All right, thanks to the organizers for organizing this nice workshop. Is the microphone working? Yes. So what I want to talk about is three different projects that I'll try to combine into these 30 minutes. In particular, I'm focusing on developing methods that focus on ideally Appinicio Hamiltonians and specifically electronic degrees of freedom. And so what I specifically want to talk about is, as I said, three projects that cover each of what I think are the big pillars of making quantum-anybody solvers. And that's, you know, eigenstate search, time evolution, and open quantum systems. And then even time evolution within open systems. So let me focus on the first one. Eigenstate search made a lot of progress in the last two years, let's say, or three years on developing new algorithms to look for eigenstates, also specifically for electronic degrees of freedom. And what I specifically want to talk about is, OK, that doesn't work, is about this one new way of optimizing any wave function in continuous space. So if you have an electronic, you want to model some molecules. You have the continuous space Hamiltonian. You want to optimize it in a better way. So what I want to do is I want to recap a bit in my own language how I see imaginary time evolution specifically in this case. The reason I wanted to reformulate this is because, you know, on this, I had the discussion with Marcus Hallow, so he told me, in principle, if you optimize a wave function and you do imaginary time evolution, then everything has to go right. And I'm going to show you that this is actually not the case. There are actually better ways to work than doing imaginary time evolution to optimize the ground state. So what I want to start off from is the imaginary time trading equation first line. So I've just written that out in terms of some wave function. And since we're working with, we have some time reversal symmetry, we have a Hermitian Hamiltonian. So we can actually recast this in terms of real valued wave functions. So I can actually rewrite everything in terms of probabilities. And this is where it gets really interesting because, well, this has worked together with a bunch of machine learning researchers, so Maxwelling, for example, and we have Kirill at Vector Institute, who are pure machine learning researchers. And so we discussed a bit, OK, what is variational Monte Carlo now really? So we can recast this thing of wave functions in terms of something of completely probabilities. So what I have is a continuity equation. And this continuity equation tells me how probability flows throughout imaginary time. What I see there is that as the probability evolves, the evolution of my probability is proportional to the probability itself. And that will be a key factor that is a bit problematic that I'll try to sketch in the next slide also, where the problems really can come from. And then since we're working with a variational model, so we have a restricted variational manifold, we have to project it back onto the variational manifold so we can do this, for example, by optimizing a KL divergence that reprojects this green arrow back onto the manifold. And so that's how we obtain a new set of parameters that have a better energy. So if I can reformulate VMC, what we're actually trying to do, and this is, again, this is the way to communicate with pure machine learning researchers who are not necessarily physicists, is we're trying to minimize a functional, so the energy functional, in a space of probability distributions. And we do that over a variational manifold. Now there are a lot of cases, of course, in machine learning that are very equivalent to this idea. And so the idea is that while you're minimizing this functional, you're following an ODE for your probabilities. And this is an interesting idea, again, because, well, there are some famous examples. So this is an example that I took from a paper of Wasserstein Gun, so if you've been in the machine learning community for a while, there was this very popular generative adversarial networks, I think in 2015 and 2016 or so. They were very powerful, if I'm not mistaken. But they were completely untrainable. If you ever tried to train this, it just didn't work at all until, yeah, I see somebody nodding, yes, until somebody realized, well, OK, what we're actually trying to do is we're trying to take the data images, which are high-dimensional pixels, but they are actually living. The data is living in a lower-dimensional manifold. We have a lot of correlations, so the actual data is lower-dimensional. And so if we initialize a model, this model that tries to capture distributions, we initialize it initially on a manifold very far away from the actual data distribution. So if we do an ethyl experiment, we can think about a distribution that is a single line. So we just have the blue line here. That's my distribution that I'm trying to capture. And the model that I put forward in order to capture this is, well, the same. It's a one-dimensional model living in two-dimensional space. And it's just parametrized by one parameter, theta, that says how far it is along the axis. And so what I can do is I can ask myself, OK, what are the typical kind of distance measures or loss functions that I would typically use? So we all know, for example, the second one, the KL divergence, which measures, gives you a distance between distributions. And if you look at what the distance is for this specific example, again, we're in a two-dimensional space, but the actual data lies on a lower-dimensional, one-dimensional manifold, then you see that the KL divergence is infinite if we have a theta that is not exactly zero, and otherwise it makes a discrete jump. Of course, I mean, you cannot optimize this thing. You will never get actually anything that is close to the result theta equals zero. OK, so of course, in the machine and community, people have thought about this. And the answer came from the field of optimal transport, which knows this kind of problem. They know about the fact that two distributions sometimes don't overlap. And the way that they formulate the distance is, and I'm not going to explain at this point what this means, but they essentially say, try to quantify the distance between two distribution by seeing how much effort, let's say, it costs to transport one distribution into another one. So and indeed, if you compute the Wasserstein distance or the Earth Mover distance between these two distributions, you get something that is proportional to theta. So now this is great, because now I have something that I can optimize. I just, I can obtain theta in the right way. And so what we did is we took this example and we said, OK, let's try to define also, let's look at Wasserstein metrics in continuous space. And this is a bit more complicated way of writing things down. But again, Wasserstein metric, essentially what this says is we have two distributions, p0 and p1. We want to compute a distance measured between them. And we compute some expectation value where we're looking over all the possibilities of how we can transport one distribution, the mass of one distribution to the mass of the other distribution. That is, in broad terms, what this equation says. And then again, if you define a way of what distance is, you typically also get an ODE from that. And so the ODE that you get from that is this on the second line, which is that now we have a continuity equation where the distribution, sort of the probability mass goes not along a term that is proportional to the density already present, but it's rather along a vector field. So we're propagating this idea of optimal transport. We have now a vector field that transports one mass into the other one. I'll show some visualizations later. And then if we try to optimize some functional now with this approach, we get a functional minimizing C Wasserstein approach. And so we can compute what this vector field is actually what it's like, depending on the function that we're trying to optimize, which in our case is the energy. So if you write it all down and again to recap, what we had before was, if we're using in the imaginary time Schrodinger equation, which I can just tell you is an evolution according to the Fisher-Rau metric, we get something that is proportional to density itself. And now what I'm saying is we need to basically add an extra term that can help us to overcome this problem of these different manifolds. And so again, this is another sketch of what I'm trying to say here is what I told you that variation in Monte Carlo is. It's defining a distribution and how it evolves throughout time. And then we do this projection on to the variational manifold. What I've just told you is that instead of taking a Fisher-Rau gradient flow, which is what I would find if I look at the