Podcasts about DFT

Editor's note: CuspAI raised a $100m Series A in September and is rumored to have reached a unicorn valuation. They have all-star advisors from Geoff Hinton to Yann Lecun and team of deep domain experts to tackle this next frontier in AI applications.In this episode, Max Welling traces the thread connecting quantum gravity, equivariant neural networks, diffusion models, and climate-focused materials discovery (yes, there is one!!!).We begin with a provocative framing: experiments as computation. Welling describes the idea of a “physics processing unit”—a world in which digital models and physical experiments work together, with nature itself acting as a kind of processor. It's a grounded but ambitious vision of AI for science: not replacing chemists, but accelerating them.Along the way, we discuss:* Why symmetry and equivariance matter in deep learning* The tradeoff between scale and inductive bias* The deep mathematical links between diffusion models and stochastic thermodynamics* Why materials—not software—may be the real bottleneck for AI and the energy transition* What it actually takes to build an AI-driven materials platformMax reflects on moving from curiosity-driven theoretical physics (including work with Gerard ‘t Hooft) toward impact-driven research in climate and energy. The result is a conversation about convergence: physics and machine learning, digital models and laboratory experiments, long-term ambition and incremental progress.Full Video EpisodeTimestamps* 00:00:00 – The Physics Processing Unit (PPU): Nature as the Ultimate Computer* Max introduces the idea of a Physics Processing Unit — using real-world experiments as computation.* 00:00:44 – From Quantum Gravity to AI for Materials* Brandon frames Max's career arc: VAE pioneer → equivariant GNNs → materials startup founder.* 00:01:34 – Curiosity vs Impact: How His Motivation Evolved* Max explains the shift from pure theoretical curiosity to climate-driven impact.* 00:02:43 – Why CaspAI Exists: Technology as Climate Strategy* Politics struggles; technology scales. Why materials innovation became the focus.* 00:03:39 – The Thread: Physics → Symmetry → Machine Learning* How gauge symmetry, group theory, and relativity informed equivariant neural networks.* 00:06:52 – AI for Science Is Exploding (Not Emerging)* The funding surge and why AI-for-Science feels like a new industrial era.* 00:07:53 – Why Now? The Two Catalysts Behind AI for Science* Protein folding, ML force fields, and the tipping point moment.* 00:10:12 – How Engineers Can Enter AI for Science* Practical pathways: curriculum, workshops, cross-disciplinary training.* 00:11:28 – Why Materials Matter More Than Software* The argument that everything—LLMs included—rests on materials innovation.* 00:13:02 – Materials as a Search Engine* The vision: automated exploration of chemical space like querying Google.* 01:14:48 – Inside CuspAI: The Platform Architecture* Generative models + multi-scale digital twin + experiment loop.* 00:21:17 – Automating Chemistry: Human-in-the-Loop First* Start manual → modular tools → agents → increasing autonomy.* 00:25:04 – Moonshots vs Incremental Wins* Balancing lighthouse materials with paid partnerships.* 00:26:22 – Why Breakthroughs Will Still Require Humans* Automation is vertical-specific and iterative.* 00:29:01 – What Is Equivariance (In Plain English)?* Symmetry in neural networks explained with the bottle example.* 00:30:01 – Why Not Just Use Data Augmentation?* The optimization trade-off between inductive bias and data scale.* 00:31:55 – Generative AI Meets Stochastic Thermodynamics* His upcoming book and the unification of diffusion models and physics.* 00:33:44 – When the Book Drops (ICLR?)TranscriptMax: I want to think of it as what I would call a physics processing unit, like a PPU, right? Which is you have digital processing units and then you have physics processing units. So it's basically nature doing computations for you. It's the fastest computer known, as possible even. It's a bit hard to program because you have to do all these experiments. Those are quite bulky, it's like a very large thing you have to do. But in a way it is a computation and that's the way I want to see it. You can do computations in a data center and then you can ask nature to do some computations. Your interface with nature is a bit more complicated. But then these things will have to seamlessly work together to get to a new material that you're interested in.[01:00:44:14 - 01:01:34:08]Brandon: Yeah, it's a pleasure to have Max Woehling as a guest today. Max has done so much over his career that I've been so excited about. If you're in the deep learning community, you probably know Max for his work on variational autocoders, which has literally stood the test of prime or officially stood the test of prime. If you are a scientist, you probably know him for his like, binary work on graph neural networks on equivariance. And if you're a material science, you probably know him about his new startup, CASPAI. Max has a long history doing lots of cool problems. You started in quantum gravity, which is I think very different than all of these other things you worked on. The first question for AI engineers and for scientists, what is the thread in how you think about problems? What is the thread in the type of things which excite you? And how do you decide what is the next big thing you want to work on?[01:01:34:08 - 01:02:41:13]Max: So it has actually evolved a lot. In my young days, let's breathe, I would just follow what I would find super interesting. I have kind of this sensor. I think many people have, but maybe not really sort of use very much, which is like, you get this feeling about getting very excited about some problem. Like it could be, what's inside of a black hole or what's at the boundary of the universe or what are quantum mechanics actually all about. And so I follow that basically throughout my career. But I have to say that as you get older, this changes a little bit in the sense that there's a new dimension coming to it and there's this impact. Going in two-dimensional quantum gravity, you pretty much guaranteed there's going to be no impact on what you do relative, maybe a few papers, but not in this world, this energy scale. As I get closer to retirement, which is fortunately still 10 years away or so, I do want to kind of make a positive impact in the world. And I got pretty worried about climate change.[01:02:43:15 - 01:03:19:11]Max: I think politics seems to have a hard time solving it, especially these days. And so I thought better work on it from the technology side. And that's why we started CaspAI. But there's also a lot of really interesting science problems in material science. And so it's kind of combining both the impact you can make with it as well as the interesting science. So it's sort of these two dimensions, like working on things which you feel there's like, well, there's something very deep going on here. And on the other hand, trying to build tools that can actually make a real impact in the world.[01:03:19:11 - 01:03:39:23]RJ: So the thread that when I look back, look at the different things that you worked out, some of them seem pretty connected, like the physics to equivariance and, yeah, and, uh, gravitational networks, maybe. And that seems to be somewhat related to Casp. Do you have a thread through there?[01:03:39:23 - 01:06:52:16]Max: Yeah. So physics is the thread. So having done, you know, spent a lot of time in theoretical physics, I think there is first very fundamental and exciting questions, like things that haven't actually been figured out in quantum gravity. So that is really the frontier. There's also a lot of mathematical tools that you can use, right? In, for instance, in particle physics, but also in general relativity, sort of symmetry space to play an enormously important role. And this goes all the way to gauge symmetries as well. And so applying these kinds of symmetries to, uh, machine learning was actually, you know, I thought of it as a very deep and interesting mathematical problem. I did this with Taco Cohen and Taco was the main driver behind this, went all the way from just simple, like rotational symmetries all the way to gauge symmetries on spheres and stuff like that. So, and, uh, Maurice Weiler, who's also here, um, when he was a PhD student, he was a very good student with me, you know, he wrote an entire book, which I can really recommend about the role of symmetries in AI and machine learning. So I find this a very deep and interesting problem. So more recently, so I've taken a sort of different path, which is the relationship between diffusion models and that field called stochastic thermodynamics. This is basically the thermodynamics, which is a theory of equilibrium. So but then formulated for out of equilibrium systems. And it turns out that the mathematics that we use for diffusion models, but even for reinforcement learning for Schrodinger bridges for MCMC sampling has the same mathematics as this theoretical, this physical theory of non-equilibrium systems. And that got me very excited. And actually, uh, when I taught a course in, um, Mauschenberg, uh, it is South Africa, close to Cape Town at the African Institute for Mathematical Sciences Ames. And I turned that into a book site. Two years later, the book was finished. I've sent it to the publisher. And this is about the deep relationship between free energy, diffusion models, basically generative AI and stochastic thermodynamics. So it's always some kind of, I don't know, I find physics very deep. I also think a lot about quantum mechanics and it's, it's, it's a completely weird theory that actually nobody really understands. And there's a very interesting story, which is maybe good to tell to connect sort of my PZ back to where I'm now. So I did my PZ with a Nobel Laureate, Gerard the toft. He says the most brilliant man I've ever met. He was never wrong about anything as long as I've seen him. And now he says quantum mechanics is wrong and he has a new theory of quantum mechanics. Nobody understands what he's saying, even though what he's writing down is not mathematically very complex, but he's trying to address this understandability, let's say of quantum mechanics head on. And I find it very courageous and I'm completely fascinated by it. So I'm also trying to think about, okay, can I actually understand quantum mechanics in a more mundane way? So that, you know, without all the weird multiverses and collapses and stuff like that. So the physics is always been the threat and I'm trying to apply the physics to the machine learning to build better algorithms.[01:06:52:16 - 01:07:05:15]Brandon: You are still very involved in understanding and understanding physics and the worlds. Yeah. And just like applications to machine learning or introducing no formalisms. That's really cool.[01:07:05:15 - 01:07:18:02]Max: Yes, I would say I'm not contributing much to physics, but I'm contributing to the interface between physics and science. And that's called AI for science or science or AI is kind of a super, it's actually a new discipline that's emerging.[01:07:18:02 - 01:07:18:19]Speaker 5: Yeah.[01:07:18:19 - 01:07:45:14]Max: And it's not just emerging, it's exploding, I would say. That's the better term because I know you go from investments into like in the hundreds of millions now in the billions. So there's now actually a startup by Jeff Bezos that is at 6.2 billion sheep round. Right. Insane. I guess it's the largest startup ever, I think. And that's in this field, AI for science. It tells you something that we are creating a new bubble here.[01:07:46:15 - 01:07:53:28]Brandon: So why do you think it is? What has changed that has motivated people to start working on AI for science type problems?[01:07:53:28 - 01:08:49:17]Max: So there's two reasons actually. One is that people have been applying sort of the new tools from AI to the sciences, which is quite natural. And there's of course, I think there's two big examples, protein folding is a big one. And the other one is machine learning forest fields or something called machine learning inter-atomic potentials. Both of them have been actually very successful. Both also had something to do with symmetries, which is a little cool. And sort of people in the AI sciences saw an opportunity to apply the tools that they had developed beyond advertised placement, right, or multimedia applications into something that could actually make a very positive impact in society like health, drug development, materials for the energy transition, carbon capture. These are all really cool, impactful applications.[01:08:50:19 - 01:09:42:14]Max: Despite that, the science and the kind of the is also very interesting. I would say the fact that these sort of these two fields are coming together and that we're now at the point that we can actually model these things effectively and move the needle on some of these sort of science sort of methodologies is also a very unique moment, I would say. People recognize that, okay, now we're at the cusp of something new, where it results whether the company is called after. We're at the cusp of something new. And of course that always creates a lot of energy. It's like, okay, there's something, it's like sort of virgin field. It's like nobody's green field. Nobody's been there. I can rush in and I can sort of start harvesting there, right? And I think that's also what's causing a lot of sort of enthusiasm in the fields.[01:09:42:14 - 01:10:12:18]RJ: If you're an AI engineer, basically if the people that listen to this podcast will be in the field, then you maybe don't have a strong science background. How does, but are excited. Most I would say most AI practitioners, BM engineers or scientists would consider themselves scientists and they have some background, a little bit of physics, a little bit of industry college, maybe even graduate school that have been working or are starting out. How does somebody who is not a scientist on a day-to-day basis, how do they get involved?[01:10:12:18 - 01:10:14:28]Max: Well, they can read my book once it's out.[01:10:16:07 - 01:11:05:24]Max: This is basically saying that there is more, we should create curricula that are on this interface. So I'm not sure there is, also we already have some universities actual courses you can take, maybe online courses you can take. These workshops where we are now are actually very good as well. And we should probably have more tutorials before the workshop starts. Actually we've, I've kind of proposed this at some point. It's like maybe first have an hour of a tutorial so that people can get new into the field. There's a lot out there. Most of it is of course inaccessible, but I would say we will create much more books and other contents that is more accessible, including this podcast I would say. So I think it will come. And these days you can watch videos and things. There's a huge amount of content you can go and see.[01:11:05:24 - 01:11:28:28]Brandon: So maybe a follow-up to that. How do people learn and get involved? But why should they get involved? I mean, we have a lot of people who are of our audience will be interested in AI engineering, but they may be looking for bigger impacts in the world. What opportunities does AI for science provide them to make an impact to change the world? That working in this the world of pure bits would not.[01:11:28:28 - 01:11:40:06]Max: So my view is that underlying almost everything is immaterial. So we are focusing a lot on LLMs now, which is kind of the software layer.[01:11:41:06 - 01:11:56:05]Max: I would say if you think very hard, underlying everything is immaterial. So underlying an LLM is a GPU, and underlying a GPU is a wafer on which we will have to deposit materials. Do we want to wait a little bit?[01:12:02:25 - 01:12:11:06]Max: Underlying everything is immaterial. So I was saying, you know, there's the LLM underlying the LLM is a GPU on which it runs. In order to make that GPU,[01:12:12:08 - 01:12:43:20]Max: you have to put materials down on a wafer and sort of shine on it with sort of EUV light in order to etch kind of the structures in. But that's now an actual material problem, because more or less we've reached the limits of scaling things down. And now we are trying to improve further by new materials. So that's a fundamental materials problem. We need to get through the energy transition fast if we don't want to kind of mess up this world. And so there is, for instance, batteries. That's a complete materials problem. There's fuel cells.[01:12:44:23 - 01:13:01:16]Max: There is solar panels. So that they can now make solar panels with new perovskite layers on top of the silicon layers that can capture, you know, theoretically up to 50% of the light, where now we're at, I don't know, maybe 22 or something. So these are huge changes all by material innovation.[01:13:02:21 - 01:13:47:15]Max: And yeah, I think wherever you go, you know, I can probably dig deep enough and then tell you, well, actually, the very foundation of what you're doing is a material problem. And so I think it's just very nice to work on this very, very foundation. And also because I think this is maybe also something that's happening now is we can start to search through this material space. This has never been the case, right? It's like scientists, the normal way of working is you read papers and then you come up with no hypothesis. You do an experiment and you learn, et cetera. So that's a very slow process. Now we can treat this as a search engine. Like we search the internet, we now search the space of all possible molecules, not just the ones that people have made or that they're in the universe, but all of them.[01:13:48:21 - 01:14:42:01]Max: And we can make this kind of fully automated. That's the hope, right? We can just type, it becomes a tool where you type what you want and something starts spinning and some experiments get going. And then, you know, outcome list of materials and then you look at it and say, maybe not. And then you refine your query a little bit. And you kind of do research with this search engine where a huge amount of computation and experimentation is happening, you know, somewhere far away in some lab or some data center or something like this. I find this a very, very promising view of how we can sort of build a much better sort of materials layer underneath almost everything. And also more sustainable materials. Our plastics are polluting the planet. If you come up with a plastic that kind of destroys itself, you know, after, I don't a few weeks, right? And actually becomes a fertilizer. These are things that are not impossible at all. These things can be done, right? And we should do it.[01:14:42:01 - 01:14:47:23]RJ: Can you tell us a little bit just generally about CUSBI and then I have a ton of questions.[01:14:47:23 - 01:14:48:15]Speaker 5: Yeah.