our second annual AI UX demo day in SF on Apr 28. Sign up to demo here! And don't forget tickets for the AI Engineer World's Fair — for early birds who join before keynote announcements!It's become fashionable for many AI startups to project themselves as “the next Google” - while the search engine is so 2000s, both Perplexity and Exa referred to themselves as a “research engine” or “answer engine” in our NeurIPS pod. However these searches tend to be relatively shallow, and it is challenging to zoom up and down the ladders of abstraction to garner insights. For serious researchers, this level of simple one-off search will not cut it.We've commented in our Jan 2024 Recap that Flow Engineering (simply; multi-turn processes over many-shot single prompts) seems to offer far more performance, control and reliability for a given cost budget. Our experiments with Devin and our understanding of what the new Elicit Notebooks offer a glimpse into the potential for very deep, open ended, thoughtful human-AI collaboration at scale.It starts with promptsWhen ChatGPT exploded in popularity in November 2022 everyone was turned into a prompt engineer. While generative models were good at "vibe based" outcomes (tell me a joke, write a poem, etc) with basic prompts, they struggled with more complex questions, especially in symbolic fields like math, logic, etc. Two of the most important "tricks" that people picked up on were:* Chain of Thought prompting strategy proposed by Wei et al in the “Chain-of-Thought Prompting Elicits Reasoning in Large Language Models”. Rather than doing traditional few-shot prompting with just question and answers, adding the thinking process that led to the answer resulted in much better outcomes.* Adding "Let's think step by step" to the prompt as a way to boost zero-shot reasoning, which was popularized by Kojima et al in the Large Language Models are Zero-Shot Reasoners paper from NeurIPS 2022. This bumped accuracy from 17% to 79% compared to zero-shot.Nowadays, prompts include everything from promises of monetary rewards to… whatever the Nous folks are doing to turn a model into a world simulator. At the end of the day, the goal of prompt engineering is increasing accuracy, structure, and repeatability in the generation of a model.From prompts to agentsAs prompt engineering got more and more popular, agents (see “The Anatomy of Autonomy”) took over Twitter with cool demos and AutoGPT became the fastest growing repo in Github history. The thing about AutoGPT that fascinated people was the ability to simply put in an objective without worrying about explaining HOW to achieve it, or having to write very sophisticated prompts. The system would create an execution plan on its own, and then loop through each task. The problem with open-ended agents like AutoGPT is that 1) it's hard to replicate the same workflow over and over again 2) there isn't a way to hard-code specific steps that the agent should take without actually coding them yourself, which isn't what most people want from a product. From agents to productsPrompt engineering and open-ended agents were great in the experimentation phase, but this year more and more of these workflows are starting to become polished products. Today's guests are Andreas Stuhlmüller and Jungwon Byun of Elicit (previously Ought), an AI research assistant that they think of as “the best place to understand what is known”. Ought was a non-profit, but last September, Elicit spun off into a PBC with a $9m seed round. It is hard to quantify how much a workflow can be improved, but Elicit boasts some impressive numbers for research assistants:Just four months after launch, Elicit crossed $1M ARR, which shows how much interest there is for AI products that just work.One of the main takeaways we had from the episode is how teams should focus on supervising the process, not the output. Their philosophy at Elicit isn't to train general models, but to train models that are extremely good at focusing processes. This allows them to have pre-created steps that the user can add to their workflow (like classifying certain features that are specific to their research field) without having to write a prompt for it. And for Hamel Husain's happiness, they always show you the underlying prompt. Elicit recently announced notebooks as a new interface to interact with their products: (fun fact, they tried to implement this 4 times before they landed on the right UX! We discuss this ~33:00 in the podcast)The reasons why they picked notebooks as a UX all tie back to process:* They are systematic; once you have a instruction/prompt that works on a paper, you can run hundreds of papers through the same workflow by creating a column. Notebooks can also be edited and exported at any point during the flow.* They are transparent - Many papers include an opaque literature review as perfunctory context before getting to their novel contribution. But PDFs are “dead” and it is difficult to follow the thought process and exact research flow of the authors. Sharing “living” Elicit Notebooks opens up this process.* They are unbounded - Research is an endless stream of rabbit holes. So it must be easy to dive deeper and follow up with extra steps, without losing the ability to surface for air. We had a lot of fun recording this, and hope you have as much fun listening!AI UX in SFLong time Latent Spacenauts might remember our first AI UX meetup with Linus Lee, Geoffrey Litt, and Maggie Appleton last year. Well, Maggie has since joined Elicit, and they are all returning at the end of this month! Sign up here: https://lu.ma/aiuxAnd submit demos here! https://forms.gle/iSwiesgBkn8oo4SS8We expect the 200 seats to “sell out” fast. Attendees with demos will be prioritized.Show Notes* Elicit* Ought (their previous non-profit)* “Pivoting” with GPT-4* Elicit notebooks launch* Charlie* Andreas' BlogTimestamps* [00:00:00] Introductions* [00:07:45] How Johan and Andreas Joined Forces to Create Elicit* [00:10:26] Why Products > Research* [00:15:49] The Evolution of Elicit's Product* [00:19:44] Automating Literature Review Workflow* [00:22:48] How GPT-3 to GPT-4 Changed Things* [00:25:37] Managing LLM Pricing and Performance* [00:31:07] Open vs. Closed: Elicit's Approach to Model Selection* [00:31:56] Moving to Notebooks* [00:39:11] Elicit's Budget for Model Queries and Evaluations* [00:41:44] Impact of Long Context Windows* [00:47:19] Underrated Features and Surprising Applications* [00:51:35] Driving Systematic and Efficient Research* [00:53:00] Elicit's Team Growth and Transition to a Public Benefit Corporation* [00:55:22] Building AI for GoodFull Interview on YouTubeAs always, a plug for our youtube version for the 80% of communication that is nonverbal:TranscriptAlessio [00:00:00]: Hey everyone, welcome to the Latent Space Podcast. This is Alessio, partner and CTO at Residence at Decibel Partners, and I'm joined by my co-host Swyx, founder of Smol AI.Swyx [00:00:15]: Hey, and today we are back in the studio with Andreas and Jungwon from Elicit. Welcome.Jungwon [00:00:20]: Thanks guys.Andreas [00:00:21]: It's great to be here.Swyx [00:00:22]: Yeah. So I'll introduce you separately, but also, you know, we'd love to learn a little bit more about you personally. So Andreas, it looks like you started Elicit first, Jungwon joined later.Andreas [00:00:32]: That's right. For all intents and purposes, the Elicit and also the Ought that existed before then were very different from what I started. So I think it's like fair to say that you co-founded it.Swyx [00:00:43]: Got it. And Jungwon, you're a co-founder and COO of Elicit now.Jungwon [00:00:46]: Yeah, that's right.Swyx [00:00:47]: So there's a little bit of a history to this. I'm not super aware of like the sort of journey. I was aware of OTT and Elicit as sort of a nonprofit type situation. And recently you turned into like a B Corp, Public Benefit Corporation. So yeah, maybe if you want, you could take us through that journey of finding the problem. You know, obviously you're working together now. So like, how do you get together to decide to leave your startup career to join him?Andreas [00:01:10]: Yeah, it's truly a very long journey. I guess truly, it kind of started in Germany when I was born. So even as a kid, I was always interested in AI, like I kind of went to the library. There were books about how to write programs in QBasic and like some of them talked about how to implement chatbots.Jungwon [00:01:27]: To be clear, he grew up in like a tiny village on the outskirts of Munich called Dinkelschirben, where it's like a very, very idyllic German village.Andreas [00:01:36]: Yeah, important to the story. So basically, the main thing is I've kind of always been thinking about AI my entire life and been thinking about, well, at some point, this is going to be a huge deal. It's going to be transformative. How can I work on it? And was thinking about it from when I was a teenager, after high school did a year where I started a startup with the intention to become rich. And then once I'm rich, I can affect the trajectory of AI. Did not become rich, decided to go back to college and study cognitive science there, which was like the closest thing I could find at the time to AI. In the last year of college, moved to the US to do a PhD at MIT, working on broadly kind of new programming languages for AI because it kind of seemed like the existing languages were not great at expressing world models and learning world models doing Bayesian inference. Was always thinking about, well, ultimately, the goal is to actually build tools that help people reason more clearly, ask and answer better questions and make better decisions. But for a long time, it seemed like the technology to put reasoning in machines just wasn't there. Initially, at the end of my postdoc at Stanford, I was thinking about, well, what to do? I think the standard path is you become an academic and do research. But it's really hard to actually build interesting tools as an academic. You can't really hire great engineers. Everything is kind of on a paper-to-paper timeline. And so I was like, well, maybe I should start a startup, pursued that for a little bit. But it seemed like it was too early because you could have tried to do an AI startup, but probably would not have been this kind of AI startup we're seeing now. So then decided to just start a nonprofit research lab that's going to do research for a while until we better figure out how to do thinking in machines. And that was odd. And then over time, it became clear how to actually build actual tools for reasoning. And only over time, we developed a better way to... I'll let you fill in some of the details here.Jungwon [00:03:26]: Yeah. So I guess my story maybe starts around 2015. I kind of wanted to be a founder for a long time, and I wanted to work on an idea that stood the test of time for me, like an idea that stuck with me for a long time. And starting in 2015, actually, originally, I became interested in AI-based tools from the perspective of mental health. So there are a bunch of people around me who are really struggling. One really close friend in particular is really struggling with mental health and didn't have any support, and it didn't feel like there was anything before kind of like getting hospitalized that could just help her. And so luckily, she came and stayed with me for a while, and we were just able to talk through some things. But it seemed like lots of people might not have that resource, and something maybe AI-enabled could be much more scalable. I didn't feel ready to start a company then, that's 2015. And I also didn't feel like the technology was ready. So then I went into FinTech and kind of learned how to do the tech thing. And then in 2019, I felt like it was time for me to just jump in and build something on my own I really wanted to create. And at the time, I looked around at tech and felt like not super inspired by the options. I didn't want to have a tech career ladder, or I didn't want to climb the career ladder. There are two kind of interesting technologies at the time, there was AI and there was crypto. And I was like, well, the AI people seem like a little bit more nice, maybe like slightly more trustworthy, both super exciting, but threw my bet in on the AI side. And then I got connected to Andreas. And actually, the way he was thinking about pursuing the research agenda at OTT was really compatible with what I had envisioned for an ideal AI product, something that helps kind of take down really complex thinking, overwhelming thoughts and breaks it down into small pieces. And then this kind of mission that we need AI to help us figure out what we ought to do was really inspiring, right? Yeah, because I think it was clear that we were building the most powerful optimizer of our time. But as a society, we hadn't figured out how to direct that optimization potential. And if you kind of direct tremendous amounts of optimization potential at the wrong thing, that's really disastrous. So the goal of OTT was make sure that if we build the most transformative technology of our lifetime, it can be used for something really impactful, like good reasoning, like not just generating ads. My background was in marketing, but like, so I was like, I want to do more than generate ads with this. But also if these AI systems get to be super intelligent enough that they are doing this really complex reasoning, that we can trust them, that they are aligned with us and we have ways of evaluating that they're doing the right thing. So that's what OTT did. We did a lot of experiments, you know, like I just said, before foundation models really like took off. A lot of the issues we were seeing were more in reinforcement learning, but we saw a future where AI would be able to do more kind of logical reasoning, not just kind of extrapolate from numerical trends. We actually kind of set up experiments with people where kind of people stood in as super intelligent systems and we effectively gave them context windows. So they would have to like read a bunch of text and one person would get less text and one person would get all the texts and the person with less text would have to evaluate the work of the person who could read much more. So like in a world we were basically simulating, like in 2018, 2019, a world where an AI system could read significantly more than you and you as the person who couldn't read that much had to evaluate the work of the AI system. Yeah. So there's a lot of the work we did. And from that, we kind of iterated on the idea of breaking complex tasks down into smaller tasks, like complex tasks, like open-ended reasoning, logical reasoning into smaller tasks so that it's easier to train AI systems on them. And also so that it's easier to evaluate the work of the AI system when it's done. And then also kind of, you know, really pioneered this idea, the importance of supervising the process of AI systems, not just the outcomes. So a big part of how Elicit is built is we're very intentional about not just throwing a ton of data into a model and training it and then saying, cool, here's like scientific output. Like that's not at all what we do. Our approach is very much like, what are the steps that an expert human does or what is like an ideal process as granularly as possible, let's break that down and then train AI systems to perform each of those steps very robustly. When you train like that from the start, after the fact, it's much easier to evaluate, it's much easier to troubleshoot at each point. Like where did something break down? So yeah, we were working on those experiments for a while. And then at the start of 2021, decided to build a product.Swyx [00:07:45]: Do you mind if I, because I think you're about to go into more modern thought and Elicit. And I just wanted to, because I think a lot of people are in where you were like sort of 2018, 19, where you chose a partner to work with. Yeah. Right. And you didn't know him. Yeah. Yeah. You were just kind of cold introduced. A lot of people are cold introduced. Yeah. Never work with them. I assume you had a lot, a lot of other options, right? Like how do you advise people to make those choices?Jungwon [00:08:10]: We were not totally cold introduced. So one of our closest friends introduced us. And then Andreas had written a lot on the OTT website, a lot of blog posts, a lot of publications. And I just read it and I was like, wow, this sounds like my writing. And even other people, some of my closest friends I asked for advice from, they were like, oh, this sounds like your writing. But I think I also had some kind of like things I was looking for. I wanted someone with a complimentary skillset. I want someone who was very values aligned. And yeah, that was all a good fit.Andreas [00:08:38]: We also did a pretty lengthy mutual evaluation process where we had a Google doc where we had all kinds of questions for each other. And I think it ended up being around 50 pages or so of like various like questions and back and forth.Swyx [00:08:52]: Was it the YC list? There's some lists going around for co-founder questions.Andreas [00:08:55]: No, we just made our own questions. But I guess it's probably related in that you ask yourself, what are the values you care about? How would you approach various decisions and things like that?Jungwon [00:09:04]: I shared like all of my past performance reviews. Yeah. Yeah.Swyx [00:09:08]: And he never had any. No.Andreas [00:09:10]: Yeah.Swyx [00:09:11]: Sorry, I just had to, a lot of people are going through that phase and you kind of skipped over it. I was like, no, no, no, no. There's like an interesting story.Jungwon [00:09:20]: Yeah.Alessio [00:09:21]: Yeah. Before we jump into what a list it is today, the history is a bit counterintuitive. So you start with figuring out, oh, if we had a super powerful model, how would we align it? But then you were actually like, well, let's just build the product so that people can actually leverage it. And I think there are a lot of folks today that are now back to where you were maybe five years ago that are like, oh, what if this happens rather than focusing on actually building something useful with it? What clicked for you to like move into a list and then we can cover that story too.Andreas [00:09:49]: I think in many ways, the approach is still the same because the way we are building illicit is not let's train a foundation model to do more stuff. It's like, let's build a scaffolding such that we can deploy powerful models to good ends. I think it's different now in that we actually have like some of the models to plug in. But if in 2017, we had had the models, we could have run the same experiments we did run with humans back then, just with models. And so in many ways, our philosophy is always, let's think ahead to the future of what models are going to exist in one, two years or longer. And how can we make it so that they can actually be deployed in kind of transparent, controllableJungwon [00:10:26]: ways? I think motivationally, we both are kind of product people at heart. The research was really important and it didn't make sense to build a product at that time. But at the end of the day, the thing that always motivated us is imagining a world where high quality reasoning is really abundant and AI is a technology that's going to get us there. And there's a way to guide that technology with research, but we can have a more direct effect through product because with research, you publish the research and someone else has to implement that into the product and the product felt like a more direct path. And we wanted to concretely have an impact on people's lives. Yeah, I think the kind of personally, the motivation was we want to build for people.Swyx [00:11:03]: Yep. And then just to recap as well, like the models you were using back then were like, I don't know, would they like BERT type stuff or T5 or I don't know what timeframe we're talking about here.Andreas [00:11:14]: I guess to be clear, at the very beginning, we had humans do the work. And then I think the first models that kind of make sense were TPT-2 and TNLG and like Yeah, early generative models. We do also use like T5 based models even now started with TPT-2.Swyx [00:11:30]: Yeah, cool. I'm just kind of curious about like, how do you start so early? You know, like now it's obvious where to start, but back then it wasn't.Jungwon [00:11:37]: Yeah, I used to nag Andreas a lot. I was like, why are you talking to this? I don't know. I felt like TPT-2 is like clearly can't do anything. And I was like, Andreas, you're wasting your time, like playing with this toy. But yeah, he was right.Alessio [00:11:50]: So what's the history of what Elicit actually does as a product? You recently announced that after four months, you get to a million in revenue. Obviously, a lot of people use it, get a lot of value, but it would initially kind of like structured data extraction from papers. Then you had kind of like concept grouping. And today, it's maybe like a more full stack research enabler, kind of like paper understander platform. What's the definitive definition of what Elicit is? And how did you get here?Jungwon [00:12:15]: Yeah, we say Elicit is an AI research assistant. I think it will continue to evolve. That's part of why we're so excited about building and research, because there's just so much space. I think the current phase we're in right now, we talk about it as really trying to make Elicit the best place to understand what is known. So it's all a lot about like literature summarization. There's a ton of information that the world already knows. It's really hard to navigate, hard to make it relevant. So a lot of it is around document discovery and processing and analysis. I really kind of want to import some of the incredible productivity improvements we've seen in software engineering and data science and into research. So it's like, how can we make researchers like data scientists of text? That's why we're launching this new set of features called Notebooks. It's very much inspired by computational notebooks, like Jupyter Notebooks, you know, DeepNode or Colab, because they're so powerful and so flexible. And ultimately, when people are trying to get to an answer or understand insight, they're kind of like manipulating evidence and information. Today, that's all packaged in PDFs, which are super brittle. So with language models, we can decompose these PDFs into their underlying claims and evidence and insights, and then let researchers mash them up together, remix them and analyze them together. So yeah, I would say quite simply, overall, Elicit is an AI research assistant. Right now we're focused on text-based workflows, but long term, really want to kind of go further and further into reasoning and decision making.Alessio [00:13:35]: And when you say AI research assistant, this is kind of meta research. So researchers use Elicit as a research assistant. It's not a generic you-can-research-anything type of tool, or it could be, but like, what are people using it for today?Andreas [00:13:49]: Yeah. So specifically in science, a lot of people use human research assistants to do things. You tell your grad student, hey, here are a couple of papers. Can you look at all of these, see which of these have kind of sufficiently large populations and actually study the disease that I'm interested in, and then write out like, what are the experiments they did? What are the interventions they did? What are the outcomes? And kind of organize that for me. And the first phase of understanding what is known really focuses on automating that workflow because a lot of that work is pretty rote work. I think it's not the kind of thing that we need humans to do. Language models can do it. And then if language models can do it, you can obviously