imaginary time Schrodinger equation, I can just define another direction according to another metric, which is the Wasserstein gradient flow. And then I just do the same approach like I did before. I project it back onto the variational manifold. And so what is the difference now between both? In terms of the energy, the left-hand side, I think everybody who has done variational Monte Carlo recognizes this, right? So we have some differences between local energies, but then again something proportional to the existing probability. And on the right-hand side, we now have our different continuity equation. And so on the left-hand side, this is said to be trend. We teleport the same mouse. So the idea is there that, again, because it's proportional, the change of density with the density itself, we can only, it's a kind of sink-source kind of problem where we remove some mass here and then we let it pop up somewhere else. So if we would look at a two-dimensional bimodal distribution, it needs to first overlap with part of the distribution, right? So it needs to already overlap. And then it can reduce and put it somewhere else. And initially, it goes quite fast, but then at some point, it needs to really transport all this mass, and that's when it really goes slow. On the other hand, if we do the same on the right-hand side, and now we don't do this teleportation, but rather make a continuous flow, things behave a bit more nicely. It's now a simulation where, again, we're just following the probability vector field and we nicely match between the two distributions without ever needing to do this teleportation. And so, OK, if you now are curious, I do variational Monte Carlo, what do I need to do in order to implement this algorithm? It's actually pretty easy to do it. It's almost a one-line change. In practice, it's not, but in theory it is. So given that this is my variational Monte Carlo algorithm, I have some samples from a distribution queue. What I do is I evolve, imaginary time evolve my distribution. I project it back to the variational manifold, and I go through this loop again. And I'm telling you now is you can just change this loop, this one item in the loop, and go along a different direction on the probability distribution manifold, but then you just project it back. And so here are some results. It's a bit noisy because it's molecules. So anybody who's done molecules know that these things are noisy. What you see is the blue curve are the energies with the traditional variational Monte Carlo. And then the other curve, so the green one, is purely Wasserstein. The orange one would be like a hybrid version between both, where we take equal amounts according both to both directions. And we see that in all cases, we end up under the ground state energies obtained with normal variational Monte Carlo, specifically in the H10, where you have a lot of multimodality. We consistently go beyond that. You can see this more clearly in the variance. So the variances, if it goes to zero, we know that we're hitting an eigenstate. And you see, for example, on the right-hand side, that we gain almost an order of magnitude improvement with Wasserstein and variational Monte Carlo. So this is a really exciting approach that it's really helping you go. Yeah, you can make it hybrid. It's in every loop, you can choose what you do, right? We didn't optimize that principle, you could, yeah. So yeah, this was together with Kiril at Vector Institute. So this was really exciting work, just from making a connection and sort of trying to explain to each other what we're now actually doing and how we can use the field of machinery and research and the theory from there to improve also our variational Monte Carlo algorithms. Okay, so that was how we can obtain better ground state energies. Now the second thing I wanna talk about is one of the works we've done recently, which is on doing time evolution. And so again, focusing on up-in-issue electronic systems. So for that, I'll, even though I used that in the previous slides in principle, let me zoom into what are the kind of models that we can use for electronic degrees of freedom. And the reason I wanna focus a bit more on that is that for ground states, ground state searches are often easy in a way because they contain not too much correlation. You have a lot of locality, but if you start time evolving things, things that are way more difficult. Correlations start building up, they become longer range. And so your simple approximations, I mean, you can think about tensor networks, okay, they're not simple, but the approximations that you make there once you start doing time evolution, things become, yeah, quite difficult. So in what the traditional way is of parameterizing things in electronic degrees of freedom is you take, the simplest is Harti-Fock, right? So you take a single state determinant, the particles only interact with a mean field. So you have single particle orbitals. We can make those time dependent. We just evolve this throughout time. Again, there's no really correlations that we can include except, you know, sort of interaction with the mean field. The simplest next thing we can do is to say, well, maybe one determinant was not enough, so let's do the same like we did before, just multiple determinants. But with a polynomial amount of determinants, if you go throughout time, correlation start building up, you won't be able to describe anything anymore. The next thing that people haven't done then is to look at just throw factor, so we can make that also time dependent. And the difficulty there is, it handles correlations really well, but it's a bit restricted in the sense that it inherits all the nodal structure from the single determinant as well. So we're a bit limited there. This would be, as if you would do the fusion Monte Carlo on top of a choice, you cannot change where the nodal surface is. So the one thing that I'll show is to use time dependent backflow transformations that we introduced. So you can think of a backflow transformation in easy terms as we have an interacting system and we map the system of interacting particles onto a non-interacting system and then we use the typical Harti-Fock approach. So right, we take the original particle positions, we map into a new set of particle positions that knows about the positions of the other ones and we just take a single state of the determinant and evaluate it. That's how I see backflow transformations. So that's this transformation going from interacting to non-interacting as a backflow transformation. We can make that time dependent again as well. And now we can change the nodal surface and principle describe whatever ground state that we want. And yeah, by making it time dependent now as well, we can also throughout time change the nodal surface and we can accurately capture the states of fermionic systems. And so how do we evolve this thing through time? For that we use, in this case, well, the first slides will be based on that and the other one based on a new approach. But we use a time dependent variational principle and so the idea is there that we look at what is the distance between an initial parameterized state phi of theta t. We do a very small time evolution projected back onto the variational manifold just like I did in the Fisher-Rau approach before. And what follows from that is a linear set of equations where we have theta dot, which is the change of the parameters throughout time. So how I need to update my parameters to move through time. And in order to obtain that, I need to compute what's called the forces of the energy gradients. Can estimate that with Monte Carlo. I do that all the time with in variational Monte Carlo as well. And on the left hand side, we have the geometric tensor, which is sort of the correlations between the gradients of your model. And so for that one, actually, the TIA has a really nice poster on how to do that. So definitely check that out because his method really made it possible to do these things before. For me, at least, it was not really feasible to do that in continuous space. So without going into details, there are a lot of details behind this approach, but I just want to show some results and convince you that what we're doing makes sense and that it works. So on the left hand side, we have the first benchmark case. So we want to compare to a solvable model. So what I can do is I can take one-dimensional fermions, I put them in some harmonic well, and I make them interact with some harmonic interaction.  