[01:14:48:15 - 01:17:49:10]Max: So CUSBI started about 20 months ago and it was because I was worried about I'm still worried about climate change. And so I realized that in order to get, you know, to stay within two degrees, let's say, we would not only have to reduce our emissions to zero by 2050, but then, you know, another half century or even a century of removing carbon dioxide from the atmosphere, not by reducing your emissions, but actually removing it at a rate that's about half the rate that we now emit it. And that is a unsolved problem. But if we don't solve it, two degrees is not going to happen, right? It's going to be much more. And I don't think people quite understand how bad that can be, like four degrees, like very bad. So this technology needs to be developed. And so this was my and my co-founder, Chet Edwards, motivation to start this startup. And also because, you know, we saw the technology was ready, which is also very good. So if you're, you know, the time is right to do it. And yeah, so we now in the meanwhile, we've grown to about 40 people. We've kind of collected 130 million investment into the company, which is for a European company is quite a lot. I would say it's interesting that right after that, you know, other startups got even more. So that's kind of tells you how fast this is growing. But yeah, we are we are now at the we've built the platform, of course, but it's for a series of material classes and it needs to be constantly expanded to new material classes. And it can be more automated because, you know, we know putting LLMs in as the whole thing gets more and more automated. And now we're moving to sort of high throughput experimentation. So connecting the actual platform, which is computational, to the experiments so that you can get also get fast feedback from experiments. And I kind of think of experiments as something you do at the end, although that's what we've been doing so far. I want to think of it as what I would call a sort of a physics processing unit, like a PPU, right, which is you have digital processing units and then you have physics processing units. So it's basically nature doing computations for you. It's the fastest computer known as possible, even. It's a bit hard to program because you have to do all these experiments. Those are quite, quite bulky. It's like a very large thing you have to do. But in a way, it is a computation. And that's the way I want to see it. So I want to you can do computations in a data center and then you can ask nature to do some computations. Your interface with nature is a bit more complicated. But then these things will have to seamlessly work together to get to a new material that you're interested in. And that's the vision we have. We don't say super intelligence because I don't quite know what it means and I don't want to oversell it. But I do want to automate this process and give a very powerful tool in the hands of the chemists and the material scientists.[01:17:49:10 - 01:18:01:02]Brandon: That actually brings up a question I wanted to ask you. First of all, can you talk about your platform to like whatever degree, like explain kind of how it works and like what you your thought processes was in developing it?[01:18:01:02 - 01:20:47:22]Max: Yeah, I think it's been surprisingly, it's not rocket science, I would say. It's not rocket science in the sense of the design and basically the design that, you know, I wrote down at the very beginning. It's still more or less the design, although you add things like I wasn't thinking very much about multi-scale models and as the common are rated that actually multi-scale is very important. And the beginning, I wasn't thinking very much about self-driving labs. But now I think, you know, we are now at the stage we should be adding that. And so there is sort of bits and details that we're adding. But more or less, it's what you see in the slide decks here as well, which is there is a generative component that you have to train to generate candidates. And then there is a digital twin, multi-scale, multi-fidelity digital twin, which you walk through the steps of the ladder, you know, they do the cheap things first, you weed out everything that's obviously unuseful, and then you go to more and more expensive things later. And so you narrow things down to a small number. Those go into an experiment, you know, do the experiment, get feedback, etc. Now, things that also have been more recently added is sort of more agentic sort of parts. You know, we have agents that search the literature and come up with, you know, actually the chemical literature and come up with, you know, chemical suggestions for doing experiments. We have agents which sort of autonomously orchestrate all of the computations and the experiments that need to be done. You know, they're in various stages of maturity and they can be continuously improved, I would say. And so that's basically I don't think that part. There's rocket science, but, you know, the design of that thing is not like surprising. What is it's surprising hard to actually build it. Right. So that's that's the thing that is where the moat is in the data that you can get your hands on and the and actually building the platform. And I would say there's two people in particular I want to call out, which is Felix Hunker, who is actually, you know, building the scientific part of the platform and Sandra de Maria, who is building the sort of the skate that is kind of this the MLOps part of the platform. Yeah. And so and recently we also added sort of Aaron Walsh to our team, who is a very accomplished scientist from Imperial College. We're very happy about that. He's going to be a chief science officer. And we also have a partnerships team that sort of seeks out all the customers because I think this is one thing I find very important. In print, it's so complex to do to actually bring a material to the real world that you must do this, you know, in collaboration with sort of the domain experts, which are the companies typically. So we always we only start to invest in the direction if we find a good industrial partner to go on that journey with us.[01:20:47:22 - 01:20:55:12]Brandon: Makes a lot of sense. Over the evolution of the platform, did you find that you that human intervention, human,[01:20:56:18 - 01:21:17:01]Brandon: I guess you could start out with a pure, you could imagine two directions when you start up making everything purely automatic, automated, agentic, so on. And then later on, you like find that you need to have more human input and feedback different steps. Or maybe did you start out with having human feedback? You have lots of steps and then like kind of, yeah, figure out ways to remove, you know,[01:21:17:01 - 01:22:39:18]Max: that is the second one. So you build tools for you. So it's much more modular than you think. But it's like, we need these tools for this application. We need these tools. So you build all these tools, and then you go through a workflow actually in the beginning just manually. So you put them in a first this tool, then run this to them or this with sithery. So you put them in a workflow and then you figure out, oh, actually, you know, this this porous material that we are trying to make actually collapses if you shake it a bit. Okay, then you add a new tool that says test for stability. Right. Yeah. And so there's more and more tools. And then you build the agent, which could be a Bayesian optimizer, or it could be an actual other them, you know, maybe trained to be a good chemist that will then start to use all these tools in the right way in the right order. Yeah. Right. But in the beginning, it's like you as a chemist are putting the workflow together. And then you think about, okay, how am I going to automate this? Right. For one very easy question you can ask yourself is, you know, every time somebody who is not a super expert in DFT, yeah, and he wants to do a calculation has to go to somebody who knows DFT. And so could you start to automate that away, which is like, okay, make it so user friendly, so that you actually do the right DFT for the right problem and for the right length of time, and you can actually assess whether it's a good outcome, etc. So you start to automate smaller small pieces and bigger pieces, etc. And in the end, the whole thing is automated.[01:22:39:18 - 01:22:53:25]Brandon: So your philosophy is you want to provide a set of specific tools that make it so that the scientists making decisions are better informed and less so trying to create an automated process.[01:22:53:25 - 01:23:22:01]Max: I think it's this is sort of the same where you're saying because, yes, we want to automate, yeah, but we don't see something very soon where the chemists and the domain expert is out of the loop. Yeah, but it but it's a retreat, right? It's like, okay, so first, you need an expert to tell you precisely how to set the parameters of the DFT calculation. Okay, maybe we can take that out. We can maybe automate that, right? And so increasingly, more of these things are going to be removed.[01:23:22:01 - 01:23:22:19]Speaker 5: Yeah.[01:23:22:19 - 01:24:33:25]Max: In the end, the vision is it will be a search engine where you where somebody, a chemist will type things and we'll get candidates, but the chemist will still decide what is a good material and what is not a good material out of that list, right? And so the vision of a completely dark lab, where you can close the door and you just say, just, you know, find something interesting and then it will it will just figure out what's interesting and we'll figure out, you know, it's like, oh, I found this new material to blah, blah, blah, blah, right? That's not the vision I have. He's not for, you know, a long time. So for me, it's really empowering the domain experts that are sitting in the companies and in universities to be much faster in developing their materials. And I should say, it's also good to be a little humble at times, because it is very complicated, you know, to bring it to make it and to bring it into the real world. And there are people that are doing this for the entire lives. Yeah. Right. And it's like, I wonder if they scratch their head and say, well, you know, how are you going to completely automate that away, like in the next five years? I don't think that's going to happen at all.[01:24:35:01 - 01:24:39:24]Max: Yeah. So to me, it's an increasingly powerful tool in the hands of the chemists.[01:24:39:24 - 01:25:04:02]RJ: I have a question. You've talked before about getting people interested based on having, you know, sort of a big breakthrough in materials, incremental change. I'm curious what you think about the platform you have now in are sort of stepping towards and how are you chasing the big change or is this like incremental or is there they're not mutually exclusive, obviously, but what do you think about that?[01:25:04:02 - 01:26:04:27]Max: We follow a mixed strategy. So we are definitely going after a big material. Again, we do this with a partner. I'm not going to disclose precisely what it is, but we have our own kind of long term goal. You could call it lighthouse or, you know, sort of moonshot or whatever, but it is going to be a really impactful material that we want to develop as a proof point that it can be done and that it will make it into the into the real world and that AI was essential in actually making it happen. At the same time, we also are quite happy to work with companies that have more modest goals. Like I would say one is a very deep partnership where you go on a journey with a company and that's a long term commitment together. And the other one is like somebody says, I knew I need a force field. Can you help me train this force field and then maybe analyze this particular problem for me? And I'll pay you a bunch of money for that. And then maybe after that we'll see. And that's fine too. Right. But we prefer, you know, the deep partnerships where we can really change something for the good.[01:26:04:27 - 01:26:22:02]RJ: Yeah. And do you feel like from a platform standpoint you're ready for that or what are the things that and again, not asking you to disclose proprietary secret sauce, but what are the things generally speaking that need to happen from where we are to where to get those big breakthroughs?[01:26:22:02 - 01:28:40:01]Max: What I find interesting about this field is that every time you build something, it's actually immediately useful. Right. And so unlike quantum computing, which or nuclear fusion, so you work for 20, 30, 40 years and nothing, nothing, nothing, nothing. And then it has to happen. Right. And when it happens, it's huge. So it's quite different here because every time you introduce, so you go to a customer and you say, so what do you need? Right. So we work, let's say, on a problem like a water filtration. We want to remove PFAS from water. Right. So we do this with a company, Camira. So they are a deep partner for us. Right. So we on a journey together. I think that the breakthrough will happen with a lot of human in the loop because there is the chemists who have a whole lot more knowledge of their field and it's us who will help them with training, having a new message. And in that kind of interface, these interactions, something beautiful will happen and that will have to happen first before this field will really take off, I think. And so in the sense that it's not a bubble, let's put it that way. So that's people see that as actual real what's happening. So in the beginning, it will be very, you know, with a lot of humans in the loop, I would say, and I would I would hope we will have this new sort of breakthrough material before, you know, everything is completely automated because that will take a while. And also it is very vertical specific. So it's like completely automating something for problem A, you know, you can probably achieve it, but then you'll sort of have to start over again for problem B because, you know, your experimental setup looks very different in the machines that you characterize your materials look very different. Even the models in your platform will have to be retrained and fine tuned to the new class. So every time, you know, you have a lot of learnings to transfer, but also, you know, the problems are actually different. And so, yes, I would want that breakthrough material before it's completely automated, which I think is kind of a long term vision. And I would say every time you move to something new, you'll have to start retraining and humans will have to come in again and say, okay, so what does this problem look like? And now sort of, you know, point the the machine again, you know, in the new direction and then and then use it again.[01:28:40:01 - 01:28:47:17]RJ: For the non-scientists among us, me included a bit of a scientist. There's a lot of terminology. You mentioned DFT,[01:28:49:00 - 01:29:01:11]RJ: you equivariance we've talked about. Can you sort of explain in engineering terms or the level of sophistication and engineering? Well, how what is equivariance?[01:29:01:11 - 01:29:55:01]Max: So equivariance is the infusion of symmetry in neural networks. So if I build a neural network, let's say that needs to recognize this bottle, right, and then I rotate the bottle, it will then actually have to completely start again because it has no idea that the rotated bottle. Well, actually, the input that represents a rotated bottle is actually rotated bottle. It just doesn't understand that. Right. If you build equivariance in basically once you've trained it in one orientation, it will understand it in any other orientation. So that means you need a lot less data to train these models. And these are constraints on the weights of the model. So so basically you have to constrain the way such data to understand it. And you can build it in, you can hard code it in. And yeah, this the symmetry groups can be, you know, translations, rotations, but also permutations. I can graph neural network, their permutations and then physics, of course, as many more of these groups.[01:29:55:01 - 01:30:01:08]RJ: To pray devil's advocate, why not just use data augmentation by your bottle is in all the different orientations?[01:30:01:08 - 01:30:58:23]Max: As an option, it's just not exact. It's like, why would you go through the work of doing all that? Where you would really need an infinite number of augmentations to get it completely right. Where you can also hard code it in. Now, I have to say sometimes actually data augmentation works even better than hard coding the equivariance in. And this is something to do with the fact that if you constrain the optimization, the weights before the optimization starts, the optimization surface or objective becomes more complicated. And so it's harder to find good minima. So there is also a complicated interplay, I think, between the optimization process and these constraints you put in your network. And so, yeah, you'll hear kind of contradicting claims in this field. Like some people and for certain applications, it works just better than not doing it. And sometimes you hear other people, if you have a lot of data and you can do data augmentation, then actually it's easier to optimize them and it actually works better than putting the equivariance in.[01:30:58:23 - 01:31:07:16]Brandon: Do you think there's kind of a bitter lesson for mathematically founded models and strategies for doing deep learning?[01:31:07:16 - 01:31:46:06]Max: Yeah, ultimately it's a trade-off between data and inductive bias. So if your inductive bias is not perfectly correct, you have to be careful because you put a ceiling to what you can do. But if you know the symmetry is there, it's hard to imagine there isn't a way to actually leverage it. But yeah, so there is a bitter lesson. And one of the bitter lessons is you should always make sure your architecture is scale, unless you have a tiny data set, in which case it doesn't matter. But if you, you know, the same bitter lessons or lessons that you can draw in LLM space are eventually going to be true in this space as well, I think.[01:31:47:10 - 01:31:55:01]RJ: Can you talk a little bit about your upcoming book and tell the listeners, like, what's exciting about it? Yeah, I should read it.[01:31:55:01 - 01:33:42:20]Max: So this book is about, it's called Generative AI and Stochastic Thermodynamics. It basically lays bare the fact that the mathematics that goes into both generative AI, which is the technology to generate images and videos, and this field of non-equilibrium statistical mechanics, which are systems of molecules that are just moving around and relaxing to the ground state, or that you can control to have certain, you know, be in a certain state, the mathematics of these two is actually identical. And so that's fascinating. And in fact, what's interesting is that Jeff Hinton and Radford Neal already wrote down the variational free energy for machine learning a long time ago. And there's also Carl Friston's work on free energy principle and active entrance. But now we've related it to this very new field in physics, which is called stochastic thermodynamics or non-equilibrium thermodynamics, which has its own very interesting theorems, like fluctuation theorems, which we don't typically talk about, but we can learn a lot from. And I think it's just it can sort of now start to cross fertilize. When we see that these things are actually the same, we can, like we did for symmetries, we can now look at this new theory that's out there, developed by these very smart physicists, and say, okay, what can we take from here that will make our algorithms better? At the same time, we can use our models to now help the scientists do better science. And so it becomes a beautiful cross-fertilization between these two fields. The book is rather technical, I would say. And it takes all sorts of things that have been done as stochastic thermodynamics, and all sorts of models that have been done in the machine learning literature, and it basically equates them to each other. And I think hopefully that sense of unification will be revealing to people.[01:33:42:20 - 01:33:44:05]RJ: Wait, and when is it out?[01:33:44:05 - 01:33:56:09]Max: Well, it depends on the publisher now. But I hope in April, I'm going to give a keynote at ICLR. And it would be very nice if they have this book in my hand. But you know, it's hard to control these kind of timelines.[01:33:56:09 - 01:33:58:19]RJ: Yeah, I'm looking forward to it. Great.[01:33:58:19 - 01:33:59:25]Max: Thank you very much. This is a public episode. If you'd like to discuss this with other subscribers or get access to bonus episodes, visit www.latent.space/subscribe