scale it up much more than a grad student or undergrad research assistant would be able to do.Jungwon [00:14:31]: Yeah. The use cases are pretty broad. So we do have a very large percent of our users are just using it personally or for a mix of personal and professional things. People who care a lot about health or biohacking or parents who have children with a kind of rare disease and want to understand the literature directly. So there is an individual kind of consumer use case. We're most focused on the power users. So that's where we're really excited to build. So Lissette was very much inspired by this workflow in literature called systematic reviews or meta-analysis, which is basically the human state of the art for summarizing scientific literature. And it typically involves like five people working together for over a year. And they kind of first start by trying to find the maximally comprehensive set of papers possible. So it's like 10,000 papers. And they kind of systematically narrow that down to like hundreds or 50 extract key details from every single paper. Usually have two people doing it, like a third person reviewing it. So it's like an incredibly laborious, time consuming process, but you see it in every single domain. So in science, in machine learning, in policy, because it's so structured and designed to be reproducible, it's really amenable to automation. So that's kind of the workflow that we want to automate first. And then you make that accessible for any question and make these really robust living summaries of science. So yeah, that's one of the workflows that we're starting with.Alessio [00:15:49]: Our previous guest, Mike Conover, he's building a new company called Brightwave, which is an AI research assistant for financial research. How do you see the future of these tools? Does everything converge to like a God researcher assistant, or is every domain going to have its own thing?Andreas [00:16:03]: I think that's a good and mostly open question. I do think there are some differences across domains. For example, some research is more quantitative data analysis, and other research is more high level cross domain thinking. And we definitely want to contribute to the broad generalist reasoning type space. Like if researchers are making discoveries often, it's like, hey, this thing in biology is actually analogous to like these equations in economics or something. And that's just fundamentally a thing that where you need to reason across domains. At least within research, I think there will be like one best platform more or less for this type of generalist research. I think there may still be like some particular tools like for genomics, like particular types of modules of genes and proteins and whatnot. But for a lot of the kind of high level reasoning that humans do, I think that is a more of a winner type all thing.Swyx [00:16:52]: I wanted to ask a little bit deeper about, I guess, the workflow that you mentioned. I like that phrase. I see that in your UI now, but that's as it is today. And I think you were about to tell us about how it was in 2021 and how it may be progressed. How has this workflow evolved over time?Jungwon [00:17:07]: Yeah. So the very first version of Elicit actually wasn't even a research assistant. It was a forecasting assistant. So we set out and we were thinking about, you know, what are some of the most impactful types of reasoning that if we could scale up, AI would really transform the world. We actually started with literature review, but we're like, oh, so many people are going to build literature review tools. So let's start there. So then we focused on geopolitical forecasting. So I don't know if you're familiar with like manifold or manifold markets. That kind of stuff. Before manifold. Yeah. Yeah. I'm not predicting relationships. We're predicting like, is China going to invade Taiwan?Swyx [00:17:38]: Markets for everything.Andreas [00:17:39]: Yeah. That's a relationship.Swyx [00:17:41]: Yeah.Jungwon [00:17:42]: Yeah. It's true. And then we worked on that for a while. And then after GPT-3 came out, I think by that time we realized that originally we were trying to help people convert their beliefs into probability distributions. And so take fuzzy beliefs, but like model them more concretely. And then after a few months of iterating on that, just realize, oh, the thing that's blocking people from making interesting predictions about important events in the world is less kind of on the probabilistic side and much more on the research side. And so that kind of combined with the very generalist capabilities of GPT-3 prompted us to make a more general research assistant. Then we spent a few months iterating on what even is a research assistant. So we would embed with different researchers. We built data labeling workflows in the beginning, kind of right off the bat. We built ways to find experts in a field and like ways to ask good research questions. So we just kind of iterated through a lot of workflows and no one else was really building at this time. And it was like very quick to just do some prompt engineering and see like what is a task that is at the intersection of what's technologically capable and like important for researchers. And we had like a very nondescript landing page. It said nothing. But somehow people were signing up and we had to sign a form that was like, why are you here? And everyone was like, I need help with literature review. And we're like, oh, literature review. That sounds so hard. I don't even know what that means. We're like, we don't want to work on it. But then eventually we were like, okay, everyone is saying literature review. It's overwhelmingly people want to-Swyx [00:19:02]: And all domains, not like medicine or physics or just all domains. Yeah.Jungwon [00:19:06]: And we also kind of personally knew literature review was hard. And if you look at the graphs for academic literature being published every single month, you guys know this in machine learning, it's like up into the right, like superhuman amounts of papers. So we're like, all right, let's just try it. I was really nervous, but Andreas was like, this is kind of like the right problem space to jump into, even if we don't know what we're doing. So my take was like, fine, this feels really scary, but let's just launch a feature every single week and double our user numbers every month. And if we can do that, we'll fail fast and we will find something. I was worried about like getting lost in the kind of academic white space. So the very first version was actually a weekend prototype that Andreas made. Do you want to explain how that worked?Andreas [00:19:44]: I mostly remember that it was really bad. The thing I remember is you entered a question and it would give you back a list of claims. So your question could be, I don't know, how does creatine affect cognition? It would give you back some claims that are to some extent based on papers, but they were often irrelevant. The papers were often irrelevant. And so we ended up soon just printing out a bunch of examples of results and putting them up on the wall so that we would kind of feel the constant shame of having such a bad product and would be incentivized to make it better. And I think over time it has gotten a lot better, but I think the initial version was like really very bad. Yeah.Jungwon [00:20:20]: But it was basically like a natural language summary of an abstract, like kind of a one sentence summary, and which we still have. And then as we learned kind of more about this systematic review workflow, we started expanding the capability so that you could extract a lot more data from the papers and do more with that.Swyx [00:20:33]: And were you using like embeddings and cosine similarity, that kind of stuff for retrieval, or was it keyword based?Andreas [00:20:40]: I think the very first version didn't even have its own search engine. I think the very first version probably used the Semantic Scholar or API or something similar. And only later when we discovered that API is not very semantic, we then built our own search engine that has helped a lot.Swyx [00:20:58]: And then we're going to go into like more recent products stuff, but like, you know, I think you seem the more sort of startup oriented business person and you seem sort of more ideologically like interested in research, obviously, because of your PhD. What kind of market sizing were you guys thinking? Right? Like, because you're here saying like, we have to double every month. And I'm like, I don't know how you make that conclusion from this, right? Especially also as a nonprofit at the time.Jungwon [00:21:22]: I mean, market size wise, I felt like in this space where so much was changing and it was very unclear what of today was actually going to be true tomorrow. We just like really rested a lot on very, very simple fundamental principles, which is like, if you can understand the truth, that is very economically beneficial and valuable. If you like know the truth.Swyx [00:21:42]: On principle.Jungwon [00:21:43]: Yeah. That's enough for you. Yeah. Research is the key to many breakthroughs that are very commercially valuable.Swyx [00:21:47]: Because my version of it is students are poor and they don't pay for anything. Right? But that's obviously not true. As you guys have found out. But you had to have some market insight for me to have believed that, but you skipped that.Andreas [00:21:58]: Yeah. I remember talking to VCs for our seed round. A lot of VCs were like, you know, researchers, they don't have any money. Why don't you build legal assistant? I think in some short sighted way, maybe that's true. But I think in the long run, R&D is such a big space of the economy. I think if you can substantially improve how quickly people find new discoveries or avoid controlled trials that don't go anywhere, I think that's just huge amounts of money. And there are a lot of questions obviously about between here and there. But I think as long as the fundamental principle is there, we were okay with that. And I guess we found some investors who also were. Yeah.Swyx [00:22:35]: Congrats. I mean, I'm sure we can cover the sort of flip later. I think you're about to start us on like GPT-3 and how that changed things for you. It's funny. I guess every major GPT version, you have some big insight. Yeah.Jungwon [00:22:48]: Yeah. I mean, what do you think?Andreas [00:22:51]: I think it's a little bit less true for us than for others, because we always believed that there will basically be human level machine work. And so it is definitely true that in practice for your product, as new models come out, your product starts working better, you can add some features that you couldn't add before. But I don't think we really ever had the moment where we were like, oh, wow, that is super unanticipated. We need to do something entirely different now from what was on the roadmap.Jungwon [00:23:21]: I think GPT-3 was a big change because it kind of said, oh, now is the time that we can use AI to build these tools. And then GPT-4 was maybe a little bit more of an extension of GPT-3. GPT-3 over GPT-2 was like qualitative level shift. And then GPT-4 was like, okay, great. Now it's like more accurate. We're more accurate on these things. We can answer harder questions. But the shape of the product had already taken place by that time.Swyx [00:23:44]: I kind of want to ask you about this sort of pivot that you've made. But I guess that was just a way to sell what you were doing, which is you're adding extra features on grouping by concepts. The GPT-4 pivot, quote unquote pivot that you-Jungwon [00:23:55]: Oh, yeah, yeah, exactly. Right, right, right. Yeah. Yeah. When we launched this workflow, now that GPT-4 was available, basically Elisa was at a place where we have very tabular interfaces. So given a table of papers, you can extract data across all the tables. But you kind of want to take the analysis a step further. Sometimes what you'd care about is not having a list of papers, but a list of arguments, a list of effects, a list of interventions, a list of techniques. And so that's one of the things we're working on is now that you've extracted this information in a more structured way, can you pivot it or group by whatever the information that you extracted to have more insight first information still supported by the academic literature?Swyx [00:24:33]: Yeah, that was a big revelation when I saw it. Basically, I think I'm very just impressed by how first principles, your ideas around what the workflow is. And I think that's why you're not as reliant on like the LLM improving, because it's actually just about improving the workflow that you would recommend to people. Today we might call it an agent, I don't know, but you're not relying on the LLM to drive it. It's relying on this is the way that Elicit does research. And this is what we think is most effective based on talking to our users.Jungwon [00:25:01]: The problem space is still huge. Like if it's like this big, we are all still operating at this tiny part, bit of it. So I think about this a lot in the context of moats, people are like, oh, what's your moat? What happens if GPT-5 comes out? It's like, if GPT-5 comes out, there's still like all of this other space that we can go into. So I think being really obsessed with the problem, which is very, very big, has helped us like stay robust and just kind of directly incorporate model improvements and they keep going.Swyx [00:25:26]: And then I first encountered you guys with Charlie, you can tell us about that project. Basically, yeah. Like how much did cost become a concern as you're working more and more with OpenAI? How do you manage that relationship?Jungwon [00:25:37]: Let me talk about who Charlie is. And then you can talk about the tech, because Charlie is a special character. So Charlie, when we found him was, had just finished his freshman year at the University of Warwick. And I think he had heard about us on some discord. And then he applied and we were like, wow, who is this freshman? And then we just saw that he had done so many incredible side projects. And we were actually on a team retreat in Barcelona visiting our head of engineering at that time. And everyone was talking about this wonder kid or like this kid. And then on our take home project, he had done like the best of anyone to that point. And so people were just like so excited to hire him. So we hired him as an intern and they were like, Charlie, what if you just dropped out of school? And so then we convinced him to take a year off. And he was just incredibly productive. And I think the thing you're referring to is at the start of 2023, Anthropic kind of launched their constitutional AI paper. And within a few days, I think four days, he had basically implemented that in production. And then we had it in app a week or so after that. And he has since kind of contributed to major improvements, like cutting costs down to a tenth of what they were really large scale. But yeah, you can talk about the technical stuff. Yeah.Andreas [00:26:39]: On the constitutional AI project, this was for abstract summarization, where in illicit, if you run a query, it'll return papers to you, and then it will summarize each paper with respect to your query for you on the fly. And that's a really important part of illicit because illicit does it so much. If you run a few searches, it'll have done it a few hundred times for you. And so we cared a lot about this both being fast, cheap, and also very low on hallucination. I think if illicit hallucinates something about the abstract, that's really not good. And so what Charlie did in that project was create a constitution that expressed what are the attributes of a good summary? Everything in the summary is reflected in the actual abstract, and it's like very concise, et cetera, et cetera. And then used RLHF with a model that was trained on the constitution to basically fine tune a better summarizer on an open source model. Yeah. I think that might still be in use.Jungwon [00:27:34]: Yeah. Yeah, definitely. Yeah. I think at the time, the models hadn't been trained at all to be faithful to a text. So they were just generating. So then when you ask them a question, they tried too hard to answer the question and didn't try hard enough to answer the question given the text or answer what the text said about the question. So we had to basically teach the models to do that specific task.Swyx [00:27:54]: How do you monitor the ongoing performance of your models? Not to get too LLM-opsy, but you are one of the larger, more well-known operations doing NLP at scale. I guess effectively, you have to monitor these things and nobody has a good answer that I talk to.Andreas [00:28:10]: I don't think we have a good answer yet. I think the answers are actually a little bit clearer on the just kind of basic robustness side of where you can import ideas from normal software engineering and normal kind of DevOps. You're like, well, you need to monitor kind of latencies and response times and uptime and whatnot.Swyx [00:28:27]: I think when we say performance, it's more about hallucination rate, isn't it?Andreas [00:28:30]: And then things like hallucination rate where I think there, the really important thing is training time. So we care a lot about having our own internal benchmarks for model development that reflect the distribution of user queries so that we can know ahead of time how well is the model going to perform on different types of tasks. So the tasks being summarization, question answering, given a paper, ranking. And for each of those, we want to know what's the distribution of things the model is going to see so that we can have well-calibrated predictions on how well the model is going to do in production. And I think, yeah, there's some chance that there's distribution shift and actually the things users enter are going to be different. But I think that's much less important than getting the kind of training right and having very high quality, well-vetted data sets at training time.Jungwon [00:29:18]: I think we also end up effectively monitoring by trying to evaluate new models as they come out. And so that kind of prompts us to go through our eval suite every couple of months. And every time a new model comes out, we have to see how is this performing relative to production and what we currently have.Swyx [00:29:32]: Yeah. I mean, since we're on this topic, any new models that have really caught your eye this year?Jungwon [00:29:37]: Like Claude came out with a bunch. Yeah. I think Claude is pretty, I think the team's pretty excited about Claude. Yeah.Andreas [00:29:41]: Specifically, Claude Haiku is like a good point on the kind of Pareto frontier. It's neither the cheapest model, nor is it the most accurate, most high quality model, but it's just like a really good trade-off between cost and accuracy.Swyx [00:29:57]: You apparently have to 10-shot it to make it good. I tried using Haiku for summarization, but zero-shot was not great. Then they were like, you know, it's a skill issue, you have to try harder.Jungwon [00:30:07]: I think GPT-4 unlocked tables for us, processing data from tables, which was huge. GPT-4 Vision.Andreas [00:30:13]: Yeah.Swyx [00:30:14]: Yeah. Did you try like Fuyu? I guess you can't try Fuyu because it's non-commercial. That's the adept model.Jungwon [00:30:19]: Yeah.Swyx [00:30:20]: We haven't tried that one. Yeah. Yeah. Yeah. But Claude is multimodal as well. Yeah. I think the interesting insight that we got from talking to David Luan, who is CEO of multimodality has effectively two different flavors. One is we recognize images from a camera in the outside natural world. And actually the more important multimodality for knowledge work is screenshots and PDFs and charts and graphs. So we need a new term for that kind of multimodality.Andreas [00:30:45]: But is the claim that current models are good at one or the other? Yeah.Swyx [00:30:50]: They're over-indexed because of the history of computer vision is Coco, right? So now we're like, oh, actually, you know, screens are more important, OCR, handwriting. You mentioned a lot of like closed model lab stuff, and then you also have like this open source model fine tuning stuff. Like what is your workload now between closed and open? It's a good question.Andreas [00:31:07]: I think- Is it half and half? It's a-Swyx [00:31:10]: Is that even a relevant question or not? Is this a nonsensical question?Andreas [00:31:13]: It depends a little bit on like how you index, whether you index by like computer cost or number of queries. I'd say like in terms of number of queries, it's maybe similar. In terms of like cost and compute, I think the closed models make up more of the budget since the main cases where you want to use closed models are cases where they're just smarter, where no existing open source models are quite smart enough.Jungwon [00:31:35]: Yeah. Yeah.Alessio [00:31:37]: We have a lot of interesting technical questions to go in, but just to wrap the kind of like UX evolution, now you have the notebooks. We talked a lot about how chatbots are not the final frontier, you know? How did you decide to get into notebooks, which is a very iterative kind of like interactive interface and yeah, maybe learnings from that.Jungwon [00:31:56]: Yeah. This is actually our fourth time trying to make this work. Okay. I think the first time was probably in early 2021. I think because we've always been obsessed with this idea of task decomposition and like branching, we always wanted a tool that could be kind of unbounded where you could keep going, could do a lot of branching where you could kind of apply language model operations or computations on other tasks. So in 2021, we had this thing called composite tasks where you could use GPT-3 to brainstorm a bunch of research questions and then take each research question and decompose those further into sub questions. This kind of, again, that like task decomposition tree type thing was always very exciting to us, but that was like, it didn't work and it was kind of overwhelming. Then at the end of 22, I think we tried again and at that point we were thinking, okay, we've done a lot with this literature review thing. We also want to start helping with kind of adjacent domains and different workflows. Like we want to help more with machine learning. What does that look like? And as we were thinking about it, we're like, well, there are so many research workflows. How do we not just build three new workflows into Elicit, but make Elicit really generic to lots of workflows? What is like a generic composable system with nice abstractions that can like scale to all these workflows? So we like iterated on that a bunch and then didn't quite narrow the problem space enough or like quite get to what we wanted. And then I think it was at the beginning of 2023 where we're like, wow, computational notebooks kind of enable this, where they have a lot of flexibility, but kind of robust primitives such that you can extend the workflow and it's not limited. It's not like you ask a query, you get an answer, you're done. You can just constantly keep building on top of that. And each little step seems like a really good unit of work for the language model. And also there was just like really helpful to have a bit more preexisting work to emulate. Yeah, that's kind of how we ended up at computational notebooks for Elicit.Andreas [00:33:44]: Maybe one thing that's worth making explicit is the difference between computational notebooks and chat, because on the surface, they seem pretty similar. It's kind of this iterative interaction where you add stuff. In both cases, you have a back and forth between you enter stuff and then you get some output and then you enter stuff. But