So you see the monopole, so you see the fermions going out and in based on this driving of the system that I'm doing. What you see is, well, you don't see it, but the exact solution is shown in orange, and then you have the green one, which is the neural network quantum state approach to this, and you see, well, you see no difference, which means that up to long times, even if it's an interacting system, we can actually reproduce the dynamics of the system very well. Then we want to look at a more realistic example, and in quantum chemistry, a lot of people have looked into what is the effect of shining an intense laser on a diatomic molecule. So we simulate the system, and so what happens is just to, well, let's maybe visualize it first, so on the top we see the electric field, and on the bottom we see the distribution of the electrons. We see that as we move through time, the electrons start moving around. So this is shown here, according to the dipole moment, so I'm comparing here with time-dependent Hartree-Fock, with ED within a given basis set, and we typically choose a basis set which also restricts the accuracy that we can have. And so the first thing you can see is that I'm showing in the Astriot-Rigid basis, which is a small basis set, the results of ED, and this is like the smallest green curve. If you're using neural network quantum states in that same basis in second quantization, we can do the dynamics almost exactly the same. We don't see a difference. Now if I start increasing the basis set, so I start looking at a bigger Hilbert space, I'm getting more accurate to the real dynamics, and so what we see again is that the effect seems to be that the oscillations are a bit damped. We see some interference structure on top of it, and then at later times they start oscillating a bit longer. Now we don't actually have to be restricted because we're doing it fully up in issue. We don't need to choose a basis set, so we can actually take a continuous model. It can be a neural network, whatever you want, and evolve that through our time. And you see some, which is now the S plus C plus BF, so the backflow transformation throughout time, and we can actually get really good results that go beyond exact diagonalization in a given basis set. And then the last example I wanna show is the quantum dot. So the idea there is that we take fewer electrons, we put them in a harmonic well, and then they interact with each other through the Coulomb potential. And by changing the properties of the material that this quantum dot is in, we can quench the interaction so we can, it's as if we are modifying the Coulomb potential. So that's this kappa. So we quench this system, so we first look at the ground state, we quench the system, and we look at how it evolves through time. What will happen is again a sort of monopole form on the left, but I'm not gonna show that, what I wanna show is, what is the effect of these backflow transformation and time, well, time dependent backflow transformation. So on the top you see R square, which is the integration error. So the lower the R2, the more we satisfy the time dependent shading equation. And so what you see is the S mean such the single state of the term and then in blue, I add a adjuster, a time dependent adjuster to it, and then finally a backflow transformation. And you see that as we evolve through time, the accuracy improves by an order of magnitude so we can really using time dependent backflow transformation can get accurate results. And I wanna tell you also always that in dynamics, it's mainly the correlations that are important and I just wanna highlight that by looking at the G2. So the G2 is a quantity that looks at correlations and it's zero if you have no correlations. So indeed the green, we confirm this by looking at our single state of the term and there are never correlations. And what we observe is if we look at just through unbackflow correlations, that indeed in very first few time steps, a lot of correlations build up and then they dominate the rest of the dynamics. So you cannot even simple approximations will typically break down at the initial few time steps. And then this is with another method that it's not on the archive yet so I didn't wanna show the approach but it's a new approach of the dynamics and it's specifically shown now for a simple model. It's a spinless fermions that say, so fermions interacting via the TV model. So we have some hopping terms and a nearest neighbor interaction term. And again, what we do is we look at three fermions and then we quench it and make them interact with each other so it's like changing the medium. And what we see is you see the different kinds of lines. The S again corresponds to a single state of the term and so things start deviating quite rapidly compared to ED. And on the bottom plot, I show you the infidelity from step to step which is also the lower the better. And you see that way again with backflow transformation, time dependent backflow transformations you can get essentially any accuracy you want. And then finally, this is a bit of a different topic but I'm still enthusiastic about what we did there so it's not necessarily fermions but it would be cool to extend this also to fermions. It's the idea of now doing the same like before looking at quantum dynamics but seeing what the effect is of putting things at a finite temperature. So the first thing we do is we prepare a thermal state. So how do you prepare a thermal state? Well, typically that's done through something which is imaginary time evolving. So the idea behind that is that if you write down what a thermal observable looks like we have and we rewrite things a bit we get this sum over n which is the Hilbert space and we evolve an initial state just a basis state over an imaginary time beta over two according to the Hamiltonian that we're considering. And so there are multiple different approaches to do that. So there are some popular techniques and the first one is just to take this formula as it is and to sample indeed initial sample basis stays in my Hilbert space evolving them over beta over two where beta is the inverse temperature and just doing this multiple times and then the TPQ theorem tells us that as the system size increases we actually need exponentially few samples to do this. And METS is another project commonly used for tensor networks and there is a sort of same idea but you do a Markov chain version of it, let's say.  Now with neuronetic quantum states we preferably don't do too many time evolutions because it's honestly expensive but what we can do better than these other methods is we can better handle correlations, right? That's the whole thing about neural networks is in principle they can handle volume law entanglement. So preferably I take something that is different than these approaches but something that can actually go through highly entangled states. So what we do is we think again about what a thermal observable looks like. And so we look at the stress and what we can also do is instead of sampling over these states and evolving them through time it's rather to introduce an auxiliary system that takes the effect of tracing out the money, generating this trace. And so the idea is that we introduce what's called thermo field doubles. So it's essentially as if you would take the density matrix, you have the rows, you have the columns, the thermo field doubles would be sort of the columns. These are the column samples. And so what this equation tells us is that if we start from the identity state, so again in terms of density matrix it's just the identity matrix, the diagonal matrix, if we now evolve it over beta over two according to Hamiltonian that only operates on let's say the rows, then we will actually be able to compute thermal observables. And so what we need to do in order to start this evolution is we need to start from the identity state so the infinite temperature state which is basically a set of product states where we pairwise entangle or spin systems which is the one that we consider in sigma which are maximally entangled with an additional auxiliary system, the thermo field doubles which again are these columns of the density matrix. So the first thing we need to solve is we need to make sure that the neural network that we evolve through time can exactly represent this initial state. And so yeah we have multiple ways of doing that now but I don't want to necessarily show about how well we are preparing thermal states. I want to show that the next cool thing which I like even more which is now once we've prepared the thermal state is that we can also quench it and look at quantum dynamics of it. So the first question we have is okay we have a thermal state now I've introduced these thermal field doubles. What is the Hamiltonian that we need to evolve over? So if you do the math, simple math but you get in the end something like this so again what I'm doing is I'm looking rather as an open system but I'm just rewriting it as a unitary dynamics within this doubled space. And so the Hamiltonian that I need to evolve over is my Hamiltonian