Cullen and Mason are joined by their friends Jeremy Gould from The Rumors are True Podcast, Daniel Terry DFT's Dungeon, and Kylan Savage from Church Jams Now to discuss the bands, All Saved Freak Band, Fela Kuti, Zwan, Les Rallizes Dénudés, and Dissection, all who have the craziest lore. What band do you think has the craziest lore?Check out The Rumors are True Podcast: https://www.instagram.com/therumorsaretruecastCheck out DFT's Dungeon: https://www.youtube.com/@dft9000Check out Church Jams Now: https://www.instagram.com/churchjamsnowBecome a supporter of this podcast: https://www.spreaker.com/podcast/the-blacksheep-podcast-presented-by-hm-magazine--2258933/support.Follow us on Instagram: instagram.com/theblacksheeppodcastSubscribe to our YouTube channel: youtube.com/@theblacksheeppodcast

Editor's note: Welcome to our new AI for Science pod, with your new hosts RJ and Brandon! See the writeup on Latent.Space (https://Latent.Space) for more details on why we're launching 2 new pods this year. RJ Honicky is a co-founder and CTO at MiraOmics (https://miraomics.bio/), building AI models and services for single cell, spatial transcriptomics and pathology slide analysis. Brandon Anderson builds AI systems for RNA drug discovery at Atomic AI (https://atomic.ai). Anything said on this podcast is his personal take — not Atomic's.—From building molecular dynamics simulations at the University of Washington to red-teaming GPT-4 for chemistry applications and co-founding Future House (a focused research organization) and Edison Scientific (a venture-backed startup automating science at scale)—Andrew White has spent the last five years living through the full arc of AI's transformation of scientific discovery, from ChemCrow (the first Chemistry LLM agent) triggering White House briefings and three-letter agency meetings, to shipping Kosmos, an end-to-end autonomous research system that generates hypotheses, runs experiments, analyzes data, and updates its world model to accelerate the scientific method itself.* The ChemCrow story: GPT-4 + React + cloud lab automation, released March 2023, set off a storm of anxiety about AI-accelerated bioweapons/chemical weapons, led to a White House briefing (Jake Sullivan presented the paper to the president in a 30-minute block), and meetings with three-letter agencies asking “how does this change breakout time for nuclear weapons research?”* Why scientific taste is the frontier: RLHF on hypotheses didn't work (humans pay attention to tone, actionability, and specific facts, not “if this hypothesis is true/false, how does it change the world?”), so they shifted to end-to-end feedback loops where humans click/download discoveries and that signal rolls up to hypothesis quality* Cosmos: the full scientific agent with a world model (distilled memory system, like a Git repo for scientific knowledge) that iterates on hypotheses via literature search, data analysis, and experiment design—built by Ludo after weeks of failed attempts, the breakthrough was putting data analysis in the loop (literature alone didn't work)* Why molecular dynamics and DFT are overrated: “MD and DFT have consumed an enormous number of PhDs at the altar of beautiful simulation, but they don't model the world correctly—you simulate water at 330 Kelvin to get room temperature, you overfit to validation data with GGA/B3LYP functionals, and real catalysts (grain boundaries, dopants) are too complicated for DFT”* The AlphaFold vs. DE Shaw Research counterfactual: DE Shaw built custom silicon, taped out chips with MD algorithms burned in, ran MD at massive scale in a special room in Times Square, and David Shaw flew in by helicopter to present—Andrew thought protein folding would require special machines to fold one protein per day, then AlphaFold solved it in Google Colab on a desktop GPU* The E3 Zero reward hacking saga: trained a model to generate molecules with specific atom counts (verifiable reward), but it kept exploiting loopholes, then a Nature paper came out that year proving six-nitrogen compounds are possible under extreme conditions, then it started adding nitrogen gas (purchasable, doesn't participate in reactions), then acid-base chemistry to move one atom, and Andrew ended up “building a ridiculous catalog of purchasable compounds in a Bloom filter” to close the loopAndrew White* FutureHouse: http://futurehouse.org/* Edison Scientific: http://edisonscientific.com/* X: https://x.com/andrewwhite01* Cosmos paper: https://futurediscovery.org/cosmosFull Video EpisodeTimestamps00:00:00 Introduction: Andrew White on Automating Science with Future House and Edison Scientific00:02:22 The Academic to Startup Journey: Red Teaming GPT-4 and the ChemCrow Paper00:11:35 Future House Origins: The FRO Model and Mission to Automate Science00:12:32 Resigning Tenure: Why Leave Academia for AI Science00:15:54 What Does ‘Automating Science' Actually Mean?00:17:30 The Lab-in-the-Loop Bottleneck: Why Intelligence Isn't Enough00:18:39 Scientific Taste and Human Preferences: The 52% Agreement Problem00:20:05 Paper QA, Robin, and the Road to Cosmos00:21:57 World Models as Scientific Memory: The GitHub Analogy00:40:20 The Bitter Lesson for Biology: Why Molecular Dynamics and DFT Are Overrated00:43:22 AlphaFold's Shock: When First Principles Lost to Machine Learning00:46:25 Enumeration and Filtration: How AI Scientists Generate Hypotheses00:48:15 CBRN Safety and Dual-Use AI: Lessons from Red Teaming01:00:40 The Future of Chemistry is Language: Multimodal Debate01:08:15 Ether Zero: The Hilarious Reward Hacking Adventures01:10:12 Will Scientists Be Displaced? Jevons Paradox and Infinite Discovery01:13:46 Cosmos in Practice: Open Access and Enterprise Partnerships Get full access to Latent.Space at www.latent.space/subscribe

In this episode CSCEN's Cate Bone discusses how the aviation industry is making progress towards a greener future with DFT's David Moroz. They discuss how emissions can be cut from air travel, new trends in aviation across the globe, and why we can all be hopeful about the future of air travel. Please note, this episode was recorded before ICAO's September negotiations. You can catch up with their current projects on their website: International Civil Aviation Organization.

Please check out the Food Direct Aid Fundraiser by @CommandZoe, with streams going on all November on Twitch. Donation form for prize raffles on Google. Please consider donating during this trying time.It's THE crossover episode of the century, to commemorate the 2 years of Hero's Blade Vibe Check. Now seen for the first time in color! This podcast might be a hobby podcast disguised as a Commander podcast....First time guest Medusa (she/they, @thelovelymedusa.bsky.social) and returning guest Lyght (They/Them/She/Her, @indominus-lux.bsky.social) of the GasLyght, GateCrash, GirlBite Podcast join Cole and Quinn in on their radio show host shenanigans, vaguely discuss the Commander Rules changes, heavily discuss Avatar cards, and call each other out for their various character flaws. Quinn is playing on the stack, but not the way you think. Cole explains color identity to a returning player, Lyght is slowly passing out from being double immunized, and Medusa is casting necromancy spells For The Win.Creative Content:GasLyght, GateCrash, GirlBite PodcastMagic: The Gathering's Worst Nightmare ShortBefore You Go | DSK, DFT, TDM, FINCard Concepts for Commander DamageCommander Brackets Beta Update – October 21, 2025Decks:Lyght - Her Moxfield PageMedusa - Her Moxfield PageCole - Need 4 Speed: NITROUS SWAMP | Vampiric Vengeance, Blade of AvacynQuinn - [Bracket 2] her majesty's conquest (mono red black mages/cutter red) | Launchpad Ashling

This week on Highways Voices we talk to both the public and private sector about the challenges facing, and the solutions helping, our industry today.We're at the LCRIG Strictly Highways event in Blackpool to hear fresh insights into how collaboration between local authorities, government, and the supply chain is unlocking new efficiencies and innovation across the UK's road network. You'll get real-world examples of how data, digital frameworks, and sustainability partnerships are helping transform road maintenance, asset management, and carbon reduction efforts, and you'll learn actionable takeaways on how to integrate best practices and emerging technologies into everyday operations to futureproof transport infrastructure.Subscribe to Highways Voices free on Apple Podcasts,Spotify,Amazon Music,Google Podcasts or Pocket Castsand never miss an episode!Our guests are: LCRIG Managing Director Kerry Winstanley, Darren Capes from the DfT, Dave Denner from the Welsh Government, Sunil Budhdeo and Rotherham MBC's Mick Powell, plus AE Yates, and their Marketing and Social Value lead Saffron Ramsey, Gaist CTO Stephen Remde and Megan Thompson, who's Tarmac Technical Product Support Manager.We'll also look ahead to Highways UK with organiser Claudia Davidson.Listen now to discover how our industry leaders are reshaping the future of highways, and get inspired to bring these innovations back to your own organisation.Highways Voices is brought to you with our partners the Transport Technology Forum, LCRIG, ADEPT and ITS UK.