the important difference in our minds is with notebooks, you can define a process. So in data science, you can be like, here's like my data analysis process that takes in a CSV and then does some extraction and then generates a figure at the end. And you can prototype it using a small CSV and then you can run it over a much larger CSV later. And similarly, the vision for notebooks in our case is to not make it this like one-off chat interaction, but to allow you to then say, if you start and first you're like, okay, let me just analyze a few papers and see, do I get to the correct conclusions for those few papers? Can I then later go back and say, now let me run this over 10,000 papers now that I've debugged the process using a few papers. And that's an interaction that doesn't fit quite as well into the chat framework because that's more for kind of quick back and forth interaction.Alessio [00:34:49]: Do you think in notebooks, it's kind of like structure, editable chain of thought, basically step by step? Like, is that kind of where you see this going? And then are people going to reuse notebooks as like templates? And maybe in traditional notebooks, it's like cookbooks, right? You share a cookbook, you can start from there. Is this similar in Elizit?Andreas [00:35:06]: Yeah, that's exactly right. So that's our hope that people will build templates, share them with other people. I think chain of thought is maybe still like kind of one level lower on the abstraction hierarchy than we would think of notebooks. I think we'll probably want to think about more semantic pieces like a building block is more like a paper search or an extraction or a list of concepts. And then the model's detailed reasoning will probably often be one level down. You always want to be able to see it, but you don't always want it to be front and center.Alessio [00:35:36]: Yeah, what's the difference between a notebook and an agent? Since everybody always asks me, what's an agent? Like how do you think about where the line is?Andreas [00:35:44]: Yeah, it's an interesting question. In the notebook world, I would generally think of the human as the agent in the first iteration. So you have the notebook and the human kind of adds little action steps. And then the next point on this kind of progress gradient is, okay, now you can use language models to predict which action would you take as a human. And at some point, you're probably going to be very good at this, you'll be like, okay, in some cases I can, with 99.9% accuracy, predict what you do. And then you might as well just execute it, like why wait for the human? And eventually, as you get better at this, that will just look more and more like agents taking actions as opposed to you doing the thing. I think templates are a specific case of this where you're like, okay, well, there's just particular sequences of actions that you often want to chunk and have available as primitives, just like in normal programming. And those, you can view them as action sequences of agents, or you can view them as more normal programming language abstraction thing. And I think those are two valid views. Yeah.Alessio [00:36:40]: How do you see this change as, like you said, the models get better and you need less and less human actual interfacing with the model, you just get the results? Like how does the UX and the way people perceive it change?Jungwon [00:36:52]: Yeah, I think this kind of interaction paradigms for evaluation is not really something the internet has encountered yet, because up to now, the internet has all been about getting data and work from people. So increasingly, I really want kind of evaluation, both from an interface perspective and from like a technical perspective and operation perspective to be a superpower for Elicit, because I think over time, models will do more and more of the work, and people will have to do more and more of the evaluation. So I think, yeah, in terms of the interface, some of the things we have today, you know, for every kind of language model generation, there's some citation back, and we kind of try to highlight the ground truth in the paper that is most relevant to whatever Elicit said, and make it super easy so that you can click on it and quickly see in context and validate whether the text actually supports the answer that Elicit gave. So I think we'd probably want to scale things up like that, like the ability to kind of spot check the model's work super quickly, scale up interfaces like that. And-Swyx [00:37:44]: Who would spot check? The user?Jungwon [00:37:46]: Yeah, to start, it would be the user. One of the other things we do is also kind of flag the model's uncertainty. So we have models report out, how confident are you that this was the sample size of this study? The model's not sure, we throw a flag. And so the user knows to prioritize checking that. So again, we can kind of scale that up. So when the model's like, well, I searched this on Google, I'm not sure if that was the right thing. I have an uncertainty flag, and the user can go and be like, oh, okay, that was actually the right thing to do or not.Swyx [00:38:10]: I've tried to do uncertainty readings from models. I don't know if you have this live. You do? Yeah. Because I just didn't find them reliable because they just hallucinated their own uncertainty. I would love to base it on log probs or something more native within the model rather than generated. But okay, it sounds like they scale properly for you. Yeah.Jungwon [00:38:30]: We found it to be pretty calibrated. It varies on the model.Andreas [00:38:32]: I think in some cases, we also use two different models for the uncertainty estimates than for the question answering. So one model would say, here's my chain of thought, here's my answer. And then a different type of model. Let's say the first model is Llama, and let's say the second model is GPT-3.5. And then the second model just looks over the results and is like, okay, how confident are you in this? And I think sometimes using a different model can be better than using the same model. Yeah.Swyx [00:38:58]: On the topic of models, evaluating models, obviously you can do that all day long. What's your budget? Because your queries fan out a lot. And then you have models evaluating models. One person typing in a question can lead to a thousand calls.Andreas [00:39:11]: It depends on the project. So if the project is basically a systematic review that otherwise human research assistants would do, then the project is basically a human equivalent spend. And the spend can get quite large for those projects. I don't know, let's say $100,000. In those cases, you're happier to spend compute then in the kind of shallow search case where someone just enters a question because, I don't know, maybe I heard about creatine. What's it about? Probably don't want to spend a lot of compute on that. This sort of being able to invest more or less compute into getting more or less accurate answers is I think one of the core things we care about. And that I think is currently undervalued in the AI space. I think currently you can choose which model you want and you can sometimes, I don't know, you'll tip it and it'll try harder or you can try various things to get it to work harder. But you don't have great ways of converting willingness to spend into better answers. And we really want to build a product that has this sort of unbounded flavor where if you care about it a lot, you should be able to get really high quality answers, really double checked in every way.Alessio [00:40:14]: And you have a credits-based pricing. So unlike most products, it's not a fixed monthly fee.Jungwon [00:40:19]: Right, exactly. So some of the higher costs are tiered. So for most casual users, they'll just get the abstract summary, which is kind of an open source model. Then you can add more columns, which have more extractions and these uncertainty features. And then you can also add the same columns in high accuracy mode, which also parses the table. So we kind of stack the complexity on the calls.Swyx [00:40:39]: You know, the fun thing you can do with a credit system, which is data for data, basically you can give people more credits if they give data back to you. I don't know if you've already done that. We've thought about something like this.Jungwon [00:40:49]: It's like if you don't have money, but you have time, how do you exchange that?Swyx [00:40:54]: It's a fair trade.Jungwon [00:40:55]: I think it's interesting. We haven't quite operationalized it. And then, you know, there's been some kind of like adverse selection. Like, you know, for example, it would be really valuable to get feedback on our model. So maybe if you were willing to give more robust feedback on our results, we could give you credits or something like that. But then there's kind of this, will people take it seriously? And you want the good people. Exactly.Swyx [00:41:11]: Can you tell who are the good people? Not right now.Jungwon [00:41:13]: But yeah, maybe at the point where we can, we can offer it. We can offer it up to them.Swyx [00:41:16]: The perplexity of questions asked, you know, if it's higher perplexity, these are the smarterJungwon [00:41:20]: people. Yeah, maybe.Andreas [00:41:23]: If you put typos in your queries, you're not going to get off the stage.Swyx [00:41:28]: Negative social credit. It's very topical right now to think about the threat of long context windows. All these models that we're talking about these days, all like a million token plus. Is that relevant for you? Can you make use of that? Is that just prohibitively expensive because you're just paying for all those tokens or you're just doing rag?Andreas [00:41:44]: It's definitely relevant. And when we think about search, as many people do, we think about kind of a staged pipeline of retrieval where first you use semantic search database with embeddings, get like the, in our case, maybe 400 or so most relevant papers. And then, then you still need to rank those. And I think at that point it becomes pretty interesting to use larger models. So specifically in the past, I think a lot of ranking was kind of per item ranking where you would score each individual item, maybe using increasingly expensive scoring methods and then rank based on the scores. But I think list-wise re-ranking where you have a model that can see all the elements is a lot more powerful because often you can only really tell how good a thing is in comparison to other things and what things should come first. It really depends on like, well, what other things that are available, maybe you even care about diversity in your results. You don't want to show 10 very similar papers as the first 10 results. So I think a long context models are quite interesting there. And especially for our case where we care more about power users who are perhaps a little bit more willing to wait a little bit longer to get higher quality results relative to people who just quickly check out things because why not? And I think being able to spend more on longer contexts is quite valuable.Jungwon [00:42:55]: Yeah. I think one thing the longer context models changed for us is maybe a focus from breaking down tasks to breaking down the evaluation. So before, you know, if we wanted to answer a question from the full text of a paper, we had to figure out how to chunk it and like find the relevant chunk and then answer based on that chunk. And the nice thing was then, you know, kind of which chunk the model used to answer the question. So if you want to help the user track it, yeah, you can be like, well, this was the chunk that the model got. And now if you put the whole text in the paper, you have to like kind of find the chunk like more retroactively basically. And so you need kind of like a different set of abilities and obviously like a different technology to figure out. You still want to point the user to the supporting quotes in the text, but then the interaction is a little different.Swyx [00:43:38]: You like scan through and find some rouge score floor.Andreas [00:43:41]: I think there's an interesting space of almost research problems here because you would ideally make causal claims like if this hadn't been in the text, the model wouldn't have said this thing. And maybe you can do expensive approximations to that where like, I don't know, you just throw out chunk of the paper and re-answer and see what happens. But hopefully there are better ways of doing that where you just get that kind of counterfactual information for free from the model.Alessio [00:44:06]: Do you think at all about the cost of maintaining REG versus just putting more tokens in the window? I think in software development, a lot of times people buy developer productivity things so that we don't have to worry about it. Context window is kind of the same, right? You have to maintain chunking and like REG retrieval and like re-ranking and all of this versus I just shove everything into the context and like it costs a little more, but at least I don't have to do all of that. Is that something you thought about?Jungwon [00:44:31]: I think we still like hit up against context limits enough that it's not really, do we still want to keep this REG around? It's like we do still need it for the scale of the work that we're doing, yeah.Andreas [00:44:41]: And I think there are different kinds of maintainability. In one sense, I think you're right that throw everything into the context window thing is easier to maintain because you just can swap out a model. In another sense, if things go wrong, it's harder to debug where like, if you know, here's the process that we go through to go from 200 million papers to an answer. And there are like little steps and you understand, okay, this is the step that finds the relevant paragraph or whatever it may be. You'll know which step breaks if the answers are bad, whereas if it's just like a new model version came out and now it suddenly doesn't find your needle in a haystack anymore, then you're like, okay, what can you do? You're kind of at a loss.Alessio [00:45:21]: Let's talk a bit about, yeah, needle in a haystack and like maybe the opposite of it, which is like hard grounding. I don't know if that's like the best name to think about it, but I was using one of these chatwitcher documents features and I put the AMD MI300 specs and the new Blackwell chips from NVIDIA and I was asking questions and does the AMD chip support NVLink? And the response was like, oh, it doesn't say in the specs. But if you ask GPD 4 without the docs, it would tell you no, because NVLink it's a NVIDIA technology.Swyx [00:45:49]: It just says in the thing.Alessio [00:45:53]: How do you think about that? Does using the context sometimes suppress the knowledge that the model has?Andreas [00:45:57]: It really depends on the task because I think sometimes that is exactly what you want. So imagine you're a researcher, you're writing the background section of your paper and you're trying to describe what these other papers say. You really don't want extra information to be introduced there. In other cases where you're just trying to figure out the truth and you're giving the documents because you think they will help the model figure out what the truth is. I think you do want, if the model has a hunch that there might be something that's not in the papers, you do want to surface that. I think ideally you still don't want the model to just tell you, probably the ideal thing looks a bit more like agent control where the model can issue a query that then is intended to surface documents that substantiate its hunch. That's maybe a reasonable middle ground between model just telling you and model being fully limited to the papers you give it.Jungwon [00:46:44]: Yeah, I would say it's, they're just kind of different tasks right now. And the task that Elicit is mostly focused on is what do these papers say? But there's another task which is like, just give me the best possible answer and that give me the best possible answer sometimes depends on what do these papers say, but it can also depend on other stuff that's not in the papers. So ideally we can do both and then kind of do this overall task for you more going forward.Alessio [00:47:08]: We see a lot of details, but just to zoom back out a little bit, what are maybe the most underrated features of Elicit and what is one thing that maybe the users surprise you the most by using it?Jungwon [00:47:19]: I think the most powerful feature of Elicit is the ability to extract, add columns to this table, which effectively extracts data from all of your papers at once. It's well used, but there are kind of many different extensions of that that I think users are still discovering. So one is we let you give a description of the column. We let you give instructions of a column. We let you create custom columns. So we have like 30 plus predefined fields that users can extract, like what were the methods? What were the main findings? How many people were studied? And we actually show you basically the prompts that we're using to
Streamlining Life with Organized Processes Continuing from our previous discussion on the importance of understanding values, let's delve into the practical aspect of implementing systematic processes to enhance efficiency and effectiveness in our lives. From Chaos to Order Systematizing tasks is akin to transforming chaos into order. By organizing repetitive tasks into structured systems, we streamline our workflow and reduce the time and effort required for completion. This applies not only to work-related responsibilities but also to everyday chores and commitments. The Three-Step Approach: Organize, Supervise, Deputize The process of organizing tasks is just the first step. The subsequent phases—supervision and deputization—are equally vital. Once a system is established, it's essential to train others or delegate tasks to ensure continuity and efficiency. Supervising the execution of these tasks ensures that they are performed effectively and identifies any areas for improvement. Ultimately, successful delegation enables us to focus on higher-priority activities and fosters growth both personally and professionally. Linking Tasks to Values A key aspect of effective task management is aligning each task with our values. This principle of "link it or sync it" ensures that every action resonates with our intrinsic or extrinsic values. By infusing purpose into our daily tasks, we cultivate a sense of fulfillment and motivation, driving us towards our goals with clarity and conviction. Reframing Tomorrow with Madonna's Process The Madonna process offers a simple yet powerful technique for reframing our approach to daily tasks. By associating each activity with a value or aspiration, we transform our perception of mundane tasks into meaningful endeavors. This shift in perspective not only enhances our productivity but also imbues our day with purpose and excitement. Embracing Total Recall: The Arnie Process As we reflect on our day, the Arnie process—total recall—empowers us to recognize the moments that align with our values and aspirations. By revisiting each hour before sleep, we reinforce our sense of self-worth and purpose. This nightly ritual instills a deep sense of gratitude and contentment, reaffirming our commitment to our journey and fostering restful sleep. Conclusion: Embracing Efficiency and Purpose Incorporating systematic processes and aligning tasks with our values are essential components of a fulfilling and purpose-driven life. By organizing, supervising, and delegating tasks effectively, we maximize productivity and create space for growth and self-reflection. As we navigate each day with intention and mindfulness, we cultivate a sense of fulfillment and alignment with our true purpose. So, let's embrace the power of organized processes and conscious living as we journey towards our dreams and aspirations. Wishing you a day filled with purpose and productivity. Warm regards, Chris
Frank and Jacque discuss pool chemical safety and things pool owners and parents can do to reduce drowning risks. Get 10% off on Camereye purchase from camereye.ai with coupon code DEEPEND24 - the ultimate pool safety and monitoring solution. The Deep End Pool Podcast focuses on residential pool maintenance and may not cover commercial pool requirements. Please consult the CDC and local authorities and code requirements for commercial pool maintenance. Email us questions and show suggestions at deependfrank@gmail.com. visit our home page thedeependpoolpodcast.com Our sponsors for the 2024 podcast season. poolwerx.com. jandy.com. bluerayxl.com cyclonefiltertools.com. ipssa.com allsafepool.com clearcomfort.com poolmagazine.com 00:00 Intro 08:30 pool chemical storage 09:39 neutralize acid spills with alkalinity increaser/sodium bicarbonate 11:00 do not vacuum chemical spills with a vacuum cleaner 11:40 How to add acid to your pool, and always add chemicals to water, never add water to chemicals. 13:35 Do not add chemicals to your skimmer unless the instructions on that particular chemical call for it 16:15 Diatomaceous Earth is an inhalation hazard, where breathing protection, like a covid mask, to prevent inhaling the DE dust 17:40 teach children to swim. You can start as young as 4 to 6 months old. 18:45 Drowning is the number one cause of death for children between ages of 1 to 4, and the number 2 cause of death for children 5 to 13. A kid with formal swim training is 88% less likely to become a drowning statistic. 20:20 do not swim or allow children to swim in cloudy water 20:49 make sure swim vests or drowning prevention vests or floats are certified by the USCG United States Coast Guard 21:15 make sure children have adult supervision when around water. Don't just be there, be aware 22:50 learn CPR 23:30 ASTM approved barriers to prevent entry to all pools and spa areas. 26:00 child proof locks and alarms on windows and doors that open into a pool area 26:20 camera systems. Camerey.ai has an incredible monitoring system that uses artificial intelligence to identify potential danger in and around the pool. Use coupon code DEEPEND24 to receive 10% discount on online purchases 32:50 stay away from floor or wall drains. make sure existing drain covers are VGB compliant 34:07 Keep long hair pulled up when swimming 34:35 wear well fitted swimsuits and avoid swimsuits with lots of strings and decorations that can be caught on ladders, drain and return fittings, etc... 35:55 Red Cross list: 1. Never swim alone. 2. Supervise children. 3. Always wear life vests. 4. Always jump in feet first. 5. Reach, throw, don't go. 6. stay away from pool drains 7. only swim designated areas 8. avoid alcohol 9. Know CPR 39:41 if having a party for adults that will include alcohol, have a designated sober person
The old jarhead is back with great career advice.• The advice is guaranteed to work and is based on the BAMCIS concept: Begin planning, arrange for the reconnaissance, make the reconnaissance, complete the order, issue the order, and supervise.• This concept was taught at the beginning of his Marine Corps career and can be applied to any job or situation.• Begin planning by setting aside time to think about what needs to be done.• Arrange for the reconnaissance by talking to other people who may be involved.• Make the reconnaissance by gathering all necessary information.• Complete the order by delegating responsibilities to team members.• Issue the order by clearly communicating tasks and expectations.• Supervise and make yourself available for guidance and help as needed.• BAMCIS can be helpful in a variety of situations and should be customized to fit your specific circumstances.• To learn more, check out "Find a Job That Fits Your Life" on Amazon.
María Santos nos trae las noticias del sector.