applied to the physical system minus my Hamiltonian applied to the unphysical system. So again I just use the same machinery that I used in the previous slides on doing quantum dynamics for electrons and I just evolve this thermal state through time. So here are some results on the four by four and the six by six transverse field ising. So what we've done is we create the thermal states of the transverse field ising and then we quench it with the longitudinal field and we break the symmetry. And so the left hand side is the ZZ correlation, YY correlation, YY is just very difficult in Monte Carlo approximations because it's a cancellation between over diagonal terms so it's one that we really wanted to get right. And so by introducing a new way of doing imaginary time evolution which we call PITE, I won't discuss the details but check out the paper. It's a really stable method that allowed us to do this otherwise it wouldn't have been possible. There was some work on this already before also from Yusuke Nimura who was able to do the imaginary time but then if we really wanted to do the real time after we needed to do this way more accurately like with a higher precision than was available before. And so you see that we can accurately reproduce so we're comparing it to METs that we can run for these four by four systems. We can actually reproduce those results once we've evolved through imaginary time. We pick out some of the beta values and we quench it in the real time and that's what you see on the right hand side is the observables, the thermal observables throughout time and you see that you don't see that clearly but the effect of the temperature seems to be in it that the oscillation sort of get damped a bit for higher temperatures. So some nice side products of this project is that we have a new way of representing physical density meter so avoiding that we go outside the space of physical density meter specifically we found a new way of representing thermal states which you call Arno as a thermal states free or autoregressive model so if you wanna study topological states and see the effect of temperature on topological states this is the way to go. So if you like that kind of stuff read the paper. We can actually represent now any neural network quantum states as a thermal state so we're not only restricted to previous work that just used RBMs. And the last one is as I mentioned the only reason that we actually were able to do this is by inventing a new way of doing imaginary time evolution which is based on this sort of convolutional sampling by optimizing fidelity. So again, won't give the details just wanted to flash it so if you're interested so you would read the paper. And I'll finish there. So just to recap what I've shown you is three sort of related projects but I found this is the role a bit related. The first one is a new way to do imaginary time evolution. Well, something different than it but to look for ground states a new way of doing variational Monte Carlo. The second one was to look at quantum dynamics of Appian issue electronic Hamiltonians and the last one is to accurately model quantum dynamics of thermal states and stop there. Thank you. Questions? Maybe I can start. Once you perform the backflow in the determinant why do you need also the just throw factor? You don't need it. You can also absorb it. It's just something I always start from that one and then I add the backflow to it. It's just a more, it's often a more efficient way of capturing things but you can choose like we also did the electron gas and there we don't even need a just throw factor. But in principle you can in principle you don't need the just throw factor. Hey, so to combine your two topics of interest what would it take just a speculative question? What would it take to do fermions in real space for finite temperature? Because that's what a lot of condensed matter physicists care about. And you know, if you can show some phase diagram of a decent number of fermions as a function of a temperature using ab initio methods ally and QS that'd be really cool. Working on it and yeah, so I have a method now based on some of these topics that I've introduced that will actually allow you to do that but it's not an easy one because they're in continuous space. The first question you have is how do you represent the infinite temperature state, right? So the first thing you need to do is find a way around that. But yeah, good question. Yeah, yeah, this is McLaughlin. So it depends like they all combine to the same thing if you're looking at holomorphic functions. So some of the results here were actually with holomorphic neural networks. So then it doesn't really matter. So McLaughlin is a nicer one. Some of them just don't respect, for example, energy conservation. So it depends on what you're after. For me, McLaughlin makes most sense. It conserves the energy in principle. Other questions? Maybe we can say thanks again to the speaker.


is that there is no question that there will be a challenge to the coming administration in the arena of infectious diseases both chronic infectious diseases in the sense of already ongoing disease and we have certainly a large burden of that but also there will be a surprise outbreak but also there will be a surprise outbreak. The other thing I'm curious about you know we keep hearing that the virus is going to dictate the timeline. Dr. Fauci has said that. Dr. Fauci has said that. When you look at this virus Dr. Fauci has said that. I'd like to call to order this secret conclave of America's media empires.  Well I think NBC you are here to listen and not speak. I think we should go with a good old-fashioned public health care. A new disease. No one's immune. It's like the summer of the shark except instead of a shark it's an epidemic and instead of summer it's all the time. This can't be a made-up disease. We do have something we've been holding on to but it hasn't been tested. Get over here NBC. We certainly believe in testing but I oh oh oh. Wow wow oh yeah. So we've got our deadly disease. Now we just have to blame it on something that's in every household. House cat flu is coming people. The center for disease disinformation predicts with some degree of probability that the house cat flu might spread in the following hypothetical outbreak pattern. About how things work. When I woke up here I'm breaking the ceremony for a new factory. Did you mention seeing anyone who was sick? Anyone on a plane? The airport? She said she was jet lagged. The average person touches their face three to five times every waking minute. In between we're touching doorknobs, water fountains and each other. Matt. No no I go up to your room honey. So we have a virus. No treatment protocol and no vaccine at this time. We had a seizure this morning Beth. She had the flu before. No no no. As of last night there were 32 cases.  Right. Can I go talk to her? Mr. Muff. Your life is dead. What are you talking about? What happened to her? What happened to her? Is there any way someone can weaponize the bird flu is how we're looking at? Someone doesn't have to weaponize the bird flu. The birds are doing that. Watch this. It's transmission. So we just need to know which direction. On day one there were two people. And then four and then 16. In three months it's a billion. That's where we're heading. They're calling out the National Guard. They're moving the president underground. People will panic. It will tip over. The truth is being kept from the world. Cook your samples. Destroy everything. Hello. I need you to get me the names of everyone who service this room. It's an emergency. You can't do that now. I'm gonna get you home. I got people too. Dr. Cheever. We all do. Don't talk to anyone. Don't touch anyone. Stay away from other people. We're not safe. It's figuring us out faster than we're figuring it out. It's mutated. Storm started. Something happened. His face. His eyes. Different. The infection is everywhere. The virus is harvesting. What do you mean? It's a business. The scientific