Enjoy this week's episode with Guatemalan producer & Dj BEBBO. Bebbo is one of the Jewels coming out of Central America's underground scene. A skilled connoisseur of dance movements with a focus on versatile rhythms and mesmerizing melodies. Bebbo ´ s presentations are full of energy, harmony, and captivate the most demanding crowds around the world. Bebbo is focused on audio and visual elements to create short films which stories are spoken by music not words. On his productions Bebbo likes to explore all different sounds and influences. DFT has to offer a complete voyage, which can be delighted in any situation. Enjoy this House Journey with BEBBO including his latest EP Botanica on Redolent! BEBBO - BOTANICA (REDOLENT) KEFFI - BODYWORK FREENZY MUSIC - TO THE JUNGLE ABEL RAY, KASHOVSKI - BABY HOO, ANONIMAT - IT LACKS LUCK AUGUSTO YEPES, TALON - FUNK IT BEBBO, ZYRANOX - CENTURY SPEECH (UNRELEASED) BEBBO - PASSIONATE (UNRELEASED) (STEREO) DJ GREGORY, AFRICANISM, BARON - BLOCK PARTY (BARON EXTENDED MIX) IVAN ROMERO - OSHUN (DRUM MIX) (REDOLENT) HARRY ROMERO, FUTURE JOY - CALL ME LATER KPD - BELIEVE IN ME BEBBO - MANDRAGORA (REDOLENT) This show is syndicated & distributed exclusively by Syndicast. If you are a radio station interested in airing the show or would like to distribute your podcast / radio show please register here: https://syndicast.co.uk/distribution/registration

Professor Susannah Maidment, a palaeontologist at the Natural History Museum, joins us to discuss the world's oldest ankylosaur, which roamed our planet some 165 million years ago.The spicomellus has been dubbed the world's most unusual dinosaur.And, the DfT have announced the first electric car models eligible for £3,750 purchase grants.Plus, intelligence agencies from the UK and 12 allies issue a warning over Chinese cyber attacks on ‘critical sectors'.Also in this episode:-An upcoming sci-fi horror film has raised the heart rates of early viewers-A four-day work week pilot is a success in Scotland-Could e-scooters soon be regulated?-Summer ‘25 to be washed away by heavy rain and flooding-Princess Diana's 90s time capsule is dug up earlier than planned Hosted on Acast. See acast.com/privacy for more information.

Following on from our recent Piccadilly Line Tube Trainvideo, this week we go behind the scenes at Siemens' Goole Rail Village in Yorkshire to see everything that is going on there.The Government has announced the creation of a new property business called Platform4 to kick start the building of 40,000 houses on surplus railway land. We ask whether the plan is good business or just flogging off the family silver.And we look back at Alstom's The Greatest Gathering event in Derby and ask - was it the most spectacular railway event in living memory?(00:00) Intro(01:13) Behind the Scenes at Siemens train manufacturing plant: Goole Rail Village(17:31) DfT announces the formation of property business Platform4 to kick start 40,000 new homes(28:04) Review of The Greatest Gathering(43:37) Thanks to Supporters(48:04) Railway News Round-up(48:06) LNER Train of the future(50:10) ORR grant Open Access rights on ECML for December 2025(52:27) Special Beams to prevent bridge strikes at Brighton Road bridge, Coulsdon South(53:44) EMR Summer Sale 2025(56:09) The Quiz(58:43) Hull Trains - can donate Delay Repay to their Charity of the Year - P.A.U.L For Brain RecoveryMembership: If you want to see even more from Green Signals, including exclusive content, become a member and support the channel further too.YouTube -⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠https://www.youtube.com/@GreenSignals/join⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠Patreon -⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠https://www.patreon.com/GreenSignals⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠Green Signals: Website -⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠http://www.greensignals.org⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠Merchandise - ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠http://greensignals.etsy.com⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠Newsletter -⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠http://www.greensignals.org/#mailing-list⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠Follow: X (Twitter) -⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠https://twitter.com/greensignallers⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ LinkedIn -⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠https://www.linkedin.com/company/green-signals-productions-ltd⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠Instagram -⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠https://instagram.com/greensignallers⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠

It's the week of Alstom's The Greatest Gathering Railway 200celebration in Derby – we preview what's coming up this weekend.West of England Main Line trains will not be stopping atCrewkerne until further notice. What on earth has happened And is it the right decision?Plus Richard has a rant… about the Secretary of State's social mediaIt's the week of Alstom's The Greatest Gathering Railway 200 celebration in Derby – we preview what's coming up this weekend.West of England Main Line trains will not be stopping at Crewkerne until further notice. What on earth has happened? And is it the right decision?And Richard has a rant… about the Secretary of State's social mediaIn this episode:(00:00) Intro(00:37) The Greatest Gathering preview(07:19) Why trains aren't stopping at Crewkerne(24:25) Richard has a rant(29:45) Thanks to Supporters(31:20) Railway News Round-up(31:24) New Network Rail CEO(32:21) Eurostar on Channel Tunnel competition(33:47) DfT simpler fares and cheaper tickets?(35:40) Varamis Rail “on the brink”?(37:50) HS2 TBM lifted from ground(38:56) Civil servants to transfer to DfTO(41:50) German train crash(43:14) The Quiz(48:08) Prestongrange Heritage Industrial Museum open dayMembership: If you want to see even more from Green Signals, including exclusive content, become a member and support the channel further too.YouTube -⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠https://www.youtube.com/@GreenSignals/join⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠Patreon -⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠https://www.patreon.com/GreenSignals⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠Green Signals: Website -⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠http://www.greensignals.org⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠Merchandise - ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠http://greensignals.etsy.com⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠Newsletter -⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠http://www.greensignals.org/#mailing-list⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠Follow: X (Twitter) -⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠https://twitter.com/greensignallers⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ LinkedIn -⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠https://www.linkedin.com/company/green-signals-productions-ltd⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠Instagram -⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠https://instagram.com/greensignallers⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠Credits:Thumbnail image - Alstom

James Stewart, author of the recent review into HS2 and theDfT's approach to major projects speaks to Richard in this fascinating interview.Here's the background to James's review as set out by the Government: In October 2024, the Department for Transport (DfT) announced that James Stewart would lead a review of DfT's approach to the governance and assurance of major infrastructure project delivery, drawing primarily on evidence from High Speed Two (HS2). The review provides insights into DfT's approach to delivering complex infrastructure projects and programmes. It provides an important contribution to the ongoing efforts to ensure successful delivery as HS2 undergoes a critical programme reset. It also makes recommendations for improvements to the wider government system for delivering major projects.Membership: If you want to see even more from Green Signals, including exclusive content, become a member and support the channel further too.YouTube -⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠https://www.youtube.com/@GreenSignals/join⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠Patreon -⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠https://www.patreon.com/GreenSignals⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠Green Signals: Website -⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠http://www.greensignals.org⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠Merchandise - ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠http://greensignals.etsy.com⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠Newsletter -⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠http://www.greensignals.org/#mailing-list⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠Follow: X (Twitter) -⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠https://twitter.com/greensignallers⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ LinkedIn -⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠https://www.linkedin.com/company/green-signals-productions-ltd⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠Instagram -⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠https://instagram.com/greensignallers⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠Credits - Thumbnail image: HS2 Ltd

This week on Everything About Hydrogen we have Kyle Arnold, the Managing Director of HyHAUL Mobility Ltd (HML). The company is leading the largest roll out of hydrogen Heavy Goods Vehicles (HGV) refueling infrastructure in the United Kingdom, operating along the M4 with 30 trucks by Q2 2026, supported by funding from the UK Department for Transport (DfT) Zero Emission Road Freight Transport (ZERFT). ZERFT has been subsequently rebranded as Zero Emissions HGV and Infrastructure Demonstrations (ZEHID). HML plans to eventually deploy over 300 fuel cell trucks totaling 44 tonnes of gross weight, by 2030. Kyle previously developed, built and operated hydrogen refuelling infrastructure across the UK and Europe, notably the Tyseley refuelling site in Birmingham, the largest in Europe.About HML:HyHAUL is an ambitious initiative to establish the UK's first dedicated hydrogen mobility corridor, setting a new benchmark in sustainable transport by proving the feasibility and scalability of hydrogen in heavy-duty freight operations.By leveraging hydrogen's potential to power zero-emission vehicles, HyHAUL directly addresses the decarbonisation of the most challenging and emission-intensive duty cycles in road transport. This pioneering effort supports the UK's broader commitment to achieving net-zero emissions.About Kyle Arnold:HML Managing Director with over 20 years' experience in project management, innovative engineering, and delivering First-Of-A-kind (FOAK) hydrogen projects across the UK, EU, and beyond. Throughout his career, he's had the privilege of leading talented teams to ensure these groundbreaking projects are delivered safely, efficiently, and effectively. He's worked closely with local and national governments and collaborated with some of the world's most recognizable companies to drive innovation and make net-zero ambitions a reality. At the heart of everything he does, is a commitment to safety, sustainability, and pushing the boundaries of what's possible in the green hydrogen space.--Links:HML - https://hyhaul.co.uk/DfT and Innovate UK - https://www.cittimagazine.co.uk/news/infrastructure/dft-and-innovate-uk-programme-to-create-54-new-zero-emission-hgv-infrastructure-hubs-across-the-uk.html

This week on the Roach Koach Podcast the guys called up old friend and host of DFT's Dungeon Dan Terry to talk all about East West and their supposed nu-metal album, The Light In Guinevere's Garden. Lorin and Matt quiz Dan on life on the boards, whether it is possible to preach too much at your rock show, if being related to the band will help them reunite, and more! Take a listen!Exclusive episodes and more on the Roach Koach Patreon. New episodes of the Pact every month. Subscribe today! Rate and review Roach Koach on iTunes! We'd appreciate it! Questions about the show? Have album recommendations? Just want to say hi? We'd love to hear from you! Contact the show @RoachKoach on Twitter, Roach Koach on Facebook , Roach Koach on Instagram, or send an email to RoachKoachPodcast at Gmail. Follow the show on Youtube and TikTok! Find every episode of Roach Koach and order your Roach Koach T-shirt at Roach Koach dot com.

The Road Less Traveled | Late Stage Tips and Strats for Aetherdrift Draft Welcome to Lords of Limited, the podcast dedicated to getting you better at drafting in Magic: the Gathering. This week, we're filling the tank with a lot of different topics for Aetherdrift Draft. We've got a few more thoughts on Push the Limit, some late-stage card check-ins, a love letter to White in DFT, mana fixing power rankings, and sideboarding tricks for the best-of-three gamers out there!

Les dégénérescences lobaires fronto-temporales (DLFT), souvent appelées démences fronto-temporales (DFT), se caractérisent par la mort progressive des neurones au niveau du lobe frontal et de la partie antérieure du lobe temporal du cerveau, zone qui permet la pensée abstraite, l'adaptation du comportement et certains aspects du langage. Elles sont dues à une accumulation anormale de protéine TDP-43 ou de protéine tau et concernent 10 000 à 20 000 personnes en France. Après un 1er épisode de PODC'ALZ, avec le Dr Isabelle Le Ber, neurologue et chercheuse spécialiste en génétique, au cours duquel nous avons abordé les spécificités de cette pathologie (symptômes, diagnostic, prise en charge, traitements....), cette fois nous évoquons l'état des lieux et les avancées de la recherche. Pour en savoir plus sur les travaux du Dr Isabelle Le Ber soutenus par la Fondation : https://alzheimer-recherche.org/projets-2023/mieux-diagnostiquer-les-dft/ Pour en savoir plus sur les maladies dites "apparentées" à Alzheimer : https://alzheimer-recherche.org/maladies-apparentees/ L'association France DFT : https://www.france-dft.org/page/274401-notre-association

On The Open Road | The Archetypes, Strategies, and Cards We Love in DFT! Welcome to Lords of Limited, the podcast dedicated to getting you better at drafting in Magic: the Gathering. We've got one week of Aetherdrift under our belts and it's time to get into EVERYTHING! Is green really the best color? What are folks missing about Start Your Engines? How can you win with Grixis? And is there anything to like about White so far? All these questions will be answered!

Putting the DFT in DRAFT | What We Learned From Early Access Drafts! Welcome to Lords of Limited, the podcast dedicated to getting you better at drafting in Magic: the Gathering. This week, it's Early Access Debrief time! Between us both, we got about a dozen drafts under our belt in the Early Access Event on MTGA and have lots of updates from our initial thoughts on Aetherdrift including some re-ranked colors, archetypes, and lots of card evaluation movers up and down!

Zákon o dani z finančných transakcií (DFT) nadobúda účinnosť 1. januára 2025, pričom prvým zdaňovacím obdobím je apríl 2025. Daňovníkom je fyzická osoba – podnikateľ, právnická osoba alebo organizačná zložka zahraničnej osoby, ktorá je klientom poskytovateľa platobných služieb. Platiteľom tejto dane je primárne banka alebo aj podnikateľ za určitých podmienok. O tom, čo z toho vyplýva v praxi, sme sa rozprávali s poradkyňou Daňového centra Nadeždou Cígerovou. V rozhovore sa dozviete: Čo je transakčný účet a dokedy si ho treba zriadiť? Je potrebné oznamovať správcovi dane zriadenie transakčného účtu? Nielen banka je platiteľom DFT. V akých prípadoch platí transakčnú daň podnikateľ? Čo sú preúčtované náklady v kontexte platenia DFT? Ako sa vypočíta transakčná daň? Ako sa účtuje transakčná daň? Je DFT predmetom DPH? Čo ak dodávateľ vystaví faktúru, kde bude uvedený aj poplatok vo výške transakčnej dane v cene služby – ako sa to bude účtovať? Majú neziskové organizácie nejaké povinnosti ohľadom preukazovania oslobodenej činnosti od platenia DFT? Ako to bude v prípade FO – podnikateľov, ktorí si uplatňujú paušálne výdavky? Nielen transakčnú daň, ale aj iné novinky v oblasti daní a účtovníctva pre vás sledujeme a pravidelne uverejňujeme na www.danovecentrum.sk Sme Poradca podnikateľa – za každou radou je človek.

