Okay. So I wanted to cover two topics today related to Markov chains. The first one is LEM, which is actually a Markov chain extension, and then the second one is in the classical model of Markov chains, but it's how to learn a Markov chain in a particular setting. They're both kind of web motivated. So let me start with LEM. There's a paper from Wodob that's referenced here that I can send the slides later if anybody would like to see more details. So we're interested in sequences of actions, so user actions or item consumptions, and we're saying that the output of a particular time step can depend on kind of what's happened earlier in the history. As an example, let's say that we have a universe of science fiction novels that we can recommend to people on a website like Amazon, and we may observe that people who read this first book are likely to read Ender's Game, and likewise for the other ones we have certain statistics, and so given a sequence of consumptions, we'd like to know what's a likely next element, or maybe more practical, we'd like to know what element should I recommend to this user given the consumptions that they've made so far. So this is a classical problem in recommendations. We often wind up augmenting the representation with other information features about the user, features about the timing of the prior consumptions, and maybe more details about how engaged the user seemed to be, and so forth, the session structure. We're going to kind of simplify in this setting and talk about something more stylized that looks just like this sequence here. So the simplest approach would be to use first order Markov model. So in this setting, we'd say that the most recent letter, the letter C right before the question mark, is something that's most representative of the user's current state. It should be the most predictive. We'll ignore the rest and we'll write the likelihood of a particular element following C, and maybe we can do that based on some count statistics like I show here. And so we can normalize these to produce the matrix of the Markov chain, and then we have an equation for the evolution of the process. Generally though, we think that looking at more history than a single most recent element should provide better models. And in fact, there are a lot of approaches to using these long range dependencies. Maybe the earliest and most pervasive is to use higher order Markov processes, but these days everybody's talking about deep network sequence models, which learn neural networks to control the evolution of the process. There's also field around point processes, which further will allow you to predict the time of the next consumption and make statements about likelihood of consumption occurring within a particular interval, and many more. So let's talk about higher order Markov processes. So in this case, maybe we have a case order Markov process which is allowed to look at the last case states, and based on the K previous characters, the process will make a determination about what the distribution should be over the next set. The parameter space blows up exponentially in this model as a function of K. So in many cases, people would instead use variable order Markov processes, which would use a first order process in many situations. But if further data is available for a particular prior symbol, maybe there would be a decision to keep two elements of history instead. Nonetheless, if at any point you're trying to track an order D dependency, then you would require space that's exponential into even in the variable order model. Deep neural nets have been very successful for sequence modeling, starting with natural language tasks like translation, and now used all over the place, including in the specific recommendation problem that I introduced at the beginning. There are a couple of architectures that are most well known. LSTMs have a long history. The primary target of these architectures is to address the issue that if you imagine propagating a gradient backwards through a series of recurrences in a network, then the gradient may shrink at each step. Over time, in much the same way that the higher order Markov chains require exponential data, the back propagation also would require exponential data because the gradient will be vanishing exponentially, and you need to see enough to make a significant change based on a longer range dependency. So there have been a number of architectures that have been proposed in order to get around this vanishing gradient problem. LSTMs and GRUs are probably the most successful right now. LSTMs have this slightly complicated architecture that you can see here on the screen to control the flow of errors back to earlier elements and allow the idea that depending on the settings of the current instance, an earlier element potentially far back in the sequence could flow directly through the network to influence the current decision, and the gradient similarly could propagate backwards without the vanishing issue. It's a heuristic attempt to make that happen. It's slow to train. It can also be not so robust in the training and tends to require a lot of data. So for the approach that we're going to talk about today, I want to just kind of introduce a technique that we're going to use that solves a much simpler problem based on Herb Simon's copying model from the 1950s. So in this setting, we have a sequence and we'd like to predict, but rather than saying that a previous element in the sequence will influence our prediction, we're going to say instead that the next element will simply be copied directly from an earlier element. So if the cell with the question mark is the one that we would like to infer, then it may be a letter D. And if so, that would be because it was copied from one of the three earlier occurrences of letter D. And the model for solving this problem inspired by Simon's copying model is to learn a weight for each previous time in history. So there's a weight associated with copying the most recent element, another weight with the second most recent element and so forth. And now the probability of consuming D next would be just the sum of the weights of all the previous occurrences of D. So the generative version of the process says that I will look back into the past and select distance from this weight distribution and then I'll copy whatever is that many steps back. So we'll use this as kind of a black box inside the lamp process that I want to introduce. So we want to do exactly the same thing. We want to say here's an example of some states representing restaurants that the user has visited and we're trying to predict what the next restaurant visit will be. So in a first order setting we would say that we decide based on Ruth's Chris. In a variable order setting we might say that the sequence Morton's, Shaky's and Ruth's Chris together would lead to a particular prediction. In this new model we would say that based on the past history we will use a recency distribution to choose how many steps back into the history we should look and then based on what we select from there we'll pick a next element according to the previous state that we've selected. So the definition of lamp says that a lamp process is defined as a recency weight vector and a single stochastic transition matrix. The way the process works is that the probability of choosing a particular element for the next state given the history so far is a sum of the probability that I choose some element i steps from the past which is wi from the weight vector and then if I choose to move from i steps backwards then I'll take a single step in the Markov process as if I were in state i. So sorry as if I were in the state from i steps ago x sub t minus i. So one can imagine that the user maybe has certain facets of their taste or of their personality and those represent different hats that the user wears. Sometimes the user's in the mood for a dramatic novel, sometimes for something lighter, sometimes for poetry and depending on the first probabilistic decision of wi we determine which hat the user will be wearing by determining which point in the past we will emulate and then based on where they were at that point in the past we'll then take one step forward in the Markov chain. So rather than any exponential growth in the parameter set as we go further and further back the total complexity is just the non-zero of the transition matrix plus k values for this weight distribution that determines for the particular task how much we focus on recent behavior versus how much we're willing to look back into the history. So in order to learn a lamp model rather than just learning the transition matrix we have to jointly learn both the matrix and the weight distribution w. The learning we do through alternating minimization the joint learning problem is non-convex and we don't know of any way to do it faster. There's some details in the paper on the optimization. Okay so maybe we can do an example here. So here's a Markov process with some transition probabilities that aren't shown and we're currently in state A. So from state A we will move from A following this edge to state C. Now we're in state C and our history is A to C. So now we'll make a decision where we'll move from and maybe we flip the coin and decide that we'll move from one element back in our history moving from A again and we'll follow the edge to B. Now our history looks like A, C, B. This time maybe we decide to move from B. It's typically most likely to move from the most recent state and then we follow this edge to state E. So we have A, C, B, E. Now we choose another element from the history distribution. We choose C and move forward to state G, move from A, move to state B. This is an example where it's a transition that had zero probability in the underlying Markov chain but in the LAMP model it has non-zero probability. Okay so maybe with that in mind we can quickly talk about how expressive this model is. We've taken the transition matrix and we've added a single weight vector in terms of the parameter complexity. So it's easy to see that a LAMP process with access to K elements of the history cannot be approximated by a K minus first order Markov process even though the K minus first order Markov process has unreasonable parameter settings many more weights. However it can be approximated, it can be captured entirely by a K-th order Markov process. Okay so let's take a look at how this LAMP distribution evolves. So at time zero we imagine that we're in some starting distribution pi zero over the states of the Markov process. In time one we take one step forward by applying the transition matrix and now we're in a new distribution pi zero times w. Now at time two with some probability we take a step forward from the current state in which case we will be in pi zero w squared but with the remaining probability we take our step forward from the initial state pi zero in which case we will again be distributed as pi zero w. So at time two we're actually a mixture over the distributions pi zero w squared and pi zero w. And then in the next step the same thing happens again. We can get to pi zero w cubed if we again flip a coin that moves us forward from the most recent state