I'm Brian Astley. I'm 25 years old. I'm from Pasco, Washington, and I was invited to hunger generation by Solomita. When I came to church it was, I was uncomfortable. It was overwhelming. But the more I came, I felt more, I was more comfortable being here and it's, everybody here is welcoming. My life before I came to church was, I started using drugs and alcohol when I was 14 years old and until, and used until I was 20, 25 years old. When I started using drugs at a young age, I went through life. Everything I did was about getting high or drinking. Things would go good and then they would take, and then they would take a step. I would take steps backwards. I graduated, I still graduated high school on time. I went to college right after, or two years after I got out of high school. I had a full-time job while using drugs the whole time and it just got to the point where it was overwhelming. Trying to manage my life while using drugs and do all that so I quit going to school and quit working. And that's when I got into meth and heroin. My life got way worse from there. Growing up I never had any, I had a father that lived here in town. He was never in my life. He wasn't there to guide me through life when I needed him the most and so my drug use got worse. It was the way I coped with everything. It was the only thing I knew. It was the only thing I knew to do. I was unhappy. I always had a feeling inside of me that I knew I was doing the wrong thing. But I continued to do those wrong things because that's the only thing I knew. And then in 2014 I went to treatment two times in a year. The first time I got out I got out and I continued to use. And then I ended up going back eight months or so later and that's when my life started to turn around. And I had friends that went to church had religious backgrounds but I never really knew anything about it. The second time I went to treatment was when I realized it. And I actually accepted the fact that I needed something, I needed a higher power. I needed something greater than myself that would help me go through life more at ease. Before I went to treatment the second time I knew that I needed some type of help because I was an unhappy person and the drugs were taking over my life. And I had, within a month and a half span, I had OD'd on heroin four times. One of the times I OD'd luckily there were people around me that were able to bring me back to get me breathing again. And then I got a DUI and I got a DUI because I overdosed on heroin while I was driving. When the cops showed up they didn't think they were going to have to book me into jail because when they showed up I was pronounced dead. And the next thing I knew was I was waking up and getting put into an ambulance. Ambulance and I went to the, they took me to the hospital. It was a few weeks later that I ended up going back to jail and I was talking to the officer that took me in and I was talking to him and telling him how I just got. I was just in there a couple weeks ago for a DUI because I overdosed on heroin. And he was shocked because he remembered that and he asked me if that was you. He said that Benton County didn't even think that they were going to have to book me into jail because when they arrived I was pronounced dead. It was from all that stuff that, I had some type of, you know, the spiritual side came out.  From then on I kind of decided to take a step forward and accept Jesus into my life and just see what it was all about because I had no idea. Since I've been coming to church and getting more involved with reading the Bible and just coming to church, my life has been a lot better. I went from not being able to get a job just months ago seeing, you know, I saw hope but I knew it was going to take, I thought it was going to take a long time. Just recently I got my full-time job back. It's working for a family, my family's company and that was, to me that was, you know, that was a big step just because my, it's working for my dad and he basically gave up on me because all of my past experiences he, you know, there was nothing was ever changing. It was always going back to the same thing. I was trying to get clean and then I would go right back. And so to me, you know, it's, it feels good to know that, you know, the most important people in my life, my family, see a difference in me and especially my dad because he wasn't a big part of my life and it was, there were times where we didn't speak for six months. There was a time where it was close to a year that we never spoke and so it feels good to have that back in my life. And I feel like a lot of it is due to me accepting Jesus into my life and being a lot more at ease and okay with things, with everything that goes on in my life. Everything that I had done before, up to now, it doesn't really, it doesn't make a big difference. I feel a lot more at ease now that I've been coming to church and accepting Jesus in my life because I know that my past is over with and I'm able to move forward in it. I just, I have been able to accept the fact that that's not who I really was. Today I'm getting baptized to show people and the public that I made a decision to accept Jesus in my life and as a follower of Christ, my goals are to walk with the Holy Spirit. I'd like to help people that don't think it's possible for them to have a better life, that it is possible because of my past and just to be an example that no matter what you do, God forgives you for everything that you've ever done. We are excited to see people's lives being changed for Jesus Christ, amen? And this is what church is all about. Seeing people like Brian gives their life to Jesus Christ and today publicly stand before the whole world to declare that I want to serve Jesus Christ with all my life, amen? Are you excited church? Put your hands together for Jesus Christ. Now Brian, do you believe in Jesus Christ as God's Son and your personal Lord and Savior? Yes, I do. Do you promise to follow Him with good and clear conscience for the rest of your life? Yes. Now based on your faith, confession and your commitment, we'll baptize you in the name of the Father, the Son and the Holy Spirit.


Good morning everybody. You've survived work camp. Congratulations. It's been a great weekend, hasn't it? Awesome. Can you guys hear me okay? Yes. This is about as good as I can do, but hopefully I can project well enough to get you guys into that. Yeah, so my name is Nathan Ingram. I'm the host at iThemes Training. We do two or three live webinars a week on all sorts of WordPress topics from business development to code to blogging to SEO, all of those things. Kind of like being at work camp all year long. Most of those webinars are free, by the way. It's pretty awesome. I also have a small agency in Birmingham, Alabama where I'm from. I work with clients, small business nonprofit professional firm, and I also do coaching with WordPress freelancers. So what we're talking about today is the challenge of change. How to thrive in the new world of WordPress. Now, you know, they say it's your first slide really ought to get people's attention.  Hate it. It's going to ruin my business. These are words that I said to a friend back in 2008. I was actually talking to that same friend as I was preparing this talk, and we were called that conversation. I started in web development in 1995. So when it comes to the web, I'm a geezer. Anybody been around that long? So really, the web was just taking off. I started out using a piece of software, and for you old timers in the room, it was called Hot Dog. You remember Hot Dog? Hot Dog. Wow. Okay, this is great. So Hot Dog was a glorified text editor that was created by a company in Australia called Sausage Software. It was awesome. It was the best thing around. And then, hey, we then got Netscape Composer, which was the visual. You remember this, right? You paid for Netscape in those days. You paid 50 bucks for a browser. Then I spent a very short time in Microsoft Front Page. I don't like to talk about that. It's a pain for me. Then moved into the macromedia world in later Adobe with DreamWorks and some fireworks and those sorts of things. So I've done it all, kind of took the whole trip on evolution of software. And over the years, I was able to build, gratefully, a pretty good business. I had a few excellent clients. My business was really based on fewer clients, large monthly retainers, $500 to $1,000 per client, typically. Because back in those days, if you wanted to change your website, what did you have to do? Call a web guy. We want to change our picture. We want to change one sentence on the About Us page when you change the business hours or the phone number. So you have to call the web guy, and the web guy has to update the website. Now, that work was awful. It was drudgery. I hated it, but it was good money, right? Then the CMS revolution happened. Content management systems. And all of a sudden, my clients started to want to edit their own website. How many of you are around back in those days? All right, so this caused a real problem for me. My response was suspicion and fear. WordPress is going to ruin my business. I'm not going to be able to charge these high-dollar retainers to clients anymore. But then I realized, you know what? I have to change. Or the web is going to leave me behind. So it was around 2009 or so that I found iThemes Training, which was then called webdesign.com. And I learned WordPress over a matter of the next few months from webdesign.com.  