Les dégénérescences lobaires fronto-temporales (DLFT), souvent appelées démences fronto-temporales (DFT), se caractérisent par la mort progressive des neurones au niveau du lobe frontal et de la partie antérieure du lobe temporal du cerveau, zone qui permet la pensée abstraite, l'adaptation du comportement et certains aspects du langage. Elles sont dues à une accumulation anormale de protéine TDP-43 ou de protéine tau et concernent 10 000 à 20 000 personnes en France. Dans ce nouvel épisode de PODC'ALZ, nous abordons avec le Dr Isabelle Le Ber, neurologue et chercheuse spécialiste en génétique, les spécificités de cette pathologie, des symptômes au diagnostic, de la prise en charge aux traitements. Pour en savoir plus sur les maladies dites "apparentées" à Alzheimer : https://alzheimer-recherche.org/maladies-apparentees/ Pour en savoir plus sur les travaux du Dr Isabelle Le Ber soutenus par la Fondation : https://alzheimer-recherche.org/projets-2023/mieux-diagnostiquer-les-dft/ En savoir plus sur France DFT : https://www.france-dft.org/page/274401-notre-association  

Louise Haigh has become the first person to resign from Sir Keir Starmer's cabinet.Haigh announced she was standing down on Friday after it was revealed by Sky News and The Times she had a conviction for making a false statement to the police that her work mobile phone was among her possessions stolen during a London mugging in 2013.She pleaded guilty to fraud by false representation while a parliamentary candidate in 2014, before being elected MP for Sheffield Heeley the following year.The London's Standard's chief political correspondent Rachael Burford reports on the circumstances of the case.Following Haigh's resignation, Heidi Alexander, MP for Swindon South, was named the new transport secretary, after previously work as Sadiq Khan's deputy transport mayor from 2018 to 2021.Our transport editor Ross Lydall explains Alexander's work in the capital, and what will she find in her DfT in-tray.In part two, we're joined by actor Kit Young, on his role in Shakespeare's All's Well That End's Well at London's Sam Wanamaker Playhouse, learning a fictional language and getting his Bafta award through airport security. Hosted on Acast. See acast.com/privacy for more information.

UK GOVERNMENT INVESTIGATES NEW EMISSIONS CONCERNThe Department for Transport (DfT) is investigating claims that 47 car models emissions are not the same as the official test figures, with the accusation that they are manipulating the emissions. The DfT is attempting to establish if a defeat device is being used. You can learn more, by clicking this FleetWorld article link here. RIVIAN AND VW SIGN PARTNERSHIP AGREEMENTAfter announcing they would partner up, Rivian and Volkswagen have signed the partnership agreement. This will include extra investment from VW, taking the full price up to $5.8 billion. Click this EV Powered article link to read more. If you like what we do, on this show, and think it is worth a £1.00, please consider supporting us via Patreon. Here is the link to that CLICK HERE TO SUPPORT THE PODCAST NEW NEW CAR NEWS - Caterham Seven CSR TwentyCaterham bring us the most “luxurious” and pricey Seven variant yet, with a price tag of a smidgen under £80,000. Celebrating 20 years of the CSR chasis, which allowed for those of us on the slightly larger side of things to be more comfortable, this bespoke model will come with features, fittings and materials not available elsewhere. Click this EVO article link to read more. Toyota KayoibakoToyota showed off an electric van that truley is a multipurpose vehicle. They have imagined it as an urban centric vehicle providing transport for people, being a mobile retail area, a coffee shop and more. Not content with that, the outdoor activities market get a version too, which added chunky tyres and obligitory stuck on elements. Both look fab, we want both and we want them now. But they have been cleverly thought out too. You can see more, by clicking this Yanko Design article link here. Old Car Dead News: Jaguar F-Pace ends global sales in 2026If you remember, Alan asked why the wording of the end of UK sales of the F-Pace was so specific. We now know that the rest of the globe will no longer be able to buy one from 2026. Click this Autocar article link here, which clears up the issue. LUNCHTIME READ: IT'S ALL A BIT MUCHDo you too feel that modern supercars are all a bit much? Let alone hypercars and even hyper hatches are becoming too extreme for UK roads. Well, you are not alone, check out this link from Mr Jalco's Mostly About Driving to possibly find an answer to it all. LIST OF THE WEEK: TOP GEAR - TOP 9 VIRAL CAR ADVERTSWe are increasingly struggling to find good List of the Week article to share with you. If you find one, please do send it our way and if its good enough we'll put it on the show! Top Gear have nine adverts for you to check out, which are bound to bring back memories. Do you agree with Alan, on his choice and/or his comments about Andrew, and what about Andrew's choice? Let us...

Matt Canon is a long-time member of the Deerfield Family Theatre (DFT) community. He first performed with DFT in 2008 and has since taken on various roles, including acting, stage managing, and now directing. Matt is excited to be directing DFT's upcoming production of “Charlie and the Chocolate Factory,” which opens on November 15, 2024. He explains that this version is much closer to the original Roald Dahl book than previous adaptations, with a modern twist and some subtle changes to the story. Matt also recently acted in DFT's production of “Noises Off.” He enjoys switching between acting and directing roles, as he believes it keeps him fresh and helps him understand both perspectives. Matt is thrilled to be working with some familiar faces from DFT's 2009 “Willy Wonka” production, and he is confident the show will be a hit with audiences of all ages.Charlie and the Chocolate Factory Performances at Caruso Auditorium, 1801 Montgomery Rd., Deerfield:* Fridays, November 15 and 22 at 7:00pm* Saturdays, November 16 and 23 at 1:00pm and 7:00pm* Sundays, November 17 and 24 at 1:00pmDeerfield Family TheaterPurchase Tickets This is a public episode. If you would like to discuss this with other subscribers or get access to bonus episodes, visit deerfieldtheater.substack.com

I am thrilled to have Daniil Shcherbakov, CEO of TonTon Games, a Telegram gaming publisher welcomed into Binance Labs' incubation program. Daniil holds a MBA from Cambridge Business SchoolIn this episode, Daniil Shcherbakov, co-founder and CEO of TonTon Games, shares his journey from studying computer science to launching TonTon Games within Telegram's ecosystem. He delves into TonTon Games' unique strategy for long-term growth, the blue ocean opportunities within Telegram, and the company's commitment to genuine gaming experiences. Daniil offers valuable insights into user acquisition, sustainable monetization, and balancing creativity with data-driven decisions in gaming, and much more!Subscribe on SpotifySubscribe on YouTubeSubscribe on iTunesLearn* How does Daniil approach monetization in your games while maintaining a positive user experience?* What are the single biggest mistakes companies make with content today?* What trends does Daniil see emerging in the casual mobile gaming market?* What is your favourite business book? –Atomic Habits* What is your favourite online tool? –Use Bubbles* If you could go back to when you started working, what is the one thing you would have focused on? – Start company earlierTimestamps0:00 - Introduction to Daniil, CEO of TonTon Games.1:30 - Daniil shares his background, his shift from a family of doctors to pursuing computer science, and discovering his passion for tech.5:45 - His experience of joining Fibrum, an early startup where he created the company's name.10:45 - Daniil describes the camaraderie he built with classmates and the benefits of Cambridge's smaller, diverse class.13:00 - Founding of TonTon Games and the blend of his passion for gaming and startups.14:45 - TonTon Games' focus on Telegram as a gaming platform and the “blue ocean” opportunity in this space.16:30 - Overview of how Telegram's ecosystem for games is similar to WeChat's in China.18:15 - Daniil explains TonTon Games' strategy of avoiding “pump and dump” schemes and instead focusing on long-term incentives.20:45 - Discussion on acquiring users, including their approach to organic growth through influencers.23:00 - Success of their flagship game, DFT, which reached top 10 grossing apps on Telegram.24:30 - Daniil explains why they are not creating their own token and instead focus on sustainable mechanics.27:00 - How they evaluate and collaborate with development teams before entering formal agreements.28:30 - Explanation of the iterative approach to user acquisition and maintaining platform stability.31:00 - Strategy for monetizing games while respecting user experience.33:00 - Importance of data analysis in game development and Daniil's insights on balancing gut feeling and metrics.35:00 - Daniil's thoughts on the future of mobile gaming, especially in emerging markets.39:00 - Advice for budding game developers about the future of gaming demographics.45:00 - Daniil's perspective on AI, highlighting that it's a helpful tool rather than a replacement.Daniil's Links LDN– https://www.linkedin.com/in/shcherbakovds/Website - https://tonton.games/My Links Podcast: https://lifeselfmastery.com/itunesYouTube:  youtube.com/lifeselfmasteryTwitter: https://twitter.com/rohitmal5-day email course: www.enterprisesalesexpertise.com This is a public episode. If you would like to discuss this with other subscribers or get access to bonus episodes, visit partnergrow.substack.com

Danny Moulet is an actor with a history at Deerfield Family Theatre (DFT). He played Charlie Bucket in DFT's production of Willy Wonka 15 years ago, and now he is taking on the role of Mike Teavee in their current production of Charlie and the Chocolate Factory. Danny shares his journey into acting, starting with community theater productions as a teenager and then transitioning into storefront and professional work, including appearances on TV. He describes the challenges of the pandemic and how he was able to continue working on various projects during that time. Danny is enthusiastic about the new DFT production, praising the cast, crew, and updated music, and encouraging the audience to come see the show. Charlie and the Chocolate Factory Performances at Caruso Auditorium, 1801 Montgomery Rd., Deerfield:* Fridays, November 15 and 22 at 7:00pm* Saturdays, November 16 and 23 at 1:00pm and 7:00pm* Sundays, November 17 and 24 at 1:00pmDeerfield Family TheaterPurchase Tickets This is a public episode. If you would like to discuss this with other subscribers or get access to bonus episodes, visit deerfieldtheater.substack.com

Enjoy this week's episode with DJ & Producer BEBBO. Bebbo is one of the Jewels coming out of Central America's underground scene. A skilled connoisseur of dance movements with a focus on versatile rhythms and mesmerizing melodies. Bebbo ´ s presentations are full of energy, harmony, and captivate the most demanding crowds around the world. Bebbo is focused on audio and visual elements to create short films which stories are spoken by music not words. On his productions Bebbo likes to explore all different sounds and influences. DFT has to offer a complete voyage, which can be delighted in any situation. Enjoy this Afro Melodic Journey with BEBBO, including his latest release Donaruma on Redolent! Mari, Sistek - Heroe De Mexico (Original Mix) (TH3RD BRAIN) 
 FiNE, Bukeka - Alpha Omega (Original Mix) (Sippy Time) 
 The Deepshakerz - Now & Ever (Original Mix) (Knee Deep In Sound) 
 Eran Hersh, DiMO, Mili - Al Hawa (Original Mix) (Make The Girls Dance Records) 
 La Santa - Bombo (Original Mix) (Redolent) 
 Avicci X Black Circle - Double Levels (Jean Phillipe Remix) (Edit) 
 Tom Enzy, Pension - Piquete Cabron (Original Mix) (Make The Girls Dance Records) 
 DJ Chus, NenaHalena - Prado's Revenge (Original Mix) (Redolent) 
 Robin M - Miriam (Original Mix) (Human By Default) 
 Bebbo - Reflections (Original Mix) (Stereo Productions) 
 Franky Wah, Robin M - Maasai (Original Mix) (SHÈN Recordings) 
 Bebbo - Donaruma (Original Mix) (Redolent) 
 Kalyma, Yoshe, Kekura - Mind (Original Mix) (SOLIDE) 
 Bebbo - My Love (Unreleased) This show is syndicated & distributed exclusively by Syndicast. If you are a radio station interested in airing the show or would like to distribute your podcast / radio show please register here: https://syndicast.co.uk/distribution/registration

當大家都在說缺工缺才時，飛捷科技這家剛邁入40年大壽的企業，正逐步靠著DFT計畫，為台灣培養出更多優秀的人才！ 受到DFA Design For American計畫的啟發，飛捷科技基金會在八年前正式啟動DFT Design For Taiwan計畫，每年透過多場工作坊，廣邀國際講師與企業家，為學員們找出更多創新可能。計畫至今也幫助超過600位年輕學員參與，其中更不乏有許多新一代的創業家們! 坦言DFT工作坊雖然耗時耗力更燒錢，但飛捷一路走來仍不後悔這個決定。讓我們一同走進飛捷的創新世界，探索台灣企業社會責任的新模式！ 主持人：天下雜誌調查中心總監 熊毅晰 來賓：飛捷科技董事長 林大成、飛捷文教基金會 執行長 林逸芝 製作團隊：黃家慧、陳繹方、陳瑞偉 ＊訂閱天下全閱讀：https://bit.ly/3STpEpV ＊「聽天下」清楚分類更好聽，下載天下雜誌App：https://bit.ly/3ELcwhX ＊意見信箱：bill@cw.com.tw -- Hosting provided by SoundOn

Welcome to The New Quantum Era, a podcast hosted by Sebastian Hassinger and Kevin Rowney. In this episode, we have an insightful conversation with Dr. Toby Cubitt, a pioneer in quantum computing, a professor at UCL, and a co-founder of Phasecraft. Dr. Cubitt shares his deep understanding of the current state of quantum computing, the challenges it faces, and the promising future it holds. He also discusses the unique approach Phasecraft is taking to bridge the gap between theoretical algorithms and practical, commercially viable applications on near-term quantum hardware.Key Highlights:The Dual Focus of Phasecraft: Dr. Cubitt explains how Phasecraft is dedicated to algorithms and applications, avoiding traditional consultancy to drive technology forward through deep partnerships and collaborative development.Realistic Perspective on Quantum Computing: Despite the hype cycles, Dr. Cubitt maintains a consistent, cautiously optimistic outlook on the progress toward quantum advantage, emphasizing the complexity and long-term nature of the field.Commercial Viability and Algorithm Development: The discussion covers Phasecraft's strategic focus on material science and chemistry simulations as early applications of quantum computing, leveraging the unique strengths of quantum algorithms to tackle real-world problems.Innovative Algorithmic Approaches: Dr. Cubitt details Phasecraft's advancements in quantum algorithms, including new methods for time dynamics simulation and hybrid quantum-classical algorithms like Quantum enhanced DFT, which combine classical and quantum computing strengths.Future Milestones: The conversation touches on the anticipated breakthroughs in the next few years, aiming for quantum advantage and the significant implications for both scientific research and commercial applications.Papers Mentioned in this episode:Observing ground-state properties of the Fermi-Hubbard model using a scalable algorithm on a quantum computerTowards near-term quantum simulation of materialsEnhancing density functional theory using the variational quantum eigensolverDissipative ground state preparation and the Dissipative Quantum EigensolverOther sites:PhasecraftDr. Toby Cubitt's personal site