Kate Walker joins Allison in today's episode to explore why wanting to be a better supervisor than you had isn't going to make you a better supervisor & how to mitigate your liability as a supervisor. Sponsored by: TherapyNotes®: Use promo code Abundant for 2 months free To learn more about today's guest, visit https://www.abundancepracticebuilding.com/blog. Attention Abundance Community members: Kate Walker is our March trainer. For details on the live training via Zoom, check out the event listing in the private Abundance Community Facebook group &/or the "Upcoming Events" section of your membership portal. To check out our free resources, including weekly worksheets & our Tasky Checklist, visit https://www.abundancepracticebuilding.com/links. Learn how to fill your practice with the Abundance Party! Join today & get 75% off your first month with promo code PODCAST: https://www.abundancepracticebuilding.com/abundanceparty
In this episode of the Learning While Working Podcast, Andrea Laus explores the importance of role plays for developing crucial human skills, the potential pitfalls in traditional role play designs, and the transformative impact of a digital approach to role plays guided by technology. Andrea als unpacks how AI can enhance role plays, improve the feedback process, and ultimately revolutionise the L&D landscape.About Andrea LausAndrea Laus has spent the last 20 years developing effective strategies for talent development. He is the CEO of SkillGym, which designs state-of-the-art digital role plays for rebalancing knowledge-based training approaches with actionable practice. He regularly shares his ideas about effective training methodologies and strategies through his blog, and speaks at several HR and L&D conferences around the world on these fascinating subjects. Key takeaways:The importance of role plays in learning experiences: Andrea shares how it's crucial for developing human skills such as communication, collaboration, and problem-solving. It also creates a safe environment for practising real-life scenariosOn the challenges and misconceptions about role plays: Learners often feel judged and uncomfortable during role plays. There is a common misconception too that soft skills are “soft” – in reality they require dedicated effort and practice. It helps to understand these barriers so you can create the best learning environment.The application of technology and AI: Andrea highlights that, when used thoughtfully, technology can have a very positive impact. AI can help generate dialogues and responses, standardised and effective feedback, and it can assist in tracking and analysing learner actions. However, it is vital to select the right technology for specific learning objectives. Segmented time stamps:(00:00) Introduction(04:05) Handling the feeling of judgement in role plays(07:06) Leveraging role plays for sense making in learning(12:15) Practice with digital standardised and accelerates improvement(17:50) Supervise generative AI for writing dialogues(23:39) Measure and improve with technology-driven feedback(26:37) Utilise strategies, trust the process, embrace technologyLinks from the podcastConnect with Andrea Laus on LinkedInCheck out SkillGymWatch the recording of the Upskilling Using Artificial Intelligence: AI Digital Role Play webinar
3 Steps to Potty Train Your Puppy. More info in my book Potty Training Your Puppy.1) Your puppy should always be supervised or confined while indoors. Supervise your puppy closely or have them in the crate. Supervised means you will see it taking place if your puppy has an accident. The only exception to this rule is if you know your puppy has just gone potty and now has an empty bladder or colon. Then, you may be able to get away with a brief period of less intense supervision, but never leave your puppy completely unsupervised. Watch for sniffing, crying, circling, panting, or suddenly wandering away from you and going off to the corner or near a wall. These are signs that they need to go potty.2) Take your puppy outside on a leash as often as possible. Puppies 8-12 weeks must go out at least every hour, supervised while on a leash. Set up your walk to match your puppy's patterns. Take them to their place to go potty. Now say “go potty, go potty” very enthusiastically. Keep repeating this command until they do. If they do not potty after 10-15 minutes, bring them back inside, put them in a crate for 10 minutes, and then bring them outside again to repeat the process.3) Give your puppy praise and a treat immediately after they go potty outside. Choose a high-value food reward you will use to give your puppy once they go potty outside on the grass. Praise your puppy for going potty on the grass, provide them with a lot of affection and say “good boy or good girl” so they understand that you are praising them for doing something good. More info in my book Potty Training Your Puppy.Purchase my new book Potty Training Your Puppy here https://www.amazon.com/dp/B0BNGRNXNX Discover a simple and effective method for loose-leash walking your puppy with my new book Leash Training Your Puppy.RESOURCES:Podcast Website: http://puppytalkpodcast.comSponsor Website: http://topgundogtraining.comDale's books: https://www.amazon.com/author/dalebuchanan
Clare parents are being advised to supervise their children with videogames and smart devices they get this Christmas A CyberSafeKids report found over a quarter of primary school aged children have faced cyberbullying in the past year. With smartphones, game consoles and tablets among the most popular Christmas presents, parents are advised to understand the technology before giving to their children. Pat Clarke Browne from Munster Business in Shannon is urging parents to lay ground rules with children around internet safety.
Will swarms of unmanned aerial vehicles be able to aid humans in wildland firefighting or package delivery? Research summarized in a new paper in Field Robotics represents a big step towards realizing such a future. In this interview, Professor Julie A. Adams describes the research showing that one person can supervise more than 100 autonomous ground and aerial robots.
This is a podcast episode where we explain the many rules for our staff to supervise dog playing together. We never leave our client's dogs unattended without a staff member supervising their play, and this podcast episode explains how we make sure everybody is safe and comfortable during playtime!
Do professional cleaners require supervision? Host Angela Brown and AK Building Services VP Shari Cedar tackle this common question. While responsible crews work independently, Shari explains oversight is key. Hear how cleaning companies aim for accountability through staff training, checklists, and leadership. Discover the keys to maintaining a high standard of cleanliness, efficiency, and client satisfaction through structured supervision, and learn how this can be applied in various cleaning contexts. Do We Need to Supervise Professional Cleaners Chapters: 00:00 Introduction and Excitement for Guest Speaker Shari Cedar 00:22 Importance of Training and Supervision in Commercial Cleaning 01:47 Quality Assurance and Retraining for Correct Cleaning Practices 02:10 The Use of Scan Codes for Accountability and Inventory Tracking 03:46 Different Perspectives on the Use of Scan Codes in Cleaning RESOURCES ----------------- The Ultimate Guide to Move In Move Out Cleaning - https://amzn.to/45RX0KZ Dyson Slim Ball Multi Floor Animal Upright Vacuum Cleaner - https://amzn.to/3QwQ28z OdoBan Professional Cleaning BioStain and Odor Remover - https://amzn.to/47uHbvb Forlivese 3 Pack 25 Inch Drain Clog Remover - https://amzn.to/47hmi6u Magic Erasers from Mr. Clean Professional - https://amzn.to/49lKfeP (When available, we use affiliate links and as Amazon Associates we earn a commission on qualifying purchases.) *** RATE THIS PODCAST *** https://ratethispodcast.com/askahousecleaner *** TRAINING & CLEANING CERTIFICATION*** https://savvycleaner.com/join *** MOST REQUESTED LIST OF CLEANING STUFF I USE *** https://www.Amazon.com/shop/AngelaBrown SOCIAL MEDIA --------------- *** CONNECT WITH SHARI ON SOCIAL MEDIA *** LinkedIn: https://www.linkedin.com/in/sharisolomoncedar/ *** CONNECT WITH ANGELA ON SOCIAL MEDIA *** YouTube: https://www.youtube.com/@AskAngelaBrown Facebook: https://www.Facebook.com/AskAngelaBrown Twitter: https://Twitter.com/AskAngelaBrown Instagram: https://instagram.com/AskAngelaBrown Pinterest: https://Pinterest.com/AskAngelaBrown Linkedin: https://www.linkedin.com/in/AskAngelaBrown TikTok: https://www.tiktok.com/@askangelabrown Store: https://www.amazon.com/shop/AngelaBrown URL: https://AngelaBrown.com NEED MORE CLEANING HELP? ------------- *** GOT A QUESTION FOR A SHOW? *** Please email it to Angela[at]AskaHouseCleaner.com Voice Mail: Click on the blue button at https://askahousecleaner.com *** PROFESSIONAL HOUSE CLEANERS PRIVATE FACEBOOK GROUP *** https://www.facebook.com/groups/ProfessionalHouseCleaners/ *** VRBO AIRBNB CLEANING FACEBOOK GROUP *** https://www.facebook.com/groups/VRBO.Airbnb.Cleaning/ *** LOOKING FOR A WAY TO GET MORE CLEANING LEADS *** https://housecleaning360.com SPONSORSHIPS & BRANDS ------------------- Today's #AskaHouseCleaner sponsor is #SavvyCleaner training and certification for house cleaners and maids. (https://savvycleaner.com/join) And your host today is #AngelaBrown - https://g.page/r/CbMI6YFuLU2GEBI/review *** ADVERTISE WITH US *** We do work with sponsors and brands. If you are interested in working with us and you have a product or service that makes sense for the cleaning industry here's how to work with us -https://savvycleaner.com/brand-deals *** SAVVY CLEANER BRANDS *** SAVVY CLEANER - House Cleaner Training and Certification – https://savvycleaner.com/join VRBO AIRBNB CLEANING – Cleaning tips and strategies for your short-term rental https://TurnoverCleaningTips.com FUNNY CLEANING SHIRTS – Incentive and thank-you gifts for house cleaners and maids. https://FunnyCleaningShirts.com HOARDING WORLD - Helping you change your relationship with stuff https://HoardingWorld.com REALTY SUCCESS HUB - Helping you sell your home fast https://realtysuccesshub.com CREDITS -------------------------- Show Produced by: Savvy Cleaner: https://savvycleaner.com Show Host: Angela Brown Show Editor: Anna Nikitchuk Show Producer: Anna Nikitchuk
This newish Urbana resident and newish CEO to the Don Moyer Boys & Girls Club (DMGBC) is a much needed and welcome addition to our community. Her sweet demeanor, extensive experience in the non-profit sector and tireless work ethic is beyond commendable. Listen as Amy talks about raising babies while going to school and working as a housekeeper, becoming a temporary guardian simply because there were kids in her orbit who needed a home, why she signs her emails "peace," the overall increase in guns and violence since she got her specialized degree a few decades ago and the overall decrease in violence in our community since she started at the DMBGC and why her house was the one kids gravitated towards. Lastly, Amy plugs a spectacular fundraiser: Dancing With the CU Stars on November 3, vote at one.bidpal.net/dwtcus23.Thank you so much for listening! However your podcast host of choice allows, please positively: rate, review, comment and give all the stars! Don't forget to follow, subscribe, share and ring that notification bell so you know when the next episode drops! Also, search and follow hyperlocalscu on all social media. If I forgot anything or you need me, visit my website at HyperLocalsCU.com. Byee.
This week we will discuss Eye Safety for children. Eye injuries affect about 2.4 million people every year. Household products cause more than 125,000 serious eye injuries. Hospital emergency rooms treat nearly 23,000 victims of eye injuries from sports. Toys and home playground equipment cause more than 11,000 injuries to young eyes. Below are tips for preventing injury to your child's eyes. Here are some tips for eye safety for children: Avoid sharp, broken toys and objects. Wear sport goggles and sunglasses. Do not play around lawn mowing and fireworks. Avoid BB, pellet, NERF®, and dart guns. Always carry pointed objects such as scissors, knives or pencils with the sharp end pointing down. Never shoot objects (including toys) or spray things at others, especially in the direction of the head. Read and follow directions before playing games or using equipment. Make sure your child wears safety goggles or glasses during sports and leisure activities. Make sure your child wears sunglasses that have 100% UV protection. Only buy toys meant for their age. Show them how to use their toys safely. Supervise them when they play. Look into the durability of lens material. Ask for warranty information on both the frames and the lenses. About 90% of eye injuries can be prevented with protective eyewear. An ophthalmologist, primary care doctor, school nurse or children's health service should examine the eye as soon as possible, even if the injury seems minor at first, as a serious injury is not always immediately obvious. Delaying medical attention can cause the damaged areas to worsen and could result in permanent vision loss or blindness. While seeking medical help, care for the child as follows: DO NOT touch, rub or apply pressure to the eye. DO NOT try to remove any object stuck in the eye. For small debris, lift eye lid and ask child to blink rapidly to see if tears will flush out the particle. If not, close the eye and seek treatment. Do not apply ointment or medication to the eye. A cut or puncture wound should be gently covered. Only in the event of chemical exposure, flush with plenty of water. Credits: URMC / Encyclopedia / Preventing Eye Injuries in Children Search Encyclopedia
Instead of teaching children the basics, school officials are pushing an agenda. Constitutional expert, lawyer, author, pastor, and founder of Liberty Counsel Mat Staver discusses the important topics of the day with co-hosts and guests that impact life, liberty, and family. To stay informed and get involved, visit LC.org
Sara O'Heron, MD discusses changes in the education and training of NPs and PAs over her 35-year career.Learn more at PatientsAtRisk.comGet the new book, Imposter Doctors, available in paperback, eBook and Audible: https://www.amazon.com/Imposter-Doctors-Patients-at-Risk-ebook/dp/B0C4J3P3Z1/PhysiciansForPatientProtection.org
Tony Brewer is the Founder and Director of Orphan Voice Ministries. Have lived in Vietnam for the past 14 years. Supervise a staff of 20 who work in the general ministry areas of orphan care, care for special needs children, anti-trafficking outreaches, ministry to the poor, and underground evangelism. We operate 2 therapy centers, an orphanage, a deaf school and also conduct anti/trafficking seminars in public schools Orphan Voice on FB, twitter and linkedin.If you want a speaker in your school, email liz@savethekids.org and we will get you hooked up! OR fill out the form below.https://savethekids.wufoo.com/forms/z14ppj991ad9jfq/Make sure to check us out on Instagram!@savethekidsinc@bulliesbe.goneIf you want to support STK, use on of the affiliate links bellow for GABB and Pinwheel phones (STK approved and safe for kids)https://www.pinwheel.com/?via=lizhttps://gabbwireless.com/ - code STKSupport the show
The Troop Leading Procedures are essentially a cheat code for how to lead military teams. Whether you are in the development program, in the pipeline, on a team, or a leader of a large organization, these procedures are a basic food group for all tactical operations. For all of you folks who are thinking about a career in the military, this one is packed with information that will immediately improve your ability to lead teams. For all our civilian friends- from first responders to business professionals- this also works for you! The steps are listed in order below with time stamps and we included some acronyms we used in case we accidentally glossed over something. ACRONYMS:METT-TC : MISSION, ENEMY, TERRAIN, TROOPS AVAILABLE, TIME, CIVILIAN CONSIDERATIONSTLPs: TROOP LEADING PROCEDURESMDMP: MILITARY DECISION-MAKING PROCESSCOA: COURSE OF ACTIONISR: INTELLIGENCE, SURVEILLANCE, AND RECONNAISSANCEGOTWA- GOING, OTHERS IM TAKING, TIME OF RETURN, WHAT IF I DONT RETURN, ACTIONS ON CONTACT#podcast #military #onesready 00:00 CardoMax Code ONESREADY and Hoist ONESREADY 02:57 Intro and What are the troop leading procedures?05:23 Step 1 - Recieve the Mission - WHAT ARE YOU BEING ASKED TO DO? 08:00 Step 2 - Issue the WARNO - 5W's JUST GET THE INFORMATION OUT 11:00 Step 3 - Make a Tentative Plan - GET YOUR IDEAS OUT THERE13:00 Step 4 - Initiate Necessary Movement - GET YOUR PEOPLE MOVING 16:00 Step 5 - Conduct Reconnaissance - EYES/ISR/MAPS/SR/INTEL18:46 Step 6 - Complete the Plan - CALL YOUR SHOT AND MOVE FORWARD20:00 Step 7 - Issue the Order - BRIEF YOUR PLAN AND GET APPROVALS23:23 Step 8 - Supervise and Refine - CONTINUE PLANNING AND PLAN FOR RISK 28:11 METT-TC33:00 Priorities of work35:15 The Biggest Lie in the Military; "Work Through Lunch, Get off Early", getting sleep when you canAs always, THANK YOU for your support, we truly appreciate it.#podcast #military #pilot The views and opinions expressed by the OnesReady team and all guests are those of the team and themselves, and do not reflect the official policy or position of the DoD. Any content provided by our Podcast guests, bloggers, sponsors, or authors is their opinion and is not intended to malign the DoD, any religion, ethnic group, club, organization, company, individual, or anyone.Collabs:18A Fitness - Promo Code: 1ReadyAlpha Brew Coffee Company - Promo Code: ONESREADYATAC Fitness - Promo Code: ONESREADYCardoMax - Promo Code: ONESREADYEberlestock - Promo Code: OR10Hoist - Promo Code: ONESREADYStrike Force Energy - Promo Code: ONESREADYTrench Coffee Company - Promo Code: ONESREADYGrey Man Gear - Promo Code: ONESREADY The content provided is for informational purposes only and does not constitute legal advice. The host, guests, and affiliated entities do not guarantee the accuracy or completeness of the information provided. The use of this podcast does not create an attorney-client relationship, and the podcast is not liable for any damages resulting from its use. Any mention of products or individuals does not constitute an endorsement. All content is protected by intellectual property laws. By accessing or using this you agree to these terms and conditions.