we can get to pi zero w squared in two ways and we can get to pi zero w again by choosing to copy from the start state. Okay so this sort of suggests that the random variable that we really want to study is the random variable representing the exponent of the matrix at time t and so we'll call this e sub t the exponent at time t and the evolution of e sub t says that we pick an exponent from some previous time step according to the weight vector w and then we add one to it because we take one step of walk from there and that applies to the matrix one more time. So this is similar to a process that we're in like studied which is available on archive. Okay so what's the steady state of this of this process? So if we imagine that it's a kth order lamp process so our weight vector has k elements we're allowed to look up to k steps back then we can do sort of a simple batch wise analysis and say if we're at some time step t let's look at the last k elements and see what the minimum exponent is and now in the next step at t plus one we must be at least one greater so every time we take k steps the exponent the min exponent that we see must increase by one so over time if we take k times as many steps then we'll be distributed as as the Markov will be at least as close to the steady state of the underlying Markov chain as the Markov process with with a full t steps. So the first corollary is that lamp actually has the same steady state as the first order Markov process with transition matrix w but that dynamics can be quite different so the flows that we observe from that steady state may not look anything like the flows that we would observe if the process were actually a first order Markov process. We can we can tighten this analysis a little bit by looking at the exponent e sub t at time t and checking to see that element e sub t was generated by choosing something from the history distribution and then jumping back that many steps and taking one step forward. So we can imagine a backwards chain linking from time t to some t minus w one and then from there to a t minus w one minus w two where each of these w values is chosen from the the k element weight distribution. So this is a renewal process and by the strong law of large numbers for renewal processes this actually gives us a characterization of the the number of backward steps and the number of backward steps is exactly the number of steps forward in the Markov chain that we've taken in time t and that gives us a bound on how close we are to the steady state. So in expectation the number of steps that we jump back at each point is the mean of the weight distribution the distribution over how far to jump in history and so that that gives us both the expected number of steps including in setting where the weight distribution is unbounded and we're allowed to look arbitrarily far back into history and it also gives us a way to show concentration balance as well. So under LAMP we have these these sort of strong understanding of the way that the mixing works for LAMP based on a modification of the way that mixing works for first order Markov processes but we allow this arbitrary dependence on history and so the hope is that the model will be more accurate in terms of actually predicting evolution of sequences. So that we can test empirically. So we've looked at some data data sets from wikispedia from Reuters last FM and from an old location-based data set called Breitkite and so these are the results in terms of of perplexity the reduction in uncertainty on the guess about the next element in the set and we compared to a series of baselines and the LAMP model performs generally pretty well the language model based approaches that we look at are prone to overfitting. We tried a few different smoothing techniques to address the overfitting. They work pretty well in text data but not so well in behavior data. We also take a look at the weight distribution that the LAMP learning learned and we see that in some data sets for instance in Breitkite which has check-ins to particular locations the LAMP model has learned to use past visits pretty strongly not just the most recent visit. In wikispedia which is based on wikipedia steps the most recent state is much more important than the other states and so the LAMP process sort of devolves gracefully to something that's quite close to a first order Markov process. So I talked about deep network recurrent models like LSTMs. We compared LAMP to LSTMs on these data sets also using some settings for the LSTM that have been published previously and we found that with sufficient data LSTM is much more representative is able to outperform LAMP. For some of the data sets that are smaller LAMP does significantly better like Breitkites. For others like LSTM music consumption data the performance is similar and for text data which do have these text statistic information based on both the vocabulary and the document so far and also on kind of what's going on in the current sentence the LSTMs perform quite a bit better and as the LSTMs train more in certain data sets they become better and better and are able to outperform LAMP but generally when we use the same computational effort LAMP has a lot more assumptions made about the data typically does much better with the same amount of training time. Okay so that's that's sort of part one on on LAMP. Maybe this is a good time to pause in case anybody had any questions or comments about the LAMP process. Okay sounds good. Okay slides are okay or visible. Great so we're going to change gears a little bit here and talk about some work from the wisdom conference in in 2015 on what we call reverse engineering a Markov chain. This is joint with Ravi and Sergei Vassilvitsky and Eric V. So in in in data analysis we really like Markov Markov chains for the same reason that we like them in LAMP very simple they capture a lot of interactions the theoretical story is is very clean and easy to use and they're they're highly extensible and they've been used in a in a web setting in in a lot of different ways including including page rank. So we're going to talk here again about chains related to recommendations so imagine that I do a search on the web for some topic maybe I search for the topic of Markov chains itself I get some results I follow a link to YouTube see some videos and I pick one so I watch the video and when the video ends I'm then shown a series of recommendations for the next video that I may choose to watch on the topic and so one could imagine kind of taking a walk through the state space of YouTube videos in this way and in fact a large number of YouTube watches are derived from these watch next recommendations so so we sort of have this process that looks like this I'm in a current video markup chains part one and then I'm recommended a sequence of other videos that I may want to jump to I jump to one of those I watch it and then again I have a new set of recommendations for where to go next and at some point I may terminate this process and jump to something that looks more like a random state or something that looks more like a state derived from a search or something else but while I'm in the flow of going from video to recommended video then I evolve according to something that looks like a first order process and as a user of this system I actually have visibility into into two parts of this one is I see the recommendations themselves so I can go to YouTube and take a look at what's recommended in response to a particular video I see each recommendation I know it's positioned in the in the list and the other thing I have is the view counts for this video so I know the stationary distribution of this of this evolution and so so this is a setting that comes up pretty often the example we looked at has videos as the items and the stationary distribution information as the as the view counts and in that setting we'd like to know why is it that certain videos seem to be they have a huge number of watches in the system and it could be two things one is that it could simply be a phenomenal video and for this reason words got out everybody knows and goes and watches the video maybe recommends it to a friend and so on the other is that for some reason the process might have featured a certain video all over the place including on as a recommendation for videos that are watched very frequently and people will just watch it because it's there but it might not be any good and so we'd like to kind of tease apart the distinction between things that are truly high quality and that's reflected by having been looked at a lot versus things that are high view count due to their position in the graph and so so that's maybe one motivation we could have for understanding what the actual underlying process really looks like because it will give us some sense of how people are choosing one recommended video over another one okay so so that motivates this problem of inverting a markup chain so the problem is we're given the stationary distribution and we want to find the markup chain that generated it so ordinarily the inference is the opposite ordinarily we're given the markup chain and we'd like to find the stationary distribution which we can do through some sort of matrix techniques like power iteration in this setting though we want to flip that around we're saying we're given this graph G which we can observe in the youtube setting we are given also a steady state distribution pi which we can observe also we'd like to output the transition matrix m that generated this steady state distribution over the graph and so the graph essentially represents a constraint that edges that are missing from the graph must be zeros in the transition matrix but otherwise edges that are present in the graph can be given any any weight so of course it's not always feasible to do this i can exhibit a chain here that maybe is not even ergodic and and so it's it's not possible to establish a markup process with the given establish some transition probabilities that will yield the given steady state we define a directed graph as consistent if whatever the target steady state is that we're asked to produce there is a flow that preserves that steady state on the graph so for example any strongly connected graph with self loops is is consistent consistent is a property that's defined in the presence of a target steady state distribution and then the theorem is that for any consistent graph there is a markup chain with pi as its stationary distribution so for any pi for any consistent graph with pi as the target there is a markup chain the problem is under constrained we have these end constraints on the steady state but we have possibly a dense matrix or a fully connected graph we could have an enormous number of variables certainly we expect there to be in this recommendation case a hefty handful of recommendations from each vertex and so the number of variables that we have control over is typically much larger than the number of constraints that we have so we have to address this in some way um there is a classical approach from 2003 from John Tomlin saying that we could simply write this as an optimization problem with uh max and objective and so maybe because we we simply