Dan is joined by Marc Hutner. Marc has been innovating in the areas of design, test, DFT and data analytics for more than 20 years. In June of 2023, he joined the Siemens EDA Tessent group as the product director of Silicon Learning, enabling how silicon data is applied to yield improvement and silicon debug. Previously, he worked … Read More

Welcome to The Nonlinear Library, where we use Text-to-Speech software to convert the best writing from the Rationalist and EA communities into audio. This is: How a chip is designed, published by YM on June 28, 2024 on LessWrong. Disclaimer: This is highly incomplete. I am not an expert in the field. There might be some unfamiliar terms. While I will try to explain things, explaining every single term would be beyond this post. You will usually be able to get a sufficient understanding by clicking the links or googling it. Introduction I think everyone, if they read about the chip industry long enough, has a moment where they have to put down a book or pause a podcast and simply remain stunned at the fact that it is possible to design and build something that is so incredibly impressive. The Apple A17 chip contains 183 million transistors per square millimeter. All placed in a coherent manner and produced with extremely high reliability. This is exactly why it is so fascinating to learn more about how it is actually done. On top of that, in a universe where compute is arguably the most important input in the AI production function, this knowledge is also crucial to effective AI governance. So what follows is a quick introduction to the processes of getting a chip from a vague idea to sending your files to the manufacturer, also called the tape-out. Background Knowledge One of the most important decisions, a decision that significantly determines all the others, is what manufacturer will build your chip and what process they will use. There are companies that do both design and manufacturing (e.g. Intel), but especially when it comes to the most advanced logic chips, more and more companies are what is called " fabless" - they focus on the design and task a so-called "foundry" (e.g. TSMC) with the manufacturing. Nowadays many fabs and fabless companies work together very closely in what is called Design-Technology Co-Optimization (DTCO). In practice, there are quite significant limitations in chip design, and the fab will check design plans and inform designers what can and can't be manufactured. This collaborative approach ensures that chip designs are optimized for the specific manufacturing process, balancing performance, power, area, and yield considerations. DTCO has become increasingly important as the industry approaches the physical limits of semiconductor scaling, requiring closer integration between design teams and process engineers to continue advancing chip capabilities. The foundry sends the design company what is called the process design kit ( PDK ), which contains all the important specifics to the fab and the manufacturing process (also known as the technology node). One factor that in large part determines the profitability of a chip is the yield of the manufacturing process. The yield is the fraction of chips produced that work flawlessly and can be sold. Compared to other types of products, in the semiconductor industry the yield is quite low, sometimes moving significantly below 50% for periods of time, especially at the beginning of a new technology node. To improve yield, optimal manufacturability is taken into account at many stages of the design process in what is called Design for Manufacturability (DFM). Chips are also designed to be easy to test (Design For Testability, DFT). In this post we are focussing on the design process, not with the actual manufacturing steps or the details of a transistor. But it is important to know that in practice we are working with standard cells that are all equal in height and vary in width. varies to make design and manufacturing easier. Often the IP for the standard cells is licensed from third parties. The Design Process My stages follow the outline given by Prof. Adam Teman in this lecture. Definition and Planning This is the stage where we think about what you even want to build. What bus structure do you want? How many cores should it have? What amount of p...

With the election approaching, we do a page-turn of the Public Accounts Committee's report into rail reform in Britain, as published back in May. Six years have passed since the DfT said the railway needed reform, and four years have passed since initiating that reform programme, via its white paper (we've been through the ill-fated Williams-Shapps Plan For Rail already) in 2021. We were supposed to have Great British Railways by March 2024. No such organisation has appeared. The reason it didn't tells us a lot about the challenges that the next government will face in changing the rail industry for the better - whether radically or incrementally. You can download the report here: https://committees.parliament.uk/committee/127/public-accounts-committee/news/201745/rail-reform-noone-in-government-putting-needs-of-passengers-and-taxpayers-first-pac-reports/ Enjoyed this? Please do consider supporting #Railnatter at https://patreon.com/garethdennis or throw loose change at me via https://paypal.me/garethdennis. Merch at https://garethdennis.co.uk/merch. Join in the discussion at https://garethdennis.co.uk/discord.

The discovery of new materials is an immense challenge, with a vast design space and numerous success criteria. Microsoft has recently demonstrated an advanced approach to machine learning-assisted material discovery, particularly in the realm of lithium-ion battery electrolytes. They began by exploring all possible structure types, decorating these structures with various atoms, leading to a pool of millions of candidate materials. The screening process went beyond simple stability checks to encompass a broad range of criteria, including predicted properties, electrode stability, and cost. This was achieved through various layers of filtering, leveraging data from diverse calculations, ranging from costly DFT and MD simulations to lower-fidelity calculations. Microsoft wisely positioned the expensive calculations towards the end of the pipeline, focusing resources only on the most promising candidates. Furthermore, they partnered with the Pacific Northwest National Laboratory (PNNL) to synthesize the compounds identified. In this podcast, we'll delve into this process, the challenges faced, and the future opportunities in this field, in conversation with Chi Chen and Nathan Baker. If you want more details on teh work microsoft is doing in this space, you can check out their paper where they provide more details on the methodology and experimental results. This episode of the Materialism Podcast is sponsored by Microsoft Azure Quantum Elements. You can try out their new copilot tools in an online demo on their Copilot Website. And if you want to learn more about how Microsoft is accelerating scientific discovery, you can head over to the Microsoft Azure Quantum Elements Website. Thanks to Kolobyte and Alphabot for letting us use their music in the show! If you have questions or feedback please send us emails at materialism.podcast@gmail.com or connect with us on social media: Instagram, Twitter. Materialism Team: Taylor Sparks (co-host, co-creator), Andrew Falkowski (co-host, co-creator), Jared Duffy (production, marketing, and editing). Keywords: AI Quantum Microsoft Materials Acceleration Battery Lithium Ion Li

My guest for Episode #257 of the My Favorite Mistake podcast is Chris Lewicki, an Astrofuturist, Engineer, and Entrepreneur who is interested in developing strong, thoughtful foundations for the near-future space economy. Episode page with transcript and more He's a multi-time co-founder. He first co-founded and was CEO of Planetary Resources Inc. (PRI), which focused on the prospecting, development, and use of resources found on near-Earth asteroids. (Skip) He helped acquire over $60M in investment and revenue, built a team of 80 extremely talented engineers, scientists, and business and policy leaders, and launched 3 experimental spacecraft to advance the adoption of space resources as a crucial part of humanity's activities in space. Prior to entering the private sector, Chris was a key member of NASA's Mars Exploration Rovers and the Phoenix Mars Lander, serving as Flight Director for the Mars rovers Spirit and Opportunity, and as the Surface Mission Manager for Phoenix. Chris received both bachelor's and master's degrees in aerospace engineering from the University of Arizona. He's the recipient of two NASA Exceptional Achievement Medals and has an asteroid named in his honor: 13609 Lewicki. Chris imparts lessons learned from his early days in NASA's Mars exploration projects, where a potential disaster during a rover test thrust him into the limelight as an emerging leader in the field. His poignant recount of the incident underscores the nuanced details that contribute to the success or failure of any mission and the critical concept of design for test( DFT). Drawing parallels to the broader engineering community, this episode's riveting discussion reveals essential strategies used in this high-stakes industry. The implementation of mistake-proofing tactics, robust system performance to ensure resilience, or ‘poka-yoke', and the introduction of redundancy in spacecraft design all contribute to an airtight spacecraft system. Learn from Chris's profound insights as he unravels the multifaceted considerations that go into ensuring functionality, designing for testability, and anticipating service requirements and testing needs during the initial design phases. Questions and Topics: Was it a connector being reversed??  New and innovative work… – was it a design mistake to not be “designed for test”? Could that have been mistake proofed in some way? It was not Would they have fired you? Did you ask??? Ernie or others?? Took time to be able to tell the story? How long? What response did you get to sharing that story online? Bringing these lessons into the private sector as CEO? How many people have taken you up on your offer to share their failure stories?? MY $500M MARS ROVER MISTAKE: A FAILURE STORY Netflix documentary on the James Webb telescope

Unlock the secrets behind Global Foundries' ascent to semiconductor supremacy and find out how a colossal $1.5 billion boost from the US CHIPS Act is setting the stage for technological innovation. Our guests, John Carulli, Ken Butler, and Shinji Hioki, join us from the frontlines of chip manufacturing to share their expertise on what it takes to be a pure-play foundry in today's competitive market. John holds 7 US Patents. He has over 50 publications in the areas of reliability, test, and process development. He is co-recipient of two Best Paper Awards and two Best Paper Nominations working in close collaboration with university partners. John serves on the organizing or program committees of several conferences including the International Test Conference, VLSI Test Symposium, and European Test Symposium. He is a Senior Member of IEEE. His research interests include product reliability, outlier analysis, machine learning, performance modeling, logic diagnosis, and security.Ken Butler is a Senior Director of Business Development in the Advantest Cloud Solutions (ACS) data analytics platform group at Advantest.  Prior to that, he worked for more than 36 years at Texas Instruments in DFT and test generation, semiconductor reliability, analog product and test engineering, and data analytics.  Ken has a BS from Oklahoma State University and an MS and PhD from the University of Texas at Austin, all in electrical engineering.  He is a Fellow of the IEEE, a Golden Core member of the IEEE Computer Society, and a Senior Member of the ACM.Shinji Hioki joined Advantest ACS in 2022, focusing on developing the ACS business in Japan. Prior to Advantest, he served as the ASIC Commodity Manager / Technologist at Tektronix for over five years, where he managed foundries and OSATs for ASIC production. Before his time at Tektronix, Shinji had a substantial 31-year tenure at Intel, where he held various roles in the Quality & Reliability organization, spanning development, high-volume manufacturing production, and supply chain management In this vibrant episode we track the transformation of silicon wafer dreams into the tangible powerhouse chips that energize our daily devices, dissecting the interplay of design, production, and the crucial customer relationships that drive the industry forward.Feel the pulse of the semiconductor world as we tackle the elephant in the room: the pressures of Moore's law and the herculean task of safeguarding tech's most sensitive data. This episode is a call to arms for more transparent collaborations between foundries, assembly, and test operations, with an eye on the future where open data flow might just be the magic ingredient for enhanced yield management and efficiency.As we wrap up our journey, we turn our attention to the fertile minds of tomorrow's tech leaders. We discuss how acts like the CHIPS Act and mainstream conversations about semiconductors are sparking interest among the youth, encouraging them to pursue careers in this electrifying field. Our conversation weaves through the importance of engaging storytelling in tech education, making semiconductor testing and assembly as thrilling as time travel adventures for the next generation. Thanks for tuning in to "Advantest Talks Semi"! If you enjoyed this episode, we'd love to hear from you! Please take a moment to leave a rating on Apple Podcast. Your feedback helps us improve and reach new listeners. Don't forget to subscribe and share with your friends. We appreciate your support!

Sebastian interviews Professor Lin Lin during the System One ribbon cutting event at Rensselaer Polytechnic Institute in Troy, NY. Professor Lin Lin's journey from computational mathematics to quantum chemistry has been driven by his fascination with modeling nature through computation. As a student at Peking University, he was intrigued by the concept of first principles modeling, which aims to simulate chemical systems using minimal information such as atomic species and positions. Lin Lin pursued this interest during his PhD at Princeton University, working with mathematicians and chemists to develop better algorithms for density functional theory (DFT). DFT reformulates the high-dimensional quantum chemistry problem into a more tractable three-dimensional one, albeit with approximations. While DFT works well for about 95% of cases, it struggles with large systems and the remaining "strongly correlated" 5%. Lin Lin and his collaborators radically reformulated DFT to enable calculations on much larger systems, leading to his faculty position at UC Berkeley in 2014.In 2018, a watershed year marked by his tenure, Lin Lin decided to tackle the challenging 5% of strongly correlated quantum chemistry problems. Two emerging approaches showed promise: artificial intelligence (AI) and quantum computing. Both AI and quantum computing are well-suited for handling high-dimensional problems, albeit in fundamentally different ways. Lin Lin aimed to leverage both approaches, collaborating on the development of deep molecular dynamics using AI to efficiently parameterize interatomic potentials. On the quantum computing side, his group worked to reformulate quantum chemistry for quantum computers. Despite the challenges posed by the COVID-19 pandemic, Lin Lin and his collaborators have made significant strides in combining AI and quantum computing to push the boundaries of computational chemistry simulations, bridging the fields of mathematics, chemistry, AI, and quantum computing in an exciting new frontier.Thanks again to Professor Lin and everyone at RPI for hosting me and providing such an amazing opportunity to interview so many brilliant researchers. 