Friday Hour 1, Segment 1The Mike Taylor show airs weekdays on Ticket 760 (KTKR) from 2PM to 5PM.Follow Mike on Twitter: @MikeTaylorShowFollow Puma on Twitter: @biggestpumaFollow EZ on Twitter: @ErvinZelaya
Indianapolis Metropolitan Police Department (IMPD)Indianapolis Metropolitan Police Department (IMPD)15 yrs Public Affairs (Media Relations) Supervisor - LieutenantSupervise a team of officers who are responsible for promoting the agency both internally and externally through a variety of methods including interviews, press releases, social media and direct interpersonal communication.Supervise a team of officers who are responsible for promoting the agency both internally and externally through a variety of methods including interviews, press releases, social media and direct interpersonal communication.Sponsored by the Social Media Strategies Summit. Check out their website to learn more about their upcoming social media conferences for Public Safety and Government professionals. https://bit.ly/3IrRdDL
Get another inside scoop of what it's like to work in Hollywood as Michael Jamin sits down and talks with Eric Fogel, a DreamWorks animator.Show NotesEric Fogel Website: https://www.eric-fogel.com/Eric Fogel Wikipedia: https://en.wikipedia.org/wiki/Eric_FogelIMDB: https://www.imdb.com/name/nm0283888/Michael's Online Screenwriting Course - https://michaeljamin.com/courseFree Screenwriting Lesson - https://michaeljamin.com/freeJoin My Watchlist - https://michaeljamin.com/watchlistAutomated TranscriptEric Fogel (00:00):You gotta have, you know, there's, there are a couple of key ingredients, right? You, you gotta have the passion, right. For it, for the craft. You have to have the ability mm-hmm. to have, to have the skills. Michael Jamin (00:14):But you didn't have the ability when you started. Right?Eric Fogel (00:18):I had some ability.Michael Jamin (00:19):Some ability. AndEric Fogel (00:20):I kind of, yeah. I mean, a lot of it is you, you have to immerse yourself and you have to just make things. And you have to learn as you make things. You can't, you know, you can watch YouTube videos all day long, but you gotta like, just get in it.Michael Jamin (00:35):You're listening to Screenwriters Need to hear this with Michael Jamin.Michael Jamin (00:43):Hey everyone, it's Michael Jamin. Welcome back to Screenwriters. Need to hear this. This is the podcast that it's not just for screenwriters. Cuz I, I have a special guest today. This is my friend and once collaborator Eric Fogel. And he, we were, we were debating like, how do I, how do I introduce him? Cuz he does so much. He's a writer, he's a director, he's an animator. He's now a dreamworks. And Eric Fogel's now gonna tell us is how, how, how all this works. He's gonna explain to me, Eric Fogel, thank you so much for being on the show. Say hi. Hello.Eric Fogel (01:13):Hello. Hello. Hello.Michael Jamin (01:15):You're not an actor though. That's the one thing you, that's the one credit you don't get.Eric Fogel (01:19):I do a little voice acting.Michael Jamin (01:20):Do you do, doEric Fogel (01:21):You know I've done, yeah, I, yeah, I I actually got my SAG card. Yeah.Michael Jamin (01:25):ReallyEric Fogel (01:27):Little, little.Michael Jamin (01:28):So, so for everyone's listening, so Eric and I worked together years ago on a show called Glen Martin dds, which he cr co-created. And on that show, he was the he was one of the, he directed with me, directed the animation. He was in charge of all the designs, all the character designs. And then he had the misfortune of having to fly back and forth from Los Angeles to Toronto, like every week to oversee the animation focal. How did that, how, how did that all come about? How did, how did you sell that show? How did it come about that show?Eric Fogel (02:01):Man so yeah, I think I was, I was in town. I was, you know, I was living in New York at the time, and so I, I was I, I did a trip out here to, to LA to do like, around the meetings. And I was, I was in my I was up in my manager's office and the, the owner of the company, Gotham sh just kind of walked by and she goes, oh, yeah, he should meet Scoop,Michael Jamin (02:31):Right?Eric Fogel (02:31):And I'm like, what the fuck is a scoop? Can I say ? Is that all right?Michael Jamin (02:37):We all, we're all thinking of it.Eric Fogel (02:38):Yeah. Yeah. What's, what's a Scoop scoop?Eric Fogel (02:43):That was my, so that was my introduction. So yeah, we, we set up a meeting, I met with Scoop in LA on that same trip, I think it was my last meeting. And they had a scriptMichael Jamin (02:55):Just a, so Scoop was a, the nickname of one of the executive producers, or Michael Eisner's company.Eric Fogel (02:59):Scoop is a human. Yeah. He was, I guess running development for Michael Eisner's company, which was Tornante. Yeah, right. And they had, they had a script. They had like a version of a pilot that was written by Alex Berger. Right, right. And you know, it was still pretty rough at that time. It needed, needed some love. And, you know, there was no, there were no designs. You know, there was nothing there. But couple weeks later I met, I g I met with Michael Eisner in New York, and we sat down, we started talking about this project, and he had seen some stuff on my reel, and he saw some, some stop motion that I did, you know, I created Celebrity Death Match. So I think he was aware of, of that. But I, I did this other show called Star Val with a studio called Cup of Coffee in Toronto.Michael Jamin (03:51):I didn't realize that was Cuppa, but Wait, hold on. Was that, was, was what Network was surveillance onEric Fogel (03:56):EMichael Jamin (03:57):E. So I wanna, I wanna slow this down. Yeah. I wanna interrupt you for a second. So celebrity Death Match was like a huge hit. I was on MTV for a couple seasons, right? Yeah. And it was a stop motion animation, and you were in charge, and you create, created that with custom and you were in charge of the a It was a big, it was like a big deal for like, I don't know, 10 minutes, but it was .Eric Fogel (04:17):Yeah, no, we, we, we, we ran for Yeah. A couple years and, you know, close to a hundred episodes a lot.Michael Jamin (04:23):So, all right. But then, okay, so back it up and how, cuz you have a very unusual career because you kind of, you've carved a career for yourself that doesn't really, it doesn't even exist really. You know, not many people who do what you've done. Like, how, how did you start when you were a kid? Did you wanna, what did you wanna be?Eric Fogel (04:41):I, I knew I wanted to be in the film business in some way. I think, you know, when I was, you know, I was always drawing like little comic books when I was a kid. And these, these comic books were basically storyboards.Michael Jamin (04:54):Right. Eric is really good, talented artist. So that, I should mention that Illustra Illustrate. I don't know what you would call yourself. You're good though. Go on. You're okay.Eric Fogel (05:03):But by the time I was like, you know, in, in high school, I, I sort of learned that there was like, you could actually go to school to learn how to make films. Yeah. You know, like, there was such a thing. And, and I became aware of, you know, Y u and that, that sort of became my, you know, the thing that was driving me. I even before that, I started taking some film while I was still in high school. I took a couple film classes at, at school of Visual Arts, just taking college level classes there while, you know, still still a kid in high school and starting to like, figure out how to make, make films and, you know, put stuff together. And then I gotMichael Jamin (05:42):Live, it wasn't stop motion, it wasn't animation, it was just film.Eric Fogel (05:45):It was live action. I was still, I was also experimenting, you know, I got, I got a super eight camera, so I was trying, I was trying some stop motion. I was doing like, hand drawn animation. I was just trying everything I want. I was just absorbing everything. Yeah. You know? And yeah. And then got accepted to NYU and inMichael Jamin (06:05):The film program.Eric Fogel (06:06):Film program. Okay. 19. Yeah. Graduated class of 91.Michael Jamin (06:13):91.Eric Fogel (06:13):And, you know, I was pretty prolific there. Like they, I think they only required you to make, to finish like one film. And I ended up making four, finishing four films. Two were live action and two were animated. Right. And one of the animated films was this really violent like a post-apocalyptic thing. It was called The Mutilated. I've heard ofMichael Jamin (06:39):It. Ok.Eric Fogel (06:40):That, yeah, there's actually a,Michael Jamin (06:42):Well, look, you gotta sell. Okay.Eric Fogel (06:44):Yeah. There's a mu later.Michael Jamin (06:46):That's from, and that was from a college?Eric Fogel (06:48):Yeah, this was my college. This was my college film. Mutilate. But the, so this film got got licensed to like a, an animated like a film festivalMichael Jamin (07:02):Called, well, you, wait, you submitted it to a film festival. What doEric Fogel (07:04):They They saw it, they saw it in the Y U Circuit. Okay. Cause premiered there. And then they reached out to me and they said, we wanna a license Mutilators to be, it was a Spike and Mike spike and Mike's Festival of Animation.Michael Jamin (07:19):Right.Eric Fogel (07:20):AndMichael Jamin (07:21):So they paid you forEric Fogel (07:22):It? They, they wrote me a check, and that was the first time, you know, someone was like, paying me to, to make a thing.Michael Jamin (07:30):And then what happened?Eric Fogel (07:31):So I said, all right, that, that worked well. I want to keep doing that. So I just kept making, making like little short films. And I, I licensed a couple more to, to those guys, to the Spike and Mike Festival. And they would do this thing where they would, they would option the film, but they would also give you like com like a little money to, to finish the film. Which was, which was pretty, you know, it's not a, not a great deal. But it was, at that timeMichael Jamin (07:59):It was, these were like shorts, right?Eric Fogel (08:01):Yeah. Yeah. Just shorts. But, you know, you would send them, like, you could send them like a pencil test, and then they, they'd say like, here's a couple grand to finish it. And then, then they would like show it in their, their circuit.Michael Jamin (08:15):So, all right. So then, but you're okay, you're selling some stuff. It's got after college, you're not making a fortune. Yeah. You're, but you also have like a day job.Eric Fogel (08:24):I was I was hired. So I started working in a, in a small animation studio in New York, Uhhuh at that time. And I was learning, you know, just learning stuff. So one of the one of the directors at that studio he, he had a little problem with substance, substance abuse problem. Interesting. I'm not gonna mention any, any names, but he would, he would spend a lot of time just sleeping, sleeping it off. Yeah. And I, and he and I would, I would be animating his shots. And that's how I learned a lot of, a lot of stop motion. It was, it was like a stop motion studio. And I learned a lot. SoMichael Jamin (09:01):You, so you're right. So this is before computer animation, really. You're just kind of you're drawing, you're basically cell by frame By frame.Eric Fogel (09:07):Yeah. Yeah. And just using like a big old Mitchell 35 millimeter camera, just frame one frame at a time.Michael Jamin (09:14):And then, okay, so you did that for a little bit, then what happened?Eric Fogel (09:17):So at, so at the same time, I'm still making these little short films eventually.Michael Jamin (09:23):What was the point of making these short films, though? They're not adding slide actionEric Fogel (09:26):To get a reel together. So, so you to have like a sample sample of your, your stuff. Right. So eventually this real end ends up on the desk at the president of MTV Animation.Michael Jamin (09:40):How, how did it wind up there?Eric Fogel (09:42):I don't know.Michael Jamin (09:44):, but this is a good point. Like, cuz you're just putting your work out there. Yeah. And it's gonna, and it's good. So it's making the rounds, right?Eric Fogel (09:51):Yeah. It's, well, it's, it's, it's making the rounds. I don't know if it's good, but PE people are, there's no, but if itMichael Jamin (09:58):Wasn't good, they wouldn't pass it along. I mean, that's the truth.Eric Fogel (10:01):Yeah. Well, it, it was something, you know, at that time, M T V was, you know, animation was brand new and they, they were looking, you know, they were just looking for weird shit. Yeah. You know, and they saw, they, you know, they probably saw this, this spike in Mike festival and, and you know, like liquid television was becoming a thing. Right, right. And so they were hungry for stuff and, you know, just weird stuff. Right. And I, you know, I had some weird stuff on my reel.Michael Jamin (10:27):Yeah, you did. Well, yeah. And so, okay, so then what happened?Eric Fogel (10:31):So they, so M T v made, made me a deal to option this mutilated.Michael Jamin (10:37):Okay. AndEric Fogel (10:37):The plan was to have the, the Mutilators character appear within the Beavis and Butthead show. Mm-Hmm. . And, and it would be like, it was gonna be like this thing that they were gonna watch on tv and it was gonna be this cool thing that they liked. Right. Kind of fit, fit with their, their thing. Yeah. And then something, something tragic happened there were, there were some kids out west somewhere who burned their family's trailer down. And they said they, they learned how to, like, about fire from Beavis and Butthead.Michael Jamin (11:15):Oh, I, I At least it wasn't mutilated.Eric Fogel (11:18):No, no. But this created this whole wave, like this backlash. And all of a sudden MTV got scared and they said, oh, you know, we got, we can't, we have to be careful. And Mutilators was like violent. Yeah. Even though it was, it was sci-fi it was fantasy violence. It wasn't real. Yeah. But they were, they were just, they got cold feet. So I went to this meeting knowing that they were gonna shit can Mutilators and, and I had already set up like a little studio in my, in my house at, on Long Island, and I was like in production on this thing. So I was, I was nervous. Yeah. So I go to this meeting and, and Mike Judge is actually there. Mike Judge, the creator of Beavis and Butthead, he's, he's in this meeting and they're like, Eric, you know, we we're not, we can't go forward with Mutilators, but we, we like you, do you have anything else?(12:08):And I, I had this storyboard. I actually brought it to that meeting. And this, it was for this other thing that I had come up with about this guy with like a giant head and, and an alien that lived inside of this head. And it was like, about the symbiotic relationship Yeah. Between a guy, a guy, and an alien. And my judge, I just, I'll never forget this. He was kind of like hanging back and he was looking at my drawings and he was just laughing. Yeah. And these other two MTV execs were like, oh, Mike, Mike likes it. We should buy this. And they did and,Michael Jamin (12:44):And Muo was that,Eric Fogel (12:45):That was called the Head. Right. And that was it was part of like, it was called MTV's Oddities.Michael Jamin (12:51):Uhhuh .Eric Fogel (12:51):And that was, I was like 24 or 25. And that was the first show that I ran as a creator.Michael Jamin (12:58):But this is the kind of, this speaks to which is so important. It's like you were making this stuff because you were making it, and you were, it wasn't like, it wasn't even like, you weren't trying to sell that you were just making, you had, you have to have stuff to have.Eric Fogel (13:09):I had an idea.Michael Jamin (13:10):Right. And you worked on it. You didn't wait to get paid on it. You worked on it.Eric Fogel (13:14):Yeah.Michael Jamin (13:15):Right. And so, and you were, you were right. Did you have a small staff on that show?Eric Fogel (13:20):Yeah, we had, you know, we had a full staffMichael Jamin (13:23):On that and now was at Outta New York.Eric Fogel (13:26):We, we did, we ran the, the show out of, yeah. Out of MTV Animation in Midtown Manhattan. Wow. You know, set up shop there. I wrote, and I wrote an and show around that show with a, I had a, a writing partner at that time. And yeah, we wrote all the episodes and it was, it was wonderful because it was like, it's not like now, like, it was like, they were hands off, like creatively. They were like, yeah, great. It's great. Just do it. Do it. Do what you want. Do what you want.Michael Jamin (13:57):Interesting. That's so interesting. Wow. And then, and then at what point was this? Is there, what point did you make a leap to LA? Or, or am I missing something in between?Eric Fogel (14:05):Yeah, so I, you know, I stuck it out. So after the head, I did Celebrity Death Match.Michael Jamin (14:10):Right. That was outta New York.Eric Fogel (14:11):And then, you know, I continued working at small studios in New York. MTV animation closed, like shortly after nine 11, they shuttered. And, you know, business in New York kind of started to dry up after nine 11.Michael Jamin (14:27):There wasn't, there was never even a lot of business in New York. But I didn't even, you know,Eric Fogel (14:30):You No, but there was, yeah, there was, you know, m there was M T V and then there was some small commercial studios there. And I continued working at some of those smaller studios. You know, and we, all our family was there, so Right. We were sort of resisting the, the, the big move to, to la And then finally in 2008 when Glen Martin happened, and we made the move.Michael Jamin (14:54):Right. With your whole family. Yes. And then you flew back to tra that was the tragic part. If you had only stayed in New York, , your flight would've been soEric Fogel (15:02):Much. Yeah. I was like, honey, here's, here's our house kids. There's, there's your rooms. I gotta go. You guys figure it out.Michael Jamin (15:11):Enjoy the sunshine.Eric Fogel (15:13):My, my wife's still, she, you know, she, she's still pissed at me. We, no, we love each other, but No, it was, it was a tough move. We didn't know anybody here in la. Right. You know, it was a big, it was a big, big adjustment. And yeah, it was bit a shock.Michael Jamin (15:29):What does she think of it now? Is she happy you're here or No,Eric Fogel (15:31):I think, yeah, we've, we've made our peace with it. You know, we still miss our family. Our families are still all back east. Yeah. but we, we feel like it was a good thing for our family, you know, for our kids.Michael Jamin (15:44):Oh, you think so? You think they're, they're probably getting ready for college now. Your kids?Eric Fogel (15:48):Oh, they're almost done.Michael Jamin (15:50):They're almost done withEric Fogel (15:50):Cops. Well, one is, yeah. One our oldest is out. He's already graduated. And our, we have twin girls and they're graduating this this year.Michael Jamin (15:57):Oh God. We'll talk about that one. I know. Wonder what that's gonna happen. What happened there? Okay, so then, and then, alright. We did Glen Martin. And the thing about that is, so my partner and I were siber, we write these episodes. We come into your office and say, this is, this is the crazy that the craziest job you ever No, probably not. Cuz we would give you an assignment, like, this is the, what does this character look like in your head? Then you'd sketch a design and then we'd maybe give you notes or not. And then you'd run off. Then you'd fly to Toronto and they started a animated this thing. And you had to oversee every time there was a problem, we'd yell at you . And, and then you'd have to fixEric Fogel (16:33):It. Then I go yell at them and you'dMichael Jamin (16:35):Yell at them. And there was, yeah. There was always problems. It's always you know, because it's a, it's such a long process to, it took, you know, nine months to animate that show.Eric Fogel (16:43):That that show. I mean, there will never be another show like that. Right.Michael Jamin (16:49):Why do you feel that way?Eric Fogel (16:50):It was, I mean, just the concept was super ambitious, right? Yeah. You got, you got a family, you know, traveling from, from town to town every episode. Yeah. So every single episode you have to build a brand new world for this family to play in. Yeah. Right. That's a huge amount to build. And you have to build it all from scratchMichael Jamin (17:16):There. And there was a lot, we also did a lot of CGI on. We, not a lot. Some, you know, not,Eric Fogel (17:21):Not a lot.Michael Jamin (17:22):The mouses, the mouses, and also sometimes the backgrounds. Right. We would doEric Fogel (17:26):We would do some green screen. We'd do green screen. But, but a lot of those, I mean, most of those sets were, were Yeah. Physical, practical, physical models.Michael Jamin (17:36):I have all, I still have my dolls, just so you know. They're all here.Eric Fogel (17:40):Oh, hey, wait, IMichael Jamin (17:41):Got one. You have more. I remember when you had, you had your dolls. I was like, how do I get a hand? How do I get my hand on someone? Focals Dolls Eric Fogel (17:48):There.Michael Jamin (17:49):How Steal your dog. Which one's that? What's, oh, wait, but is that, was that from Glen? What was he, what was that?Eric Fogel (17:54):That hok? Honk Hawks The Clown. The Killer Clown. That'sMichael Jamin (17:57):Oh, we see What episode was that?Eric Fogel (17:59):I don't know. Sunshine. Fun, fun, fun. Bill Hawks.Michael Jamin (18:02):The Killer Clown did. There's so much about that show. I don't even remember.Eric Fogel (18:04):Remember who did The Voice?Michael Jamin (18:07):Who?Eric Fogel (18:08):Ty Burrell.Michael Jamin (18:09):That was Ty. Dude. We can you imagine We directed some amazing, amazing, remember we did, we directed Brian Cranston. Yep. When he was coming off break, he was doing BreakingEric Fogel (18:19):Bad. Still doing it. Yeah. Yeah.Michael Jamin (18:21):And he loved it. He's like, this is great.Eric Fogel (18:24):. He was amazing. We almost, we almost had a spinoffMichael Jamin (18:28):With him. Yes. Hi. That's him over here. Yeah. That'sEric Fogel (18:32):Drake Stone.Michael Jamin (18:34):That was a bummer. That didn't happen.Eric Fogel (18:36):Yep.Michael Jamin (18:36):Yep. Oh, well,Eric Fogel (18:38):But the cat, yeah. I, I mean we should talk about some of the other day players on that show because I meanMichael Jamin (18:45):Yeah, we, I mean it was amazing. The cat, we Every,Eric Fogel (18:48):Every day. Mel Brooks.Michael Jamin (18:50):Mel Brooks. Right.Eric Fogel (18:51):Billy Idol.Michael Jamin (18:53):Billy Idol. I don't remember Billy Idol.Eric Fogel (18:55):. He did a, he did the Christmas episode and he sang a song. He sang aMichael Jamin (18:59):Oh, right. Maybe it wasn't there. That I remember we had friend Drescher. Yeah. Remember were you there thatEric Fogel (19:04):Day? Yep.Michael Jamin (19:05):And we couldn't get her Remember? So, so Erica, we direct together, we'd whispered each other and it's not quite right. How did we get her to do, you know? And then I remember we finally walked up to her cuz she wasn't, the character wasn't quite white. And I was said, listen, can you do the nanny? She's like, oh sure. And then the then she started basically doing the nanny.Eric Fogel (19:23):You want the nanny,Michael Jamin (19:25):You want the nanny. You kind of, youEric Fogel (19:26):Want it, youMichael Jamin (19:27):Don't wanna ask. You wanna, you don't really wanna ask. You wanna get them there. Yeah. You know, I don't wanna insult her, but she was like, delight French. She was so sweet.Eric Fogel (19:35):Alison Jenny, she was great. She an Alexander.Michael Jamin (19:38):Yep.Eric Fogel (19:39):George Decay.Michael Jamin (19:40):Decay.Eric Fogel (19:42):My God. Fergie.Michael Jamin (19:44):Yep. Yep.Eric Fogel (19:47):I meanMichael Jamin (19:47):So much. Mc Hammer, we remember we had Mc HammerEric Fogel (19:50):Pen. GilletteMichael Jamin (19:51):Pen Gillette. I forgot. She's the what? A Oh my God.Eric Fogel (19:54):Was Jean Simmons.Michael Jamin (19:57):. Jean Simmons. Yeah. I remember that. . That was a day. And then, okay, so then once, once Glen Martin went down. Yeah. What happened to you then?Eric Fogel (20:08):? I don't know. What happened. So, you know, it was, that was a sort of a tricky time because I, I, I had to kind of reinvent myself. Did.Michael Jamin (20:20):Right.Eric Fogel (20:20):I was here in town. We did that show. That show was ama you know, it was an amazing experience, but nobody fucking saw it.Michael Jamin (20:29):Right,Eric Fogel (20:29):Right.Michael Jamin (20:30):And no one understood what you did on it either, because you create, you, you, you kind of invented a, you were a necessary incredibly important cog. But who, how do you describe, you know, how do you describe it to people? I, cause I'm even asking you, well, you were, you were one of the executive producers, but I'm almost like, well, what was your ion job? I mean, what, that was your job title, but it'd be, it'd be hard for me to describe what you did. Cause you did so