don't know anything about these further constraints we'll try and pick the one with max entropy um today we're going to pick a different approach we're going to try to limit the degrees of freedom of the of the process um because we think that it actually captures what happens in in many settings and by learning in this framework we'll be able to induce some other usable information about the vertices of the graph so we will say that every vertex has a score which is intended to be capturing some elements of the quality or the attractiveness of the vertex and the Markov chain will be expressible as a function of the scores so if um if we imagine some probability from uh a to c in the chain um transition probability we'll say that this depends on the score s sub c of the destination vertex c and also possibly it may depend on some properties of the edge uh w from a to c uh for example maybe the wac edge encodes the fact that c is ranked at the top of all the recommendations when you're on page a um so uh in uh in sort of the simplest variant of this setting that we'll spend some time looking at we can say that the transition probability to a particular destination is proportional to the score of the destination and the constant of proportionality is given by um what options are available so uh any edge has probability which is the score of the destination divided by the sum of the scores of all the alternate destinations from that start point um and uh so so already this sort of suggests that the transition probabilities to a particular vertex are are highly contextual so in this example we've got our same example from a to either b c or d and i've assigned some scores here so under these scores uh the probability of going from a to c is maybe nine percent or so um on the other hand if i introduce a new node f which has only c and d as options then um the chance of going from f to c is 91 percent because the highly desirable node b is no longer present to siphon off traffic okay so um uh just to sort of formalize what the result actually shows um we we're saying that we depend on the score of the destination the weight of the edge um the results hold for um this setting here that can be an arbitrary function of the score of the destination and the uh the edge properties um and then the transition probabilities are given by uh making uh the uh different values of f be a distribution um we also for our results to hold we're going to require some sanity check properties on f so it should be the case that as the score of a vertex um increases uh f should increase continuously so we don't expect that um there are any thresholds in behavior where increasing a score causes a discrete jump in in f and uh we also expect that a score gets better f should get better so as the score goes up the node should become more desirable and finally we expect that um as we increase the score unboundedly then we can make the score of f arbitrarily large and if we hold all other scores fixed that should mean that with unbounded score that destination vertex should become more and more desirable until uh the probability of transitioning to it becomes one okay so these seem like um reasonable uh sanity check conditions on on functions f that we might consider and in particular the the one that we looked at earlier that the transition is just given by the scores uh has these properties trivially okay so uh so we'll actually take a look at this simple version where we say transitions are proportional to scores um and uh uh we we we can use the edge weight uh in in a few different ways we can use it for rank information as i as i mentioned we can also use it to say that um it might encode uh the similarity between the two nodes so given that you're on vertex a which is about markov chains we're recommending b c and d but c might be particularly desirable because it's also about markov chains whereas b moves into some other element of stochastic processes and so we might use that w ac edge weight to encode some kind of similarity as well um so uh so overall this is our target we want to know whether items are popular due to high scores or due to their location in the graph and the main theorem that we have is the following uh given a consistent input g g and pi and given uh function f that controls the um uh the uh map from scores to transition matrix uh there exists a unique set of scores one for each vertex such that pi is the stationary distribution induced by the markov process that you get by applying f to those scores and these scores can be found in poly time um and so unique here means unique up to scaling so there is one uh one scale parameter that's free um the stationary distribution actually we find up to plus minus epsilon um and uh so now we can maybe move into a little bit of discussion about how this works so we say s are the scores um and uh what i'm going to call a permutation pi isn't really a permutation this is going to be the uh distribution of uh probability mass a current distribution of probability mass over the vertices of the uh markov chain so here's an example um and uh we'll we'll say that uh q sub i of s will be this quantity that says let's say i begin with my probability distributed according to pi um then q sub i of s is the uh new distribution i get if i take uh one step from pi using the current scores s that i have so the current scores and the function f induce a transition matrix and with that transition matrix i can go from pi to um some new state uh q sub i will be the new mass at uh vertex v sub i um under the current score vector s and so in this setting um given the pi that i started with in red and given the scores in blue the q sub i values um for that score vector s um are then written in in black okay so um one more definition we'll need we'll say that a node is underweight um if it's uh um if it's q sub i value is uh bounded below its target um so uh q sub i of s is underweight if it's less than one minus epsilon times uh its target pi sub i value and uh the algorithm is going to repeatedly increase the scores of nodes that are underweight and it won't touch the scores of nodes that are not underweight so in this case um the uh yellow node d here um is uh um underweight and so we could increase its score okay so uh so now we can go through the algorithm um so the definitions are listed at the top and the algorithm works as follows so it says start out with all the scores equal and maybe we'll make them one over n we'll say this is the score s sub i at time zero and then we'll repeat the following step for every vertex if the vertex is underweight then we will raise its score um until we've closed uh half of the distance towards the target steady state otherwise we'll keep the score unchanged um okay so let me just say that slightly more carefully so um uh because f has these properties of being unbounded as we increase the score s sub i of t if s sub i is underweight it means we're uh less than one minus epsilon of our target value pi sub i um we're going to increase the score continuously until um q sub i of s becomes one minus epsilon by two of the target pi sub i value and then we will stop um so if it happens to be underweight at exactly one minus epsilon pi sub i we would move uh until we had closed half of the gap if it was more underweight we'll move a little bit more um okay so this um this new value of s sub i is guaranteed to exist um this is why we need these properties of being monotone continuous and unbounded and we use the consistency of the graph g to say that there's always enough flow for us to push in order to have this outcome um the only step we ever take is increasing an s sub i score and so under this algorithm no score ever decreases um and as soon as uh the q value for a vertex is below pi um it will never cross over because the only operation we ever make is either increasing the score of that vertex but only until it's closer to pi without reaching it or increasing the score of another vertex which by the properties of f will never increase the um the score on uh on v sub i um so once a q value is below pi it'll always stay below pi okay so the so the key limit for the convergence proof says that there's some explicit value m such that for all vertices i and all times t um all the scores are below this upper bound m and the sketch of the proof says if we uh assume by contradiction that there's some set of scores that in fact grow without bound then we know these scores must all be underweight because otherwise they would not grow um and we know that not all scores can be underweight um the some of the underweight scores must be below one because the uh probability has to sum to one overall and we know that the target steady state is a distribution um so the scores that are growing without bound must take all the probability mass from the scores that are bounded because of the unbounded property of f and so by consistency the demand that they have must be met which leads to a contradiction because they would um move probability towards one when we've argued that their probability must be bounded away from one so there's there's quite a few technical details in uh in getting that proof to go through that are are in the paper um okay so once we have that key lemma we know there's a bound on m and we've shown that the scores must increase multiplicatively by a factor of one plus epsilon over two just the way the algorithm is constructed um we have a bound on m and so overall we can show that poly many iterations um will suffice to reach uh an epsilon approximation of the steady state okay so that's the um that's the theoretical statement and the algorithm the algorithm is a little bit weird it doesn't look like a regular learning algorithm it has these two asymmetries in that only this uh vanishing subset of the vertices ever have their scores touched and in that we never reduce a score um but um with that in hand we can take a look at some uh experimental work so the way that we do this is we look at a data set of empirical transitions from some system um and we take the transition graph the skeleton of the matrix and the actual steady state in practice for a particular data set like this feed it to our algorithm and we ask uh for it to output um the scores and transition probabilities and then we'll measure whether we're correctly capturing the way the transitions actually work in the in the real data okay so we look at um some navigation paths through wikipedia uh we look at some restaurant data from uh restaurant queries to google uh the entree data set with uh chicago restaurant recommendations and uh we look at some uh uh data set of of uh comedy videos um the baselines we consider are algorithms that uh transition just proportionally to the steady state distribution so this seems like a pretty reasonable uh approximation um we look at a uniform uh approach where it's uh um whatever out edges are present they get uniform score um we look at page rank itself um where the transitions are proportional to the page rank at the node um we look at the maxent based approach that we mentioned before from 2003 and then we look at our uh inversion steady state inversion algorithm and uh in terms of the root mean square error of