Podcasts about Kadabra

Following a packed-out première in 2024, the award-winning documentary Show Her The Money is returning to Ireland this May for a second ever Dublin screening as part of the TechFoundHer Summit 2025 - Women Innovators Rise. The screening will take place as part of Summit 2025 on May 14th at the Round Room at the Mansion House, Dublin and includes an exclusive post-screening panel discussion with international investors, founders, and innovation leaders. Wendy Ryan, one of the star investors featured in the award winning documentary, is flying in from the U.S. to take part in the discussion, alongside Lata Setty, globally renowned tech entrepreneur and investor. The panel will also spotlight leading voices in Ireland's startup ecosystem including Mary Rodgers (PorterShed), Suzanne Mills and Eshna Gogia (Republic of Work). A Film That's Fuelled a Global Movement Catherine Gray is the producer and driving force behind Show Her the Money, a film that addresses how women are getting less than 2% of venture capital funding and demystifies what venture capital is. Directed by Ky Dickens, Show Her The Money follows four dynamic female founders battling systemic barriers to secure venture capital - and the game-changing women investors who back them. From inclusive fashion to beauty rooted in Ayurveda, the featured businesses challenge norms and stereotypes, and their journey highlights a core reality: women receive less than 2% of venture capital funding globally. This documentary is a rallying cry to change that. The movie also features rock-star female investors who invest in diverse women entrepreneurs with innovations that will change the world including - Wendy Ryan, a powerhouse investor using her generational wealth to empower women and BIPOC entrepreneurs. "Show Her The Money" reminds us that money is power, and women need it to achieve true equality. Watch the trailer here About the Panel: Women Investing in Women Wendy Ryan, CEO of Kadabra and bestselling author of Learn Lead Lift, uses her generational wealth to empower women entrepreneurs. Wendy advises and invests in early-stage companies. Her impact facilitating access to capital for historically excluded entrepreneurs is featured in the movie. She explains the rationale for investing in women, "If I write a woman a $10,000 cheque she is going to go much further with it than a similarly situated male would - returns are actually better when you invest in women." She is an executive producer in Show Her The Money along with Sharon Gless from Cagney and Lacey fame. Joining her in Dublin is VC and Angel investor Lata Setty who has a diverse background in patent litigation and tech entrepreneurship. Setty is the inaugural Investor and on Advisory Board of Silicon Valley Women's Founder Fund. She was also the inaugural investor at How Women Invest Funds l, ll & lll leveraging her experience in launching and scaling successful VC-funded startups. Their insights will be complemented by Irish ecosystem leaders Mary Rodger, Suzanne Mills and Eshna Gogia, who each work to support and scale women-led ventures across Ireland. Máirín Murray, Founder of TechFoundHer, said of the upcoming screening, "Show Her The Money is more than a documentary - it's a catalyst for change. We're bringing it back to Dublin because the conversation is far from over. If we want a future where innovation is truly inclusive, we need to see, hear, and fund women entrepreneurs. This film opens eyes - and doors." About TechFoundHer Summit 2025 - Women Innovators Rise Taking place at the Round Room at the Mansion House, the TechFoundHer Summit 2025 is a high-energy event featuring global leaders in tech and investment. Key speakers include Kelly Vero, legendary developer behind Tomb Raider and Halo 3, and innovators like Lesley Sackey, Dr Patricia Scanlon, Barbara McCarthy, and Áine Kerr. Themes for the summit include: Tech Has No Gender Funding Forward: Angel to VC Breaking Through: Scaling Startups Women ...

Have you ever wondered what it takes to leave a lasting legacy in the world of entrepreneurship? In this illuminating episode of The Angel Next Door Podcast, host Marcia Dawood engages in a thought-provoking conversation with Wendy Ryan, who transforms our understanding of leadership, investment, and legacy-building. Wendy's journey from human resources to becoming a game-changing investor offers valuable insights for anyone looking to make a meaningful impact in the business world.Our guest, Wendy Ryan, is no ordinary investor. She launched her career in human resources and organizational development before founding her company, Kadabra, in 2014. Wendy's commitment to fostering leadership and extending support to women-led businesses emerged from her own life experiences and generational wealth. A published author and executive producer, Wendy is also a featured star in the influential film, "Show Her the Money."Throughout the episode, Wendy explains her revolutionary "Learn Lead Lift"(also the title of her book) framework, exploring how leadership rooted in mindfulness, skill acquisition, and altruistic motivation can transform not just businesses but entire communities. Listeners will discover how to leverage their resources for broader social impact and navigate the complex landscape of early-stage investing. This episode is a must-listen for aspiring entrepreneurs, seasoned investors, and anyone interested in creating a legacy that resonates across generations. Wendy's wisdom and Marcia's insightful questions offer a blueprint for making significant, lasting contributions in a rapidly evolving world. To get the latest from Wendy Ryan, you can follow her below!LinkedIn - https://www.linkedin.com/in/wendyryankadabra/https://www.wearekadabra.com/  Sign up for Marcia's newsletter to receive tips and the latest on Angel Investing!Website: www.marciadawood.comLearn more about the documentary Show Her the Money: www.showherthemoneymovie.comAnd don't forget to follow us wherever you are!Apple Podcasts: https://pod.link/1586445642.appleSpotify: https://pod.link/1586445642.spotifyLinkedIn: https://www.linkedin.com/company/angel-next-door-podcast/Instagram: https://www.instagram.com/theangelnextdoorpodcast/TikTok: https://www.tiktok.com/@marciadawood

Wendy Ryan (she/her), CEO of Kadabra, author of the award-winning bestseller, Learn Lead Lift: How to Think, Act, and Inspire Your Way to Greatness and I recap the latest 5 Things (Good Vibes in DEI) in just 15 minutes. This week our conversation is about a unique cure for travel anxiety, period leave progress in Odisha, a Staten Island Parade with a little more pride, and more!Here Are This Week's Good Vibes:Staten Island Parade Finally Catches UpDarts, Drama, and Breaking BarriersLlama Kisses: Travel Anxiety, CuredPeriod Leave Progress in OdishaEqual Rights for Everyone, Period.Good Vibes to Go: Bernadette's GVTG: On Wednesday, attend Rex Wilde's next virtual gathering space for DEI, HR, and ERG leaders to discuss all things TGX+.Wendy's GVTG: Find one thing you can do each day to move yourself forward in a time in which it can be easy to feel stuck. Whether it's a self-care yoga class or sending someone a thoughtful note, or something else entirely, stay in action!Read the 5 Things Stories.Connect with Wendy Ryan Join thousands of readers by subscribing to the 5 Things newsletter. Enjoy some good vibes in DEI every Saturday morning. https://5thingsdei.com/

Mogoče bosta ugotovila, da jima čarovnija uspe le, če čarata skupaj. Pripoveduje: Majda Grbac. Napisala: Bina Štampe Žmavc. Posneto v studiih Radia Slovenija 2003.

En este número de La Ruleta Rusa hemos escuchado a Dead Meadow; Kadabra; King Crimson; Peter Hammill; The Heavy Minds; Pristine; Rory Gallagher. Leer Más La Ruleta Rusa. Entrega 41.2024. at La Ruleta Rusa Radio Rock.

This week on the Zen Perry Project, we welcome Eddie Brnabic - guitarist and founding member of the Portland-based stoner metal power-trio, HIPPIE DEATH CULT. Freshly returned from a summer European tour and gearing up for a fall North American run, Eddie talks everything from the experience of performing with the backdrop of a Sardinian sunset on the beach of the legendary Duna Jam festival to reminiscing on how he and bandmates Laura Phillips & Harry Silvers have effectively challenged each other to creatively gel. Don't miss Hippie Death Cult's North American Transcendental Trip which kicks off TONIGHT in Boise with KADABRA as support. Photo courtesy of Danilo Piludu. Support the Show.Introspective interviews with artistic individuals - an ongoing audiovisual journal of Zen Perry. Behold a wall of periodically updated webpages!Official Website: https://www.zenperryproject.com/Patreon: https://www.patreon.com/breakingnorthInstagram: @https://www.instagram.com/zenperryproject/Facebook: https://www.facebook.com/breakingnorthpodcastTwitter: @BreakingNorthTwitch: https://www.twitch.tv/breakingnorth_Youtube: https://www.youtube.com/@zenperryproject160Email: info@zenperryproject.comThanks for listening - hope you enjoy!

Throughout her 25+ year career in human resources, organizational development and executive development Wendy Ryan has partnered with hundreds of individuals, teams and organizations globally, propelling front-line through C-suite leaders and board members to new levels of success. As CEO of Kadabra, Wendy leads an interdisciplinary team of experts who are revolutionizing how leaders think, what they do and how they show up to others through The Learn Lead Lift Framework® and Kadabra's unique learning solutions.Elevate Your Brand is the #1 marketing podcast for entrepreneurs and “wantrepreneurs” looking for insider tips and secrets from the most exciting new and growing brands in Los Angeles and the US at large. Each week, entrepreneurial special guests join Laurel Mintz, founder and CEO of award-winning marketing agency Elevate My Brand, to discuss the marketing failures and successes that have brought their brands to the next level. Learn from real-life experiences and be inspired by leaders in your industry about how smart digital and experiential marketing can elevate your brand.Contact us: https://www.elevatemybrand.com/contactStay connected & DM us feedback on the podcast:Instagram: https://www.instagram.com/elevatemybrandla/ LinkedIn: https://www.linkedin.com/company/elevatemybrandla/ TikTok: https://www.tiktok.com/@elevatemybrandContact us: https://www.elevatemybrand.com/contact Stay connected & DM us feedback on the podcast:Instagram: https://www.instagram.com/elevatemybrandla/ LinkedIn: https://www.linkedin.com/company/elevatemybrandla/ TikTok: https://www.tiktok.com/@elevatemybrand