One of my largest clients was ironically a hair salon in Birmingham. And this client I was doing some IT work for. I was their web guide. I did some photography. And back in those days, I'd do anything to bring in money. So if you guys have lived through that, part of the work here, right? So I walk in. And how many of you remember what was happening in the business landscape in 2009? Those were bad years. I walked in to that client expecting just to fix a couple of problems and leave. And I left without the job anymore. In that one 10-minute conversation with the owner. It was sad about it, but had to let me go. I lost a third of my income and the health insurance for my family. That was a bad day. I walked out of there. And I remember I parked at the far end of the parking lot. It was a large parking lot. I tried a long walk back to my car. And I remember saying to myself these words, I will never let this happen again. Never let this happen again. So I was already kind of in motion for change. But I was afraid of it. This little push made me change. It was time for innovation. Over the next year, I changed to a new business model that was based on WordPress and website management contracts. Now WordPress is awesome. But it needs somebody to watch over it to keep it running well. We all know that. So what I realized was that if I took on more clients at a lesser dollar, I ultimately became more profitable. Because now clients could manage their own websites. And I get less support requests doing things that I hated to do anyway. And I'm starting to make as much money as I was before. Because more clients, same amount of money, less work. I mean, what's not to like about this, right? And also I'm no longer beholden to one single client anymore. I don't change well. I was forced to change. And sometimes that's the best change at all. Because my business started to grow faster than it ever had before. And this is sort of the big idea of the talk today. Change often begins with suspicion and fear. But it results, many times, in innovation and growth. Now I've been all WordPress since 2010. I've seen a lot of changes in the WordPress landscape since that time. But we are entering into a period of transition in the WordPress ecosystem unlike we've ever experienced before. Because Gutenberg is coming. How many of you know what Gutenberg is? How many of you knew what Gutenberg is before this conference? Okay. Gutenberg is a completely new approach to creating content in WordPress. And the question is, why? Why do they have to change WordPress? Isn't it good enough the way it is? We love WordPress. Why do they have to change? Now I have a confession to make. I'm something of a history nerd. Does anybody else share that proclivity? Okay. All right. So what I want to do, if you will indulge me, is to give you a brief history of WordPress. Because it's important to understand where we've been so that we know where we're going. How many of you have been using WordPress at least two years? Raise your hands. Keep them up for four, five, six, eight, 10, 12, 13. Give me 11. 14? When did you start using WordPress? 2004. 2004. You were in on the ground floor, my friend. You should get a T-shirt or something. I'll post it at a camp like this. Okay. So we're going to go back 14 years to the beginning of WordPress, which started with this blog post. A blog post on Matt Mullenweg's blog on January 24, 2003. This kid from Houston named Matt Mullenweg had a blog where he liked to share photos. He was using an open-source software back then that was called B2 Cafe Log, and he was frustrated about the lack of functionality. Now, if you look at this line right here, it says my logging software hasn't been updated for months. Logging is web-logged, which became blog. And the main developer has disappeared. I can only hope that he's okay. You can actually go there. If you Google this, it's all there. All the old comments, the whole thing, it's all there. So this was January 24, 2003. So Matt started coding himself. What should I do? And this article, by the way, wraps up with this incredible statement. Well, it would be nice to have the flexibility of movable type, which is a big CMS back then, the parsing of text pattern, the hackability of B2, and the ease of setup of blogger. Some day, right? The comment popped in the next day from a developer named Mike Little. If you're serious about forking B2, I'd be interested in contributing. I'm sure there are one or two others in the community who would be too. This reply is the beginning of what is now 30% of the internet. Isn't that amazing?  It's pretty interesting. Your WordPress 1.0 was released January 2004. Beautiful, isn't it? Yeah. That's WordPress 1.0. It had a new SEO-friendly URL structure in multiple categories. You could post pictures, you could post text. Very easy to use. A few months later, 1.2 added this new thing called plugins back in 2004. WordPress 1.5, came about a year later, added pages and posts to WordPress. Phenomenal. It's something that still confuses users to this day. What's the thing? What's the code? All right. 2005. WordPress 2.0. Complete overhaul to the interface. Lots faster. It's running on Ajax now to perform certain tasks. WordPress is starting to grow up. To WordPress 2.3 in 2007, WordPress is checking along. Not many. Huge improvements, but 2.3 adds tags. Which also confuses users to this day. Why categories? Why tags? There's a reason. WordPress 2.5, major upgrade. WordPress team collaborated with a design firm to totally overhaul the user interface. They added a beautiful dashboard. It's really the foundation of how we use WordPress today. Also, this introduced the one-click upgrade for plugins, which is just huge. The other big thing that 2.5 brought in was this. How many of you could use this today? We know exactly what it is. It's the Tiny NC editor that we used today in our blog and WordPress as it stands today. 4.9.5-ish of where we are now. That came back in 2008. Ten years ago was when TinyNCE was introduced into WordPress. This visual editor. Now, let's get forward 5.5 years. It's now 2013. A lot has changed with WordPress under the hood. But the editor interface is virtually the same. It's still TinyNCE. Now, 3.8 brought in this mobile-friendly stuff so you could now do your blog on your phone. It's fantastic. This is essentially the same design that we see today in WordPress. That was 2013. That's a geological epoch in web years. WordPress 4.9 dropped in November 2017. Four more years forward. The interface has cleaned up a little bit but it's virtually the same. But for 14 years since WordPress 1.0 there's one major thing that has never changed. You know what it is? You type your stuff in the box. WordPress 4.9 You type your stuff in the box. It's still the same thing we use today. It's not very hard to use but oftentimes what you type in the box doesn't really look like what you get on the front end of the website. The fonts aren't right. The sizes aren't right. You can't make columns without using an add-in of some sort. We got this quirky thing called a shortcode which we're using to this day. It's a necessary evil but it's clunky. It is what it is. WordPress 5.0 is coming at some point this year. And this is what it's going to look like. It's a big box but it's a lot different than what we're used to today. This is Gutenberg. It's a completely new approach to add-in content in WordPress. Everything is a block. Paragraphs are blocks. Headings are blocks. Images are blocks. Lists are blocks. Galleries are blocks. Photos are blocks. Embedded media is a block. How many of you have tried Gutenberg so far? Interesting. It's demo time. Somebody made a really great flat icon of Gutenberg, isn't it? We're going to do something that I hate to do which is flip out of PowerPoint and into a browser so the world may come crashing down but this is live so we'll let you our best. We're going to mirror our screens and hopefully everything is going to work. Okay, that's amazing. Now this is a really great website called TestGutenberg.com This is something that Automati put together. This is the back end of Gutenberg on the front end of the website. You can play with this by the way, you can also today on your WordPress site download and activate Gutenberg as a plugin just don't do it on your website because bad things might happen. Probably not but it could. It's still under development. So here's Gutenberg and let's go to the top here. Now notice as I'm hovering over things see things are highlighting. There's a block. Here's another block. A lot of text with an image. Here's a pull quote. It's a block. Each of these things operates independently. It's a nice clean interface. If anybody has used Medium or Squarespace or some of the other editing platforms out there they're a lot easier to use than WordPress. They just are. This is a step in the direction of making WordPress easier to use for the average