this prediction task um we've normalized the error to be one for the popularity baseline and uh you can see that the inversion model actually does better job in all of the data sets at predicting the the transitions um this is a convergence graph to show um as a function of number number of iterations what the um log likelihood on one of these data sets looks like and then on the right side the rms error um and so you can see that uh it's an iterative algorithm that adjusts weights according to the um the underweightness criterion and by about 15 iterations of the algorithm it's uh it's converged pretty uh pretty effectively okay so that's the um that's the end of the of the talk so happy to discuss any comments or questions questions so um I I didn't understand the uh w matrix that is also fixed as a parameter in the second one the inverting the steady state in the second part yes in the inverse uh yeah so the um the um the the skeleton of the matrix is fixed so we know which entries are allowed to be non-zero but we are not given the values for the entries the task is to pick values that lead to the target steady state and rather than allowing full freedom to do that we require that the values be picked so that they are consistent with a uh end dimensional score vector um according to this function f that maps from the scores to the transitions yeah so as far if I understood correctly so the model that proposes uh proposes having only the first order mark of chains so have you tried a second order or a higher order for mark of chains and sees how how well it fits in in comparison with first order I I think so I think the question was in the in the first part of the talk whether we'd looked at maybe a second order mark of chain well yeah no because um if I understood correctly the model that you're proposing is only first order right you mean in the second part yes it's first order mark of chain uh yes so my question is if you have tried uh so far with a higher order with I see um so uh yeah it's a it's an interesting question we haven't we haven't thought about it so the idea would be that um I'd like to consider something that might have n-squared many parameters um and uh see if I can so in a sense we're sort of saying just learning the um just learning the first order transition matrix is uh under constrained and we place this additional constraint to use the scores um learning a second order would be kind of even more under constrained and we'd need a way to either use the scores of the maybe previous two elements to predict the next one um or maybe change our representation to have sort of a set of first order scores versus second order scores or something um I don't have a good intuition for whether the proof technique would would go through in that setting it seems like uh it would be quite a bit harder thank you it was one more question I think oh no no more questions from you this okay thank you again for your talk okay thank you very much


How's everybody doing thank you guys for tuning in for this week's video. I'm gonna be explaining everything in Spanish Why are you mad? So make sure to check out my latest Check out my last video You guys just just go check out my channel. I have a lot of videos in English Ma'am, what are you gonna do for tomorrow's video? Tomorrow I'm planning to make a big project, from the shoulder to the wrist The concept is a lion and a bull And a what?  Bull Bull Why do you change your voice when you speak in Spanish? I just want to listen to you guys As a reporter of Univision, first impact But if you want I can give you my natural voice I forgot how I speak This idea of a kitten and a dog The idea came from my client, he likes cats and dogs And I said I would look good as a manga And here I'm gonna start tomorrow Tomorrow I'm gonna start at 8am Because the one who wakes up in the morning, God will help you Do you want to say something else? Please come to the whole video You're gonna learn a lot in this video Tomorrow's lesson is how to tattoo So that your client doesn't faint How to make a manga in a day? Now it's time to start the stencil I have the two stencils that I'm going to be using tomorrow I don't like adding so much detail to my stencils I get confused sometimes So this is just what I like I feel more comfortable I don't know how to make a manga in a day This is just what works for me I feel more comfortable And if you want to try it, try it And let me know if it works for you I hope you didn't get a tattoo There's traffic I woke up late I had to go at 6.30 And it's 7am Traffic Let's burn some time Let's burn some time Because I'm in traffic Oh, oh, oh, oh They said my mind was empty But there's only memories I don't remember I've always been a wolf I control everything I control everything I change everything I change everything in this gold With the gold Gold Gold Oh, there's traffic Now yes, gentlemen And ladies I bring you another video in Spanish For what you like And send And as always I'm going to show you the needles That I'm going to use For today Which is going to be the 14RS 15 Magnum with Curve And 27 Magnum with Curve Which is my favorite needle And this is the battery that I use With my Spectra Which is called Lining Bob And it's wonderful Solar ink is my favorite ink And for today It's going to be something very different Watch out Because I'm only going to use One tone And that's going to be Black Solid Hey, man You're crazy You start really well And then it's like Dark as hell I know my answer Let's see The brand that I'm going to be using Stenzo Stuff I like to exaggerate How much I add to my arm So that the flies This is my Stenzo The big deal I guess Where I look that it's going to look good I'm going to tan The beard ends exactly Where it's going to start The head of the beard And that's how it's going to connect The two things And we start with the 27 Magnum With Curve Which is going through the right sleeve With the 5.5 voltage It finds itself calm It finds itself determined With a technique Which is quite peculiar It looks a little weird Or it seems that I'm Picking the skin And now I've just changed The 14 RS That I don't know What I would do without this needle And here Returning to the technique Which is not found in the market You break the rules Have fun Are you able to find Another technique Another style You do it We begin to tattoo Too early And I'm about to finish This move So it's time To have breakfast In my town And here We start with The second time Of this project Hopefully we don't go To extra time We're going to continue Using the 27 Magnum With Curve With the 5.5 voltage And we're going to start With the Stylion beard And hopefully it won't bite us To make the hair Of the beard I decided to use The 15 Magnum with Curve Because I felt more comfortable This technique Which you're going to see Next I call it The Technique Pen The reason I call it Is because As it looks I don't know What I'm doing I make circles Lines Go and go And I scratch the skin But it works And sometimes I make miracles with that Everything I'm explaining In this video Is simply What works for me I'm not saying That it's the only way To make a tattoo Or that it's the correct way Not at all But if I have The purpose of That hopefully These techniques Will work for someone Next I started recording To my client Because of the pain I started to laugh And I said This is not normal And I started to record To have evidence That maybe My client is a mutant And I think you do this On purpose You enjoy this I'm doing nothing on purpose This And here we are To finish This extravagant project To put the last details With the white With the 14RL Read, read The secret To put this white Perfect Is What is my voltage? 5.5 0.5 The needle Outside Massive Outside And And Make the sound Rat, rat, rat, rat That one That sound Rat, rat, rat When you know This is coming To perfection And this is how The whiteness is executed The white And that's how the skin is cleaned Finally We finished all this manga We started Like 8.5 Right? We started at 8.5 To tattoo We took a break Like at 11 11 Like 30 minutes And then We finished What time is it? It's 2.22 8.5 9.5 10.5 11.5 6 hours 6 hours? Like 6 hours I was relaxed Relaxed Navigating From all this project Without Being there All purified We have all day But We finished early So Maybe it was because I memorized the pieces Maybe It helped me a lot That They were big Expanded All the images Thank you very much for watching this video I'll see you next week


My name's Kevin Garn, I'm a detective backing inspector in the regional crime coordinator for the Northern Region. The spelling is G-O-A-N. That's why we're here today. It's, uh, investigators asked that we release a copy of the triple-O call that relates to the, uh, the hours leading up to the demise of young Erika Liddy, uh, who, um, she was located, uh, at a bus stop about 1.7 Ks to the northwest of our location here, um, with a head injury, um, she was taken to the hospital and as we know she, uh, passed away as a result of her injuries. The hope by releasing the triple-O call is that we can identify the caller. We believe that he may have additional information which he can assist our investigations with. It's probably important to pass on to the triple-O caller that he is not the subject of our investigations, but we believe that he will have information that may be able to assist us in inventing our inquiries to bring it to a, uh, successful resolution for the sake of the families involved. Do you know anything about the quarry? Uh, we understand from his voice that he's, um, probably, uh, a middle-aged gentleman, uh, and we understand that he may have been on a push-bike, uh, in the area of, um, the bus stop at about 1.30 A.M. on the 12th of April this year. How are inquiries going outside of this group? Uh, our inquiries are still progressing. We have a number of lines of inquiries, but we're certainly eager to speak to, uh, the triple-O caller in this instance. As I mentioned earlier, uh, we're talking about, uh, kids that may be in the area as well. Has there been progress? Uh, yeah, a number of inquiries have been conducted in relation to that, but, um, we believe the triple-O caller in this instance may be able to give us significant direction. In the car as well, the condo? Uh, those investigations are continuing. What do the triple-O call the same? A copy of the triple-O call will be released to you, but essentially that, uh, he had come by the young lady in the, uh, bus shelter and that she was suffering from, she was then unconscious, uh, and he was urging the arrival of, um, the emergency services. Well, makes you sure that he isn't a suspect? Uh, it's, the nature of the call is such that we want to identify who the triple-O caller is so that he can tell us, um, what other things may have transpired in the area at that time. And so was the man not there by the time police had arrived? No, that's the case, yes. Is that unusual? Uh, not, uh, given the proximity of the phone box here, to the proximity where Erica was, uh, discovered. The area is approximately 1.7Ks from this location, so, um, it is some distance for him to return to that area. I understand that this was the nearest phone box that was available to him.