It's return guest season here at Latent Space! We last talked to Kanjun in October and Jonathan in May (and December post Databricks acquisition): Imbue and Databricks are back for a rare treat: a double-header interview talking about DBRX from Databricks and Imbue 70B, a new internal LLM that “outperforms GPT-4o” zero-shot on a range of reasoning and coding-related benchmarks and datasets, while using 7x less data than Llama 3 70B.While Imbue, being an agents company rather than a model provider, are not releasing their models today, they are releasing almost everything else: * Cleaned-up and extended versions of 11 of the most popular NLP reasoning benchmarks* An entirely new code-focused reasoning benchmark* A fine-tuned 70B model, built with Meta Llama 3, to identify ambiguity* A new dataset of 450,000 human judgments about ambiguity* Infrastructure scripts for bringing a cluster from bare metal to robust, high performance training* Our cost-aware hyperparameter optimizer, CARBS, which automatically and systematically fine-tunes all hyperparameters to derive optimum performance for models of any sizeAs well as EXTREMELY detailed posts on the infrastructure needs, hyperparameter search, and clean versions of the sorry state of industry standard benchmarks. This means for the FIRST TIME (perhaps since Meta's OPT-175B in 2022?) you have this level of educational detail into the hardware and ML nitty gritty of training extremely large LLMs, and if you are in fact training LLMs of this scale you now have evals, optimizers, scripts, and human data/benchmarks you can use to move the industry forward together with Imbue.We are busy running the sold-out AI Engineer World's Fair today, and so are unable to do our usual quality writeup, however, please enjoy our show notes and the excellent conversation! Thanks also to Kanjun, Ashley, Tom and the rest of team Imbue for setting up this interview behind the scenes.Video podTimestamps* [00:00:00] Introduction and catch up with guests* [00:01:55] Databricks' text to image model release* [00:03:46] Details about the DBRX model* [00:05:26] Imbue's infrastructure, evaluation, and hyperparameter optimizer releases* [00:09:18] Challenges of training foundation models and getting infrastructure to work* [00:12:03] Details of Imbue's cluster setup* [00:18:53] Process of bringing machines online and common failures* [00:22:52] Health checks and monitoring for the cluster* [00:25:06] Typical timelines and team composition for setting up a cluster* [00:27:24] Monitoring GPU utilization and performance* [00:29:39] Open source tools and libraries used* [00:32:33] Reproducibility and portability of cluster setup* [00:35:57] Infrastructure changes needed for different model architectures* [00:40:49] Imbue's focus on text-only models for coding and reasoning* [00:42:26] CARBS hyperparameter tuner and cost-aware optimization* [00:51:01] Emergence and CARBS* [00:53:18] Evaluation datasets and reproducing them with high quality* [00:58:40] Challenges of evaluating on more realistic tasks* [01:06:01] Abstract reasoning benchmarks like ARC* [01:10:13] Long context evaluation and needle-in-a-haystack tasks* [01:13:50] Function calling and tool use evaluation* [01:19:19] Imbue's future plans for coding and reasoning applications* [01:20:14] Databricks' future plans for useful applications and upcoming blog postsTranscriptSWYX [00:00:00]: Welcome to the Latent Space Podcast, another super special edition. Today, we have sort of like a two-header. John Frankel from Mosaic Databricks, or Databricks Mosaic, and Josh Albrecht from MBU. Welcome.JOSH [00:00:12]: Hey, glad to be here.SWYX [00:00:14]: Thank you for having us. Hey, so both of you are kind of past guests. Jonathan, you were actually one of the most popular episodes from last year talking about MPT7B. Remember the days when we trained large models and there was 7B?JONATHAN [00:00:30]: Yeah, back when reproducing LLAMA1-7B was considered a huge accomplishment for the field. Those are the good old days. I miss that.SWYX [00:00:38]: As the things have accelerated a lot. Actually, let's do a quick catch up and Josh, you can chime on in as well. So Databricks got acquired. I talked to you at New York.JONATHAN [00:00:45]: Mosaic got acquired, although sometimes it feels like Mosaic acquired Databricks because, you know, we're having a lot of fun being here. But, you know, yeah.SWYX [00:00:52]: Yeah. I mean, you are chief scientist now of Databricks.JONATHAN [00:00:55]: Chief AI scientist. Careful with the title. As much as I would love to understand how Spark works, I'm going to have to defer that to much smarter people than me.SWYX [00:01:03]: Got it. And I don't know about like what you would highlight so far as a post-acquisition, but the most recent news is that you guys released DBRX. Is that the thing that most people should be aware of?JONATHAN [00:01:13]: Actually, that's no longer the most recent news. Honestly, the most recent news, we announced this, but it was at our Data and AI Summit last week. So it was announced among like 100,000 other things, is that we finally released our text to image model, which has been a year in the making through a collaboration directly with Shutterstock. There was a lot of work put into finding a dataset that we were comfortable with working on and trying to build a model that honestly, I felt like I could trust and that others might be able to trust to put out in the world. So that model was released last week. It's unfortunately just available via API due to the fact that the data is quite sensitive and quite valuable. It's Shutterstock's entire business in a lot of ways, but I'm still really excited that there's now a model that is trained on a dataset where the provenance of every single image is known, and it's a damn good model. So I'm really proud of the team on that.SWYX [00:01:55]: Yeah, amazing. Josh, do you have any thoughts on image model questions?JOSH [00:01:59]: That is not my area of expertise, but I was excited to see the release of it last week as well, and very happy that you guys did a nice job on the data side of everything there. So that was cool to see.SWYX [00:02:09]: I think what's unusual is like, I think Shutterstock's doing multiple deals in multiple labs. So what is the Shutterstock model? Like, I guess, is this the house model for Shutterstock? Is this Databricks' version of the Shutterstock model? Like, what is this?JONATHAN [00:02:22]: The way that I would think about it is that Shutterstock is doing an amazing business in AI across the board. Their dataset is kind of widely known to be the best stock photos dataset in the world, the most comprehensive, the biggest. When you think about like, what dataset am I going to train a multimodal model on? You call Shutterstock. And I, at least I've heard in the news, like OpenAI, Google, Meta, Apple have all called Shutterstock and made those deals. So a lot of models have had Shutterstock data incorporated into them. But this is the only model I know of so far where it was, you know, exclusively and specifically trained just on the vanilla Shutterstock data. There was nothing else mixed in. We didn't go and scrape the web and find other data or combined datasets or anything like that. And so this is, in some sense, the house blend. But the other piece is that it's just a dataset where the provenance of every image is known in public. Where did the data come from? It is the Shutterstock collection. That's it. You know, nothing less, nothing more. And certainly being at Databricks, if I've learned one thing, I've learned about enterprise customers and what they want out of AI. And one of the things they ask for most is just, what can you tell me about the data the model was trained on? And here, especially for text to image models, where images are just tricky subject matter, there's been a lot of kind of legal conversation about images, especially. It's nice to just have something where I can point to it and say, you know, if you want to know where the images came from, these are what they are and this is how they got there.SWYX [00:03:36]: I will talk a little bit about Databricks because it's relevant to the rest of today's episode. So Databricks, sorry, I keep misspeaking. It's DBRX.JONATHAN [00:03:46]: DBRX, actually, there's been a pronunciation update. It is now D-B-Rex. So we have decided to add a dinosaur mascot because what model doesn't like a mascot? So literally, I wish I could pull it up. There is a little plush dinosaur that we had made. It's like the world's cutest dinosaur, but it is the official mascot of D-B-Rex. And there's a little dinosaur logo that, you know, you'll probably see around a little bit more because DBRX is a mouthful, but D-B-Rex, like, you know, it's just kind of...SWYX [00:04:13]: Rolls off the tongue. I love mascots. Like every company should have a mascot. And I think Hugging Face got it right. You need an emoji mascot because that's the minimal viable image.JONATHAN [00:04:21]: I probably shouldn't talk at all about, you know, Velociraptor, but, you know, that's a, maybe that's something we can talk about later in the summer. I'll just leave it at that.SWYX [00:04:28]: Okay. That's a hint to names. I feel like your names leak a lot of alpha. So just to quickly cover the headline details, DBRX, as Make Sure Experts model, that's fairly big, 132 billion total parameters, so 36 billion active on any input, pre-trained on 12 trillion tokens of text and code, and did really well on evals to the point where you had to dye your hair blue. That's my high level conclusion.JONATHAN [00:04:53]: Never make a bet with your team two weeks out from model launch, even when, you know, human eval is looking quite bad. Because if you set some bar, even if it's arbitrary and you think there's no way in hell they're going to hit it, apparently money doesn't motivate people anymore. Humiliating their boss motivates people. So Josh, you should really take a hint from this. You know, you cannot pay someone enough money to make up for you dyeing your hair blue.JOSH [00:05:15]: I'll keep that in mind for our next model.SWYX [00:05:17]: It works. So speaking of Imbue's next model, perhaps Josh, you want to actually just say hi to the general sort of latent space audience and talk about what we're releasing today. Yeah.JOSH [00:05:26]: I'm Josh, CTO of Imbue, and we're not releasing the model. We're not releasing the weights, but we are releasing a bunch of different things that should make it easier for other people to make their own models. So I think right now, training foundation models from scratch is like a very difficult, time-consuming, expensive, kind of risky endeavor, especially for smaller companies. And the things that we're releasing hopefully make that at least a little bit easier. So the things that we're releasing fall into kind of three different buckets. One is infrastructure and scripts for dealing with the kind of hardware and hardware failures and understanding how well is the actually lowest level of thing actually working so that you can actually do your training at all and at a reasonable speed without having to constantly restart, etc. So infrastructure and training scripts. A second set of things is around the evaluation. So after you've trained it, like how well is this actually working and how do you know how well it's working? We're releasing a whole bunch of different data there, a new benchmark about code, reasoning, understanding, as well as our own private versions of 11 different open source benchmarks. So things like pool queue or ANLI, where we've gone through and kind of cleaned up the data as much as possible by looking at all the ones that models get wrong or that are flagged for ambiguity and also our own kind of private reproductions of those where we've done like a kind of clean room black box, like, okay, this is what the data set is supposed to be. Here are some examples. Let's make our own version of this to make sure that there is no data contamination, etc. To make sure that we're actually, you know, not testing on train. And then I think a final thing that we're releasing there is around 450,000 human judgments about ambiguity and question quality, which we used in the process of cleaning these evaluations and we also hope will be helpful for other people training kind of similar models. And then the third thing is CARBS, our hyperparameter, our cost-aware hyperparameter optimizer, which was especially helpful for being able to experiment at much smaller scales and then scale those experiments up to the much larger scale kind of on the first try without having to retry it. You don't want to be training, you know, 10, 20 different 70B models. You really want to get these larger modelsSWYX [00:07:30]: right on the first try.JOSH [00:07:30]: And so the ability to kind of tune things very precisely and learn scaling laws, not just for, you know, the like data and flops, but also for learning rate and all the other hyperparameters and see like how should you scale these things up was extremely valuable to us as we were training the larger models. Yeah, that's a lot of stuff.SWYX [00:07:49]: Yeah, exactly. So there's a bunch of stuffJOSH [00:07:50]: we'll have to go through all of it.JONATHAN [00:07:52]: Yeah, I just want to throw in how excited I am about this. This is the stuff that nobody ever talks about. That is the difference between success and failure in this stuff. Like, can you get your cluster to run? Can you get software on your cluster? Can you figure out what broke? Because fault tolerance is still not really built into any of the fundamental primitives of training models. And so if something breaks, you have to go figure out what broke, your job stops, you have to restart your job. It is a nightmare just to get to the point where anything can train on the cluster. A basic MPI hello world that has the GPUs talk to each other is hard enough, let alone actually training a model, let alone getting good performance out of the GPUs, let alone actually getting a model that converges to anything interesting. There's so many levels of things you have to accomplish. This is the kind of stuff that matters. I think to a point that Josh made earlier, before we got on here, there are plenty of weights out there. Nobody's released this.JOSH [00:08:46]: Yeah, that was part of the motivation actually is that there are lots of other things that are complimentary, but I have not seen nearly as much discussion about some of these other things that we think are pretty important. I mean, in some sense,SWYX [00:08:56]: I'm very excited to have Jonathan on because this is a little bit, you're a bread and butter with Mosaic. And I think you've released some part with Composer. And I think it's just really interesting to see like a different take, basically a full stack take that's kind of open source today.JONATHAN [00:09:18]: Yeah, it's really kind of, it's been an ordeal to figure this out. And every time something changes, whether it's a new GPU or even a new driver update, you get new creative errors and new things go wrong. And, you know, we've dealt with the weirdest things from, you know, our InfiniBand cables getting stolen from the data center twice, like in boxes before they arrived at the data center. Like, you know, Porch Pirate basically had stolen our InfiniBand cables back when those were hard to come by. To like, you know, weird recalls of switches to like the strangest stuff has happened. I have my favorite GPU failures I've seen, like ones where the GPU doesn't fail, it has a correctable memory issue and the memory correction causes the GPU to become a straggler and hold up the whole job. Like weird stuff happens and figuring out how to not just identify all of that, but then eventually productize it, is in some sense, the entire story of Mosaic and now Databricks in terms of our ML offering. Really, the thing we offer is we have gone through this suffering and figured out how to even productize that. It has been a pain in the butt.SWYX [00:10:20]: Yeah, it's a lot of work.JOSH [00:10:20]: I think my favorite failure was GPU is just giving wrong math. Like if they give errors, great, because you can see the errors, but if they just give you the wrong math back, not so fun.SWYX [00:10:30]: When did they give you wrong math?JOSH [00:10:32]: Like literally you could just, you know, add two things. For example, the numbers come back. They're not the numbers that they're supposed to be.JONATHAN [00:10:40]: I think it's important to say at this stage, just because like it, I think it goes without saying for Josh and I, but it's worth saying here, this isn't to say that like anything is wrong with us. It's not like NVIDIA did a bad job or, you know, Mellanox did a bad job or the like the server builder, the data center operator, the cloud provider, like the million other parties that are involved in building this. We are running these insane chips that are huge and complicated and built on tiny transistors at insane frequencies with insane heat in data centers that for the most part, were not built remotely for this kind of power or heat and have been retrofitted for this. Like failures happen on a good day with normal CPUs. And this is not a good day and not a normal CPU for the most part. It's fun to joke about all the weird things we see. This is not to say anybody's done anything wrong. This is just kind of part and parcel of working on a massive cluster running at multiple megawatts of power at a time.SWYX [00:11:32]: It's crazy. Yeah.JONATHAN [00:11:33]: So optical cables, like all sorts, like everything.SWYX [00:11:37]: I'll take the opportunity to start going to the sort of infra piece. There's just like a description of the infra just to give people a sense of what we talk about when we talk about massive clusters. So I'm just going to read off the blog post here. This post is about one cluster that has 4,092 H100 GPUs spread across 511 computers. They use unified fabric manager nodes, which manage the infinite band network. And you talk a little bit about your networking. Is there anything unusual about this setup that you'll call out to people?JOSH [00:12:03]: Yeah, actually this particular cluster is a little bit non-standard. The normal, like vanilla setup for these large clusters as vanilla as it can be is what's normally like a 127 node cluster. So closer to like 1024 GPUs instead of 4,000. Here we have a larger cluster. As you start to get into the larger clusters, the networking becomes a little bit more custom. It's a little bit more, it's a little bit trickier. It's a little bit more difficult to get these things to all be able to talk to each other at the same speed. And so this has, in this particular case, this is a three tier network architecture instead of two tiers, kind of the normal one. So most of the clusters are a little bit smaller. As you get to even larger scales, then this becomes even much more complicated,SWYX [00:12:43]: much more expensive.JOSH [00:12:43]: So we chose this particular scale, kind of knowing our own workloads and kind of what we wanted to do. This was kind of the right size for us. But yeah, I think it's not exactly vanilla already. It's already getting into kind of the custom territory.SWYX [00:12:54]: So my understanding is that there, and is there any part of this that comes with the Voltage Park deal that you guys had? Is that part of the hardware that you got from the deal with them?JOSH [00:13:04]: Yeah, so we worked really closely with Voltage Park to set up all their clusters and infrastructure and everything and kind of decide even like what to order, how should the networking work? Like we were very involved in kind of the construction and bring up of this. And that's what this post is about, is about that process of like bringing up all these, there's like different clusters in different places of different scales. So in this particular post, we're talking about this one 4096 GPU, but there are other clusters that they have as well. And we were very closely involved with figuring out the exact architecture and kind of the trade-offs that go along with picking, you know, those exact components. You really don't want to like place the wrong order because it takes months to get it and it's very expensive. So yeah, we were happy to help out with that.JONATHAN [00:13:43]: And then your bit of good cables get stolen.SWYX [00:13:44]: Yeah, yeah, exactly.JOSH [00:13:47]: We wanted to make sure that we ended up with compute that would work for us and that would also work for their other customers. And so we kind of helped design something so that we would get exactly what we were looking for. We knew that these kinds of details would be super important and that getting down to the level of the hardware and like having these good scripts and everything was going to be a core part of like actually getting this to work. I'm very glad that we did that. I don't think that most companies kind of take that full stack approach, but for us, it certainly paid off.SWYX [00:14:12]: Yeah, it's basically sort of built to spec. It's interesting that relationship because you usually, for the rest of us who don't operate at your scale, we take whatever we can get from cloud providers, but you are basically co-designing from the single machine up. And you described that a little bit. Do you want to take us through the process that you described here?JOSH [00:14:27]: Yeah, so for the actual, like the blog post and kind of bringing these machines online.SWYX [00:14:32]: Yeah.JOSH [00:14:32]: So yeah, I think the process, as we have it broken down in the blog post, there's kind of a few different layers. First is like getting the individual machines to work at all and then getting the machines to actually be able to talk to each other. So getting the InfiniBand networking to work and then getting to a point where, you know, not just the machines are working and they can talk to each other, but everything is actually working correctly. There's a big gap between like it's working at all to it's working perfectly correctly. And then after you have all this stuff working perfectly correctly, nice and healthy, then now you get into kind of the software data, like training issues. And then after that, you're still not done. Like now, even once you're training at full speed, things are going to fail over time. Things are going to change. There's going to be new, you know, firmware updates. Like how do you kind of deal with this change and flux over time without going crazySWYX [00:15:16]: and pulling your hair out,JOSH [00:15:16]: trying to like reproduce things or understand why there were regressions. And so there's a lot of work to kind of automate the infrastructure tooling as well. And kind of the first step, like bringing these things online in the first place, you know, you have hundreds of machines at this point. So you don't necessarily want to be like walking around with like a CD-ROM or a USB drive, like plugging it in with your keyboard, like hitting next, next, next on the OS install. That's not how this works. You do that for one machine. And then you use, we use this thing called Metal as a Service to bring up all the other machines. So it's a kind of server that can kind of install the operating system on these other machines. So most like when you're talking about these machines, like each machine is, you know, on the order of hundreds of thousands of dollars. So they usually come with a kind of out-of-band management interface as well. So they don't, they have their InfiniBand networking. They have their normal 100 gigabit per second Ethernet networking. These are like dual, redundant, et cetera. And then you also have this extra out-of-band management network. So you can log in and you can see like the boot screen or you can see the blue screen of death. You can like get in there and actually see what was wrong, which is pretty fun. And it makes it like possible to automate a lot of this work. So the beginning of that, and the blog post goes into much more detail about like exactly how we set these up and kind of the other errors that we ran into. When you're bringing these online, you'll definitely have failures. Even if they all worked in the factory, they get shipped, some parts come loose, something fails, something goes wrong. So when you're bringing them online, there'll be some that don't quite work for all sorts of reasons. As you start to be working with machines at this scale, like if something happens one in a thousand times, you're like pretty likely to see it. And so you can get pretty rare, weird things, especially since we had fairly early builds and fairly early versions of this hardware. Like these are some of the like first machines that were ever produced, some of the first GPUs. So you've got some extra special things there. We definitely worked with Dell, for example, on making fixes in the firmware level to be like, okay, like this thing is wrong. Like we need to update this at the firmware to like actually fix this particular thing. So we worked pretty closely with Dell and Nvidia. Yeah, that's what I'm saying. Like this stuff gets complicated. And the thing is like, you know, taking a step back, the whole reason we're doing this, right, is that we knew that this was going to be complicated. There would be these kinds of failures. And if we're just using, you know, AWS or some other cloud provider, these errors are still gonna be there and you're gonna have no way to know and no way to debug this and no way to diagnose what's going wrong. And so we would much rather be able to like call up Dell and say, hey, this isn't working. And they're like, yep, okay, cool. Let's debug it together. Oh, I see. Yeah, cool. We'll ship a firmware update and actually fix this for you. That was a much better experience than like, great, just magically fails. I guess we restart and hope that that machine goes away. Like that's not a very good place to be. So yeah, that's kind of the first place is getting to a place where like GPU training is working on your single node machines. You can observe stuff. We have tons of tooling around like, you know, Prometheus and all sorts of other tools for understanding what's going on in these machines because you don't want to be like logging into each one and looking at the temperature or something you really need to have tooling to collect all these metrics, et cetera. Unfortunately, all of the scripts that we have for this are like for this entire cluster and for all this infrastructure are a little bit like special purpose for our particular thing. So it's not that every script that we have, it's not that you can just like take this and plug this in. Even if we did open source all the tooling that we have, you'd still have to do like a lot of work to open source it. What we are releasing is as many of the things that we can that are going to be useful for other people. You're still going to have to have some way of kind of managing these things, making your own like logging aggregators, et cetera, et cetera. So that's kind of bringing them up to the like, you know, the single nodes that are working. From there, it goes into, I'm happy to keep going if you want. Well, I just want to leave the opportunity for JohnSWYX [00:18:53]: to comment if there's anything that's different from how he runs things.JONATHAN [00:18:57]: Oh, I mean, all I'll say is I'll endorse this and say this s**t is hard. Like this is really, really hard. And, you know, I have a special props to, you know, the folks in Vue because they were building this from the ground up. You know, at Databricks and at Mosaic, we typically work with cloud providers because some of this stuff is just, there's too much to handle. It's complicated. There's a lot to deal with. And this doesn't even get into things like physical security, you know, securing power if you're the data center operator. Like this gets infinitely complicated and you have to abstract somewhere. Like, you know, and then you get to the folks who are literally building their own custom chips and like, good God.SWYX [00:19:36]: Like, oh my God, that's, you know,JONATHAN [00:19:38]: if you're one of those folks, you're having, you know, pour one out for the infra people at some of the AI chip startups who are having a really, really interesting time right now. But this stuff is really hard. And I don't think we talk about it much because there's so many other things that are hard. But the other hard things, I think everybody's becoming pretty familiar with at this point. This is something that I don't think there's ever really been a comprehensive discussion of, at least not that I've seen.SWYX [00:20:00]: Yeah, so my impression is that you guys, Mosaic, have your own software for sort of spinning up and down machines, just like Imbue had to build. But Imbue probably, it sounds like Imbue, you guys went fuller stack. I don't know how to describe it. Like Mosaic is not working with Dell on like their firmware.JONATHAN [00:20:21]: No, no, we're typically working with like, you know, pick your cloud provider on their Dell firmware or what have you. Like, it's kind of, I think one of the things, I don't know, Josh, you can correct me on this. It's kind of impossible if you're doing training to not go all the way through the entire stack, regardless of what happens. Like somehow I'm still chatting with cloud providers about power contracts, even though the whole point of dealing with the cloud provider is not to have to think about power contracts. Somehow I'm still asking them about which InfiniBand provider they used this time to see if this is part of the bad batch of cables I encountered on that cloud provider or what have you. Or like, we're still talking about a firmware update from pick your provider. You can't not do this. It's convenient that they have data center staff who are worrying about what to send back to which provider when, and they have people who can go and wait for the InfiniBand cables so they don't get stolen outside. But, you know, it's kind of, it's impossible not to really go full stack if you're thinking about the infrastructure at all. I don't know, Josh, correct me. No, I think that's right.JOSH [00:21:17]: That's what we expected from the beginning as well, is that we would inevitably have to get into the details here. And I'm glad that we kind of just planned for it. I think it made it a lot easier from our perspective to have direct control over this. Instead of having to go to the cloud provider that goes to the data center, that goes to the supplier, we could just go direct to NVIDIA or DellSWYX [00:21:37]: or the data center,JOSH [00:21:37]: whoever was responsible and be like, hey, this thing needs to change. And they're like, oh, okay. Yeah, that is our responsibility. Great, we can fix that. So it was just a lot easier for us to fix these bugs than if we had to go through an extra layer of email.SWYX [00:21:48]: Something we discussed in the pre-show was that you had a rule of thumb for your cluster of reliability. You say here in the post, by and large, you expect around 3% of your machines to break every week. So you're basically going to turn through all your machines in a year.JOSH [00:22:04]: As it says in the post. So that would be true if it was a uniform failure like that. But as it says in the post, it's usually these kind of problematic nodes. And to be clear, that is the number that we've heard from other people is like they're having about 3%. I don't think we're experiencing failure rates that are that high. I think ours is actually quite a bit lower than that, probably because we've taken the time to like dig into a large, maybe larger number than we should have of these failures and get to the root cause of it and be like, oh, okay, like that's exactly what's going wrong.SWYX [00:22:33]: How do we fix this?JOSH [00:22:33]: How do we prevent this from happening? How do we make automated checks for this so that if it does happen, it just goes back to whoever owns that particular part of the process and they can fix it immediately.SWYX [00:22:43]: And that's part of what you're also open sourcing, which is the health checks, right? You got the NIC health checks, GPU health check, this space health check, Docker D message. I don't know what that is.JOSH [00:22:52]: That one is just a lot of stuff.SWYX [00:22:54]: Yeah.JOSH [00:22:55]: That one is one where we realized that actually like when these machines boot, sometimes they wouldn't actually boot cleanly all the way. Or when they rebooted, they had problems that they didn't have when they were working before, which was kind of frustrating. Like usually if you restart your computer,SWYX [00:23:08]: it gets better.JOSH [00:23:08]: Here you restart. It did not get better.SWYX [00:23:10]: It got worse.JOSH [00:23:10]: That was very frustrating. So this health check looks at every particular line we've ever seen from the boot, like in D message, like every single log line that your computer emitsSWYX [00:23:21]: and says like,JOSH [00:23:21]: have we ever seen this before?SWYX [00:23:23]: Is this expected?JOSH [00:23:23]: Is this in the right order? Or is there something out of place? If there's anything out of place, let me say, okay, great. Like now it goes into this, like longer, more triage list of like, all right, great. Like, is this acceptable?SWYX [00:23:33]: Should we flag this?JOSH [00:23:33]: Like, should someone take a look at this? So we're looking down at a very, very granular detail level, what's happening on these computers to make sure that nothing is out of place. And that's critical because without that, if you're running your training, as Jonathan said, and this thing is slow, like what are you supposed to do? Right?SWYX [00:23:49]: Like you really,JOSH [00:23:49]: you really want to be very certain that like all 4,000 of these GPUs are working like they're supposed to.SWYX [00:23:54]: We know that.JOSH [00:23:54]: And so if it's slow, it's because like we messed up the config or something else and not because of this earlier thing that's like really hard to detect in software later.JONATHAN [00:24:01]: Yeah. I think the, I'm just curious to ask,SWYX [00:24:03]: like, you know,JONATHAN [00:24:03]: suppose you were to set up another, let's say another H100 cluster and it were at a different data center. And instead of the vendor being Dell, it was super micro or what have you. How much of this would be repeatable? And how much of this would you have to redo? I, you know, I genuinely don't know.SWYX [00:24:18]: A decent amount.JOSH [00:24:19]: I think it would go a lot faster the second time. I think there's lots of learnings that we had. And also the blog post,SWYX [00:24:24]: you know, yes,JOSH [00:24:24]: we are releasing the health checks, releasing some scripts, but a lot of the valuable stuff is also in the blog post itself, in the details and kind of the, you know, the learnings that we've had and the sort of errors that we run into. We tried to as much as possible surface those to other peopleSWYX [00:24:36]: could learn from thoseJOSH [00:24:36]: and avoid the same mistakes or failures as well. But I think it would go a lot faster.SWYX [00:24:41]: Although, yes,JOSH [00:24:41]: there would certainly be some things that'd be a little bit different. I mean, there'd probably be different CPUsSWYX [00:24:46]: or whatever,JOSH [00:24:46]: but I think a lot of that stuff is less,SWYX [00:24:49]: it's less,JOSH [00:24:49]: that's the like, that's less variable. I think most of it would apply the second time around. Although I'm sure next timeSWYX [00:24:56]: we're building one,JOSH [00:24:56]: it'll probably be, you know, at a scale that's 10x as big with a different chip or something like this.SWYX [00:25:00]: And then who knows?JOSH [00:25:01]: Yeah, with Kinect X8,JONATHAN [00:25:02]: that will have its own fun behavior and all that good stuff. Yeah.SWYX [00:25:06]: Perhaps there's something that people don't discuss about, and you don't even talk about this in the blog, but I always wonder is what is the timeline that's like kind of reasonable for this amount of work, at least the initial stages? And also what does the team composition look like for setting up a cluster, right? Like what are the mix of skills that you typically would require to get all this going?JOSH [00:25:27]: I'm, I can't really speak to typical. One thing I am very proud of is how much we accomplished with such a ridiculously small team. Like our infrastructure team is like, you know, fluctuates from week to week, depending on like how many things are on fire and how much we need to build. But it's like between like three and six people, like it's small. It's not like some huge team of like tons and tons of engineers. But those people are very, very good at what they do. And so that has allowed us to get a lot of mileage out of out of these things. I think it's not that we're building everything, right? It's not that three to six people build this whole thing. I definitely want to like, you know, say thanks very much to Dell and H5 and NVIDIA and the other people that have done a lot of the work, like to bring up this cluster, you know, with 4000 GPUs and three tier networking, networking architecture, you have 12,000 cables. So that's 24,000 things that need to be plugged in. Like that's just a lot of stuff to plug in, right? And you don't want to mess it up. Like each one needs to be done correctly. Like it's a little bit loose. Like it doesn't really work.SWYX [00:26:23]: If you break it,JOSH [00:26:23]: you need to replace it. Like there's a lot of workSWYX [00:26:26]: that goes into this.JOSH [00:26:27]: Yeah.SWYX [00:26:28]: And then, you know,JOSH [00:26:28]: that's just like that's it. That's if you were to do everything right the first time.SWYX [00:26:32]: And if you didn'tJOSH [00:26:32]: have to fix anything. But inevitably, you know, you will have to replace something, which means like taking all the wires out, pulling the thing out, taking all the GPUs out, going and fixing some cable, putting it all back correctly, putting it back in, doing this every time. So there were a lot of people at Dell, NVIDIA and at H5 that all helped a ton with this stuff. I don't know the exact size of the Dell team. It also fluctuated over time.SWYX [00:26:55]: Yeah, excellent. And then, you know, you so you have all the hardware set up and now you're firing it up for a single node. There's a long description that you guys have about just like monitoring the MFU, right? And what each situation might look might be indicative of. One of the most interesting things to me that I saw from here is like, you know, if training immediately starts off at 60 to 80% MFU, something's wrong.SWYX [00:27:24]: But like, you know, like what what are like, you know, some anecdotes or, you know, notable scenarios here that you might you might call out as maybe counterintuitive or super interesting.JOSH [00:27:36]: There's just so many of them. I mean, one of them, which I think is probably pretty common, like common knowledge by this point. But like we did have a sort of likeSWYX [00:27:46]: which one was this exactly?JOSH [00:27:47]: I think for the MFU, like gradually getting worse over time. I think that one, when we saw that the first time we were like, what the heck is going on? Like, why does it get just like a little bit worse? This is so strange. Like, what is it getting lazy or tired or something? Like, is it heat? Like what's going on? And in this particular case, it was memory fragmentation. Because you have hundreds of machines, they're doing garbage collection slightly different times. And then they get slightly further apart and slightly more and more jittered until eventually they're all happening kind of at random times. And just like really messing up each one of your steps. So you just turn off garbage collection and call it a day, basically,SWYX [00:28:20]: to be honest.JOSH [00:28:20]: There's other things you can do if you want to be a little bit more sophisticated about it. But you can also just manuallyJONATHAN [00:28:25]: have it all garbage collect on some interval. Like that's what we've done. We just have a garbage collection callback that just runs. But I've seen the exact same thing.JOSH [00:28:33]: Yeah, yeah, exactly. So I thought that one was kind of funny. And we did trace that one down and look and we did find the actual call. Like, again, this goes to like having good tools. So we had really good tools where we could look at a bunch of like actual traces in C and be like, OK, cool. This is the thing that's taking a lot of time. Or like, you know, this is the thing that doesn't quite line up here. Like, oh, I guess it's garbage collection. OK, cool.SWYX [00:28:52]: Interesting.JOSH [00:28:52]: Yeah, let's just try taking it off.SWYX [00:28:54]: OK, great.JOSH [00:28:54]: That's what it was. Now we can fix it. So for each of them, like basically bugs are not hard if you have good tools. But if you don't have good tools, bugs can be very, very hard. So similarly for like heat, another thing that we saw was like, oh, you know, the CPU is getting throttled. OK, well, it's easy to see if you're monitoring the CPU throttling or monitoring the heat. If you're not monitoring that, it's really hard to know why it's just suddenly one of them is going slower. I noticed also in the pieceSWYX [00:29:17]: that you mentioned FSDP with 0.3. Actually, we met, I went to iClear and Guanhua from the DSP team was there presenting 0++. I was wondering if you want to make any call outs to, you know, particular open source or open library or open whatever implementation teams that were super helpful in your process. I think we ended up actuallyJOSH [00:29:39]: pulling from a whole bunch of different ones to pull things in into our own particular pipeline. So we use things from NVIDIA's, you know, Megatron stuff. We use stuff from probably DeepSpeed. I think we pulled in a bunch of different pieces from a bunch of different places. So it was really nice to see all these working open source like examples. I think I really appreciate all the effort that has gone into actually tuning these things because you can tune them, but it's a lot of work to like tune this stuff and do all this stuff from scratch. It's really nice to have like a working example. I think those are probably the two biggest ones, DeepSpeed and Megatron alone, but there are probably other ones as well.SWYX [00:30:13]: Is there a particular thing in the ecosystem where you would call out as like, you know, there should be something here that is open source, but like it's not really, it's like everyone kind of builds it on their own. I want to say something with the file system because everyone talks about the file system eventually.JOSH [00:30:28]: The file system actually was,SWYX [00:30:30]: I mean, we did somethingJOSH [00:30:31]: kind of dumb there. Like we have our own sort of local mirror so that we can, you know, like a crappy version of S3SWYX [00:30:38]: that's local,JOSH [00:30:38]: but it's just a pretty simple script, right?SWYX [00:30:41]: Like I think we run likeJOSH [00:30:41]: a little web server that just like serves files and then, you know, it can upload themSWYX [00:30:45]: and download them.JOSH [00:30:45]: Okay, great. And part of the reason we did that is that our internet connectionSWYX [00:30:50]: in the beginningJOSH [00:30:50]: was not the like full speedSWYX [00:30:52]: one that we wouldJOSH [00:30:52]: eventually have. And so we are a little bit more kind of bottlenecked in terms of internet bandwidth. And so we had this. I think we looked at a bunch of services out there like Minio and some other ones, but a lot of these like come with a lot of extra overhead and maintenance. And since we already have so much infrastructureSWYX [00:31:09]: to deal with,JOSH [00:31:09]: we kind of didn't want to, you know, bring in a whole other like cloud provider, virtualize something, something.SWYX [00:31:14]: We just wanted something simple.JOSH [00:31:14]: So we went with that, which has been quite helpful. Like our toolsSWYX [00:31:19]: are usually quite simple.JOSH [00:31:19]: It's like Bash and Python and SSH and Docker. Like we'd like to keep things simple so that's easier to debug, like less layers of infrastructure, less layers of abstraction, make it a lot easier to work with. Like we don't use Kubernetes,SWYX [00:31:30]: for example,JOSH [00:31:30]: and we just directly launch these things. And it's just been much easier to debug this way. One tool actually that does come into mind that I will call out is Kraken from Uber. That was great. We love that tool. We were a little bit skeptical. What is it?SWYX [00:31:44]: I'm sorry. Yeah.JOSH [00:31:45]: So Kraken is this, yeah, it's a distributed like Docker registry, basically, that uses BitTorrent to like transfer things between the machines in a sort of nice optimal way. Like in the very beginning, the naive way is like you have this one Docker registry, which was outside of the cluster. So every time we change an image, you know, there's many gigabytes that each of the 500 machines needs to download.SWYX [00:32:07]: So that just takesJOSH [00:32:07]: a really long time. So what this thing does is like just one of them downloads it and then like they all sort of broadcast all the pieces to each other. And it was just like a really nice, fast way of getting these images down. And it was very robust.SWYX [00:32:19]: Like there's a lotJOSH [00:32:19]: going on under the hood, but I think it's a pretty cool tool that we haven't really had any bugs with it at all. Amazing.SWYX [00:32:26]: Yeah. I mean, that's all my questions, I guess, for the info piece. I don't know if, John, you had something that you were sort of burning to ask or.JONATHAN [00:32:33]: No, all I can say is just sameSWYX [00:32:36]: in a lot of places, like, you know, and they're done thatJONATHAN [00:32:38]: seeing this plus one. I think the one big difference, you know, perhaps in philosophies is we've tried to basically standardize on as much commodity stuff as possible, just because, you know, I think the reason I asked about trying to do thisSWYX [00:32:50]: on multiple differentJONATHAN [00:32:50]: pieces of infrastructure is like, I think we're running on like six or seven different clouds right now. And everybody has done something slightly different. And my gosh, the little differences add up as you know, you've seen. And so, you know,SWYX [00:33:04]: our philosophy has been like, whatever the hellJONATHAN [00:33:05]: we can standardize, please let's standardize it. Like vanilla off the shelf FSDB.SWYX [00:33:10]: And like, you know,JONATHAN [00:33:10]: we wrote our own data loader, but we've tried to make that as much of a standard as we can across our infrastructure and in Databricks, because things just start getting really complicatedSWYX [00:33:18]: or like we useJONATHAN [00:33:18]: Kubernetes extensively because it at least gives us a uniform set of APIs. Like that's our hardware abstraction layer to a certain extent for everything else. So it's just, you know, a difference in philosophy there. But otherwise, like, yeah, this stuff is really, really hard. And I feel like we take for granted how much of this, you know, is done for us when you go and you just query chat GPT, for example. Like, oh my God, everything going on underneath that, you know, it's kind of a miracle that the machines boot up, let alone that you can like query a giant language model that's probably doing inference across multiple machines and was trained across thousands of machines. Like, you know, minor miracle.SWYX [00:33:54]: Yeah, it is an awesome amount of power that we invoke with a single API call that we take for granted these days. It's absurd. Yeah, I mean, like Kubernetes, like that point about Kubernetes, I will say as a former AWS employee, like it seems like it would be ideal for imbue to at some point make it more abstracted or agnostic because you're going to want to, you know, replicate your setup. We do have our ownJOSH [00:34:19]: sort of replacement. It's just a much simpler version of Kubernetes. Kubernetes is really designed for running services, not for running experiments. Like that's not its like main architecture. And so for us, like we have everything that's like, cool, you're going to run an experiment. So you want it to run to completion, right?SWYX [00:34:34]: OK, great.JOSH [00:34:34]: Like the primitives are sort of built around a slightly different style. And that makes it a lot easier, like just a lot simpler to fit that the nature of like these machines are going to disappear. They will need to be rebooted for infrastructure upgrades. They will like something will happen to the GPUs. Failure is like baked into this as like a core part of our infrastructure. So it's not that we don't have an abstraction. It's that it's a sort of simpler, more tailored abstraction for the particular work that we're doing.JONATHAN [00:34:58]: Yeah, I think it all depends on what your goals are. And like, I think the challenge in a lot of the deep learning stuff right now is that people are trying to like, people often build things that are more complicated than necessary to get the job done. And the complication is the enemy of everything. You know, don't use a fancier parallelism strategy than you have to. Don't use a fancier set of libraries than you have to.SWYX [00:35:18]: Don't do anythingJONATHAN [00:35:18]: that you don't have to do because it's hard enough as it is. Like, don't overcomplicateSWYX [00:35:23]: your own life.JONATHAN [00:35:23]: Don't try to bring in more tools or more fancy architecture tweaks if you absolutely don't have to.SWYX [00:35:29]: Like getting to the minimumJONATHAN [00:35:30]: necessary to get the job done. And it's really tempting to want to try to use everything. So like, I totally understand that one.SWYX [00:35:37]: I think the last piece I'll maybe call out is that I'm just going to weave this in just because I see the opportunity to do it. Are there any infrastructure shifts that need to be, that need to rise because of changing architecture? So I think, for example,SWYX [00:35:57]: you're announcing a dense model, a 70B dense model, whereas John just worked on DBRX and the image-to-text model, which presumably has different bottlenecks.JONATHAN [00:36:10]: That's correct for us. You know, we train both dense and mixture of expert models. The one we happened to, you know, kind of get permission to open source was a mixture of expert model. And those models are very demanding when it comes to network bandwidth, at least if you're training them in kind of FSTP 03 style, where there's just a lot of parameters getting shuffled back and forth. And your ratio of kind of compute to amount of data that you have to shuffle back and forth becomes a lot worse because you're now, you know, you're only using a fraction of the parameters for every token instead of all the parameters. And so we had to really push the envelope on getting all the stuff to the right places on time. And so actually the networking part of DBRX was the single hardest thing, I think, of the entire process. Just get MOE training, working at scale across a big cluster. We still managed to, I think, do it all with commodity parts, which was very exciting. You know, we were using FSTP and we eventually used HSTP so that we could have HSTP as a version of FSTP where you have multiple smaller replicas and you're doing data parallel within those replicas. And that helped a lot with network latency issues that we were running into just because we were transmitting so much data, you know, for every single part of the process. I think it actually, like, it was instructive for how Google designs their hardware and software together personally. Their training, as far as I understand, using kind of a 03 style of training and have been for a while. They also train mixture of expert models. TPUs have a very different network bandwidth to compute ratio. They have a lot more bandwidth just objectively. And TPUs per chip tend to be a little bit less compute intensive and have a little bit less memory. You know, it's just a different design choice. So the ratio of flops to bandwidth is very different. And that means that it's much easier for Google to be able to pull offSWYX [00:37:54]: some of this stuff.JONATHAN [00:37:54]: They also have interesting, you know, Torus style network architecture or Torus style, like, literal network architectureSWYX [00:38:00]: is not like the model,JONATHAN [00:38:00]: but the network.SWYX [00:38:02]: Is this the sort of block attention? I forgot what you call it. So this is just more or the,JONATHAN [00:38:07]: yeah, this is more, not the ring attention, but these are the ring all reduces. Like you have three different dimensions of rings because they kind of put you in these three dimensional Toruses from what I understand. And so like, you know, Google's infrastructure in some sense is kind of, I wouldn't say built for this, but maybe the way that Google trains models is built for a slightly different bit of infrastructure they have. And it's kind of neat to think about that. You know, as one thing that I think NVIDIA announced for, you know, for, for both the GH200 and the GB200 is this hybrid networking where you'll have blocks of NVLink network chips. I think for the GB200, I think it's like groups of 72 GPUs will all have NVLink to each other. So higher bandwidth, then you'll have normal networking of some kind, InfiniBand or Rocky or what have you between these blocks. And that's kind of a, you know, it's a change due to the fact that, you know, it's hard to build really high bandwidth networks over very large groups, but it is now a blocked networking. And you have to think about how you architect your model and your parallelism differently. You also have to think about fault tolerance differently because it now matters where you lose a GPU, whereas it didn't before. So, you know, it's, it's, it's just all really interesting and really fun speaking personally, but it's going to mean new nightmares when we all move to that generation and have to think about, you know, new versions of these problems.JOSH [00:39:20]: As you go up to larger scales, it gets quite different. Like right now, you know, if you're experiencing, let's say, for example, you experience a GPU failure every day, that's fine.SWYX [00:39:31]: Just restart.JOSH [00:39:31]: If you make your thing 24 times as big, now it's once an hour. Now it stops being quite as easy to just restart, right? So now you have to kind of break, like bake in this sort of redundancy that you didn't have before. So I think as you go up in scale, you end up running into like a lot of really interesting problems that also inform the, the actual like design. Yeah, I mean, as an orchestration guy,SWYX [00:39:52]: this is why I always emphasize like very cheap storage or very fast storage. So you can checkpoint more, but I don't think that's probably not the best solution to for fast, you know, training.JONATHAN [00:40:05]: Which works fine when you're doing language and then you move to vision or video. And then, you know, you have multi petabyte datasetsSWYX [00:40:12]: and getting, you know,JONATHAN [00:40:13]: cheap, fast multi petabyte storage starts to bite. Like I've certainly encountered issues where the literal data center where my GPUs were did not have enough, you know, object store to fit the datasets that people wanted to bring into that data center from whichever users were, were trying to bring them in. And then you get to a wholeSWYX [00:40:31]: different world of hurtJONATHAN [00:40:31]: where you have to keep your data in a different region because the region is just out of storage. So things get fun really fast.SWYX [00:40:39]: Speaking of vision, Josh, actually, you know, Embu is an agents company, but you're only, you're announcing a text-only model. What, where does, where does the vision side come in?JOSH [00:40:49]: I think we've actually done a lot of work in the past and people can see kind of our blog posts about sort of self-supervised learning and some other kind of vision-related stuff in the past as well. So we're very familiar with, with that stuff. But I think our main focus right now is on kind of, as we say, coding and reasoning. And there, there's certainly a visual component to some problems. But, you know, it's not necessarily required for all problems. And actually we found that for most of the kind of like code writing and, and reasoning problems that we care about, the visual part isn't really a huge important part of it. Sometimes if you really need to, you can maybe describeSWYX [00:41:24]: the thing.JOSH [00:41:24]: There are other like, you know, multimodal models that you can use off the shelf to sort of plug in for those particular piecesSWYX [00:41:30]: that you need, right?JOSH [00:41:30]: Like if something is driving a browser or whatever, like you can sometimes get away with not having to have that baked into the original model. So our folk were, you know, in a sense, we kind of do a lot across the stack. We're working on our own infrastructure and pre-training and RL and fine tuning and products and everything. But in another sense, we're very narrowly focused on the application side. So all of the stuff across the stack is kind of going toward a very particular purpose. And so that particular purpose right now doesn't really need vision. So we think that people are going to make all sorts of really cool image modelsSWYX [00:42:00]: like Jonathan, right?JOSH [00:42:00]: And all sorts of interesting multimodal models into the future. We'll let them go do that. That's great. We'll take advantage of that, partner with those people in the future. And right now we're really focused on kind of the core reasoning and coding capabilities and aspects of the model.SWYX [00:42:14]: I wanted to go into carbs since that's kind of the next layer of the stack. We talked about carbs in the first episode with Kanjin because you've actually had a blog post about it like a couple of years ago. Maybe let's introduce it.JONATHAN [00:42:26]: Has that been a couple of years now?JOSH [00:42:28]: No, it must have been at least one year. Hopefully it's not multiple years.SWYX [00:42:32]: Sorry, I'm counting AI time. Yeah, yeah. Yeah, I was going to sayJONATHAN [00:42:35]: you're making me feel really old right now.SWYX [00:42:39]: I count everything before the generally intelligent rename as like, you know, prehistory. Yeah. And now sort of modernity, right? So I actually thought carbs was more about hyperparameter optimization in a sense of like sort of parameters, hyperparameter search. Whereas, you know, when you introduced it, especially in this blog post, it's more about scaling laws and predictability of like, are we sort of in the right ballpark before we scale things up? Maybe sort of recount the history of carbs.JOSH [00:43:10]: Yeah, so it really is a little bit of both. So carbs is, it's maybe a backronym, but it's for cost aware Pareto region Bayesian search. So this is about technically how it works, but carbs is like, you know, we like pastries and stuff.SWYX [00:43:26]: So great, why not? But the point is thatJOSH [00:43:29]: it's a cost aware hyperparameter tuner. So most hyperparameter tuners, you kind of say, OK, here's this objective function. I want you to make this number as big as possible or as small as possible, whichever direction you want to go. So yeah, just go make this number, you know, as small as possible. OK, so it'll try a bunch of differentSWYX [00:43:46]: hyperparameters,JOSH [00:43:46]: a bunch of different configurationsSWYX [00:43:48]: to figure out, like,JOSH [00:43:48]: how do I tweak your network and architecture, et cetera, to get the kind of best performance I possibly can. That's usually saying, like, you know, almost all of these hyperparameter configurations are, let's say they're all going to use the same number of GPUs or the same number of nodes.SWYX [00:44:01]: So it's going to runJOSH [00:44:01]: for the same amount of time.SWYX [00:44:03]: So you can do that.JOSH [00:44:03]: You can get a number out and that's great. But what carbs does is it says,SWYX [00:44:07]: OK, actually,JOSH [00:44:07]: what if we relax that constraint? What if we say each of these different points, we're going to model how expensive it will be to sample this configuration. So if what if we train with just one one hundredth of the data? Like, how well can we do?SWYX [00:44:19]: What if we trainJOSH [00:44:19]: with one tenth of the data? What if we train with all the data? That way you can understand, like, as we get more and more data, as we spend more and more compute,SWYX [00:44:26]: as we make a biggerJOSH [00:44:26]: and bigger network, how does performance change with these things that change? Like how expensive it is to even explore this data point. So by doing that, we can see the scaling laws for not just, you know,SWYX [00:44:36]: the scaling lawsJOSH [00:44:36]: from like the, you know, Chantilla paper, the scaling laws for all parameters. We can see how does how does the number of layers change with this? How does the, you know, the learning rate change? How do the like, you know, various types of regularization change? So you can see these nice scaling laws. And as you're going across costs, like how should this be changing as you're scaling up your model? So that, coupled with the kind of metric that we chose, which is a very precise way of measuring performance, allowed us to really like hone in on parameters that worked really wellSWYX [00:45:05]: and understand, like,JOSH [00:45:05]: how do we want to scale those up, especially as we're changingSWYX [00:45:08]: things about the network?JOSH [00:45:08]: Like one of the things that we did is we used a custom tokenizer. As we change this tokenizer, changes a bunch of other things about the model. So how should we scale up this entirely new tokenizer? Like no one has ever made a model this large with this tokenizer before. And so how do we want toSWYX [00:45:22]: change all these things?JOSH [00:45:22]: Harps kind of shows you, like, look, as you change these parameters, like these other ones are kind of dependent on this.SWYX [00:45:28]: Like this is the, these areJOSH [00:45:28]: the relationships between them. So you can better understand, like, OK, if I'm going to scale this up 10x or 100x, like, where do I want to be? I can only go so far. And so, you know, we did run, like, I think maybe it was like a 14b one or somethingSWYX [00:45:40]: like that to check.JOSH [00:45:41]: But and so we had a bunch of like 1b or 14b and then at 70b. I don't think we had a, I think we just did like one at 14b. So you can, we get to check that like, oh, is this on the curve? Like, is this where we expect? It was like right there. So then great, go on to the next one. Yeah, I mean, that makes a lot of sense.SWYX [00:45:56]: I wonder if, so one of the key questions, and correct me if I'm wrong, but like usually people do search or do their evals just based on loss. But you actually evaluate based on, you know, the sort of end state evals that people might expect, like HellaSwag and Lombata, whatever. What is the norm here? Is there a norm?JOSH [00:46:20]: Yeah, I don't know if there's a hundred percent.SWYX [00:46:21]: I don't know. I only see loss on most people's reports.JOSH [00:46:25]: I think it's easy to, like, loss is very nice because it's very precise. It will tell you, like, very fine grained differences between like really small changes in your hyperparameters or network architecture. Whereas, especially at the smaller scales, if you're looking at like accuracy, it's very noisy. Like it might be zero or a hundred or like, you know, fluctuating by like 10 or 20 percentage points, which makes it really hard to tell, like, did that change actually mean anything? So our loss is sort of a combination of these two. Instead of saying, like, let's just look at perplexity, we say, let's look at perplexity on the tasks that we care about for multiple choice questions effectively.SWYX [00:47:00]: So we're saying like, yes,JOSH [00:47:00]: this is formulated as a multiple choice question, and we're going to look at the, like, you know, the loss of perplexity for this particular answer token. And that ends up being something that's like both targeted to what you actually care about and also very precise. The nice thing about this though is that it's independent of the data that you train on. One thing that's annoying about perplexity or about loss is that as you change your data set, this is really obnoxious because now it fundamentally changes your loss, right? And so you can't tell, like, how do I tweak my data set? But because we have this held out evaluation dat