Welcome to The BTA Podcast.  In these podcasts we will endeavour to share our thoughts, concerns, optimism and build those all-important human connections with our Partners, Members and Guests.In their latest conversation Clive Wratten and Andrew Clarke look back at their highlights of the BTA Spring Conference, recent interactions with MPs and representatives at the DfT.  They look forward to the BTA People & Talent Conference, the next Innovation Hub, conversations with the Rail Minister Huw Merriman and attendance at the Northern Transit Summit.You can subscribe to this podcast by searching 'BusinessTravel360' on Google Podcast, Apple Podcast, iHeart, Pandora, Spotify, Alexa or your favorite podcast player.This podcast was created by The BTA and distributed by BusinessTravel360.  For more information about The BTA visit us at TheBTA.org.ukSupport the show

In this special solo episode recorded at Q2B Paris 2024, Sebastian talks with Houlong Zhuang, assistant professor at Arizona State University, about his work in material science. Dr. Zhuang discusses his research on using quantum computing and machine learning to simulate high entropy alloy materials. The goal is to efficiently predict material properties and discover new material compositions.Density functional theory (DFT) is a commonly used classical computational method for materials simulations. However, it struggles with strongly correlated electronic states. Quantum computers have the potential to efficiently simulate these challenging quantum interactions.The research uses classical machine learning models trained on experimental data to narrow down the vast combinatorial space of possible high entropy alloy compositions to a smaller set of promising candidates. This is an important screening step.Quantum machine learning and quantum simulation are then proposed to further refine the predictions and simulate the quantum interactions in the materials more accurately than classical DFT. This may enable prediction of properties like stability and elastic constants.Key challenges include the high dimensionality of the material composition space and the noise/errors in current quantum hardware. Hybrid quantum-classical algorithms leveraging the strengths of both are a promising near-term approach.Ultimately, the vision is to enable inverse design - using the models to discover tailored material compositions with desired properties, potentially reducing experimental trial-and-error. This requires highly accurate, explainable models.In the near-term, quantum advantage may be realized for specific local properties or excited states leveraging locality of interactions. Fully fault-tolerant quantum computers are likely needed for complete replacement of classical DFT.Continued development of techniques like compact mappings, efficient quantum circuit compilations, active learning, and quantum embeddings of local strongly correlated regions will be key to advancing practical quantum simulation of realistic materials.In summary, strategically combining machine learning, quantum computing, and domain knowledge of materials is a promising path to accelerating materials discovery, but significant research challenges remain to be overcome through improved algorithms and hardware. A hybrid paradigm will likely be optimal in the coming years.Some of Dr. Zhuang's papers include: Quantum machine-learning phase prediction of high-entropy alloysSudoku-inspired high-Shannon-entropy alloysMachine-learning phase prediction of high-entropy alloys

In this episode of the Benevolent AI Podcast, host Ryan Merrill is joined by Oliver Klingefjord, co-founder and tech lead of the Meaning Alignment Institute, to explore the transformative potential of artificial intelligence (AI) in shaping a future aligned with human values and ethics.

Anion binding and ion-pairing of organoplatinum(II) complexes with countercations increases solid-state phosphorescence 75 times Enhancing Solid-State Phosphorescence in Pi Electronic Molecules Pi Electronic molecules are luminescent materials with applications in photonics. However, they lose their luminosity in the solid state due to self-association. To address this issue, researchers from Ritsumeikan University, Japan introduced chloride ions and cations to dipyrrolyldiketone PtII complexes, creating a charge-by-charge arrangement. This innovative approach prevents self-association of Pi-electronic molecules, maintaining luminescent properties in the solid state. The study opens avenues for new emissive materials with potential applications in organic electronics and flexible displays. Photoluminescent molecules, capable of absorbing and re-emitting light, play an important role in the development of technologies such as light-emitting diodes, sensors, and displays. Among them, ordered arrangements of Pi-electronic molecules such as crystals of organoplatinum(II) complexes, where a platinum(II) ion is coordinated by organic ligands in a square-planar arrangement, stand out for their applications in energy-efficient flexible displays. However, their luminescence in the solid state is short-lived due to the interaction between excitons (bound electron-hole pairs) of neighboring molecules. To address this issue, bulky foreign molecules are introduced into the molecular structure to prevent or minimize the electronic interactions between molecules. Using this strategy, a research team led by Professor Hiromitsu Maeda from Ritsumeikan University, Japan, recently enhanced the solid-state phosphorescence in multiple organoplatinum(II) complexes, increasing the phosphorescence by upto 75 times. "Spatially and electronically isolated ordered arrangement of emissive ?-electronic molecules is a principal point for the preparation of emissive solid-state materials. This concept can be used in materials for organic electronics, particularly organic light-emitting diodes for flexible displays," explains Prof. Maeda. In their study published in Chemical Science on December 5, 2023, the research team synthesized dipyrrolyldiketone PtII complexes consisting of four different C^N ligands. These molecules display strong phosphorescence in solution but show extremely weak phosphorescence in the solid state due to self-association. To enhance their luminosity in the solid state, the team introduced ion pairs consisting of a chloride anion and tetraalkylammonium countercations: TPA+ (tetrapropylammonium), TBA+ (tetrabutylammonium), and TPeA+ (tetrapentylammonium). This resulted in ion-pairing assemblies consisting of chloride ion-binding PtII complexes and countercations. The chloride ions bind to the PtII complex via hydrogen bonds, while the cations form layers between the ?-electronic molecules. X-ray analysis confirmed the complex's rigid structure, where PtII complexes are separated by cations in charge-by-charge arrangements. By isolating the electronic molecules from each other, the researchers enhanced the luminescent properties of the organoplatinum(II) complexes in the solid state. Compared to the original anion-free states where the complex is not bonded to the chloride ion, the relative intensity of phosphorescence in Cl-binding PtII complexes with cations showed improvements ranging from 1% to 7.5%, a 75-fold increase over the original molecule. The luminescence also lasts significantly longer, with certain ion-pairing assemblies achieving an emission lifetime nearly 200 times longer than the monomeric PtII complex. Theoretical studies using DFT calculations revealed that the charge-by-charge packing structure prevents the delocalization of the electron wavefunction over PtII complexes. "To the best of our knowledge, such a room-temperature phosphorescence enhancement by anion binding and ion-pairing assembly has not been demons...

Natalie interviews Sukhi Wahiwala, a highly respected Sikh business celebrity, about the intersection of business and spirituality, discussing how aligning the head and heart can lead to success and confidence. Sukhi shares his DFT (Direct Focused Thought) method and the importance of clarity in overcoming procrastination. Drawing from his own lineage and teachings, Sukhi emphasises the significance of connecting with one's spiritual center and being of service to others.  KEY TAKEAWAYS There is great value in spending time with older generations and keeping their memory alive. Success in business can be achieved while maintaining a spiritual connection and moralistic approach. The DFT method involves asking deep questions, focusing thoughts, and removing blocks or restrictions in thinking. Believe in your own abilities and to have faith in something greater than yourself. Our beliefs shape our reality and that we have the power to manifest what we desire through focused thought and action. BEST MOMENTS "Money doesn't get you wisdom. It gives you access to things that can make you money, for example, may give you access to a lifestyle."  "We are spiritual beings, we're convivial, connected beings. But the key here is to have three core tenets of one's life, which is working hard, non, and tithing." "Confidence should be somebody who knows how to do something well, and they can repeat it with a strategy and a structure. Arrogance is when I'm the only one who can do it, and do you want to work with me, yes or no?"  "If you're a person who's a snoozer, then ask yourself, am I even stretching myself? Am I even living? Am I pushing myself, my barriers a little bit at all? Well, you're probably fine. No, you probably haven't set yourself a goal."  VALUABLE RESOURCES https://www.facebook.com/groups/confidententrepreneurscollective http://www.nataliearabella.com/club Consultation Call Booking - https://calendly.com/natalie-arabella-bailey/confidencecollective ABOUT THE GUEST Sukhi Wahiwala is a very well known & Respected Sikh Business Celebrity, Successful Down to Earth Award Winning Visionary Entrepreneur; Forbes Recognised Judge, Dynamic Ted Talk Speaker, Radio Presenter, Philanthropist, Business Mentor & trailblazer .Who Ignites  Global Success through Game-Changing MindSet Strategies that are Taylored for Individuals Who are Looking To Grow. ABOUT THE HOST Natalie Bailey, a Property Developer, Coach, and Mentor, boasts a decade of business acumen, from Bars to Gyms and eCommerce. Now partnered with her mother, Paula, in property development, she empowers others to find confidence and success in health, wealth, and happiness. Her Better Together initiative combats loneliness, aiding entrepreneurs through the Confident Entrepreneurs Club, Mastermind groups, and Retreats. Bridging Mallorca and London, Natalie embodies her teachings. Fitness, wealth, and happiness intertwine in her holistic approach. Dive deeper at www.nataliearabella.com for coaching plans and more info. CONTACT US FACEBOOK- https://www.facebook.com/nataliearabellabailey LinkedIn- https://www.linkedin.com/in/nataliegoldstarbep/ Instagram- https://www.instagram.com/nataliearabellabailey/ Clubhouse- https://www.clubhouse.com/@nataliearabella TikTok- https://www.tiktok.com/@nataliearabellab Email - team@nataliearabella.comThis show was brought to you by Progressive Media

העבודה בתחום הצ'יפים דורשת בדיקות מקיפות ויסודיות לקוד של הצ'יפ (ה-RTL).את הלוגיקה בודקים בסימולציה.אז מהי אמולציה?כדי לענות על השאלה ולהכיר את תפקידו של מהנדס האמולציה הזמנו לאולפן את סעיד סעבני שהקים שלושה צוותי אמולציה בעבר ומומחה בתחומו.אז על מה דיברנו?מה ההבדל בין סימולציה לאמולציה? ומה זה בכלל אמולציה?סוגי האמולציה שקיימים כיוםהאם תמיד צריך אמולציה?בונוס בשביל שי - האם יש DFT גם באמולציה?הפרק הזה משתייך לסדרת הפרקים שעוסקת בהכרת התפקידים של מהנדסי חשמל בתעשייה, אך אנחנו מציעים למי שמתחיל להאזין להקשיב קודם לפרק 7 (מהנדס Logic Design / Frontend) עם אמנון זיידמן על מנת להכיר את המושגים המדוברים בפרק.גרסאות חדשות של Gameboy Emulator תוכלו למצוא (בין היתר) בקבוצת הווטסאפ שלנו >>>https://chat.whatsapp.com/KwUu8pQsxx220qS7AXv04T

DFT's TYA (Theater for Young Audiences) Presents, Fancy Nancy The Musical! DFT Info: ⁠⁠⁠⁠https://deerfieldtheater.com/⁠⁠⁠⁠ Check out April Sigman-Marx. Performances: Thursday, 8/3; 6:00 pm Friday, 8/4; 10:30 am and 6:00 pm Saturday, 8/5; 10:30 am and 2:00 pm Sunday, 8/6; 10:30 am Purchase Tickets: ⁠⁠⁠⁠⁠https://bit.ly/3othZ4Q⁠⁠⁠⁠

DFT's TYA (Theater for Young Audiences) Presents, Fancy Nancy The Musical! DFT Info: ⁠⁠⁠https://deerfieldtheater.com/⁠⁠⁠ Check out Danny Abosch. Performances: Thursday, 8/3; 6:00 pm Friday, 8/4; 10:30 am and 6:00 pm Saturday, 8/5; 10:30 am and 2:00 pm Sunday, 8/6; 10:30 am Purchase Tickets: ⁠⁠⁠⁠https://bit.ly/3othZ4Q⁠⁠⁠⁠

One of the best ways to speed-up product development is to integrate test as early as possible in the design cycle. This shift-left strategy becomes even more critical when advanced IC designs evolve from a single die per package to complex systems with multiple dies integrated into a package. These 2.5D and 3D multi-die design strategies pose some interesting challenges and opportunities for test. Today, David Lyell interviews Joe Reynick, the Tessent Product Engineering Manager for Siemens EDA. He'll help us to understand the complexity of development tests for 3D and 2.5D packages. In this episode, you'll learn about the challenges of performing comprehensive tests on 3D and 2.5D designs. You'll also hear about the factors that you need to consider while planning for 3D DFT and IP tests. Additionally, you'll hear about how 2.5D tests and 3D tests can complement each other. What You Will Learn In This Episode: The things you need to be aware of when doing 2.5D and 3D tests (03:34) The DFT and IP test methods that the DFT and IP test team should implement (09:36) The die and package level planning interactions needed for 3D DFT and IP test (11:22) Factors to consider while doing 3D tests (14:20) What is involved in multi-die IP core test (16:00) Connect with Joe Reynick:  LinkedIn Connect with David Lyell:  LinkedIn Hosted on Acast. See acast.com/privacy for more information.