You might have seen me in two days ago in Kubernetes made-ups. I'll say the same thing but if you're not please stay, okay? Because after this, I'll ask you guys and girls a few questions. I'll give you some swag, okay? I got approval from the organisers. We're going to give you something, so just stay. And try to learn something a bit how actually Kubernetes Gateway API and Ingress can help you in your platform delivery. Okay, a little bit on myself. I won't spend too much time. I'm a sales engineer based in Singapore in Kong.  I started working at software engineering, then deaf off, and then you do everything, right? You start especially. So happy to be here and invited for the talk. And the key thing that I want to give everyone is actually how this Gateway API can help you in turn of your Kubernetes deployment, alright? So agenda, I guess gives a recap, some technical overview, some demo if the network don't dies, actually it's my phone. So I better take it out, right? Because the Wi-Fi is not very nice. Okay, and the last part, Q&A, quizzes. I have three questions you can answer. My question, my colleagues sitting there will give you a pin. And then after that, you'll be dealing with a swag from Kong, okay? So it is something we want to share to the community here. Alright, so we have Kubernetes Ingress Controller. So what is it? I think there's so many talks in the past few days of you deploy something EK, AEKS. You probably heard of it or you might have used it and you might not know or your platform engineer already provided for you, right? So what is Ingress Controller in the Kubernetes clusters? Well, Ingress, okay. The best way that I can say it's like your front door where before I come out, I need to go to the booth and register, right? So Ingress Controller is kind of the front door to check in all the incoming requests to your clusters before they conceal the service and then do the necessary routing, right? So it's something like a load balance. But to leave in term, it's just a front door to see, okay, Robin, you should go to lecture hall 2.1. You shouldn't go 2.2. That's not your speaking slot. Okay, so that's how it actually works in the Kubernetes world. No much differences. Okay, that's how we typically deploy all this Ingress Controller to direct all this traffic when they've come into our cluster. Okay, very simple. So KONG itself, we have our KONG Ingress Controller. So I think if you deploy, you have been using other Ingress Controller like Nginx, right? And some others, right? So we have our own implementation basically the same thing, okay? Just that we add on with some of our KONG features like some of the API gateway feature that I don't want to talk too much about, right? I want to keep it a bit more generic open source today. So that's where our Ingress Controller works, where you come in, then do the redirections, etc. And also, enhance with some of our plugins, APL authentications, of all this. Right, so this one I won't go in much into detail, okay? So why we want to change the Ingress, right? We are creating Ingress Object easily, creating service. Why we want to do that? Why this gateway API was introduced if you went to the KubeCon like one, two years back? Why was it introduced as an experimenter right now, okay? So in county Ingress, support all this path matching, host matching, easy, right?  Simple, okay? But then again, we realise that we need a bit more advanced usage of our gateway APIs. That's sorry, advanced use cases that Ingress doesn't support. Okay, that's where gateway API come into the picture, right? You can do header-based matching, header manipulation, traffic splitting example, 50-50 per cent new service come out, which I don't know later. How can you ensure that only 50 per cent of your incoming traffic go to the newer service? How can you do that using that kind of routing, okay? The Ingress actually don't do that, okay? So that's where gateway API come to the picture to do that kind of complex, a bit more advanced use cases. Okay, there's some other extension like other routing protocol at GRPC, TALS, okay? Okay, so what I said you try to read a bit because I will ask you question later, okay? So other routing protocol like GRPC, emphasize the data. And also custom resource definition for other backends and proprietary protocol. That's a possibility that actually this gateway API I want to achieve. All right. So quick example, I think it's better to illustrate with some, not captains, some pictures and some work, okay? So we have a company we have usually Alice Vox Cairo, very, very typical security 101, right? So, I mean a lot of you actually doing all these three things.  So I think you can start especially do everything. So, so just think of the three, three percent. What's your role in the gateway API implementation? Okay, so gateway API implementation there's a gateway class, right? So infrastructure provider like Alice for example they're actually the one that you create define the gateway class from the, from the provider, right? So for example ACME.io it could be all Kubernetes about this AWS implementation application load balancer, network load balancer, Azure application gateway, GCP, etc. So F5, etc. So this is based on vendor specific. Okay, so I'm the one that actually create this for my cluster admin. Okay, I can be someone like that. Okay, then we move on to gateway this where the platform cluster operator come into place, right? The CKE, CKE Kubernetes administrator. And then this where you define the car gateway you want in your cluster. So you have external gateway for external LB and then expose port 80 or port 443 depending on your needs, okay? To receive that kind of traffic. So when you create this, right? If you put in maybe a cloud provider like Google Cloud or AWS you spin up a load balancer coming in and then listening to port 80. So that means my traffic can only come into port 80, right? Only can come to that door, right? So that's how it works. So this give bot that kind of cluster operator that flexibility to create external LB internal LB. Why is it important? Sometime your cluster to serve internal external traffic or some kind of specific traffic that certain load balancer need to that can address, right? So this give more segregation and responsibility on the kind of setting that you want. And then the rub rub is a I think the I think some something that resonate with a lot more of you if you're working with DEF, right?  How do you want to expose services like matching create a path so that external people can use. So all this is where it come to place. It's not very a difference from how you do ingress object. But you can see that there's HPP route and just I mentioned another route GRPC route, blah, blah, blah. So give you a lot more flexibility. Okay? So I think the question is how how it helps, right? I think as I think API it's like the ingress already covered simple use cases, right? But I think from what the school of thought is actually give you API try with things like a day to operation when you want to do upgrades and management of the cluster, right? So how it helps? So consistency like the infra provider like at least they can keep their gateway class of manifest consistent maybe only the vendor they change maybe from AKS to AWS to Azure while there's also allow them to have a fix of parameter reference here. Okay? So parameter reference like I just go a bit networking your subnet mask your internet IP or you can define it consistent across different gateway classes. Okay? So this give them bit more control on how they can reuse this kind of gateway classes templates. Okay? Then if I'm a Bob I want to upgrade to my new loop answer maybe because the like for example AWS classic loop answer I want to change to network loop answer, right? Because typically just change the gateway the gateway class here already, right? So actually fix you then I can just change the gateway class name to there. So all my POTS all these I see the POTS 80 listening POT 80 POT 443 I don't need to change I just need to change the naming of the gateway that I previously updated. Okay? So you can see that flexibility you can do and then you don't recreate your what engine next or what we install the manifest everything you don't I think it's very beneficial for developers especially want to do very simple thing you have your new service version 2 you want to only lack 10% of your of your internal employees to access you can just put weightage for like 1 okay? 10% so every 10% update in the traffic will go to the new service so they can test and then when it's already right then you can install service so you can do it easily using this gateway API okay? so it's not by 3 by Kong right? it's what actually gateway API can actually achieve whichever ingress controller implementation or do it if they support this okay? it's an open standard just emphasise it okay so some concept before I go for demo I just want to we go cheat it okay? this one I also mentioned so just just read the okay? in case I ask you question okay? just remember this okay? alright I'll do a quick demo on this basically I'll install a gateway I'll do a splitting into two service and then and then that's it okay let me do a quick demo I think I don't stand better alright? so see my VS Code right? I got a mouse here it's it's working okay? so see my VS Code actually I do I will share this the slide so this is my demo report right? so let me just show you a quick one so what I did is install a gateway okay? this is quite standard just install gateway and then the gateway class and then I have two department two service one HTTP and watch HTTP okay? I already install already and then next I will actually create a HTTP route and what I do is I will do a toggle of 50-50 so you'll see 50% echo and 50% HTTP okay? so I could do a quick demo on that so there's two service here and now I'll applying the route okay? the route is applied already now let me try to consume the service okay? I'm very lazy so I will copy and paste my command yeah I think developer are all like that oh okay I want to ask question already I want to ask question already ah why my request is not found you are sharp enough why my request is not found want one to try? yes please see? he is listening Tegui, can you help me? yes you are right I didn't put a header okay this is very ingress related okay? great job you are listening okay let me let's see now so you see that my header and look I'm expecting person at the end robin so that I can get so