Spokane fuzz outfit Kadabra chat to us at DesertFest about the joys of playing the UK. They discuss forming during the pandemic, potential for new music, the Spokane music scene and more. ===================== Follow The Razor's Edge online: Web: ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠https://therazorsedge.rocks⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ Facebook: ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠https://www.facebook.com/therazorsedgerocks⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ Twitter: ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠https://twitter.com/_therazorsedge_⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ Instagram: ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠https://www.instagram.com/therazorsedgerocks

Heute Ist Dr. René Cabos zu Gast bei Heldengeschichten. René arbeitet schon knapp 10 Jahre im KI-Bereich und hat sogar auf diesem Gebiet promoviert. Rene arbeitete in der Vergangenheit für Boeing, der Deutschen Bahn und S&P. Heute ist er für Hexagon tätig. Doch obwohl es ganz unterschiedliche Unternehmen und Branchen sind, war KI immer sein Thema in jeder Firma. Daher sprechen wir in dieser Folge über Bewusstsein und Kreativität von KI, die Zukunft KI und sinnvolle Anwendungsbereiche.   Webinar: Leadership Hacks for Engineers: https://my.demio.com/ref/JH5cMcQIBnqMZYWn  Mehr über Ingenieurshelden findest du hier: https://ingenieurshelden.de/ linkedin.com/in/dr-thomas-loebel Mehr über Dr. René Cabos findest du hier: linkedin.com/in/ralfrenecabos