person. Now click on the title you see the permalink up here which you can edit. You can change all these things around. Here's a cover image where you can drop in an image and type on it in WordPress. How about that? When you click on a block some context sensitive stuff appears over here in the margin. So you can change this to fixed or you can change the brightness of the background. You can move the text around. You can do all the stuff right from within the WordPress editor. Wouldn't it be nice just to change the size of text in one paragraph without having to dink around in CSS? We click on a paragraph. Look, we have the ability to change the size of just that paragraph. You have the ability to turn on and off a drop cap with a toggle. Change the color of this text with a click. You can change the background color. All this is in Gutenberg today. You can download it as a plugin. At some point later this year they will take the code in that plugin and merge it into WordPress core. Images work like blocks. This is a paragraph block with an image over here. We can make the image go left or right like today. Or we can pull it out of the paragraph and see what's worked the same way. Let's say we want to move this block quote down. Just click the arrow and now it's moved down one. The blocks simply stack on top of each other. Now, there's a lot more here. I don't want to spend a lot of time on this. I want to encourage you to install Gutenberg or use testgutenberg.com to play around with it. There's a lot to learn here. The first time, I'll be deadly honest, the first time I played with Gutenberg was October of last year. It was awful. It has gotten so much better since then. The UI has improved dramatically. There's a lot of fussing about Gutenberg. But they're developing this revolutionary editor in the public. So you're seeing the sausage made. Sometimes good things happen. Sometimes bad things happen. How many of you develop sites for clients? How many of you would like your client watching you as you built their site? That's what the Gutenberg team is doing. So this is really great. Now, on the back end, again, you can install Gutenberg as a plug-in. And when you do, it's active. I'm going to add a new post. And we're in Gutenberg. Just like this. There's documentation here. And there's a fantastic little feedback form that takes you to a response system. So the WordPress team that's developing Gutenberg wants your feedback. But please give constructive criticism.  Let's talk about that. Right? They want you to be part of the process. So respect that. We're kind of a great community. They want our input. So let's give it to you. The gallery, by the way, is fantastic. Look at this. It does this automatically. It figures out how many images are there and is it going to be two columns or three columns or whatever? And it just works all this stuff out. So many fantastic features. I'm going to jump out of this now for the sake of time. But I encourage you to play with Gutenberg yourself because there's a lot to like about what's going on there. How many of you are excited about what you just saw? How many of you are terrified about what you just saw? The response of the WordPress community to Gutenberg has been about like this. What about my site? What about page builders? How many of you are using page builders? How many of you are wondering now what the heck is going to happen to my page builder with Gutenberg? What about this certain plugin or that certain theme? Suspicion and fear. Why are they doing this? What's going to happen to WordPress? Did they have to change everything?  It's going to ruin my business. Change always begins with suspicion and fear. People typically don't like change. Gutenberg has certainly brought it to the WordPress community. But it's not the first time that a Gutenberg change has brought suspicion and fear to the world. And so if you indulge this history nerd a little bit longer, I think the perspective would be worth your time. Gutenberg sometime around 1400 in Germany. Gutenberg came from a middle class home. The middle class was just emerging out of the middle ages at this time. His father was a goldsmith. It would have been hard to get your mind around the fact that this little kid growing up in a very typical home in a very typical town in Germany would make the impact that he did. But if you Google Gutenberg, you'll read something like this. Johannes Gutenberg's printing press is perhaps the most important invention of the last thousand years. Likely without the printing press there would have been no renaissance, no industrial revolution, no technological revolution, no modern western democracy. In other words, no modern world. Now what you may not know is that Gutenberg didn't invent the printing press. The Chinese did. A thousand years before. Gutenberg didn't even invent movable type. The Chinese beat into that a few hundred years before he was born. Now here's the problem. Chinese has over 10,000 characters. Can you imagine making 10,000 little blocks? English on the other hand, in many of the European languages with 20-something characters fit the idea of movable type and made it a lot easier. So 15th century Europe that Gutenberg was born into was emerging from medieval times. There was this growing literacy in the middle class. They were frustrated because books were incredibly expensive. They had very limited access to written materials. And up until then, books had to be copied by hand by scribes. Many of whom were monks who considered the copying of literature not only a trade to be mastered but a sacred responsibility. Now Gutenberg was born the son of a goldsmith. He grew up mastering the trades of engraving and smithing and he became something of a successful businessman. So with the growing demand for books, little Johnny Gutenberg realized that there's money to be made here. So he sets out to solve this problem and experiment with a bunch of different printing methods. Now Gutenberg started with the proven methods of the Chinese that come up with. He used an oil-based ink that had been perfected in China but then he incorporated a screw press that had been created by farmers in Europe for pressing grapes and olives. Now what came out of that was a press that would actually work but the biggest innovation that Gutenberg brought were these letter blocks. Letter blocks that were precisely engraved and cast and they could be fit together with these little grooves.  Now letters were placed in a type case like this. Here's a bit of trivia. The capital letters were placed in the upper case and the smaller letters were placed in the lower case. Exactly right. So it took a while to assemble a page letter by letter but once it was done you could take that block of text and print many pages with it and once you were finished you could pull the pin out and empty your letters back and you haven't wasted anything. It was brilliant. A page of type could be emptied and reset for the next page without really any waste whatsoever. So words spread quickly from Germany across the continent about Gutenberg's remarkable machine. Now unfortunately Gutenberg's story does not end well. Gutenberg dies penniless having lost all of his savings in a legal battle with his partner. There's a whole other talk there. But his printing system became a commercial success. It changed the world. Historians say the printing press again one of the key factors in the explosion of the renaissance. At least half a million books had intercirculation by 1500 from classical Greek texts to Columbus' account of discovering the new world. And all this access to all this literature and standard works of science really sparked creativity across the western world. Now 500 years later we look back on Gutenberg's press as an amazing, amazing advancement. But not everybody in Gutenberg's time was as impressed. As a matter of fact, the response was mixed. In 1501 Pope Alexander VI threatened to excommunicate anyone who printed anything without clearing it with the authorities. And he was right to feel threatened because during that time books published by Martin Luther and John Calvin in the 1530s sparked the Protestant Reformation. In 1540 Copernicus published his theory that the earth revolves around the sun and not vice versa which challenged everything. It's definitely not the view of the established powers. Now there was also another outrage in the religious community and to some degree the community at large because the acceptance of the Gutenberg Bible meant the replacement of an entire cottage industry of monk scribes who had, you know, this whole industry had grown up supporting their work. The efficiency of the printing press meant that roomfuls of monks were put out of work and what maybe was the first technological layoffs. And there's also this