you see the first one will echo I'll take another one HTTP you see the toggle it's the same route same host okay? so it's I'm done 50-50 so you can see the magic of this using a basic HTTP route toggling just this 50-50 so developer easy for you you don't want to think of writing your code all these Kubernetes open standard you can do that easily so this is a very quick demo okay so this is what I just show so I won't say too much and additional rock support remember this TCP, GRPC, UDP so remember and this is how you can actually enable the gateway API using cong I'm not sure about other implementation but the side I shared to the organizer so I think you can download so all this information on there so basically this gateway API in cong is still in experimental you need to enable the feature gate so you have to enable and to use it and see if you got any feedback and send to the Kubernetes user group not to me which cong is sitting inside as part of the committee to actually do that okay, quiz ready? first one can I do suffix between gateway API yes our friend from API 6 give him yes, you know it you cannot answer the next question when they give chance to other people I think your implementation so you can do I think you're still in beta I didn't see okay so NIM 1 Kubernetes ingress controller implementation that support gateway API which I've been talking for the past 15 to 20 minutes organizer can I mean where you come from well open up raise your hand whatever say okay, gentlemen give him okay, so okay cong is one of the many ingress controller implementation I think API 6 do that and also engine so this is just a way to support okay last question is it possible to support GRPC route raise your hand gentlemen yes, yes you're right correct, so typically Kubernetes ingress is a way to GDP route and also maybe some flavor to TCP password but even J1 to support more modern protocol routing GRPC etc so that you can support your new use cases okay and this is a quick quick promo code for our education you can take a picture so if you happen to be using cong you want to upscale please use this promo code to get some 100% off to offset your certification because this is actually you have a projector and you do the test like a CKA AWS so it's the proper certification and then we still have our education that can go up and start for free maybe I send in a tiger education at cong or something that you can actually self base learning can do that free of charge also for the one on one courses alright then thank you thank you for your time for staying and hope you learn something and thank you for inviting me to the talk happy to hear that any questions I'm done asking so any question for me no question sorry ask question also got swag so this easy easy thing but don't ask me personal question there was no swag sorry when I come from Singapore that's very any questions on how can English control hell I mean not just cong it can be Kubernetes which I know AWS any questions yeah I don't think so so which means address a separate thing so this match is is address exposure of microservices so imagine you have 1000 services and you know everything do a cong up down up down there will be a spaghetti architecture no I don't think so it might address like you have small microservice to few but if you talk about a lot of microservice and more than 100 and you want to manage account inter-connected then a gateway is definitely not the even gateway API or any API gateway is not the right solution that's my tip you can do that but there's a lot of complex need to but then again service manage capability to overlap with some of the gateway API like this kind of grp0 using on void auto main TLS so it it depends on you but no I don't think so and just to highlight actually gateway API is not replacing your current way of English API no plan to replace that both adjust different thing you see so they say cannot replace they say so no you still use your ingress you won't die your HEP ingress you're using well continue to use it no need to rush to use gateway API okay just give it a bit more favor on that alright so whoever got the pin please go to my colleague and redeem a small t-shirt from Kong complimentary from Kong hope you take one take one only not everything just take a t-shirt for folder with pin you will see us again happy to join me not opens source me not all next year or something we can have a lot more talk on that thank you very much guys and girls thank you


Hello everyone and welcome back to enter the ether of the podcast all about the upcoming third-person MOBA ethereal clash of souls I'm her host the one and only mighty man goose that guy's jelly That's me. That's it.  Oh my good. Yeah, every god vastly You know changed my expectations. You circumvented my expectations. Is that what they tell us in the movie and video game industry? Yeah So, uh, yeah, um, how was your week brother? Dude, it's been good Yeah, lots of news. Oh, yeah, so that's probably that's gonna be the main focus today They released one of their blog posts one of their fun facts and it was all about their map We got finally they told us they were updating the map We finally got to see some images of the map and We're gonna go through today go through individually taking a look at these images and just talking about them And how they're going to affect gameplay how we see them affecting gameplay Before we get into that though So they changed their plan instead of having each lane stacked directly on top of each other There's still gonna be three separate lanes However, they're gonna be kind of side-by-side but also up above each other So you'll have the middle lane and then there'll be a lane over here Well, let me bring my hands up a lane over here and then like a lane up here So there's still a lot of verticality to the map, but it's not what They had originally planned they did this because they were afraid that it just wouldn't run well unless you had like a Super high-end graphics card. Uh, I don't know I've already had a few people mess with me saying like hey there the map's not gonna be like that was the big draw for The real was the map so I Don't know it's yet to be seen how this is gonna affect how everybody views it I wasn't really that affected by it personally. I still see it does remove some of the Kind of plays and stuff that I kind of thought that would be possible with the therial However, it's still there's a lot in effect there. Jelly. What's your thoughts man? So I probably the opposite came from you. I would I'm not gonna say that I'm like Furiated by By this change, but I was definitely Hurt I guess for lack of a better way to put it sounds a weird thing to say about a video that hasn't come out yet, but But like it was one of those things that I was definitely in the camp of like super excited about the straight vertical tiered map and Seeing it wasn't gonna be that way kind of was like oh like What else isn't gonna be like it kind of made me do that double-take a little bit And that's not to say that the map doesn't look great and I'm excited to play on this map But it was just that that like brief moment of like wait a second. What's actually happening here? So yeah, I I could see I see all the reactions from the community being valid in this scenario. Yeah A few things that like I was thinking we talked about this on the show before Abilities that would pierce layers of the map how cool that would be that's just not gonna be a thing That's you definitely won't have that happening However, they did talk about fall damage and if you get to the edge of the map and you fall off you're dead So cliffing people will be a thing which I absolutely love that's something you normally see in like first-person shooters You don't see it mob is too much it is a little bit in Kings hunt and That actually that really did affect the way you played Kings hunt I wasn't good enough to cliff anybody in that game But there were areas of the map where you could tell people were playing differently because they did not want to have Their backs to that crevice or the fire pit or whatever they didn't want to get knocked off into it So I'm sure there's going to be abilities in ethereal that will be able to knock people back And those abilities will be very effective if you can catch somebody on the edge Absolutely, and if somebody like for instance, we know you're gonna be able to fall jump from one lane to another And as long as you're not in combat, you won't take fall damage But if I can from a distance see somebody jumping shoot them and that triggers their in combat state And then they fall to their death even though they thought they were safe I think it adds another layer of things that are going to be interesting to try out in the game Yeah, you're really going to have to watch yourself And that's the thing too like if you're if you're not in combat. Yeah, you don't take fall damage, but The other thing it removes. This is something I think that would be very hard to balance is If you're able to just kind of drop through one level to another to another that would make rotations from top to bottom Much faster than from bottom to top. I would think With this it's just going to be You know Rotating from one lane to another is going to take about the same amount of time And they did mention that there will still be teleporters and cannons I guess you can load yourself to a cannon and launch yourself up to To another level, which is pretty cool But uh, I think it'd be a lot easier for them to balance and have the rotations times be Similar to other mobas and what people are used to It's also going to make it much easier to do a mini map now. So mini map just That problem's gone. Yep You won't have to toggle between lanes trying to figure out how it's going to work So that definitely a Probably a good change I mean for performance reasons for mini map reasons for balance reasons It makes sense that they made this change. It was just a shock to a lot of people. I think Finding out that the map wasn't this cake layers. Like you you've said in the past.  