Green manages to distract Sabrina and takes off with her badge. Red finds a device that is powered on seven badges. He meets up with Green, who proposes a trade: the Marsh Badge she obtained from Sabrina for his Moon Stone. Red swaps, but unexpected events arise! --- Send in a voice message: https://podcasters.spotify.com/pod/show/otakuology/message Support this podcast: https://podcasters.spotify.com/pod/show/otakuology/support

Green came to the building and meets up with her opponent: Sabrina, the Psychic Pokémon master! Sabrina's Kadabra uses its powers to attack Blastoise, but Green has a trick under her sleeve. Red, however, sends Ivysaur to battle Lt. Surge, whose Zapdos electrocutes Red. Red and Ivysaur change their tactics, which may enable them a victory! --- Send in a voice message: https://podcasters.spotify.com/pod/show/otakuology/message Support this podcast: https://podcasters.spotify.com/pod/show/otakuology/support

Whether your team needs help remembering information or navigating the complexities of virtual meetings, you can take on a meeting support role to level up the effectiveness of your team's meeting. In this episode, Lauren breaks down the need for meeting notes and tips for taking them effectively, and guest Heather Martinez discusses the rold of tech host.

In our latest episode of "Evolve: A New Era of Leadership," we had the incredible opportunity to dive deep with Wendy Ryan, a seasoned HR and organizational development expert, CEO, and author of "Learn, Lead, Lift."  

THE DOOMED & STONED SHOW ~Season 9, Episode 12~ After some holiday delays, we are proud to present to you Part 2 in our three-part series exploring the music of the fall rankings from https://DoomCharts.com, with a particular focus this episode on the month of October. We're meeting to record Part 3, which we hope to bring you before December's end! In the meanwhile, enjoy this packed, near 4-hour edition of the show, featuring commentary on the music by Billy Goate (Doomed & Stoned), John Gist (Vegas Rock Revolution), and Bucky Brown (The Ripple Effect). To purchase the music, click any of the hyperlinked band names on our website here: https://doomedandstoned.com/post/736060271216476160/. PLAYLIST: INTRO (00:00) - October Doom Charts Rankings 1. Stone Nomads (#21) - "The Tempter" (Trouble cover) (00:31) HOST SEGMENT I (30:28) 2. Giant Lungs (#17) - "Aromatico" (30:28) 3. ZQKMGDZ (#33) - "Hail & Salvation" (34:22) 4. Blood Lightning (#13) - "Bananaconda" (38:41) HOST SEGMENT II (44:44) 5. Occult Hand Order (#11) - "Sink" (1:00:54) 6. Lucid Sins (#12) - "Jack of Diamonds" (1:08:40) 7. The Heavy Minds (#19) - "Predator" (1:12:56) HOST SEGMENT III (1:19:31) 8. La Chinga (#10) - "Bolt of Lightning" (1:30:06) 9. Mooch (#9) - "Crimson" (1:33:12) 10. Bahboon (#8) - "Rampage" (1:37:13) HOST SEGMENT IV (1:41:40) 11. Deathchant (#7) - "Chariot" (2:01:26) 12. Appalooza (#6) - "Wasted Land" (2:05:09) 13. Restless Spirit (#5) - "Shadow Command" (2:12:49) HOST SEGMENT V (2:18:36) 14. Kadabra (#4) - "High Priestess" (3:01:13) 15. Hippie Death Cult (#3) - "Tomorrow's Sky" (3:07:33) 16. Dopelord (#2) - "Night of the Witch" (3:14:02) 17. Howling Giant (#1) - "Hawk in a Hurricane" (3:21:23) OUTRO (3:26:19) BONUS TRACKS : 18. Sloth (#24) - "Beyond" (3:27:27) 19. Vanishing Kids (#22) - "Demon Glove" (3:35:58) 20. The Sound of Origin (#30) - "Birthright" (3:42:43) CREDITS: Theme Song: Dylan Tucker Incidental Music: Hellvetika (https://akitevlleh.bandcamp.com) Thumbnail Art: Howling Giant

Blue and Green meet each other at Saffron City, but see there is a barrier. Red comes back home and meets Oak, who attacks him. Red fights back and finds it is a Kadabra, whose mistress tells Red to come to Saffron City to save the villagers. --- Send in a voice message: https://podcasters.spotify.com/pod/show/otakuology/message Support this podcast: https://podcasters.spotify.com/pod/show/otakuology/support