story about a group of French monks going on strike and taking to the streets of Paris because of the Gutenberg press. It's amazing. Even the general public to some degree was skeptical of the new technology. Apparently the uniformity of the columns and copy of the Gutenberg Bible was so mind blowing to people that they concluded that there had to be some kind of magic involved. It's recorded that the printer's apprentice of the day was called the printer's devil. This actually became the prevalent thought in France during that time and Gutenberg's business partner the one that sued him and took all his money his partner is actually the one that published the Bible and he was actually tried for witchcraft in Paris. Change often begins with suspicion and fear. Even though the Gutenberg press was greedy with deep skepticism by many looking back we know the impact that it had and even just a hundred years later the British philosopher Francis Bacon wrote that printing gunpowder in the compass were three inventions that changed the appearance and state of the whole world. Our own Mark Twain said what the world is today good and bad it owes to Gutenberg everything can be traced to that source so not only did the press foster the spread of new ideas but new skill sets and new markets were developed it became this growing need for writing and content creation for typography type setting editing, whole new distribution channels were created for printed material a whole new industry based on the trade of information was begun because change often begins with suspicion and fear but it usually results in innovation and growth. Now what does this mean to WordPress? What's going to happen with WordPress Gutenberg? I have no idea only time will tell but my suspicion is that Gutenberg might just spark a Cambrian explosion of innovation in the WordPress space it's going to be much easier for the average person to create rich content in WordPress Gutenberg is going to bring a whole new set of tools to WordPress developers we're finally going to get much closer to that Lizzy Wig editing experience where what you see really is what you get not in Georgia font no more need for short codes easier access to advanced features renaissance for WordPress I mean we're already at 30% market share how much bigger could it get what we may see is an explosion of new websites and new content as a result of the WordPress mission to democratize publishing I'm excited because we get to be a part of it you get to be a part of it as a WordPress user so let's spend the last couple of minutes here on what do you do what do you do to thrive WordPress the first thing I would say is get to know Gutenberg again testgutenberg.com play around with it put it on your test site if you don't know how to set up a test site ask your host they can help you Gutenberg isn't bad it's different it's different and it's not finished yet so again add your two cents with helpful critique it will be coming at some point later this year now if you are a website owner or you're a do-it-yourselfer here's my advice to you make sure you're going to be compatible with Gutenberg the way you do that is look at the theme that you're using talk to your theme provider look at their website read their blog reach out to support and just ask them if they're going to be ready for Gutenberg now you can expect a lot of Gutenberg compatible themes to be rolling out very soon if you have a developer talk to them about it if they don't know what Gutenberg is find another developer and if you don't have a developer look around here that's what this event is about if you are a WordPress freelancer or WordPress business owner look at your theme and plugin stack make sure you're going to be compatible if you're using older if you have older sites that are using older things and plugins make sure you're following the theme and plugin developers on social media their blog if they have one just look at everything you're using and see what those developers are doing to prepare for Gutenberg especially any plugin that uses a short code or puts a meta box in your page or post you want to look at that because all that's going to change make sure those themes and plugin developers have a plan for that my current plan about half my time is still spent doing client work my current plan is to use a plugin called Classic Editor for my two cents the biggest issue for me as a person supporting clients is not technology it's training because that's going to scare the daylights out of some of my clients that are editing their own WordPress sites so what Classic Editor does once Gutenberg rolls out back to that Classic Editor you can hide the entire Gutenberg everything with a single setting again it's called Classic Editor Gutenberg is still there it's just not on it will be on by default most likely when WordPress 5.0 comes out so I'm going to do that for a few months we're going to let the dust settle and then slowly client by client we'll sort onboard people into Gutenberg that's my approach you take your own the last thing I'll say is look connect to the WordPress community events like this are awesome they go on all the time Atlanta is next week work camps happen all the time you want to know people in the community so that if you're freaked out about Gutenberg or if you're wondering how to handle X, Y, or Z you have other people to talk to why is it that WordPress has grown so dramatically why is it that it's bigger than Joomla bigger than Drupal bigger than everything else why is that because of things like this happening all across the world every weekend because we have a fabulous community fabulous community of people who support not only the software but each other how many of you made a friend talk to somebody who knew this weekend that's what it's about right so join the meetup go to other word camps talk to other people about what they're doing and what they're experiencing join me on I think it's training two to three live webinars a week several upcoming on Gutenberg by the way so we'll wrap up change often begins with suspicion and fear don't stay there because change usually results in innovation and growth and I for one am really excited about what this year holds for the innovation and growth of WordPress my name is Nathan Ingram you can find me at training.ifings.com we're on Twitter at Nathan Ingram


I think it all starts with the amount of information that's going to be available or is available already. And all of that is driving business decisions in real time. The challenge is going to be having access to that information, having the tools available for that information, and having the real time analytics to make business decisions in the moment, in real time. So the big challenge is really also having the skills within the supply chain to leverage and manage that data. I'm seeing the role of people in the supply chain changing, being able to bring together the challenge of the big data and the systems and the know-how of the business to make those informed business decisions. So I see that role, the role of a data scientist being one of the most sought after role in business and also in supply chain moving forward. And also the millennials coming out of college expect business systems that are instantaneous, that are easy to access, that are 24x7, that are accessed by it in their hands wherever they are at any time. So that's how I see it.


This is where you have to take care because any any poor pass leaves us very open, okay? If he has a man, ten yards the other side, what would you do? Yes, but if they were marked, what could you do with him? I don't know. I don't know. So you could use him? Yes, that again! And then play, because what will what will what will the opposition do? Yeah, he will probably come with him and then you can play the other side. Yeah, good. I kind of work with the ball in three stages. So build up one is in the defensive third build up two in the middle third and break through in the final third So today was build up one. So the goalkeeper becomes your spare man You need the other players to have the trust in him with his feet So, you know, whenever he's got it if he can draw the player towards him Then there's going to be a spare player somewhere and then it's about finding that spare player So you can use other players as a bounce or the goalkeeper can actually play it there himself Or he plays over the pressure and you know plays into a spare man there as well As two centre backs and a defensive midfielder, we have a 4v2. We have a diamond shape So we're always trying to create a triangle in that. So we have a triangle here, triangle there And you'll see the triangles throughout the pitch. So you always have an option either side Good Play, good Let's touch this go and score go and score good bagus