I said like the only Like like a deal breaker is if they change the map They structure their map I wonder if they heard me say that we're like It's not such a huge Change like they didn't just go straight back to a normal MOBA map. It's still Very dynamic It takes a lot of um advantage of verticality and how their Their myths are set up because the sky sliders could still just move from one lane to another You know at will without having to take any teleporters or cannons or a risk jumping off of anything Pretty cool stuff there. I'm excited to see how Everything works and interacts with each other on this map now We've always kind of thought about the class abilities in the in terms of the first map that we saw two years ago And now that this map is here and we kind of have an idea of what it looks like We can change our thoughts about it, but also imagine the different plays you can make accordingly Um, but so before we get into the images. I do want to mention again the podcast the actual podcasty podcast Oh, yeah, yeah, uh, we're spotify apple Pandora now. I got the notification for Uh stitcher All the whole bunch of places that will have links in the description, but the podcast episodes will go live midnight the day before The actual video version of this of enter the ether comes out So if you can't wait to watch the video version It will be up on all the podcast places at midnight the night before But we still recommend you come here so you can see the visuals that we're talking about and Comment to us. We do live premieres So comment to us what you're thinking what our thoughts are asking any questions all of that good stuff And uh, yeah, and uh as you as you saw last week, we do We will ever once while have exclusive stuff that um If you want to get ahead of the curve and hear that before anybody else then definitely subscribe to the podcast That's our that's our ultimate end goal. We want most of the people to enjoy this on the podcast I don't want this to just be in my channel. I want this to be a main goose and a man jelly a jelly goose jelly goose cooperative effort here Sounds like some kind of future candy. Oh, did you get your jelly goose for halloween this year? That house only has man goose man jelly Anyway, I'm for the jelly goose So the map looks incredible it does Uh, it looks like it You're hopefully you have some foliage sliders because I don't know if I don't even even might give you're gonna handle that foliage There's a lot one on it is Beautiful this first image that we have up. I think Shows a lot, right? We've got the path through cutting through the rocks. You can see there are torches on the other side I'm not sure if that's a lane over there or if that's further into the jungle because we don't know which side we are on For this image But the thing that I think is really interesting to me is if you look in the top left of the image You can see a torch through the trees Which implies that you can get up into that area At least to me that's what that's what I see here Is that that's somewhere you can actually stand as a myth or as a player and look down into this opening So they there's not only verticality of the lanes themselves, but verticality in each lane As well Right, so I mean I'm thinking maybe you can walk up that log or jump on that log and go somewhere else or whatever it may be But that this just looks incredible to me What are you? This log is like Leaning over like this rock wall and you have this straight rock wall that I think reapers would be able to navigate while others couldn't the sky sliders Of course can navigate wherever the hell they want to they could fly But reapers would be able to climb up that wall the the tree that's over top of the path I would think berserkers might be able to break that and completely block that path off or drop it on top of somebody And also there's just there's so much dynamics going on with with the way their myths are set up They're different classes So you got that that tree light right there That might be a great place to take cover from a sky slider that's up above you pinging you You can just take cover under the tree until they because they're Their sky sliders will have some sort of like stamina type thing where they can't fly forever So you just take cover under that tree and wait for them to To to run out of that stamina and then take them out But um Yeah, just this one image I can see so many ways to take advantage of their math map with The class passives that they have set up for their myths And i'm really curious like you said with the berserkers I didn't even think about like breaking the tree and blocking both the path up top and down below by putting the log In the pathway But even just if they could just block this pathway, that's a huge That cuts off a huge section of that they have to go around somewhere else takes extra time Or you have to use their class ability if they're a reaper or a sky slayer trying to get over that obstacle To get where they're trying to go It just opens there's so many layers of what could happen in this small area That just that's what excites me most I think going into looking at all these images and all of that 100% 100% I think I think this image Is probably the most interesting one to me because of all that that I can see going on Uh, you ready to move over to the second one All right, the river So this image is just uh pretty standard image of a river. You got trees on either side. You got some torches again um Jelly, what are your thoughts on this on this particular image? The river looks really wide to me. I don't know if that's If that's like there's going to be depth to it on top of it that if i'm in the center I move slower while i'm going through or what the deal is Or if it's just uncrossable to begin with that I That I have to use some kind of land path over it It looks like to me we're on some kind of bridge Looking out in one direction. So I would imagine we're in the middle of the mid lane Or the I don't even the the bottom lane. I don't know we have They're calling it void lane, which doesn't make much sense to me, but On a void fire and ice lane. Yeah that that applies to the Uh neutral objective that's in that lane. So a tropos is void.  I wish the lanes resembled that description more Um, but I think at the end of the day the community is going to make a name for them no matter what Yeah, and that it'll just get figured out once we actually are able to start playing the game But yeah, this to me looks like your generic Uh river running through the middle of the map Um leading toward something We can't quite tell and make out what's in the background But you can see one of the other lanes the base of the lane it looks like Hovering in the distance. Yeah, because there's skyline in between What looks like like a mountain really, but it's not a mountain. It's the bottom of another lane Yeah, they did say that the the river only cuts through Uh void lane, right? I believe they say that in the blog post I don't remember if it's in the blog post, but I know looking at the image It looks like it only cuts through The void lane. Yeah Pretty sure that's the thing Any specific on this image man goose This third image again, it's kind of a more of a rushing sloped View of the river and there's lots of trees on either side this time This one I think just looks prettier than Anything else like it looks very pretty, but I can't really um deduce anything else from that What do you think jelly? What did you notice about this? It looks like this might be the continuation image of the last one That this is that area we couldn't quite make out that this the the River flows downward a little more opens up into multiple paths looking like they're going into the jungle Um, but yeah other than that nothing nothing crazy that I can see here This looks like it could be like a background like I would set this as my computer background It's incredibly incredibly well done and well in detailed All right, and then this next Oh shoot this next image I my personally I think that this is um the atropos or atropos pit I completely what are your thoughts? So to describe the image for those who are listening It's it looks like a cavern except there's this sort of purple glowing Ring inside of what looks like a split tree trunk or something I don't know with a couple of torches lit next to it so And it looks like the area where you could see a tropos in the video that they released last week Where they showed the jungle minions And we noticed that that area Is kind of dark in the the jungle minions video that they released So maybe this is that it's it's dark once he Breaks out of this tree trunk thing and puts out the lights or something like that I'm really curious to see Where that transition happens I guess It definitely looks like some sort of objective. It doesn't look like it would be part Of the normal lane I completely agree the other thing I heard people talking about for this is it might be one of the teleporters To another oh, yeah I don't think so it's got that purple color like we saw with that atropos But it's entirely possible that this is what the teleporters will look like and this is just they gave us one image of that But it looks like we're gonna cave. I I agree for the most part that this is probably the atropos cave Yeah Cool stuff all around So the next image we have another picture of the river and this time that to me looks like a teleporter. You've got a um In the middle of the river is a bit of an island and there are three rings floating above this sort of um Sort of destroyed rune looking island and the rings are Consecutively smaller as they go up Um, jelly. What was your thoughts on this? so I Originally thinking about it was thinking this is one of the cannons Uh, okay cannon teleporter. Yeah It's in mid lane function. Um, it's the opposite end. So if you're sorry, it's in void lane It's gonna take a while to get used to that It's in the void lane there if you follow the river one direction you get to the atropos cave If you follow it the other direction you get this stargate structure um And I originally thought it was a cannon. I've heard people say it was a teleporter The thing is on one of the later images you get like a wide shot of the three lanes There's no other Structures that look like this And if you read through the fun fact it says teleporters and canons Multiple yeah, and so you'd think that if this is what that was There would be more of them scattered around the map This also to me feels like a large structure where I don't think that those cannons and teleporters are going to be quite this like present on the map Um, but I have other than that have zero idea what this could be for Yeah, I don't know there's a structure behind it That is like this gold Spike coming out of the ground it looks like So it could be into indicating some kind of gold buff or something like that Uh, we also don't know where the purple or green buffs that