Why it was selected for "CBNation Architects": In this IAMCEO podcast episode, we learn from Wendy Ryan, MHROD, the CEO of Kadabra. Wendy possesses more than 25 years of experience in human resources, organizational development, non-profit leadership, and executive coaching. Throughout her career, she has partnered with hundreds of individuals and organizations across the U.S., helping leaders and board members achieve success both individually and in teams. CEO Story: Wendy is the author of the award-winning bestseller, Learn Lead Lift: How to Think, Act, and Inspire Your Way to Greatness, and has been featured in various publications, including Forbes, Yahoo News!, Business Digest, Authority Magazine, CEO Magazine, and Thrive Global. Business Service: Kadabra specializes in offering leadership development, strategic guidance, and executive coaching services, emphasizing diversity, equity, inclusion, and accessibility in the business landscape. Advocacy: Wendy is an active mentor, strategic advisor, angel investor, and advocate for early-stage, BIPOC, LGBTQ++, and woman-led companies. She believes expanding diversity, equity, inclusion, and accessibility is critical in the investor and business ecosystem. CEO Hack: One of Wendy's favorite CEO Hacks is Audible for accessing audiobooks on the go.   Check out our CEO Hack Buzz Newsletter--our premium newsletter with hacks and nuggets to level up your organization. Sign up HERE.  I AM CEO Handbook Volume 3 is HERE and it's FREE. Get your copy here: http://cbnation.co/iamceo3. Get the 100+ things that you can learn from 1600 business podcasts we recorded. Hear Gresh's story, learn the 16 business pillars from the podcast, find out about CBNation Architects and why you might be one and so much more. Did we mention it was FREE? Download it today!   Previous Episode: https://iamceo.co/2022/06/15/iam1402-author-helps-leaders-achieve-success-as-individuals-and-in-teams/

Hey there, all stars! It's time for another Earth 1/Earth 2 crossover! My good buddy Mart Gray is back, and we're covering the penultimate issue of Flash from my hardcover that' we've been making our way through. So, we have one more issue aft this, and one more GL story to cover (with WardHillTerry), and then it's on to our big four part finale! But, this episode is here now, and Mart and I have a blast talking about this one, especially since this was my first experience with Abra Kadabra! Plus we get three JSA'ers in this story to help combat the super science from the 64th century! If you'd like to leave any feedback for the show, you can do so through email at Aworldonfirepodcast@gmail.com or to the show on Twitter @Allsquadron or on the show's FB page. You can find Mart on Twitter as well @Martgray or on his blog Too Dangerous for a Girl. Thanks for listening! --- Send in a voice message: https://podcasters.spotify.com/pod/show/stephen-strange02/message

Lasagna hogs, tuna, MeToo'd, tipping robots, a re-enactment at a gas station, Kadabra, LVTOFU, woodcocks, condom-wrapped banana extraction, $295K for a testicle, quolls, $1.5M in stolen chicken wings, fast food Newz, a wearable beanbag, real-time shade info, Ice Whopper, and Yakuza-theme love hotel rooms. Double X Quantimino Palindromes follow-up: “go hang a salami, I'm a lasagna hog” Tuna salad vs tuna sushi Hypothetical Meta Analysis - Slam City Gets MeToo'd The easiest answer to a not-so-deep dive - Should you tip a robot? But the real matter here: Service charges!? Re-enactment - Gas station staff left horrified after finding severed human penis in car park This Is The Newz Kadabra Will Finally Return To Pokémon Card Game After 18-Year Ban Texas DMV rejects vegan license plate for ‘vulgar' phrase Bird charity locked out of Twitter after woodcock tweets Surgeons extract condom-wrapped banana man ate in ‘hormonal rage' fit Man who lost testicle from getting hit by supervisor awarded more than $295,000 Sex and no sleep may be killing endangered quolls Vera Liddell allegedly stole $1.5M in chicken wings from Illinois schools Salty strike: Arby's employees quit after posting vulgar message on restaurant sign A Chick-fil-A restaurant's traffic got so bad that city officials ordered it to be demolished and plan to build a new drive-thru-only location Burger King's Latest International Menu Item Does Not Sound Very Appetizing...Or Does It Wearable Beanbag becomes a hot topic in Japan Burrito's Nippon Newz Real-time shade information added to walking app from Navitime Japan World's first Ice Whopper on the menu at Burger King Japan Yakuza-themed love hotel rooms! Great for couples, friends, and business meetings, owners say Deepfake Sponsors: Julio Tejas, Booba Gettz The Crazy One, Thicccum Farmz Slam City Radio 24/7 x https://slamcity.co/scr247/

Join us as we dive into the brand new Japanese Pokemon 151 set including: Basic facts about the set  The backstory of Kadabra's removal and return to the TCG Details about the packaging How the cards are numbered in this set Art details about some of the cards  Artists involved in creating some of the cards Our favorite cards from the set And we do our inaugural Pokedex Entry of the week! Kadabra We also provide our next update on our Side Quest. Tune in to each episode for our latest progress as we play through Red and Blue Version.  Follow us on all social media platforms for more Pokemon content and to stay up to date as our journey unfolds Project Deckbox Podcast LinkTree And don't forget to send us a DM and share your thoughts on the topics we covered today!   Gordo's Brewhouse Coffee Use Promo Code DECKBOX40 for 40% off your next purchase!!!   SUBMIT A TOPIC! Patreon - Support Project Deckbox Podcast   Additional Links Gordo's Brewhouse Coffee US International Championship Tournament 2023 Why was Kadabra Banned From Pokemon? 151 Set Overview 151 Set Secret Rares Blastoise Illustration Rare - 151 set           Fair Use Disclaimer This audio is under Fair Use: Copyright Disclaimer Under Section 107 of the Copyright Act of 1976: Allowance is made for "Fair Use" for purposes such as criticism, comment, news reporting, teaching, scholarship, and research. Fair Use is a use permitted by copyright statute that might otherwise be infringing. All rights and credit go directly to its rightful owners. No copyright infringement intended. We simply want to share this content in a positive way to grow the fandom of the franchise.   Enjoy.

Checkt hier, ob ihr vom Deezer Datenleck betroffen seid: https://wbs.law/deezer Das neue Buch von Christian Solmecke "Welches Recht gilt bei Mord im Weltraum? JETZT vorbestellen: https://wbs.law/mord-im-weltraum TV-Mentalist Uri Geller befand sich über 20 Jahre in einem Rechtsstreit mit Nintendo. Der Grund war das Pokémon Kadabra, welches ihm angeblich zu stark ähnele. Als Folge wurde die Sammelkarte des Pokémons nicht mehr gedruckt. Wie diese skurrile Geschichte ausging und was die rechtlichen Hintergründe sind, erfahrt ihr in diesem Video. Video Uri Geller verbiegt Löffel: https://www.youtube.com/watch?v=6NIP4Va4USs Video über japanische Zeichen: https://youtu.be/nQALpc6IZ_A?t=136 https://happymag.tv/wp-content/uploads/2020/12/uri-geller-kadabra-1.jpg https://www.gesetze-im-internet.de/kunsturhg/__22.html https://www.gesetze-im-internet.de/bgb/__12.html https://twitter.com/theurigeller/status/1618297708854542336

Special Conditions Podcast 139 Recording Date - 05/03/23 Publish Date - 05/21/23   Sorry for the delay in getting this show out to Podcast Platforms!    On this week's episode Justin and Adam discuss the end of PTCGO, New cards from the 151 TCG set, Kadabra Art, and some regionals talk!   Check out the VoD Here: https://www.youtube.com/live/Jb3OUGMN3bM?feature=share    TCGO countdown https://tcg.pokemon.com/en-us/updates/  New Fossils 151 https://www.pokebeach.com/2023/05/kabutops-omastar-dome-fossil-from-pokemon-card-151  Other 151 cards https://www.serebii.net/card/pokemoncard151/  Kadabra https://www.tcgplayer.com/search/pokemon/product?productLineName=pokemon&q=kadabra&view=grid&page=1    https://bulbapedia.bulbagarden.net/wiki/Kadabra_(TCG) TCG Player Support the show by shopping at TCGPlayer.com using this link - https://bit.ly/TCGPlayerAffiliate    Pokémon Professor Network Merch Store - https://bit.ly/PPNMerchStore    SpecialConditions@PokemonProfessor.com  Voicemail, Text, and Picture Line - 732-835-8639   https://linktr.ee/PokemonProfessorNetwork    Music provided by GameChops and licensed through Creative Commons   ▾ FOLLOW GAMECHOPS ▾ http://instagram.com/GameChops http://twitter.com/GameChops http://soundcloud.com/GameChops http://facebook.com/GameChops http://youtube.com/GameChops http://www.gamechops.com   Intro Music Trapped In A Pokéball Dj CUTMAN and Belthesar GameChops - Ultraball http://gamechops.com/ultraball/  http://soundcloud.com/DjCUTMAN http://soundcloud.com/belthesar   Break Music He Walk - Furret / Accumula Town Remix  Dj Cutman http://soundcloud.com/djcutman  http://twitter.com/videogamedj  http://youtube.com/djcutman   Outro Music Kanto Trainer Battle Mykah GameChops - Ultraball http://gamechops.com/ultraball/  https://soundcloud.com/mykah   Hosts Adam Tuttle Justin Keller   Producer Ken Pescatore   Executive Producer Tish Smith   Pokémon And All Respective Names are Trademark and © of Nintendo 1996-2021 Pokémon Professor and Special Conditions are not affiliated with Niantic Inc., The Pokémon Company, Game Freak or Nintendo   #pokemon #pokemontcg #podcast  

Another action-packed episode. We discuss how after a 20-year absence, Kadabra is returning to the Pokemon Trading Card Game. Nintendo has once again taken down a popular Youtuber for copyright infringement. We discuss the company's history of aggressive copyright enforcement, its impact on fans, and what can be done to change it. The new Dungeons & Dragons movie has been well-received by critics and audiences alike. We discuss the film's success, what it means for the future of D&D, and whether it's worth watching. --- Send in a voice message: https://podcasters.spotify.com/pod/show/twoguysonelevel/message Support this podcast: https://podcasters.spotify.com/pod/show/twoguysonelevel/support

We talked to Forty Feet Tall about the national anthem, nightmare poops, the sea lion caves, Napster, album skits, Blood ceremonies, and their music. Songs this week from Forty Feet Tall, Kadabra, The Macks, Monster Watch, and Stainless 

Spooky, Scary! It's a Pokemon bar mitzvah! This week your favourite Pokemon anime rewatch and analysis podcast “To Kill A Delibird” covers the occult and paranormal in episodes 22, “Abra and the Psychic Showdown”, 23 “The Tower of Terror”, and 24 “Haunter versus Kadabra”. Here is a synopsis: Ash Ketchum doesn't stand a ghost of a chance against psychic terror lady and daughter of Chucky, Sabrina the teenage gym leader. A ghost of a chance becomes a chance of a ghost when Ash recruits the Three Stooges to prank Misty for his Youtube Channel. Finally, Brock and Misty get dolled up, an old man doles out information, and the tension gets dialed up in an explosive comedy showdown. Does that make sense? Regardless of your answer we think you will have a ton of fun with this episode! Subscribe to get every new episode of To Kill a Delibird in your subscription feed. Welcome to "To Kill A Delibird", the Pokemon anime rewatch podcast that combines a love of literary puns and analytics with pure Pokemania. Join Graham (Pokemon expat/video game and manga fanatic) and Kellan (hard boiled Pokemon die hard) as they discuss the Pokemon anime and hopefully construct some fun sentences along the way. Intro/outro music "Synthwave 80's" by AlexiAction Follow the podcast on spotify: https://open.spotify.com/episode/1yQ3EQ2P91mE6Bq0i4I3EY on Apple: https://podcasts.apple.com/us/podcast/to-kill-a-delibird/id1667957767 Amazon: https://music.amazon.com/podcasts/b37371a4-331d-4254-999b-e21fc0fdd837/to-kill-a-delibird Google: https://podcasts.google.com/feed/aHR0cHM6Ly9hbmNob3IuZm0vcy9kOTQ2MmUyMC9wb2RjYXN0L3Jzcw Stitcher: https://www.stitcher.com/show/1054965 for more half baked content: https://www.twitch.tv/skiddlewickers Tiktok is essential for new creators so: https://www.tiktok.com/@skiddlewickers #pokemon #ashketchum #pikachu #misty #brock #anime #indigoleague #ssanne #teamrocket #existentialism #comedy #haunter #sabrina #pikachu 0:00 Intro 8:10 Abra and the Psychic Showdown 41:20 The Tower of Terror1:03:20 Haunter versus Kadabra

 After Koga gets defeated it's now finally time for Green vs Sabrina! Trickster vs  psychic! Both girls have all kinds of tricks up their sleeve but only the best trainer will prevail! Also what is the weird device that Red has found? We're discussing all this and much more on today's episode and also covering a little bit of censorship that occurred in this chapter. Find out what it's all about!Music: Route 26 by Zame! Check out his music here: https://open.spotify.com/artist/5fG4nxyGNoxSIITDgr4AgM?si=r_LU-aYSRhOLpuG8DqyL8gCover Art by torterra99 on Instagram! Check out his page here: https://www.instagram.com/torterra99/

270 Mindset Agility   Changing, growing, self reflecting, and adapting is an integral part of life. If we don't hone these skills we will inevitably miss out on the amazing opportunities life has to offer, whether it be a trip to a country you need to learn a language to explore, or meeting new people and listening to their stories. Our agility and flexibility in any circumstance is what determines whether we grow or stagnate.  In this episode Sarah Elkins and Wendy Ryan discuss the importance of the aforementioned skills and how exemplifying these traits can inspire others to follow a similar path that will make way for similar healthy and happy habits.    Highlights External advice is invaluable when given in a constructive and compassionate manner. Hold up the mirror in a way that is safe and nonjudgmental.  There's nothing wrong with being vulnerable, honest, trusting and making progress.   Quotes “Being humble, being forgiving of yourself and your own learning curve, and every place is different and nuances matter.” “I've also found as a practitioner that it can sometimes do more to disrupt, in a healthy way, some of the energy that's going on and help us reset and remind us that we're all human and that some of this frankly is funny. And sometimes when we do that it's like we can take that big scary monster who seems 15 feet tall and all the sudden, no it's only the size of one of those spiders in Australia, we can deal with that.”  “This will relate, in part, to the identities we hold.”   Dear Listeners it is now your turn, What kind of healthy self reflection can you do today to make yourself a better leader no matter where you sit. And, as always, thank you for listening.    About Wendy Wendy Ryan (she/her/hers), MHROD, is the CEO of Kadabra. With over 25 years of combined experience in human resources, organizational development, nonprofit leadership and executive coaching Wendy has partnered with hundreds of individuals and organizations throughout the U.S. helping front-line through C-suite leaders and board members achieve success as individuals and in teams.   Wendy is the author of the award-winning bestseller, Learn Lead Lift: How to Think, Act, and Inspire Your Way to Greatness and has been featured in Forbes, Yahoo News! Business Digest, Authority Magazine, CEO Magazine and Thrive Global. Wendy is also an active mentor, strategic advisor and angel investor in early stage, BIPOC, LGBTQ++ and women-led companies and an advocate for expanding diversity, equity, inclusion and accessibility in the investor and business ecosystem. Check out Wendy's website We Are Kadabra, and be sure to get a copy of her book Learn, Lead, Lift. Connect with Wendy on her LinkedIn, Instagram, and Facebook! About Sarah "Uncovering the right stories for the right audiences so executives, leaders, public speakers, and job seekers can clearly and actively demonstrate their character, values, and vision." In my work with coaching clients, I guide people to improve their communication using storytelling as the foundation of our work together. What I've realized over years of coaching and podcasting is that the majority of people don't realize the impact of the stories they share - on their internal messages, and on the people they're sharing them with. My work with leaders and people who aspire to be leaders follows a similar path to the interviews on my podcast, uncovering pivotal moments in their lives and learning how to share them to connect more authentically with others, to make their presentations and speaking more engaging, to reveal patterns that have kept them stuck or moved them forward, and to improve their relationships at work and at home. The audiobook, Your Stories Don't Define You, How You Tell Them Will is now available! Included with your purchase are two bonus tracks, songs recorded by Sarah's band, Spare Change, in her living room in Montana. Be sure to check out the Job Interview Storytelling Course as well to make sure you nail that next interview!