much.Eric Fogel (20:53):Yeah. I mean, I guess on that show I was, I was more of a directing showrunner.Michael Jamin (20:58):Is that what you would call it?Eric Fogel (20:59):If you Yeah. Because, you know, I feel like there are some categories, right, with show like showrunners. So there are writing showrunners, which I consider like you and cber were like the writing showrunners. And I was on that show. More of a, the directing maybeMichael Jamin (21:14):Actually May in King of the Hill. I think they would call it a supervising director. Is that what you wereEric Fogel (21:18):Maybe. I mean, I don'tMichael Jamin (21:21):Supervise all the directors,Eric Fogel (21:22):Basically. It's different. Yeah. I guess there's, they're different credits.Michael Jamin (21:26):Yeah. I re Yeah, it was hard. It was a hard, there was so much for you to oversee. It was crazy.Eric Fogel (21:34):Yeah. And it's, I mean, and, and I love that. Like, that's, for me, that's what I do. It's soup to nuts, just mm-hmm. every, every piece of the production, I just, I I like to have a hand in holiday.Michael Jamin (21:50):Hey, it's Michael Jamin. If you like my videos and you want me to email them to you for free, join my watch list. Every Friday I send out my top three videos. These are for writers, actors, creative types. You can unsubscribe whenever you want. I'm not gonna spam you and it's absolutely free. Just go to michaeljamin.com/watchlist.Michael Jamin (22:14):So how did you reinvent yourself? Like what does that mean really?Eric Fogel (22:17):So I was here in town and after Glenn Martin, you know, there were, we had a, there were a couple things, but a couple things fell through. We were gonna do, there was another show mm-hmm. that I, I was developing with to, and it was this was weird. But we, this we, we developed this show alongside BoJack. Right. So it was like Scoop was working on, on BoJack. And then we had this other project and we, we actually sold this other project to a network. We had like, like an a, an agree, like an accepted offer. And it looked like it was going forward until the head of the studio just decided, eh, didn't wanna do animation.Michael Jamin (23:01):Yeah.Eric Fogel (23:02):That happened. So that, that got killed. And so I had to find some, some work. I ended up directing a show at Nickelodeon and it was a CG show. Mm-Hmm. . So I wanted to, it was, it was more of a kids show. Right. And it was, you know, I wanted to have the experience of, of directing cg. Okay. So I did that for a few years and it's, you know, that, and then it, you, you sort of, there you, there's stepping stones andMichael Jamin (23:31):That's just a big learning curve though.Eric Fogel (23:34):There's, there is a learning curve for sure. And it was important to me to, to have,Michael Jamin (23:39):Because you didn't learn, you didn't study that in college. What did you know about it?Eric Fogel (23:41):They didn't have, they didn't have computer animation there. Right. So you just have to, the best way to, to learn is to just be immersed in it. Right. Just on the Jobb training. So I, I did, I got that experience and that, that experience led me to, to Dreamworks.Michael Jamin (24:00):Right. And how, and you've been at Dreamworks for six years. And what do you do, what are you doing at Dreamworks? Basically do, are you, do you have a studio deal with Dreamworks? Is that what it'sMichael Jamin (24:08):Overall deal or something?Eric Fogel (24:09):They, I'm under contract. So right now it's kind of show to show.Michael Jamin (24:15):Alright. So you have a contract and they, they put you on whatever show they have going.Eric Fogel (24:19):Yeah, but they also were nice enough to keep me around. So they sort of put me on an overall deal. Cuz there was like a gap between shows. So that, that was very nice of them. Yeah. Keep me,Michael Jamin (24:31):They don't wanna lose you.Eric Fogel (24:32):I guess. They like me enough to keep me.Michael Jamin (24:34):It's so interesting cause I just had one of my previous guys, I may, I dunno if you know 'em, you probably don't. But John Abel and Glen Glen, they do all the kung They're the writers, the kung fu pander writers. They do a lot of dreamwork stuff.Eric Fogel (24:45):Yeah. Guys.Michael Jamin (24:46):Oh, you do, do you work with them?Eric Fogel (24:48):I haven't, but I'm familiar with them.Michael Jamin (24:50):So what exactly are you doing at Dreamworks then? We, as from jumping from show to show?Eric Fogel (24:55):Yeah. So they hired me initially, this is now almost six years to the day I started doing a show called Archibald's, next Big Thing. Mm-Hmm. , which was created by Mr. Tony Hale.Michael Jamin (25:10):Oh, he created, I know he's in it. I didn't know he created it.Eric Fogel (25:12):Created and voiced and was an, was an exec producer.Michael Jamin (25:18):And, and it's What network is that? Nickelodeon.Eric Fogel (25:21):That was so we started on Netflix. Okay. So we produced here at Dreamworks, we premiered on Netflix season one. And then season two we were on PeacockMichael Jamin (25:34):And Oh, is that, is there, is there a season three in the works or what?Eric Fogel (25:37):No, no. So the thing to know about animation these days is they don't order a a lot of episodes. It's, you know, the, it's, they've, especially on these streaming platforms.Michael Jamin (25:48):Oh, well that's the way it is for a live actually. Yeah. So what are you doing, se like 13 or something?Eric Fogel (25:53):We did two. So for Archibald we did two seasons and it was it was like 50. It ended up being like 50 half hours or fif 50. It's actually a hundred, a hundred episode. There are 11 minute episodes. So we did 111 minute episodes.Michael Jamin (26:08):That's actually, and are you, what are you, are you running the show? Are you running it? AreEric Fogel (26:11):You So I so that on that show, I was, I was exec producing, I was a writer and I was, I was basically doing a little of everything. Same, same thing. Directing, writing, overseeing every aspect of it.Michael Jamin (26:25):But it's not like every writer, there's a writing staff on that show. Right.Eric Fogel (26:29):We, we had, we had a, a staff and we had a couple head writers who, and they, those guys were great. I love those guys. They had never run, run a show before.Michael Jamin (26:39):Uhhuh .Eric Fogel (26:40):So I felt like I could be helpful there, you know, just in the writer's room and, and just, it just sort of organically evolved to where, you know, I didn't expect to be so involved in, in the writing process on that show. It just, it just turned out like, it just was a natural,Michael Jamin (26:57):That's the whole thing. You have a very unusual career path in career because cuz you do so many things.Eric Fogel (27:04):Yeah. I mean, I don't, there's no rules for this. I'm just making thisMichael Jamin (27:07):Up. Yeah. There's no rule. So, I mean, it's quite impressive because like, if I, I don't know what, what would, what, how would you advise? You must have kids come into you, Hey, how do I, how do I get to do what you do? Like what do you tell them?Eric Fogel (27:23):I mean you gotta have, you know, there's, there are a couple of key ingredients, right? You, you gotta have the passion,Michael Jamin (27:31):Right.Eric Fogel (27:32):For it, for the craft. You have to have the ability mm-hmm. have to have the skills. Michael Jamin (27:39):But you didn't have the ability when you started. Right.Eric Fogel (27:42):I had some ability. SomeMichael Jamin (27:44):Ability.Eric Fogel (27:44):And I kinda, yeah. I mean a lot of it is you have to immerse yourself and you have to just make things and you have to learn as you make things. You can't, you know, you can watch YouTube videos all day long, but you gotta like just get in it. And now it's one, you know, we have, the technology has changed so much. It's made it so much easier. Mm-Hmm. to make things. NowMichael Jamin (28:08):With those like those animation program, I mean, do you do anything like that on the side for yourself? Like what? Or, or, I mean, you know, at home for anyone? IEric Fogel (28:17):Don't have time for that. No. I these days. Yeah. I mean, I, I'm, you know, this, this job keeps, keeps me. ButMichael Jamin (28:24):Let's say you had a side project that you just wanted to get off the ground. Yeah. You just pitched the idea.Eric Fogel (28:29):I could, yeah. I mean, I have put things together and I've made, yeah. I've been able to make little animations you know, for projects, original projects that I've pitched. And I'll, I'll put together a whole presentation. I'll do all the visuals. I'll edit it and, and put together Yeah. Like little proof of concepts, right? That yeah. That stuff is, yeah. I love doingMichael Jamin (28:49):That. And that's on your own, but that's on your own time.Eric Fogel (28:51):That is on my own time. YourMichael Jamin (28:53):Own with, with some program you have.Eric Fogel (28:55):Yep.Michael Jamin (28:56):What's, what kind of program is this? What, what is it?Eric Fogel (28:58):I mean, I, you can, you can animate with Photoshop now. Oh. So that's, you know, that's, that's a thing. I, I use Sony movie Maker, which is this archaic system. I, I just, I'm really comfortable with it and I, I can use that to, to build projects and I can even animate on that thing.Michael Jamin (29:16):Are you doing any stop motion anymore?Eric Fogel (29:18):I haven't done stop motion in a long time.Michael Jamin (29:20):Because why the market part?Eric Fogel (29:24):You know, it's, it's just the, the right project hasn't really surfaced. And you know, I've, I've, I've pitched Project stop motion is a hard one to sell. People are afraid of it.Michael Jamin (29:36):Is it the look that's the, that's the criticism I get. They go that, here's the thing. Every, so I've been, I post a lot on social media and people will say, oh, I used to watch Glen Martin. And the, the phrase that comes back is that show is a fever dream. I was like, what's a fever dream? But everyone describes it as a fever dream. And what thatEric Fogel (29:55):Mean? Like, creepy. IMichael Jamin (29:56):Think it means like, like you were, they were in like, it felt like they were in an opium den, den era.Eric Fogel (30:03):. What it felt like for me.Michael Jamin (30:05):What's that?Eric Fogel (30:06):It's what it felt like for me Felt likeMichael Jamin (30:07):To, I mean, but it's like I, I, I don't know. There's something about like, I always like that format. Cause I always like this old bank and resting,Eric Fogel (30:17):Right. Bank ranking and backMichael Jamin (30:18):And best. Yeah. I always thought,Eric Fogel (30:20):Yeah. I mean, some people have got, I love, I've always loved the, the look of stop motion and you know, it's, there's something super charming and not just like, endearing about the, like the handcrafted aspect aspect of it. Right. Right. It's so cool. ButMichael Jamin (30:35):Don't feel that way. I guessEric Fogel (30:36):It's al it's always been the kind of like the redheaded stepchild of animation though, you know? Yeah. Always on. Always on the, on the fringes. And now, you know, it's hard enough to sell a show, any show. Right. Uhhuh . But it's in ama in the, in the animation industry, it feels like they're, they're only looking for, for CG animation these days. And there's just,Michael Jamin (30:56):Is that right? I mean, what, explain the different types of animation, because obviously there's, there's like, yeah. CG, like Shrek or somethingEric Fogel (31:03):Mm-Hmm.Michael Jamin (31:03): and then go on there actually different levels in terms of, you know, expense. What, how does that work?Eric Fogel (31:11):I mean, there, you know, there, so there there's like traditional hand drawn animation. But even that is all done mostly in computer these days. So there, there's no more like, hand painted cells. Right. But the actual movement, a lot of that stuff can still be done, done by hand.Michael Jamin (31:29):Uhhuh,Eric Fogel (31:29):. And then, you know, you got stop motion, you got cg and there, there are worlds in between where, you know, stylistically they, they're, they're doing a lot of thing, you know, design wise, they're kind of blending the, all the techniques.Michael Jamin (31:44):But it must be in terms of like, when they tell you what the budget of the show is, that greatly determines how good it's gonna look in the, how the, you know, the animation.Eric Fogel (31:52):Right. It can, you know, so right now I'm working on Megamind, the, the sequel to the, to the 2010 film Megamind. Right. And that's gonna air later this year. And I can't say a lot about it cuz they haven't announced a lot about it. Right. But the quality the quality of the animation, the technology has improved so much. Mm-Hmm. that even, even on a, a smaller tier budget, you can still, the quality of the animations really it's really improved.Michael Jamin (32:31):Right. So, so when you sell a show or when they bring you on a show, are you asking these questions or it's like, ah, someone else, you know, in terms of like, how much money do we get to spend on?Eric Fogel (32:42):Well they, yeah. They tell me and then I have to figure out how to make the show.Michael Jamin (32:47):Right. They tell you. Right. And so where will you cut corners or something.Eric Fogel (32:52):Yeah. So, so that's where it gets challenging. And, and you have to become very, you know, creative and, and and problem solving to, to be able to deliver. Right. The show the show you want and the show that they want with within these, you know, what, what can sometimes be a very small sandbox.Michael Jamin (33:10):Yeah.Eric Fogel (33:10):You know,Michael Jamin (33:11):And then so what, so what are you, you know, what are your ambitions or future ambitions or, you know, what, what excites you coming up or whatEric Fogel (33:20):You know, I would, I'd love to expand the Sandbox and be able to make a, make a leap into directing a feature would be really exciting. Oh really? Yeah.Michael Jamin (33:31):At at Dreamworks or, or any place really.Eric Fogel (33:34):Yeah. I mean I love it here. So I I would for sure love to direct a feature here. Right. But that, that would, you know, that would be a, a dream to, to be able to do that someday and, and to be able to, you know, spend three years, you know, focusing on, on like 90 minutes of content as opposed to, you know, hundreds of minutes of, of content to be able to like microfocus on that.Michael Jamin (34:00):It's so interesting cuz for me it's kind of other way around. Like, I, I, you know, I have to, I don't know. Cuz you get to every, every week you get, all right, here's something new. I have to live with something. But you're saying you, because you really wanna make the qual, you really want to spend time to make sure every frame is right.Eric Fogel (34:17):I would love, yeah, that would be, that would be a dream. Because in TV animation, you know, it's, it's like there's always this, this schedule. You're a slave to the schedule.Michael Jamin (34:29):Right.Eric Fogel (34:29):And you, you know. And soMichael Jamin (34:31):Are you, are you in the Glendale campus of Dreamwork? Is that where you are? Yeah. Are you there right now? Yeah, this is, this is really your,Eric Fogel (34:38):This is my office.Michael Jamin (34:39):This is your real office over at Dreamworks. People fa Okay. So you're okay. I don't even know if they with Covid if you're working from home or not.Eric Fogel (34:47):I still, yeah, I'm here a couple days a week.Michael Jamin (34:50):Uhhuh Eric Fogel (34:50):These days.Michael Jamin (34:52):And, and cuz this is your show. So you, well, are you working with writers? You know, how are you, how, how involved are you right now with Theri? Is there a writer's room or whatEric Fogel (35:00):Where, so the writing is, is wrapped on this show, but we were really fortunate because we got the two guys Brent Simons and Alan Schoolcraft, who wrote the original Megamind mm-hmm. were brought, were brought in as, as eps to, to basically help Showrun and, and run the writer's room. So having those guys was, was a gift, you know, cuz they, they kind of, they invented Megamind. So,Michael Jamin (35:30):And this is all on the Dreamworks campus? The writer's?Eric Fogel (35:32):Yeah. We did the writing here. A lot of the, a lot of the, the create a lot of art on this show is done not in Toronto. It's a lot of it's done in Vancouver.Michael Jamin (35:42):Oh, are you, are you ma are you making the trip up there? DoEric Fogel (35:46):You have to? I've been up there. I've been up there a couple of times. But we are, luckily, yeah, now that we've got, you know, zoom, it's, you know, I can do a lot of this right here. A lot of the work I can do right here.Michael Jamin (35:58):See, that's so wait, so, so they are, these subcontract, subcontracting out a lot of the animation at Dreamworks. I I kind of, it was under the impression they did it all themselves.Eric Fogel (36:07):They have always had partner studios, even like on the early features they, they were partnering with, with studios. So there's always been this sort of hybrid model on this particular show. Almost all of the, the, the art, the art side of it is, is outsourced on, on this show. Michael Jamin (36:29):Interesting. And then, and so they're actually, okay, so the animation houses are there. I mean, basically if you're an, so if you're an animator, it's interesting, there's different levels of animation, animators. This is all, and I've worked, I've worked in animation for many years. I still don't understand how it works. But but like, I remember like when we worked I worked at it wasn't Bento Box, it was whoever was doing King the Hill, Fort Bento. But Oh,Eric Fogel (36:56):I know who you're talking about.Michael Jamin (36:57):Yeah. I was, I'm forgetting, I'm blanking now. But they, the animators would've to come take tests. You would apply for a job of animator. Yeah. They'd give you a test, draw this frame or whatever, you know, is that how it still works there? Maybe stickEric Fogel (37:11):Computer. Yeah, I mean there's always, you know, it's like anything else, right? You have to audition, right. Or things. And yeah, there are, there are definitely, there's a big kinda leap in terms of skill levelsMichael Jamin (37:26):OfEric Fogel (37:26):Artists. Right. Because so much of art is like subjective.Michael Jamin (37:31):Yeah. It's so, it's so interesting. That's this career. But, and what about, I don't know, live action? Any interest getting back into doing more or? No,Eric Fogel (37:40):I would love to do some, some live action at some point. I, I've got like a horror movie that I would love to try to do one day. And you know, I, I'm, I'm such a huge like, horror sci-fi nut.Michael Jamin (37:55):Right. Are you, and are you pitching other shows as well? Or, or, you know, is how does it work in Dreamworks? So like, we have an idea, we have to show you're hired Fogal. I mean, is that what it is? Basically?Eric Fogel (38:06):They have, yeah. I mean they have a, an in-house development process. And when you're, when you're here, they, you know, there's like a, you have, there's a first look deal. So you, you, if you have an idea, you're sort of obligated to first.Michael Jamin (38:21):Right.Eric Fogel (38:23):And you know, the, so the industry's a little different right now cuz there's, they're not, you know, there aren't, there aren't a lot of shows being sold or bought right now , because it'sMichael Jamin (38:35):No kidding. Is that and is that the way, I didn't know if that's the way it is for animation as well.Eric Fogel (38:40):It is. So, you know, I'm very, very happy to be working on Megamind right now. .Michael Jamin (38:46):Yeah, right.Eric Fogel (38:47):This will keep me employed, you know, for the next year or so. But it's like, you know, it's like anything else. We, we work job to job and there's never any guarantee Nope. That you're gonna get hired again. You just, you know, it's all kind of on good faith.Michael Jamin (39:02):Are you working with the actors too? Directing actors as well?Eric Fogel (39:05):I'm directing all the voice actors on this show.Michael Jamin (39:08):You're the only director. Yeah. And, and then you're also supervising the animation, the, theEric Fogel (39:14):All of it. Yeah, allMichael Jamin (39:15):Of that. Yep. Good for you, man. Carved out quite a little career for yourself.Eric Fogel (39:20):It's fun.Michael Jamin (39:21):Yeah,Eric Fogel (39:21):It's fun. Keeps me busy. But I, I do love it. I do.Michael Jamin (39:25):Do you have any other advice for anybody to, you know, what's, you know, trying to break inEric Fogel (39:31):Other, I mean,Michael Jamin (39:32):Make more,Eric Fogel (39:33):You know, it's, you have to, I, it's a long time ago someone told me like, the recipe for, for a successful whatever show movie, whatever, you know, you find that, that thing that, that you love. You put, you put your, all your heart into that thing. And then, you know, you take what everyone else loves and, and it's kind of like where these two things come together that, that's kind of like your sweet spot, right? That's, that's your hit, that's your success. And so you gotta, you know, you gotta like focus in on what that thing is and, and put everything you have into it.Michael Jamin (40:08):I'm surprised they're not talking about bringing celebrity death mat back. That's gotta be next.Eric Fogel (40:13):There have been a few conversations over the years and there, there have been a couple of attempts to bring it back and we, we did. Yeah. I mean, it's, it's not dead, but ,Michael Jamin (40:27):Do they reach out to you or are you actively trying to sell that?Eric Fogel (40:30):I have. So I guess it's Viacom or Yeah, m t v. They, they own the rights to the show, but we, we have an agreement to, you know, if, if they want to bring it back, I'm, I'm attached to it. Right. And we've had, we've had some attempts and for whatever, well we, we did, we did get close. And then yes the studio that had made an offer, they went away. Michael Jamin (41:00):They went awayEric Fogel (41:01):As, as these things do. I'll, I'll tell you offline more about it, .Michael Jamin (41:05):Alright. Like, when we put the animation, the, the ama the animation studio that made Glen Martin, we put 'em outta business .Eric Fogel (41:12):They, they didn't stay in business long after that. . And it's Yeah. Funny because they, I, I don't know if they, at the time I, I'm not sure if they realized how, what, what a unique opportunity that show was for them.Michael Jamin (41:26):What do you mean by that?Eric Fogel (41:28):The, you know, I, again, like these shows, these stop,Michael Jamin (41:32):Like they, how many stop motion series have there been? Right, right. You know, they're few and far between. Right. That was the Yeah, that's another thing. There's only, they're one of the few people that actually could do it. And I don't, I don't even know what they were doing beforehand. It's Right. So when they went out of business, like there was like, what else are you gonna do? You know, they wanted be like, people aren't lining up. Yeah. Stop for stop motion shows. Right? There's only a handful. Yeah. Yeah. That's the, yeah. Anyway. Is there any way, is there, do you wanna promote anything? Do you want people to follow you anywhere? Is there anything we can do to help you help grow your brand? Eric Fogel. Violent . You can find me. I'm on you can find me on Twitter. Death Match Guy, I think is my, my oh really?(42:19):Twitter handle. I'm verified there. What? Oh. But not on Instagram, just Twitter. I do a little Instagram. I'm not a huge social media person. Yeah. Well, we'll get you there for some weird reason. Yeah. Cause you're, cuz we're the same age. Anyway. All right, dude, I wanna thank you so much. Yeah. I, you've exposed me. I've learned something. Learned something about you and your craft. Yeah, because I, I even remember when we got hired, they said, yeah, we got this guy on, on Glen Martin. We have this guy Eric Fogel. I was like, what does he do? No one can explain it because we do everything. He's the guy. He's the glue, basically. That's what he he's the glue. Yeah. That's, that's it. Yeah. I'm the glue. Yeah. All right, man. Thank you so much. Thank you so much for, for joining me e. Excellent. that's it everyone. More good stuff next week. Go check out what Eric Fogel's up to. And he's a great guy. Thank you again so much for doing this, man. Don't go anywhere. All right, everyone, until next week.Phil Hudson (43:18):This has been an episode of Screenwriters. Need to Hear This with Michael Jamin and Phil Hudson. If you'd like to support this podcast, please consider subscribing, leaving a review and sharing this podcast with someone who needs to hear today's subject. For free daily screenwriting tips, follow Michael on Instagram, Facebook, and TikTok at @MichaelJaminWriter. You can follow me on Instagram, Facebook, and TikTok at @PhilAHudson. This episode was produced by Phil Hudson and edited by Dallas Crane. Until max time, keep riding.