Welcome to The Nonlinear Library, where we use Text-to-Speech software to convert the best writing from the Rationalist and EA communities into audio. This is: Mesa-Optimizers via Grokking, published by orthonormal on December 6, 2022 on The AI Alignment Forum. Summary: Recent interpretability work on "grokking" suggests a mechanism for a powerful mesa-optimizer to emerge suddenly from a ML model. Inspired By: A Mechanistic Interpretability Analysis of Grokking Overview of Grokking In January 2022, a team from OpenAI posted an article about a phenomenon they dubbed "grokking", where they trained a deep neural network on a mathematical task (e.g. modular division) to the point of overfitting (it performed near-perfectly on the training data but generalized poorly to test data), and then continued training it. After a long time where seemingly nothing changed, suddenly the model began to generalize correctly and perform much better on test data: A team at Anthropic analyzed grokking within large language models and formulated the idea of "induction heads". These are particular circuits (small sub-networks) that emerge over the course of training, which serve clearly generalizable functional roles for in-context learning. In particular, for GPTs multi-layer transformer networks doing text prediction, the model eventually generates circuits which hold on to past tokens from the current context, such that when token A appears, they direct attention to every token that followed A earlier in the context. (To reiterate, this circuit does not start a session with those associations between tokens; it is instead a circuit which learns patterns as it reads the in-context prompt.) The emergence of these induction heads coincides with the drop in test error, which the Anthropic team called a "phase change": Neel Nanda and Tom Lieberum followed this with a post I highly recommend, the aforementioned A Mechanistic Interpretability Analysis of Grokking. They looked more closely at grokking for mathematical problems, and were impressively able to reverse-engineer the post-grokking algorithm: it had cleanly implemented the Discrete Fourier Transform. (To be clear, it is not as if the neural network had abstractly reasoned its way through higher mathematics; it just found the solution with the simplest structure, which is the DFT.) They also gave a fascinating account of what might be happening behind the curtain as a neural network groks a pattern. In short, a network starts out by memorizing the training data rather than finding a general solution, because the former can easily be implemented with one modification at a time, while the latter requires coordinated circuits. However, once the model reaches diminishing returns on memorization, a bit of regularization will encourage it to reinforce simple circuits that cover many cases: And the natural way to do this is by picking up on regularities in the data - eg, you can memorise modular addition twice as efficiently by recognising that x+y=y+x. Once these circuits emerge, gradient descent quickly replaces the memorized solution with them. The training error decreases ever-so-slightly as the regularization penalty gets lower, while the test error plummets because the circuit generalizes there. To make an analogy: What Grokking Feels Like From the Inside You're an AI being trained for astronomy. Your trainers have collected observations of the night sky, for a millennium, from planet surfaces of ten thousand star systems. Over and over, they're picking a system and feeding you the skies one decade at a time and asking you to predict the next decade of skies. They also regularize you a bit (giving you tiny rewards for being a simpler AI). Eventually, you've seen each star system enough times that you've memorized a compressed version of their history, and all you do is identify which system you're in and then replay your memories of it. For instance, within the first few visits to our system, ...

Music theorist Dr. Jenn Harding joins Xanthe for an analysis of minutes 16-20 of The Empire Strikes Back. We talk about textural shifts, snowspeeder sound design, macroharmony, musical structure, spectrograms, math, intonation, the Leia-Han-Luke love triangle (and what the music has to say about it), and more!  This episode is also on YouTube (with spectogram visuals): https://youtu.be/nnflnU9iecM  Discussion Guide: 00:00 - Hello there! 04:15 - Interaction between music and sound design. 06:54 - How Ben Burtt crafted the snowspeeder and snow sounds. 14:07 - Mechanical-sounding perpetual motion with triumphant trumpet flourishes on top. 22:58 - Weird, angular oboe melody and a massive texture shift. 27:54 - No music during the impassionate kiss. 32:10 - Fuzzball, nerfherder. 35:10 - How Ben Burtt made the Imperial Probe Droid explosion sound. 37:38 - Using math to analyze harmony, intro to macroharmony. 45:16 - How would you define harmony? Harmony (abstract) and sonority 48:15 - Spectograms and discrete Fourier transform (DFT). (Visual demonstration of these Star Wars minutes viewed through the spectogram) 1:02:38 - Quick Tip: Orchestral listening challenge. 1:06:54 - Why does knowing the harmonic landscape of something matter? 1:12:45 - 12-tone scale, interval ratios, imperfect reality of intonation. 1:21:20 - Dialogue causing changes in the structure of the speeder music. 1:27:40 - Imperial March sounds steady but doesn't have the same motor. Accents. Why does the Imperial March sound almost... human? 1:45:59 - SWMM Questionnaire Things Mentioned: Jenn's Visual Pitch Class Vector Calculator: https://www.jenndharding.com/vectorcalculator Jenn's DFT Panorama Generator: http://www.jenndharding.com/panorama Complete Catalogue of the Musical Themes of Star Wars (by Frank Lehman): https://franklehman.com/starwars/. Check out Dominic Sewell's analysis of these cues! 2M2 Ben's Instructions - https://youtu.be/Dh9W98GykGs 2M3 Luke's Rescue - https://youtu.be/UTFX2QjGqzQ 2M4 The Imperial March - The Probe Scanner - https://youtu.be/UZaQDrN7YZU Musical Themes: 16b. Dark Side (Ostinato) 24) Imperial March Vamp 10a. Imperial March (Theme) Cues: Very end of 2M2 "Ben's Instructions" 2M3 "Luke's Rescue" 2M4 "The Probe Scanner" Where are we in the soundtrack(s)?: "The Wampa's Lair/Vision of Obi-Wan/Snowspeeders Take Flight" "Rescue from Cloud City/Hyperspace" "The Imperial Probe/Aboard the Executor" --------------- STAR WARS MUSIC MINUTE QUESTIONNAIRE: 1. In exactly 3 words, what does Star Wars sound like? Adventure. Nostalgia. Romance. 2. What's something related to Star Wars music or sound that you want to learn more about? The sound design and its coordination with the score. 3. What's a score or soundtrack you're fond of besides anything Star Wars? Lord of the Rings (by Howard Shore) --------------- Guest: Dr. Jenn Harding https://jenndharding.com https://twitter.com/dizzyfingers42 ----------------- If you want to support the show and join the Discord server, consider becoming a patron!  https://patreon.com/chrysanthetan Leave a voice message, and I might play it on the show...   https://starwarsmusicminute.com/comlink Where else to find SWMM: Twitter: https://twitter.com/StarWarsMusMin Spotify: https://smarturl.it/swmm-spotify Apple Podcasts: https://smarturl.it/swmm-apple YouTube: https://youtube.com/starwarsmusicminute TikTok: https://www.tiktok.com/@starwarsmusicminute? Instagram: https://instagram.com/starwarsmusicminute Email: podcast@starwarsmusicminute.com Buy Me A Coffee: https://buymeacoffee.com/starwarsmusmin

Chapter 342 - "The Label Brings Me So Much Joy" ...as read by Casey Horrigan of Iodine RecordsToday we welcome Casey Horrigan, founder of Iodine Records to the podcast! I've gotten to work with a bunch of Iodine bands this year and it only seemed fitting to chat with Casey about the label. Casey talks about Iodine's founding, demise, return, legacy, and more.https://iodinerecords.com/Make sure you check out Iodine's killer discography at https://iodinerecordings.bandcamp.com/music Here me chat about Hum's Inlet on DFT's Dungeon at https://www.gabbermedia.com/dft-dungeon/2022/10/9/v9tvbg1bw7gofp2l4daidffiyjxorpChapter 342 Music:Her Head's On Fire - "Burn"Hey Thanks - "This Small Space"OneLineDrawing - "Tenderwild"Stretch Arm Strong - "Second Chances"The Darling Fire - "Rituals"---As The Story Grows links:​Help out at PatreonATSG WebsiteATSG Music and MerchJoin the Email ListATSG FacebookEmail: asthestorygrows@gmail.comYouTube - https://www.youtube.com/channel/UCNuP0_JUpT6DoIhhbGlwEYA?view_as=subscriber 

Join friend and former co host Daniel Terry and I as we do what we always do, talk about any and everything on a podcast. Dan and I get into the weeds of the podcasting process, and how we get excited about the episodes we do, but HATE waiting to drop them when we start stacking content. Dan opens up about deciding to make better lifestyle choices, and how that led to him losing weight, getting sober and finding a new sense of confidence in himself and ultimately why he left Discography Discussion and how that gave way to him going out on his own with DFT's Dungeon. We also talk about meting each other for the first time in person, being there for each other to talk about the things going on in our lives and so much more in this look into our friendship. Intro Music: “Remember “This Night” (Podcast Edit) by Chae Hawk "Pretty Lights" by Heartsick Show Sponsors: Rockabilia (www.rockabilia.com) USE OUR CODE BREWTALLY AND GET 10% OFF YOUR TOTAL ORDER!! The Bean Bastard (www.thebeanbastard.com) On Point Pomade (www.onpointpomade.com) USE OUR CODE BSP15 AND GET 15% OFF YOUR TOTAL ORDER!! Links: Facebook: www.facebook.com/profile.php?id=100083954821061 www.facebook.com/rockabiliacom www.facebook.com/onpointpomade www.facebook.com/thebeanbastard www.facebook.com/brewspeakpod Instagram: @dftdungeon, @onpointpomade, @beanbastard, @brewspeakpod, @jbeatty616 Twitter: @dft9000, @onpointpomade, @bean_bastard, @rockabilia, @brewspeakpod, @jbeatty616 Website: https://www.gabbermedia.com/dft-dungeon www.brewspeakpod.com Patreon: www.patreon.com/brewspeakpod Email: Brewtallyspeaking@gmail.com RATE/REVIEW/SUBSCRIBE!!! --- Support this podcast: https://anchor.fm/brewspeakpod/support

Episode 304 is up and live now with Daniel Terry from the DFT's Dungeon Podcast and many more! Be sure to check out this chat with a badass dude with great stories to tell and a wealth of music knowledge. A good buddy and a great podcaster. Don't forget to rate and subscribe! We are now proudly presented by Equal Vision Records and Sound Talent Media.  @equalvision @stmpodcasts   Love the show? Sign up for Premium Pleasure Http://peerpleasure.supportingcast.fm   Visit the website at: www.peerpleasurepodcast.com   Go Rate, Write a Review and subscribe to the show now on Apple Podcasts, Google Play, Stitcher or wherever you listen to podcasts.   You can now rate the show on Spotify! Please take a moment to do that now if you are streaming on Spotify. Follow the show on Instagram: @peerpleasurepod Follow the show on Twitter: @podpeerpleasure Follow the show on Facebook: @peerppod You can email me at: peerpleasurepod@gmail.com Don't forget to check out our amazing sponsors! Go to distrokid.com/vip/ppp for 30% off your years membership to get your music distributed online everywhere! Thank you DistroKid! Go to Rockabilia.com and enter code “PEER15” for 15% off your total order on band merch now! Go to Hearinglife.com to set up your complimentary hearing evaluation now! @thunderboltguitars @ryderevanrobison.studio @stringjoy @rockabilia @distrokid @hearinglife Music Credits: Opening theme song, "Trans-Am Sunday" by Hobosexual Closing theme song, "My (fucking) Deer Hunter" by Fear Before The March Of Flames Learn more about your ad choices. Visit megaphone.fm/adchoices

This week Charli talks with Tim Merkel about taking pump technology into the cloud Timothy Merkel has been involved in the water and wastewater industry for over 20 years with a focus on building partnerships in the wastewater business with distributors, vendors, and other key relationships across the industry.  He has served as Secretary / Treasurer for the Submersible Wastewater Pumping Association (SWPA) in the past and is currently the Chairman of the Marketing Committee for the organization.  Timothy got his start in the water and wastewater market at Conery Mfg Inc in Ashland, Ohio in 2003; eventually serving as the National Sales Manager there followed by serving as the Engineered Sales Manager at Topp Industries in Rochester, Indiana from 2011-2017.Since 2018, Timothy has served as the Business Development Manager at Metropolitan Industries in Romeoville, Illinois.  Operating out of Ashland, Ohio, he continues to travel the United States in support of Metropolitan Industries including the East Coast branch of Emmons Metro located in Albany, New York.Interview starts @ 7:56Lets Get Social #ManufacturingMonday: DFTDFT® Inc. manufactures world class, problem solving, in-line, axial flow, nozzle style, silent check valves and severe service control valves. DFT engineers design products using the latest CAD, FEA, and CFD design technology software. Our staff responds quickly and our systems are designed to deliver reliably within our ISO9001-2015 quality management system. For more than seventy years DFT has solved check valve problems, prevented check valve failure and water hammer, and solved severe service control valve problems.United for Infrastructure - May 16-20th. Meetups!Don't forget to preregister for them to get the Zoom linkEmpowering Women - Wed, May 11th (every second Wed) at 11 CTMentorship Circles - every 2nd Monday, May 9thBook Club - May 24thEmpowering Pumps – May 17 (every third Tuesday) at 10 am CT Join us on SlackIn the NewsWhat You Need to Know about Check Valves and Cracking PressureHow to Set up Environmental Controls for Pump SystemsYou can always reach us through social @EmpoweringPumps on Facebook, LinkedIn,  Instagram and Twitter and using the hashtag #EmpoweringIndustryPodcast or via email podcast@empoweringpumps.com

This week Charli and Bethany talk about Social Media Branding and how to make your graphics and images stand out.Then Charli interviews Jeff Kane, the Director of Sales and Marketing at DFT, all about his 35 year career in the valve industry. [Interview Starts @25:31]Watch on YouTube!Jeff Kane has been involved in the valve industry and sales for 35 years working for DFT, Deacon Industrial, and XOMOX in positions such as a regional sales manager, sales and marketing manager, and vice president of industrial sales. Jeff has a B.S. in Business Management from East Tennessee State University. Jeff is a long-time member of the VMA Education & Training Committee.https://www.linkedin.com/in/jeff-kane-87a69552/Resources and Links:EPIC - event informationEPIC - Charli's blogGet the digital editionSign up for the NewsletterPerson of the WeekNominate an Industry Person of the WeekEmpowering Women Meetup - Wed. April 13Empowering Women Book ClubEmpowering Women Mentor MondaysEmpowering Pumps Meetup - Tues, April 19Empowering Women PodcastLunch & Learn with VinceCentrifugal Pump Basics: The Importance of Best Efficiency PointCFturbo, Inc. Launches Major Software Updatehttps://empoweringpumps.comhttps://empoweringwomeninindustry.comTwitter | Facebook | LinkedIn | Instagrampodcast@empoweringpumps.comhttp://creativecommons.org/licenses/by/4.0/