This episode is our shortest regular episode ever. This episode just went swimming and it's cold.

In Ep. 547, Sam and I cover Kadabra returning to Pokemon TCG, the Dawn of DC #1's, The Last of Us getting renewed for S2, and more! FOLLOW/SUPPORT SAM: Ronin Council (SoundCloud) @samuelboylston (Sam's Instagram) As always, we appreciate your constructive Feedback, Suggestions, and Questions. You can also leave us an audio question on SpeakPipe. Thank you for the continued love and support! Enjoy the show. Daniel and Kelli Podcast Awards 2019 || Games & Hobbies (Winner) Podcast Awards 2017 - 2018, 2020 - 2022 || Games & Hobbies (Nominated) Official Site SUBSCRIBE:Apple Podcasts / Spotify / Google Podcasts / Stitcher / iHeartRadio / TuneIn / Overcast FOLLOW US: - Twitter | @ReasonsImBroke, @PalpaKelli, and @TRIBPod - Instagram- Pinterest- Tumblr - Discord Lounge - YouTube Channel SUPPORT THE POD: Getting $1's worth of entertainment and information each month? Support us on Patreon or visit our TeePublic storefront! SPREAD THE WORD: If you're enjoying the show, please head over to iTunes and leave us a rating and a review! Each one helps new Brokettes discover the podcast. Donate to Hero Initiative to help comic creators in need. CREDITS: Opening/Closing Jingles - Alex Scott Show Logo By - Opanaldiova

#162 Avada Kadabra by Mantuary

Dani, Jordan and Nate discuss the latest in Pokemon, including new episodes of Pokémon coming to Netflix soon, our initial thoughts on Scarlet ex and Violet ex TCG sets in Japan, a new TCG set coming to Japan "Pokémon Card 151" and it makes us question... Is Kadabra making a return to the TCG? 

• Intro • Xbox, Sony, Nintendo all skipping E3 • Xbox Developer Direct • Goldeneye now on Switch/Xbox • The Last of Us Part 3 might not happen/Uncharted is done • Did Sony tease a new Uncharted? • Halo Infinite is OVER, next Halo might be in UNREAL ENGINE • Xbox Series prices rise in Japan • Amazon Tomb Raider show  • LEAP FROG has been emulated • Kadabra returns to Pokemon card game • Sony cuts Psvr2 production  • Capcom Cup switches from PS4 to PC • RE4 remake details • Jedi survivor delayed  • TWEET OF THE WEEK • Q&A Streamed: January 31st, 2022 on http://twitch.tv/wulffden

Welcome back to another episode of the Online Warriors Podcast! This week we cover videogames, videogame card games, and tv shows based off of videogames! - Phoebe Waller-Bridge to write upcoming Tomb Raider Series (5:30) - Kadabra is returning to the trading card game (16:50) - Xbox and Bethesda Developer Direct (27:10)   - Hi-Fi Rush (27:32)   - Redfall (31:26)   - Forza (31:43)   - Elder Scrolls Online (32:13)   - Minecraft Legends (39:31) Then we roll into what we have been up to. - Nerdbomber finished reading Elektra and watches The White Lotus (43:17) - Illeagle plays the Dead Space Remake (47:50) - Techtic watches The Menu (50:38) Then we find out who's the boss with Bruce Springsteen Trivia (52:24)   Special shoutout to our Patreon Producer: Steven Keller We'd like to thank each and every one of you for listening in every week. If you'd like to support the show, you can drop us a review on your favorite podcast platform or, if you're feeling extra generous, drop us a subscribe over at Patreon.com/OnlineWarriorsPodcast. We have three tiers of subscriptions, each of which gives you some awesome bonus content! As always, we appreciate you tuning in, and look forward to seeing you next week! Stay safe and healthy everyone! Find us all over the web: Online Warriors Website: https://www.onlinewarriorspodcast.com Online Warriors Twitter: https://twitter.com/onlinewarriors1 Illeagle's Twitter: https://twitter.com/OWIlleagle86 Nerdbomber's Twitter: https://twitter.com/OWNerdbomber Techtic's Twitter: https://twitter.com/OWTechtic Facebook: https://www.facebook.com/onlinewarriorspodcast Instagram: https://www.instagram.com/onlinewarriorspodcast/ YouTube: https://www.youtube.com/channel/UCwOwzY6aBcTFucWEeFEtwIg Merch Store: https://teespring.com/stores/onlinewarriorspodcast

We run down the new Pokemon card set! Plus, Ash and Misty reunite, a new Pokemon Go event, a brand new PokeFact of the Week! To learn more about listener data and our privacy practices visit: https://www.audacyinc.com/privacy-policy Learn more about your ad choices. Visit https://podcastchoices.com/adchoices

The Psi Pokémon was the subject of a lawsuit.

Another Just Jamie episode, that focuses on the surge of new RPG game sales, how an illusionist made Kadabra disappear, and some great stuff in the new hotness. 

Hello, is this Pizza Hut? Excellent. My name is Ben Shapiro. Conservative thought leader. Prominent white YouTuber. The Muggsy Bogues of the intellectual dark Web. And—look, it's just a fact—I would like to order some pizza pie. If you are triggered by that request, I do not care. I truly do not. Now let's discuss conditions. First, thank you for agreeing to debate me. Typically, in fora such as this, I am met with ad-hominem mudslinging, anything from “You racist creep” or “Is that your real voice?” to raucous schoolyard laughter and threats of the dreaded “toilet swirly.” However, your willingness to engage with me over the phone on the subject of pizza shows an intellectual fortitude and openness to dangerous ideas which reflects highly on your character. Huzzah, good sir. Huzzah. Second, any pizza I order will be male. None of this “Our pizza identifies as trans-fluid-pan-poly”—no. Pizza is a boy. With a penis. It's that simple. It's been true for all of human history, from Plato to Socrates to Mr. Mistoffelees, and any attempt to rewrite the pillars of Western thought will be met with a hearty “Fuh!” by yours truly. And, trust me, that is not a fate you wish to meet. Now. With regard to my topping preference. I have eaten from your pizzeria in times past, and it must be said: your pepperoni is embarrassingly spicy. Frankly, it boggles the mind. I mean, what kind of drugs are you inhaling over there? Pot?! One bite of that stuff and I had to take a shower. So tread lightly when it comes to spice, my good man. You do not want to see me at my most epic. Like the great white hero of Zack Snyder's classic film “300,” I will kick you. Onions, peppers—no, thank you. If I wanted veggies, I'd go to a salad bar. I'm not some sort of vegan, Cory Booker weirdo. And your efforts to Michelle Obama-ize the great American pizza pie are, frankly, hilarious. Though not as funny as the impressively named P'Zone—when I finally figured out that genuinely creative pun, I laughed until I cried and peed. A true Spartan admits defeat, and I must admit that, in this instance, your Hut humor slayed me, Dennis Miller style. And, with that, you have earned my order. Congratulations. Ahem. Without further ado, I would like your smallest child pizza, no sauce, extra cheese. Hello? Aha. A hang-up. Another triggered lib, bested by logic. Damn it. I'm fucking starving.   I think that it's ok to be sexually aroused by Pokemon. More so, I think it should be encouraged in the games and anime, and GameFreak should lean into it. Firstly, some Pokemon are shown to be much smarter then humans. Kadabra has been said to have an IQ over 5000, which is gigantically more than the definition of an animal, which have an IQ between 0 (Worms and Fish) and 65 (Apes and Octopus). Thus, they are smarter then needed to be able to give consent. Secondly, the argument could be made they are not as empathetic as humans, and thus can't give consent. This is proven not to be true numerous times in the anime, by watching Meowth. In Season 2, Episode 16 of the Pokemon show, it is established that he is no smarter or different then regular Pokemon, he simply learnt to walk by watching a dance rehearsal and later learnt English through a picture book. Throughout the following seasons, it's shown how he schemes, laughs, cries and even at points, deceives people into thinking he is a human (in order to steal Ash's Pikachu of course). And the last piece of damning evidence - a folk tale in the Canalave Library (Pokémon Diamond and Pearl) literally STATES that humans used to marry Pokémon. This was removed in the English translation. Gamefreak, if you wanted us to fuck Pokémon, just say it. Conclusively, Pokemon aren't animals. They are intelligent, with empathy and kindness, and should be treated as equals. Denying them the right to have sex with humans removes their freedom, which is racist, and frankly, unamerican.   An Afghan, an Albanian, an Algerian, an American, an Andorran, an Angolan, an Antiguans, an Argentine, an Armenian, an Australian, an Austrian, an Azerbaijani, a Bahamian, a Bahraini, a Bangladeshi, a Barbadian, a Barbudans, a Batswanan, a Belarusian, a Belgian, a Belizean, a Beninese, a Bhutanese, a Bolivian, a Bosnian, a Brazilian, a Brit, a Bruneian, a Bulgarian, a Burkinabe, a Burmese, a Burundian, a Cambodian, a Cameroonian, a Canadian, a Cape Verdean, a Central African, a Chadian, a Chilean, a Chinese, a Colombian, a Comoran, a Congolese, a Costa Rican, a Croatian, a Cuban, a Cypriot, a Czech, a Dane, a Djibouti, a Dominican, a Dutchman, an East Timorese, an Ecuadorean, an Egyptian, an Emirian, an Equatorial Guinean, an Eritrean, an Estonian, an Ethiopian, a Fijian, a Filipino, a Finn, a Frenchman, a Gabonese, a Gambian, a Georgian, a German, a Ghanaian, a Greek, a Grenadian, a Guatemalan, a Guinea-Bissauan, a Guinean, a Guyanese, a Haitian, a Herzegovinian, a Honduran, a Hungarian, an I-Kiribati, an Icelander, an Indian, an Indonesian, an Iranian, an Iraqi, an Irishman, an Israeli, an Italian, an Ivorian, a Jamaican, a Japanese, a Jordanian, a Kazakhstani, a Kenyan, a Kittian and Nevisian, a Kuwaiti, a Kyrgyz, a Laotian, a Latvian, a Lebanese, a Liberian, a Libyan, a Liechtensteiner, a Lithuanian, a Luxembourger, a Macedonian, a Malagasy, a Malawian, a Malaysian, a Maldivan, a Malian, a Maltese, a Marshallese, a Mauritanian, a Mauritian, a Mexican, a Micronesian, a Moldovan, a Monacan, a Mongolian, a Moroccan, a Mosotho, a Motswana, a Mozambican, a Namibian, a Nauruan, a Nepalese, a New Zealander, a Nicaraguan, a Nigerian, a Nigerien, a North Korean, a Northern Irishman, a Norwegian, an Omani, a Pakistani, a Palauan, a Palestinian, a Panamanian, a Papua New Guinean, a Paraguayan, a Peruvian, a Pole, a Portuguese, a Qatari, a Romanian, a Russian, a Rwandan, a Saint Lucian, a Salvadoran, a Samoan, a San Marinese, a Sao Tomean, a Saudi, a Scottish, a Senegalese, a Serbian, a Seychellois, a Sierra Leonean, a Singaporean, a Slovakian, a Slovenian, a Solomon Islander, a Somali, a South African, a South Korean, a Spaniard, a Sri Lankan, a Sudanese, a Surinamer, a Swazi, a Swede, a Swiss, a Syrian, a Tajik, a Tanzanian, a Togolese, a Tongan, a Trinidadian or Tobagonian, a Tunisian, a Turk, a Tuvaluan, a Ugandan, a Ukrainian, a Uruguayan, a Uzbekistani, a Venezuelan, a Vietnamese, a Welshman, a Yemenite, a Zambian and a Zimbabwean all go to a bar.. The doorman stops them and says "Sorry, I can't let you in without a Thai." also i'm gay

It's the Volume 2 finale!After his adventures in Cinnabar Island, Red has decided to go back to Pallet Town. But when he gets there he finds his hometown is completely deserted! And to make matters worse Professor Oak immediately starts attacking Red as soon as he sees him! What is goin on?  What has happened to Pallet Town? And what is going on at Saffron City? Why can't anyone go inside? Find all this out on today's episode!Music Credit: Route 26 by Zame! Check out his music here: https://www.patreon.com/posts/route-26-hgss-61509502?utm_medium=clipboard_copy&utm_source=copy_to_clipboard&utm_campaign=postshare

When you break businesses down, most are a collection of different people with different brains, different backgrounds and different experiences. So how do you bring all of that wisdom together to make the most of it? Wendy Ryan, the CEO of the management and leadership coaching company Kadabra, walks us through how she helps leaders lead.Being an entrepreneur who's taking risks means you are eventually going to fail at something. That doesn't mean you stop. Wendy explains how you keep going, growing and building yourself into that leader you want to be.POINTS:Why you should think about going into grad-school for more education, even if you're already successful in your field.The business environment can be so much more inviting and productive when employees feel like they don't have to hide who they are. Hear why Wendy says this is more important today, especially after the pandemic.Not everyone has the same needs or starts in the same place, even when they're working in the same position.Being authentic as a leader sometimes means being vulnerable and realizing you don't have all the answers.Whether we realize it or not, many of us bring our traumas and problems with us to work. When managers create a safe place for everyone to open up, it helps employees balance their personal problems, so they can give more of themselves to their work.LINKS:You can follow Wendy Ryan on her LinkedIn profile:https://www.linkedin.com/in/wendyryankadabraHer website is also a goldmine of useful stories and advice:https://www.wearekadabra.com/Here's where you can find Wendy's brilliant book: Learn Lead Lift - How to Think, Act and Inspire Your Way to Greatnesshttps://www.learnleadlift.com/ Hosted on Acast. See acast.com/privacy for more information.