ResistanceResistance is essentially stress inoculation. It refers to the ability of an individual, group, organization, or even an entire population to resist manifestations of clinical distress, impairment, or dysfunction associated with critical incidents, terrorism, and even mass disasters. Resistance is a form of psychological/behavioral immunity to distress and dysfunction.ResilienceThe second is resilience. According to Dr. George Bonanno, resilience is a naturally-occurring tool most people have always had in their psychological lockers, which is enhanced or weakened by experience and circumstances. In a nutshell, resilience is the power to overcome adversity, trauma, and low self-esteem and to be strengthened.My friend, trauma survivor, and fellow author Danielle Bernock says, “To be resilient is the ability to thrive instead of being traumatized.”5 Tips for Dealing with TraumaTip # 1 – Supervise your self-talk.Tip # 2 – Stop comparing yourself to others.Tip#3 – Stretch your limiting beliefs.Tip # 4 – Build up others.Tip# 5 – Get help.Here is a link to the blogBlessings,John Thurmanwww.johnthurman.infoEmail: john@johnthurman.infoUpcoming Events with JohnFeb 26th - Dealing with Anxiety - Sunday, February 26th @ Grace Church 9:00 and 10:30 am. Church is located @ 6901 San Antonio NE, ABQ. This is a public eventMarch 3rd and 5th - Marriage and Family Conference - Evangel Christian Center 4901 Montgomery Blvd NE, here is the link. This is a public event.March 25th - Book Signing - Bibles Plus 2740 Wyoming NE Times TBAApril 1st - Mental Health for Church Security Teams - Private event
How comfortable are you with leaving your kid under the supervision of another parent?What BUZZ listener Heather does when her 9 year old daughter goes to a friend's house we'll decide if it's GOOD or BAD Parenting
In this episode, I have covered the following things in the simplest way What is the Term GPT? How was Chat GPT Built? How was Chat GPT Trained? Supervise learning Reinforcement Learning Human feedback How Chat GPT is able to answer the questions? Answering Approach of Chat GPT Check my Instagram- www.instagram.com/podcasteramit https://hubhopper.com/podcast/tech-stories/318515 https://music.amazon.com/podcasts/2fdb5c45-2016-459e-ba6a-3cbae5a1fa4d https://open.spotify.com/show/2GhCrAjQuVMFYBq8GbLbwa https://podcasts.apple.com/us/podcast/id1544510362 https://www.jiosaavn.com/shows/tech-stories/1/,LBNutZ7Fx4_ https://gaana.com/podcast/tech-stories-season-1
En su colaboración con Luis Cárdenas para la Primera Emisión de MVS Noticias, Ezra Shabot, analista político, habló sobre las precampañas y las advertencias del INE.
In this montage episode, guests return to share their favorite leadership books.
Así responde a la actual secretaria de Economía Raquel Buenrostro tras culpar su adminitración de retrasar las consultas en el sector energético
Join Host Rubin Sorrell as he finds cracks in his glass ceiling. See if he can make the grade looking for the simple pleasures as he turns his pride into selflessness.
Join Host Rubin Sorrell as he finds cracks in his glass ceiling. See if he can make the grade looking for the simple pleasures as he turns his pride into selflessness.
Script this, supervise that…what it's really like being the Script Supervisor(All of the responsibilities, none of the glory)In this episode, we take a closer look at what it feels like to be a script supervisor, and how our work on set also helps out in post. Plus, master script supervisor Mary Cybulski shares a revealing BTS story from the film “Life of Pi.” But first, we have an informative interview with the incomparable Dawn Gilliam.Dawn's multi-decade Script Supervising career began with Boyz n The Hood and includes groundbreaking and Academy Award-Winning and nominated films such as Black Panther, Fences, Star Wars: Episode IX and literally dozens of films and TV shows you've no doubt seen. She has served as President of ITASE Local 871 union for script supervisors, is responsible for getting IMDB to create a new category for Script Supervisors, and has taught the craft of script supervising through her popular online course: The Art of Continuity since 1995. https://www.theartofcontinuity.comcheck out her new business venture https://www.datemymakeup.comHosted, Created & Produced by Caryn RubyProduced and Edited by Eden WoolworthSound Mixer Adam CarlOriginal Music by Edith Mudge Logo design by Sharon WattEpisode artwork by Ana Ziegler Loes
On this episode of That's My Sports, the fellas discuss Kyler Murray's interesting clause in his new contract with the Arizona Cardinals. Would anyone consider Lamar Jackson the most disrespected player in the league? our answers may surprise you, or do they? Julio Jones has found yet another new Quarterback in the last three years, does Tom Brady put him on the TB12 diet? and lastly, where does Jimmy G end up this season? Hosts: Rayshawn Buchanan, Seyi Omonira, Aaron KassProducer: Seyi OmoniraFollow That's My Sports on Social Media:Instagram: tmspodcast Twitter: _tmspodcastTikTok:thatsmysportsDisruption Works Chit Chat - Chatbots, Voicebots & Automation, with the odd lobster!Lively chats about discussing how to automate your conversation without annoying customersListen on: Apple Podcasts Spotify PPC Ponderings PodcastConsider core questions about digital advertising, in an investigative journalism format.Listen on: Apple Podcasts Spotify
There are ups and there are downs this week, plus everything in between. While there may be rough news, there is also great news, especially with adoption of crypto and new funding. Week 28, Year 2022, Episode 18. Timestamps: (00:00:00) Intro Song (00:00:23) Introduction (00:00:43) Disclosures (00:01:14) Ethereum Merge Updated For Release in September (00:01:46) Celsius Network Files for Chapter 11 (00:02:02) Celsius Mining Division Files for Bankruptcy As Well (00:02:15) CoinFlex Arbitration To Recover $84 Million (00:02:23) Terra Switches to Polygon (00:02:32) Senator Lummis On gm Podcast (00:03:01) $2 Billion Valuation for Former Meta Exec (00:03:16) Gary Gensler Article on WSJ (00:03:25) New Brazilian Crypto Exchange (00:03:37) G20 Robust Crypto Rules Coming In October (00:03:46) GameStop Opens Ethereum NFT Marketplace (00:04:00) BlockFi CEO Doesn't Want To Be Compared to Others (00:04:30) Three Arrows Woes (00:04:36) $7.1 Billion Lightspeed Ventures Funding (00:04:51) Kevin O'Leary Mr. Wonderful on Crypto (00:05:04) Singapore Crypto Aspirations Shaken (00:05:22) Voyager Updates (00:05:44) Celsius Reclaims $410 Million stETH (00:06:23) Celsius Hires New Restructuring Lawyers (00:06:40) Crypto To Pay Salaries in Developing Economies (00:06:53) CoinFlex Takes Legal Action (00:07:07) 3AC Updates (00:07:24) Charlie Munger Crypto Quotes (00:07:58) Bitcoin Mining Rig Prices Slump (00:08:14) Crypto Miner CleanSpark Building (00:08:28) India's Crypto Advocacy Group Disbanded (00:08:41) Brazilian Congress Postpones Crypto Bill Vote (00:08:54) Latin American Crypto Report (00:09:09) The Affect of Three Arrows Capital (00:09:20) OpenSea Lays Off 20% of Staff (00:09:48) Mastercard Crypto Efforts in Indonesia (00:10:03) Anthony Pompliano Helps Crypto Recruitment Firm (00:10:20) Vitalik on PoS (00:10:40) Former Ripple Advisor to Supervise the Fed (00:10:57) New York Yankee's Players and Staff Can Convert Salary Into Bitcoin (00:11:15) In Closing -------------------------------------------------- Fort Brox Affiliate Links: Koinly Crypto Tax Software:
As I began to utilize the remote managed self storage operations model, it helped me to focus on how to separate out responsibilities for greater efficiency and profitability. I put tasks and responsibilities into 3 categories: Customer Management = Call Center: They handled all sales calls, customer service calls, collections, and payments. Facility Management = On Site Maintenance Person: they handled all of the boots on the ground duties such as security checks, overlocks, cleaning units, minor repairs, and assisting with auction preparation. Property Management = Owner Managed or 3rd Party Property Management: they tie all of the systems together with policy & procedures. Supervise the call center & on site maintenance person. Oversee and implement marketing, conduct onsite audits, focus on increasing NOI month after month…on and on. ======================== Jim Ross - The Self Storage Show & 3 Mile Storage Management Free 30 Minute Consult with Jim Ross of 3 Mile Storage Management ****In this free 30 minute consult, I have 30 minutes to find 3 ways I would increase your leads, rentals, and revenue for your self storage business! https://calendly.com/jimross/3milestoragemanagement The Ultimate Self Storage Management Playbook! This is the Most Incredible Free Gift Ever...Designed To Increase Leads, Rentals, and Revenue For Your Self Storage Business! https://www.3milestorage.com ======================== Connect With Me Website https://3milestorage.com/ Facebook Community https://www.facebook.com/groups/selfstoragecommunity Podcast https://podcasts.apple.com/us/podcast/the-self-storage-show-with-jim-ross/id1387362783 LinkedIn https://www.linkedin.com/in/selfstorageservices/ YouTube https://www.youtube.com/channel/UC2bGLy48wzIus-1ncSNVM6g Weekly Newsletter https://bit.ly/3milenewsletter ======================== About Jim Ross I started out in the self storage industry as a self storage manager. I moved up and became a district manager. Eventually after many years in the self storage industry I knew I could use my knowledge and expertise to help owners skyrocket the value of their self storage investments. That led me to create 3 Mile Storage Management. 3 Mile Storage Management offers self storage property management solutions for self storage facility owners that want to dominate their local 3 mile market with a large focus on remotely managed operations. I enjoy providing value to the self storage industry through speaking at industry events, putting together virtual summits, hosting The Self Storage Show podcast, weekly newsletter and compiling much of the content and online events I've done into The Ultimate Self Storage Management Playbook.
We first review the scope of the CFPB's supervisory authority granted by Dodd-Frank and the source of its authority to supervise nonbanks that present risks to consumers. We then discuss how we expect the CFPB to use its risk-based authority, including the types of products it may target and its decision to make public the identities nonbanks. We also look at the practical impact of CFPB supervision for targeted nonbanks and what steps companies can take both to avoid becoming a CFPB target and to prepare for the possibility of a CFPB examination. Finally, we consider how the CFPB's action could impact the approach of state regulators to nonbank providers of alternative credit products. John Grugan, a partner in Ballard Spahr's Consumer Financial Services Group, hosts the conversation, joined by Michael Gordon and Lisa Lanham, partners in the Group.
lovethylawyer.comA transcript of this podcast is available at lovethylawyer.com.Go to https://www.lovethylawyer.com/blog for transcripts. MICHAEL T. Meehan11 Northview CourtSan Rafael, CA 94903415-308-4378Michael.Meehan@NoCuffs.com | | THE STATE BAR OF CALIFORNIA Member Since December 1995 THE STATE BAR OF TENNESSEE Member Since July 2005 (inactive) THE STATE BAR OF KENTUCKY Member Since October 1999 (inactive) JURIS DOCTORATE Loyola Law School, Los Angeles, 1995 BACHELOR OF SCIENCE, Psychology University of California Los Angeles, 1989 Student Body President, 1988-1989 Chairman, ASUCLA Board of Directors, 1988-1989 Chancellor's Marshall Award Recipient, 1989 Director, UCLA Orientation Program, 1987-1988 General Representative, Student Government, 1988-1988 | | work experience | | The Kavinoky Law Firm San Francisco, CA 2007–present Chief of Legal Services n Supervise all Managing Attorneys in the Kavinoky Law Firm, including, but not limited to recruitment, training, supervision, compensation, and client relations. n Serve as a key member to the executive team in determining the expectations and direction of the firm and the direction the firm will grow. n Select and supervise the Senior Management Team leaders and how they manage the Managing attorneys under them, and the development and cultivation of future leaders in the firm. n Reflect upon and advocate for the reflection of the Firm Core Principals in all our conduct with respect to clients and team members. n Expanded the team of attorneys, increased compensation and benefits, and prioritized the accuracy of all key measurements in department. n Keep team members updated on changes in the law and best practices. Check out his book on AMAZONhttps://www.amazon.com/Keanu-Michael-Meehan/dp/1732605505/ref=sr_1_1?crid=1Z3RD11UWCJKG&keywords=michael+meehan+keanu&qid=1647987296&sprefix=michael+meehan+keanu%2Caps%2C120&sr=8-1 Louis Goodman www.louisgoodman.com louisgoodman2010@gmail.com 510.582.9090 Musical theme by Joel Katz, Seaside Recording, Maui Technical support: Bryan Matheson, Skyline Studios, OaklandAudiograms & Transcripts: Paul Roberts We'd love to hear from you. Send us an email at louisgoodman2010@gmail.com. Please subscribe and listen. Then tell us who you want to hear and what areas of interest you'd like us to cover. Please rate us and review us on Apple Podcasts.