Welcome to the 111th episode of the Meta Pod #podcast, the #PokemonTCG podcast that revolves around the evolving meta! @AtrociousGameplay & @gyrosean sit down to discuss the new #!PlayPokemon Regional Schedule, an incredible product coming out and more! -- Reach out to us with any thoughts or topic suggestions via Twitter: https://twitter.com/metapodtcg Check out the Meta Pod YouTube: https://www.youtube.com/channel/UCWcPqrzElSZKqYOIkMgOZuw Here are a few of the other places where we make content: Sean's YouTube: https://youtube.com/gyrosean Jake's YouTube: https://www.youtube.com/c/atrociousjake Sean's Twitch: https://www.twitch.tv/gyrosean Jake's Twitch: https://www.twitch.tv/atrociousjake --- Support this podcast: https://anchor.fm/metapodtcg/support

My guest for this episode is Wendy Ryan. Wendy is the CEO of Kadabra. With over 25 years of combined experience in human resources, organizational development, nonprofit leadership, and executive coaching Wendy have partnered with hundreds of individuals and organizations throughout the U.S., helping front-line through C-suite leaders and board members achieve success as individuals and in teams. Wendy is the author of the award-winning bestseller, Learn Lead Lift: How to Think, Act, and Inspire Your Way to Greatness, and has been featured in Forbes, Yahoo News!, Business Digest, Authority Magazine, CEO Magazine, and Thrive Global. Wendy is also an active mentor, strategic advisor, and angel investor in early stage, BIPOC, LGBTQ++, and womxn-led companies. She's an advocate for expanding diversity, equity, inclusion, and accessibility in the investor and business ecosystem. Wendy has a master's degree in Human Resources and Organizational Development. Here's what to expect during the episode: What are the 3 elements of the mindset framework? Why is a growth mindset needed for successful leadership? What should a leader consider before making any decision? What are the qualities of a good leader? Why do leaders need to let people know what they are thinking? Connect with Wendy Ryan! Website: https://www.wearekadabra.com/ Facebook: https://www.facebook.com/wearekadabra Instagram: https://www.instagram.com/we_are_kadabra/ LinkedIn: https://www.linkedin.com/company/wearekadabra/ | https://www.linkedin.com/in/wendyryankadabra/ Get free resources from Wendy by going to http://www.learnleadlift.com. Go to https://hilandconsulting.org/6stepsreport to get your free guide: 6 Steps You Must Know to Unleash the Potential of Your Nonprofit Board Mary's book is available on Amazon or wherever books are sold: Love Your Board! The Executive Directors' Guide to Discovering the Sources of Nonprofit Board Troubles and What to Do About Them. Be sure to subscribe to Inspired Nonprofit Leadership so that you don't miss a single episode, and while you're at it, won't you take a moment to write a short review and rate our show? It would be greatly appreciated!   Let us know the topics or questions you would like to hear about in a future episode. You can do that, and follow us, on Facebook.   Connect with Mary! LinkedIn: https://www.linkedin.com/in/maryhiland Inspired Nonprofit Leadership Facebook Group: https://tinyurl.com/inspirednonprofitleadership Company Facebook: https://www.facebook.com/hilandconsulting Website: https://www.hilandconsulting.org

Wendy Ryan is here today to share her vision of a world where people love going to work thanks to leaders who are inspiring and supportive, and who create a culture that lifts each team member up.  She is the CEO of Kadabra and an award-winning, Best-Selling Author of "Learn, Lead, Lift: How To Think, Act and Inspire Your Way to Greatness".   Guest Bio: Wendy Ryan (she/her), MHROD, is the CEO of Kadabra, an interdisciplinary team of leadership and change experts based in Silicon Valley, CA. She is also an active mentor, strategic advisor and angel investor in early stage, BIPOC, LGBTQ++ and womxn-led companies and an advocate for expanding diversity, equity, inclusion and accessibility in the investor and business ecosystem.   Guest Contact Info: WEBSITE: https://www.learnleadlift.com/ LINKEDIN: https://www.linkedin.com/in/wendyryankadabra/ TWITTER: https://twitter.com/ceo_wendy INSTAGRAM: https://www.instagram.com/ceo_wendyryan/ FACEBOOK: https://www.facebook.com/wearekadabra/   Thanks for listening to the show! It means so much to us that you listened to our podcast! If you would like to continue the conversation, please email me at allen@drallenlycka.com or visit our Facebook page at http://www.facebook.com/drallenlycka.    We would love to have you join us there, and welcome your messages. We check our Messenger often.   If you loved the podcast, be sure to subscribe on your favorite platform, share it with friends and leave a review! Dr. Lycka wants you to live your best life. Visit coachingwithdrlycka.com and book your Discovery call today. His bestselling book, "The Secrets to Living a Fantastic Life" can be found on Amazon.com. Get your copy today!    We are building a community of like-minded people in the personal development/self-help/professional development industries, and are always looking for wonderful guests for our show. If you have any recommendations, please email us!   Dr. Allen Lycka's Social Media Links Facebook: http://www.facebook.com/drallenlycka Instagram:  https://www.instagram.com/dr_allen_lycka/ Twitter:  https://www.twitter.com/drallenlycka LinkedIn:  https://www.linkedin.com/in/allenlycka YouTube:  https://www.YouTube.com/c/drallenlycka   Subscribe to the How to Live a Fantastic Life podcast We would be honored to have you subscribe to the show – you can subscribe to the podcast app on your mobile device.   Leave a review We appreciate your feedback, as every little bit helps us produce even better shows. We want to bring value to your day, and have you join us time and again.  Ratings and reviews from our listeners not only help us improve, but also help others find us in their podcast app. If you have a minute, an honest review on iTunes or your favorite app goes a long way! Thank you!

Wendy Ryan, MHROD, is the CEO of Kadabra. With over 25 years of combined experience in human resources, organizational development, non-profit leadership and executive coaching Wendy has partnered with hundreds of individuals and organizations throughout the U.S. helping front-line through C-suite leaders and board members achieve success as individuals and in teams. Wendy is the author of the award-winning bestseller, Learn Lead Lift: How to Think, Act, and Inspire Your Way to Greatness, and has been featured in Forbes, Yahoo News!, Business Digest, Authority Magazine, CEO Magazine, and Thrive Global. Wendy is also an active mentor, strategic advisor, and angel investor in early-stage, BIPOC, LGBTQ++, and womxn-led companies and an advocate for expanding diversity, equity, inclusion, and accessibility in the investor and business ecosystem. Website: www.wearekadabra.com www.wearekadabra.com/learn-lead-lift-download Facebook: wearekadabra linkedin: wendyryankadabra Instagram: we_are_kadabra

Ben and J discuss: J's new look, a Star Wars theory, eye prescriptions, Year One SCB schedule, changes and structure, surveys, echo chambers, Base Set Chansey, the Kadabra lore, Ben's first massage and the concept of Severance. Show Notes:  Star Wars: Rebels - https://en.wikipedia.org/wiki/Star_Wars_Rebels  The Mandalorian - https://en.wikipedia.org/wiki/The_Mandalorian  Peloton - https://www.onepeloton.com/  Nielsen Ratings - https://en.wikipedia.org/wiki/Nielsen_ratings  The Chansey Pokemon Card - https://www.amazon.com/Pokemon-Base-Shadowless-Holofoil-Chansey/dp/B00R6719VE  Ben's Wick of the Peek: getting a massage J's Wick of the Peek: Severance - https://en.wikipedia.org/wiki/Severance_(TV_series)  Support the Show and Vote for Host: https://www.patreon.com/popcornculture  Get your own GMA stickers: https://store.dftba.com/products/gma-stickers  Get Your Bingo Card: https://bingobaker.com#f805834af83dce50    Email the show: popcornculturepod@gmail.com  Discuss the Podcast on Reddit: https://www.reddit.com/r/PopcornCulture/  Follow the Show on Twitter: https://twitter.com/apopcast  Follow SCB on Instagram: https://www.instagram.com/carlinbrothers/  Follow SCB on TikTok: https://www.tiktok.com/@super_carlin_brothers Discuss the Podcast on YouTube: https://www.youtube.com/channel/UCHfIbq9thHPC8yrKjAdJgDA    Alternate Titles:  The Light Saber Incremental Changes The Immediacy of Tomorrow Triangles are Stronger Why Is No One on Twitter?!

Today's Guest: Wendy RyanWendy Ryan (she/her/hers), MHROD, is the CEO of Kadabra. With over 25 years of combined experience in human resources, organizational development, non-profit leadership and executive coaching Wendy has partnered with hundreds of individuals and organizations throughout the U.S. helping front-line through C-suite leaders and board members achieve success as individuals and in teams.Wendy is the author of the award-winning bestseller, Learn Lead Lift: How to Think, Act, and Inspire Your Way to Greatness and has been featured in Forbes, Yahoo News!, Business Digest, Authority Magazine, CEO Magazine and Thrive Global. Wendy is also an active mentor, strategic advisor and angel investor in early stage, BIPOC, LGBTQ++ and womxn-led companies and an advocate for expanding diversity, equity, inclusion and accessibility in the investor and business ecosystem.From the Episode:"What I love about women investors as a collective, is that we see the opportunity to push people forward. Not just the financial piece but also the support piece." -Dr. T"To love well we have to really know ourselves. We need to understand the informed compassion on ourselves." -Wendy RyanWendy Ryan:https://www.wearekadabra.com/If you know anyone who needs to hear what we talked about today please share. And if you loved it, please subscribe and leave us a review or go to https://heart-hustle-and-humor.simplecast.com/

Invest In Her host Catherine Gray talks with Wendy Ryan, the CEO of Kadabra, an interdisciplinary team of leadership and organizational change experts based in Silicon Valley, California.  With over 25 years of combined experience in human resources, organizational development, non-profit leadership and executive coaching Wendy has partnered with hundreds of individuals and organizations throughout the U.S. helping front-line through C-suite leaders and board members achieve success as individuals and in teams. Her first book, Learn Lead Lift: How to Think, Act, and Inspire Your Way to Greatness was released May 2021. ⁠Join us on Facebook LIVE every Wednesday at NOON PT @SheAngelInvestors. Subscribe on Apple Podcast https://apple.co/3citN1I, Spotify https://spoti.fi/2ZUrFZc, or wherever podcasts are available!

We meet strong leaders from time to time in the work we all do, and leaders need support. I had a chat with Wendy Ryan, an award-winning and bestselling author, speaker and CEO of Kadabra. Wendy  sheds much light on being a "change agent". Wendy is a coach, mentor, leadership strategist and a woman who believes in helping people become their very best self. Tune in and hear what she has to say about supporting leaders-- and please  check out her new book- Learn Lead Lift: How to Think, Act, and Inspire Your Way to Greatness.

Why, and how, should leaders acknowledge identity in the workplace?Pete is joined by Wendy Ryan - a CEO, author and trauma survivor exploring identity in the workplace and the leader's role not only to acknowledge it, but to actively lift others up.Wendy Ryan is the CEO of Kadabara, author of Learn Lead Lift, and advocate for expanding diversity, equity, inclusion and accessibility at work. Together they explore identity in the workplace, how culture and trauma impacts identity, and the role leaders play in creating space for employees to bring their whole selves to the workplace.Visit the (Re)Learning Leadership website for more on Wendy Ryan, Kadabra, her book Learn Lead Lift, the transcript and more 

Today's episode focuses on a new author's perspective of the book marketing process. According to Wendy Ryan — Author of Learn Lead Lift and CEO of Kadabra — it is a process that extends far beyond the book launch. She shares her experience as a new author and the lessons she learned while crafting and marketing her book, as well as how important it is for authors to be patient with themselves throughout each step of the journey. During the episode, Wendy shares: Her journey, her work in the world, and how she came to write her book, Learn Lead Lift. What she has noticed about the book marketing process as a first-time author. How she has been marketing her book since its publication, and what she envisions as she considers her future. The marketing strategies that have been most impactful for her in terms of driving the results she's most interested in. The details of her virtual launch party and what made it a success. The strategies that have worked best for her in expanding her audience. Some of the challenges she has experienced as a new author that she didn't expect. Some of the things she wishes she had known before she began her journey as an author.  Why patience and impatience lists are so helpful, and what kind of items might be found on each list. Some final thoughts about book marketing and the most important lessons she has learned throughout the process.  For our show notes, including action steps, and resources, visit: https://bit.ly/3ljFP0R (bit.ly/3ljFP0Rbit.ly/3ljFP0R) Please feel free to send a message to Becky at becky@weavinginfluence.com to share your thoughts!