有两位听众都想知道这些表示 “监督” 的词语有何区别，以及在谈论 “监考” 时，应该怎样区分并使用它们。“监督” 考试应该用哪个词？哪个词强调 “密切监视事情的进展或变化”？本期节目介绍表示 “监督” 时可以使用的词语及其用法区别。
117o: The Anglo-Saxons: Out with the Old Religion and In with the NewDescription: Today I am joined by Professor James Early to discuss how Christianity was reintroduced to the British Isles or to be precise, how it was introduced to the Anglo Saxons or maybe how it was spread among another Germanic aristocracy. If you listen to Beyond the Big Screen you will know Professor Early. He is a fascinating guy with wide historical interests and knowledge. 4/22/22About Today's Guest:James Early host of Key Battles of American History PodcastKeybattlesofamericanhistory.comYou can learn more about the History of Papacy and subscribe at all these great places:http://atozhistorypage.com/https://www.historyofthepapacypodcast.comemail: steve@atozhistorypage.comhttps://www.patreon.com/historyofthepapacyparthenonpodcast.comhttps://www.gettr.com/user/atozhistoryBeyond the Big Screen:Beyondthebigscreen.comThe History of the Papacy on YouTube:https://www.youtube.com/channel/UC6DO2leym3kizBHW0ZWl-nAGet Your History of the Papacy Podcast Products Here: https://www.atozhistorypage.com/productsHelp out the show by ordering these books from Amazon!https://smile.amazon.com/hz/wishlist/ls/1MUPNYEU65NTFMusic Provided by:"Danse Macabre" Kevin MacLeod (incompetech.com)"Virtutes Instrumenti" Kevin MacLeod (incompetech.com)"Crusades" Kevin MacLeod (incompetech.com)"Funeral March for Brass" Kevin MacLeod (incompetech.com)"String Impromptu Number 1" Kevin MacLeod (incompetech.com)"Intended Force" Kevin MacLeod (incompetech.com)Agnus Dei X - Bitter Suite Kevin MacLeaod (incomptech.com)"Folk Round" Kevin MacLeod (incompetech.com)"Celtic Impulse" Kevin MacLeod (incompetech.com)Licensed under Creative Commons: By Attribution 3.0 Licensehttp://creativecommons.org/licenses/by/3.0/Image Credits:By Ariely - Own work, CC BY 3.0, ttps://commons.wikimedia.org/w/index.php?curid=4533576By Pam Brophy, CC BY-SA 2.0, https://commons.wikimedia.org/w/index.php?curid=9124089By ACBahn - Own work, CC BY-SA 3.0, https://commons.wikimedia.org/w/index.php?curid=33810833Begin Transcript:[00:00:00] we're going to talk about the complicated cultural, political, and religious situation of the British Isles. Four and five hundreds, a D this episode will fit into the larger story of how different people's also known as barbarians entered the Roman empire mixed with the existing populations. We talked about the vandals a while back.We also talked about the Franks. Today, we will talk about the Anglo-Saxons and we will definitely get into the Visigoths and Spain and an upcoming episode. Today, we are joined by a special guest to help navigate us through this complicated time. If you listen to my other podcast beyond the big screen or Scott ranks history unplugged podcast, then you will be familiar with professor James early.James is an adjunct [00:01:00] professor of history at San Jacinto college in Pasadena, Texas, just near Houston. He has published one book and two scholarly articles. He also runs a blog and Facebook group called both called American history fanatics. His main areas of research and interest include Eastern European history, the American civil war, and the cold war.Thank you so much for coming on today, Jane. It's great to be here, Steve. Um, I'm honored and excited to be on this podcast for the first time a longtime listener. First time guest. Now a lot of people do know you as an American history guy. Why are we talking to you today about Anglo-Saxon church history?That's a very good question. That's fair. I know. Well, my reputation, I guess, as an American history person is relatively recent because when I was doing my masters and even before my master's, I was really into European history. And I don't know for whatever reason, I just got interested in the [00:02:00] Anglo-Saxons they're largely forgotten today.And people just don't know that much about them. And they have this fascinating language. They spoke old English, which. Has some similarities to what we speak today, but in many ways it's very, very different. So I just started reading about the Anglo-Saxons. I even got some information on the language and some courses on tape and what are CD?I said, tape, I'm dating myself there anyway. Uh, I learned a Lola language and readily. Of their writing and the original language. Not too much, it's fairly challenging, but I just read one book and I thought it was really great. So I read another book and another book and another book and for long. Built up some knowledge about the political history of the Anglo-Saxons, but also their church history.Cause church history has always been a hobby of mine. I've read quite a bit on church history in general. And so that's how I got into that. My specialty in my master's program, as I mentioned, was European history. And I focused [00:03:00] mainly on Southeastern Europe, especially the Balkan, Serbia, Bulgaria, and the other countries in that area.But I did take a whole course on the Anglo-Saxons, which actually designed myself. I approached this one professor who's specialized in Western Europe. And I said, um, how about teaching a course on the Anglo-Saxons? And he says, I don't really know that much about them, but if you want to design a course.Supervise it. So I picked out the readings and assigned myself a bunch of papers and we did it. So there it is. It's been a while since I've done a lot of study in the Anglo-Saxons, but hopefully we'll be okay today. Let's dive right in here. Tell us. What was the religious and cultural political situation in England at the time of the Anglo-Saxon invasions?We're talking like early four hundreds. What was going on there? Well, if you don't mind, I'd like to back up even a little bit further just to go kind of from the very beginning, the original habitants, the [00:04:00] inhabitants of. The British Isles, if you will, at the time of the Roman invasion were Celtic peoples and they weren't even originally from Britain.They believed that long ago, many, I don't know, a couple, two, 3000 years ago, they migrated into the British Isles from the continent. But by the time the Romans showed up, they had been there for quite some time. And so the people spoke a Celtic language or a series of Celtic languages. I'm sure they had at least different dialects if not different languages or they, um, That would have been similar to the modern Irish language or the Scottish Gaelic language or Welsh, but of course, much, much earlier forms of those and probably not intelligible by the, uh, by modern speakers of Celtic languages.So the Romans decided to go over. There are all buddy Julius Caesar who loved to travel around and conquer things, never met a country. He didn't want to conquer. But Caesar shows up in 55 [00:05:00] BC. And, but he didn't establish permanent control of Britain. It was almost just like a excursion. If you will forces, he went over there and busted some heads and then went back home and we know what happened to him.But the Romans later went back about a hundred years later, 43 D under the emperor Claudius and then they set up permanent controller or at least long-term control. The British Isles. And what happened was you had a blended culture, the Romans set up what they always did everywhere. They went, they set up cities, they set up camps, they set up baths.They all the trappings of Roman society were introduced into Britain. And the, the inhabitants there, a lot of them really liked it. Some of them didn't and rebelled from time to time and the Romans would brutally put it down as they do. But for the most part, you developed a blended culture, which is usually called Romano British.Or I may just eventually just call it British, but with some elements of Roman culture and some elements of British culture, [00:06:00] I need to talk about Christianity too. Christianity of course comes along with the Romans. We don't know when the first Christians or the first conversions occurred in. And the British Isles you had, there's a legend of Joseph.going to Britain and introducing Christianity and taking the cup of Christ and all that. But that's probably just a legend. There's no way to prove it or disprove it, but we know that there were definitely. There, there was a definitely a Christian presence no later than the third century. It may have even come earlier than that.We just don't know. There's no solid archeological evidence that clearly tells us any dates. And there's no, not much written evidence. We know about St. Alban, the first martyr who died in Britain in the mid third century. But, but so Christianity was there pretty early on. Third century, maybe even second century, but that doesn't mean that the pagan practices that the Celtic people had practiced, you know, they were pagans just like all, almost all European [00:07:00] inhabitants.They had several gods. We don't know too much about their deities, but what developed after the Romans came the Romans before they brought Christianity, of course, they brought their Pantheon and their. Uh, I guess you would call it a polytheism they brought their, their gods. And what would happen as, as often happened in a polytheistic system is you develop this hybrid where the Romans.Say, well, who are your gods? And they would say, well, this is our God of the sky. This is our God of the water. And they would just introduce them into the Roman Pantheon. So you got to blend it, or they would even combine gods, which is not uncommon. And polytheistic systems has already mentioned. So there was quite a bit of pagan practice and it was still present by the time the Anglo-Saxons appeared.
Welcome to The Nonlinear Library, where we use Text-to-Speech software to convert the best writing from the Rationalist and EA communities into audio. This is: Supervise Process, not Outcomes, published by stuhlmueller on April 5, 2022 on LessWrong. We can think about machine learning systems on a spectrum from process-based to outcome-based: Process-based systems are built on human-understandable task decompositions, with direct supervision of reasoning steps. Outcome-based systems are built on end-to-end optimization, with supervision of final results. This post explains why Ought is devoted to process-based systems. The argument is: In the short term, process-based ML systems have better differential capabilities: They help us apply ML to tasks where we don't have access to outcomes. These tasks include long-range forecasting, policy decisions, and theoretical research. In the long term, process-based ML systems help avoid catastrophic outcomes from systems gaming outcome measures and are thus more aligned. Both process- and outcome-based evaluation are attractors to varying degrees: Once an architecture is entrenched, it's hard to move away from it. This lock-in applies much more to outcome-based systems. Whether the most powerful ML systems will primarily be process-based or outcome-based is up in the air. So it's crucial to push toward process-based training now. There are almost no new ideas here. We're reframing the well-known outer alignment difficulties for traditional deep learning architectures and contrasting them with compositional approaches. To the extent that there are new ideas, credit primarily goes to Paul Christiano and Jon Uesato. We only describe our background worldview here. In a follow-up post, we'll explain why we're building Elicit, the AI research assistant. The spectrum Supervising outcomes Supervision of outcomes is what most people think about when they think about machine learning. Local components are optimized based on an overall feedback signal: SGD optimizes weights in a neural net to reduce its training loss Neural architecture search optimizes architectures and hyperparameters to have low validation loss Policy gradient optimizes policy neural nets to choose actions that lead to high expected rewards In each case, the system is optimized based on how well it's doing empirically. MuZero is an example of a non-trivial outcome-based architecture. MuZero is a reinforcement learning algorithm that reaches expert-level performance at Go, Chess, and Shogi without human data, domain knowledge, or hard-coded rules. The architecture has three parts: A representation network, mapping observations to states A dynamics network, mapping state and action to future state, and A prediction network, mapping state to value and distribution over next actions. Superficially, this looks like an architecture with independently meaningful components, including a “world model” (dynamics network). However, because the networks are optimized end-to-end to jointly maximize expected rewards and to be internally consistent, they need not capture interpretable dynamics or state. It's just a few functions that, if chained together, are useful for predicting reward-maximizing actions. Neural nets are always in the outcomes-based regime to some extent: In each layer and at each node, they use the matrices that make the neural net as a whole work well. Supervising process If you're not optimizing based on how well something works empirically (outcomes), then the main way you can judge it is by looking at whether it's structurally the right thing to do (process). For many tasks, we understand what pieces of work we need to do and how to combine them. We trust the result because of this reasoning, not because we've observed final results for very similar tasks: Engineers and astronomers expect the James Webb Space Telescope to work because its deployment follows a well-understood plan, and it is built out of well-understo...
How the fox got appointed as a minister in the forest? What plan did the bear tell? Why did the rabbits suffer? Why did a rabbit go to the well? What happened to it there? What did the fox tell? Why did the fox decide to get into the well? Who is the new minister of the forest? What happened to the fox?நரி அமைச்சராக எவ்வாறு பதவி வாங்கியது? கரடி என்ன யோசனை சொன்னது? முயல்கள் ஏன் துன்பப்பட்டன? கிணறுக்கு சென்ற முயலுக்கு என்ன ஆனது? அது நரியிடம் என்ன சொன்னது? நரி கிணற்றுக்குள் இறங்க ஏன் முடிவெடுத்தது? காட்டின் புதிய அமைச்சர் யார்? நரிக்கு என்ன ஆனது?Youtube Story Link: https://youtu.be/7TdMHIDaXPk You can listen to this show and other awesome shows on the new and improved IVM Podcast App on Android: https://ivm.today/android or iOS: https://ivm.today/iosYou can check out our website at http://www.ivmpodcasts.com
Get .1 ASHA CEU hereIn this week's episode we are joined by Jill d'Braunstein, an experienced SLP passionate about supervision. Jill walks us through different components of ASHA requirements and highlights the importance of relationship building through the supervision process.Learning OutcomesDescribe ASHA requirements and the role of the SLP Supervisor/Mentor.Identify at least 2 common areas new graduates need additional guidance.Describe the importance of using a needs-based approach to increase the success of your CF's experience. Resources:Clinical Fellowship Skills InventoryASHA RESOURCES: A Guide to the ASHA Clinical Fellowship ExperienceASHA RESOURCES: Template for Tracking Supervisory ActivitiesASHA RESOURCES: Supervision Requirements for Clinical Educators and Clinical Fellowship MentorsASHA RESOURCES: 2020 Clinical Fellowship Skills InventoryDisclosures:Jill D'Braunstein's financial disclosures: Jill is the owner of a private practice and JDB Speech a Teachers pay Teachers store. Jill D'Braunstein has no non-financial relationships to disclose.Kate Grandbois financial disclosures: Kate is the owner / founder of Grandbois Therapy + Consulting, LLC and co-founder of SLP Nerdcast. Kate Grandbois non-financial disclosures: Kate is a member of ASHA, SIG 12, and serves on the AAC Advisory Group for Massachusetts Advocates for Children. She is also a member of the Berkshire Association for Behavior Analysis and Therapy (BABAT), MassABA, the Association for Behavior Analysis International (ABAI) and the corresponding Speech Pathology and Applied Behavior Analysis SIG. Amy Wonkka financial disclosures: Amy is an employee of a public school system and co-founder for SLP Nerdcast. Amy Wonkka non-financial disclosures: Amy is a member of ASHA, SIG 12, and serves on the AAC Advisory Group for Massachusetts Advocates for Children.Time Ordered Agenda:15 minutes: Introduction, Disclaimers and Disclosures15 minutes: Review ASHA requirements and the role of the SLP Supervisor/Mentor15 minutes: Descriptions of common areas new graduates need additional guidance10 minutes: Descriptions of the importance of using a needs-based approach to increase the success of your CF's experience5 minutes: Summary and ClosingDisclaimerThe contents of this episode are not meant to replace clinical advice. SLP Nerdcast, its hosts and guests do not represent or endorse specific products or procedures mentioned during our episodes unless otherwise stated. We are NOT PhDs, but we do research our material. We do our best to provide a thorough review and fair representation of each topic that we tackle. That being said, it is always likely that there is an article we've missed, or another perspective that isn't shared. If you have something to add to the conversation, please email us! Wed love to hear from you!__SLP Nerdcast is a podcast for busy SLPs and teachers who need ASHA continuing education credits, CMHs, or professional development. We do the reading so you don't have to! Leave us a review if you feel so inclined!We love hearing from our listeners. Email us at info@slpnerdcast.com anytime! You can find our complaint policy here. You can also:Follow us on instagramFollow us on facebookWe are thrilled to be listed in the Top 25 SLP Podcasts!Thank you FeedSpot!
2022 is here…How is that possible? Does anyone else still feel like it's the fall of 2019? The last year has flown by, but we are geared up for some really exciting stuff in 2022… And we are starting the year off with some of our favorite topics. We have a few surprises in store too.January 3rd, 2022Podcast Course: The Critical Importance of Executive Functioning with Tera Sumpter. Offered for .1 ASHA CEU.This episode with SLP-turned-cognitive-processing nerd, Tera Sumpter, invites you to leave Speech Island (figuratively and literally) and take an excursion to Brain Boss island so that you can help your clients learn the speech and language skills they (and you) strive for. Tune in to learn about a cognitive practice model that aims to improve client and student learning outcomes by developing and using the power of executive functioning - the foundation of all learning.Register hereJanuary 7th, 2022Call for Papers Opens!Would you like to come onto the show and present with us? Do you have something to teach your community? Our Call for Papers opens January 7th and we would love to read your submission. Our call for papers is analogue to a traditional conference. Your submission are reviewed by us in conjunction with our advisory board to create as close to a peer review process as possible. We accept submission across all topics related to the scope of speech and language pathology. We accept submissions that are rooted in EBP and give our listeners clinical takeaways that help them become better clinicians. We love topics that make us think or look at a problem through a different lense. To be accepted the presentation must include:3 clear learning objectivesprinciples of evidence-based practice with emphasis on clinical application and / or relevance?opportunities for listeners to extend their self-directed learning?align with previously identified learning needs of our audienceTo submit your proposal you will need to submit:your name or the authors namestopicproposed titleabstractlearning objectivesat least 3 relevant referencesbiorelevant financial and non-financial relationshipsSubmit your proposal hereJanuary 10th, 2022Podcast Course: Contribute to your field: Supervise a Clinical FellowIn this episode, our expert guest, Jill D'Braunstein, walks us through what it means to supervise a clinical fellow, and how participating in a CF experience is a major contribution to our field. This course is registered with ASHA under Supervision and can count towards your Supervision requirement.Register HereJanuary 19th, 2022Registration Opens with Early Bird Pricing: SLP Live ConferenceWe are so excited to announce that we are co-hosting a conference this year with Tassel, a speech pathology e-learning company. Tassel has hosted this conference before, and many of you have probably heard of it or attended it under the name SLP Live or SLP Connect. We are super excited about this. Follow our social media channels or subscribe to our email list to stay up to date on speakers, giveaways, vendor hall information, and more. January 20th, 2022Live Webinar: Introduction to Special Education LawWe are thrilled to welcome Danielle Green, Esq. for a live webinar to discuss all things special education law. This course is geared towards the school-based SLP who is interested in learning more about requirements under IDEA. Registration for this course is now open and seats are limited. This course is included in our Superfan Subscription.Register HereJanuary 24th, 2022Podcast Course: Childhood Apraxia of Speech with Nancy KaufmanWe had the pleasure of interviewing a speechie household name - Nancy Kaufman. Nancy joined us for an interview about all things motor speech. She walked us through her perspectives on childhood apraxia of speech that she has gained over years of experience. Register Here.January 31st, 2022Podcast Course: AAC Evaluation Basics Part 3: Documentation and Funding.This is the audio that came out of our first live podcast recording last spring! Join us for an hour and a half review of documentation and funding as it relates to augmentative and alternative communication (AAC) evaluations. We talk about data collection, how data relates to results and recommendations, and ethical considerations throughout the evaluation and funding process.Register HereWhat's Next?Stay tuned for more great stuff in the next few months, including a few big things we've been working on, including a free course in the first few weeks of January related to goal writing and progress monitoring. We are also opening our SLP Masterclass on goal writing and progress monitoring for the second in April and early bird pricing for that starts in February too. If you aren't on the waitlist, we highly recommend signing up to make sure you get a spot! Lots of great stuff to come - can't wait to share it with you all! __SLP Nerdcast is a podcast for busy SLPs and teachers who need ASHA continuing education credits, CMHs, or professional development. We do the reading so you don't have to! Leave us a review if you feel so inclined!We love hearing from our listeners. Email us at info@slpnerdcast.com anytime! You can also:Follow us on instagramFollow us on facebookWe are thrilled to be listed in the Top 25 SLP Podcasts! Thank you FeedSpot!
25 year veteran of the fire service and experienced public information officer.Firefighter supervisor with a municipal fire agency. Supervise a crew of firefighters with emergency response and day to day business. Make command decisions as needed during emergency incidents to protect life and property and to stabilize the situation.Public information experience includes working with internal and external partners to promote fire department programs. During significant public safety incidents, provide information to members of the community and media locally and throughout the state. This is done with traditional media interview, news release, website, and social media.As a member of a federal incident management team, respond as a co-lead PIO when the team gets activated for large scale incidents. Work with hosting agency(ies) to identify information needs, manage them for the duration of the incident, and prepare for an effective transition back to the host agency at conclusion of the assignment.Experienced project initiation and management. Recent experience involved establishing a team to archive fire department records and migrating them to a new records management system that was customized to the organization's needs. Established, built up, and maintained the Garden Grove Fire Department's social media presence. This included working with other city departments to establish and formalize an official social media committee.21 years of in-class adult education experience, including 10 years of Emergency Medical Technician program coordination. Curriculum development & clinical coordination.Twitter @piothanhnSupport the show (https://t.co/GOmAg9X6e8?amp=1)
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