they described last week are going to come in So it could be that this is some kind of alternating Extra buff camp that has the purple and green buff spawn there as well I don't know it's it this one's uh, this one's quite confusing Maybe it's uh, maybe it's a ring toss for a tropos That's all it is Maybe it's a stargate. It does look stargate-ish I believe it I always need the whoosh my money when it boots up and we're good to go You changed my mind a little bit, but my money is that it is a teleporter. I'm gonna say it's a teleporter That's what my money's on All right, this next one is probably the most important image out of all of these And it shows the the the entire the entirety of the map from above So Looks crazy Yeah, so I mean it a lot I think a lot of people that were turned off by hearing That the lanes no longer float directly on top of each other. I think once they see this they'll be like Oh, okay. Okay. Well, I can dig this. I mean, this is what when I saw this I was like, oh, well, um, yeah, I'm completely on board for this. This looks awesome Absolutely and uh, if you if you're if you're listening you've got I don't know. It's like I said It's an aerial view of the entire map and you can see how the lanes float so much higher like the lane you can see closest to you, of course It is bigger because it's closer to you It's so much higher than the bottom Lane map and then uh And it's it's even much higher than than the other Side lane map which is kind of like middle lane because it's in the middle of these two Yeah, I mean we really are going to have to use this whole fire the void fire ice lane because you can't say top lane because Yeah, and it's going to be dependent on perspective one of the side lanes Yeah Yeah, so closest to us we have ice lane because we can see the ice wyverns cave or whatever it's going to be called And we can see kind of generic like outlines of pathing on that side And the opposite to that slightly lower down is the fire lane And again, we can see the pathing through and then at the very bottom We have the void lane which just looks massive And on either end it looks like those are might be the bases or what takes you to the bases or what However, that's going to work But you can make out like there's a lot of detail on this image alone that you can pick out little Things like the atropos cave opposite the weird stargate thing Or where the wyverns are going to be The thing that I think I'm most intrigued by Is that the wyvern cave has a hole in the top of it That it looks like it's an opening for sky slayers or reapers To potentially climb up there or fly up there and drop in from above on a team That's taking the ice wyvern and try and that'd be awesome try and surprise them and and steal it or whatever it's going to be And that that by itself it makes me so interested to play sky slayers and reapers And I'm like if I can just like surprise and show up That would be incredible Yeah, maybe maybe it's so high though that if you're a reaper and you're coming in and somebody notices you It gets a shot off on you. You just died of fall damage. Oh, no. Oh, man The potential is just insane And I think so I see what you're saying now that that structure is on the left side of the of the void lane As we're looking at it here. Oh the stargate thing. Yeah, yeah the stargate structure Does make it look a lot more prolific than just a teleporter. There's no structures like it anywhere else on the map that I can see um The they talked about in the extra life stream and I don't know that this is still accurate or not to take it with a grain of salt But that wards when you place a ward the ward will cover a cylinder straight up into the air Knowing that the lanes are no longer vertically stacked It's not so broken that I can place one on the bottom most lane And get vision of the entire way up But it may be if I place a ward in the center of the wyvern cave the ice wyvern cave If the sky slayer reaper tries to come in from above I might be able to see them on the mini map Yeah, which I think there's a lot of potential for counterplay or surprises and things like that That'll be really cool to try out and play with once we get our hands on the game Yeah changing the map up this like Not having the vertically tears is still there's still a lot to offer and a lot of weird Stuff that we can already come up with without even playing the game Just imagine once people get started their hands on this map and and start exploiting Various parts of the map what people are going to think of to do Yeah, I can't wait. I already have I'm not going to share them here because they're I'm gonna I'm gonna try them first I already have some ideas of things. I want to try on this map.  Yeah, no, it's I'm already theory crafting all the way I'm really not looking forward to taking a cannon somewhere and then there's three people just waiting for me Oh, no, that's gonna happen to me. The interesting thing they said with the cannons is the cannons will take you to set locations Right. So the cannon will always launch you Canon a will always launch you to point a Which I think is a great way to do it and it's It makes rotations very clear that I need to go to this cannon to get to this location as fast as possible right I'm also people know where you're going to be landing if they think somebody's going to rotate and they can be lying and wait for you Uh with this map in mind I imagine that we're going to see archmages on void lane as the solo lane Um just because they have their teleportation sigils I feel like them being able to set those up To give all the lanes at least a passing way through mid lane That if let's say they can only set up two sigils they set up one going to each lane from the void lane not mid lane And that way the person on the ice lane can take the portal walk across and then take the portal up to fire lane Instead of having to go backwards through their own teleporter to another teleporter or however It's going to work. We have no idea. Yeah, that that's assuming that other people can take the archmages Sigil they did say in the extra life stream that everyone can take the port the portals Oh, really they they take the archmage. So nice again That was I mean several months ago now So it may have changed but that's I did ask that question because I was curious about that as well all right, um so the final image Is pretty much just a pathway uh with some trees a little bit of a mountain It just really shows how much verticality they've put into each lane. There's there's all kinds of slopes and trees and um It seems like there's going to be a lot more stuff to take advantage of than there ever was in paragon at least absolutely and it looks like Learning the map Is going to be very helpful The people that learn the paths and which takes you where Are going to definitely have a clear advantage and not get lost in the map Um, and yeah, you can look up at the mini map which is definitely helpful and needed In order to help track your paths as a new player But if you can memorize that this leads me to to void lane and this leads me to the cannon to go to fire lane Like that'll be a very quick reflex that you can use To get your rotations down quicker and that I think that's part of what excites me most is running around and learning all the different paths And how to get places All right, it looks Just absolutely beautiful. Um Very sunny a lot sunnier than I expected it was going to look agreed I don't know how I don't know what I expected toward that end though, uh I was going through the footage for extra life for the q&a section and I haven't put that up yet and i'm working on it. I apologize, but Uh, one of the questions that I asked that I didn't get a straight no to was a day or night cycle in ethereal So it's possible mangus that this is just the day cycle And that it will eventually turn to a darker thing which explains the torches on the map as well torches. Yeah Hey, you could be right. You could be right And granted I could be reading this is tin foil hat level 5,000 because it could just be that they put torches there for design And I'm reading into an answer that just because it wasn't to know But that's what I do. So, you know, I just kind of saw the torches as a way of denoting what's a pathway But yeah, you could be right. It could be for like a day night I don't think that wouldn't surprise me at all with with a theory all the way they do thing So they're really interesting to see where they go with that So, yeah, it kind of sucks that they're not doing the uh Lanes right on top of each other, but I think I mean if you look at this one image Doesn't suck that bad really because I mean that's pretty amazing and that's extremely different from Anything we've ever ever experienced with a MOBA and there's still a lot of ways that you could take advantage um, I That's the my main takeaway from this this is there's so much verticality in lane to take advantage of now um Even that with the second map that we saw had a lot of verticality, but this does too and it's That that's what's really going to affect the gameplay the most not not so much the lanes being stacked at top of each other but what the verticality in lane is like and how each myth can manipulate that verticality to their advantage or um You know respond to Other myths that would be able to like maybe an arc maybe an archmage isn't able to climb a wall But they know not to get near a wall that a reaper can come up.  They did mention in their blog post that there are going to be some one-way paths that only certain myths Can get the second path in and out of Oh, really which to me is crazy If you take a wrong turn as a new player And you end up into this one way and then the reaper just jumps down on top of you. Hey, bud. Like how's it going? You're into the wrong neighborhood here, right? It's the that's an insane Thing to me that good players can capitalize on But the newer players may struggle with at the same time of like, oh clearly this isn't the right way And now they're blocked in because a berserker Locked them in there I think we're going to see a lot of plays like that where berserkers lock people in Or somebody's like At one health with the entire other enemy team chasing them and then they drop a log behind them and get away safely That's that's my thought with the berserkers is is a getaway mechanic assuming it's fast enough and it's able to Be quickly done I'm thinking Like You'd be like tallos. Hey, we need you over here. Just chop this down for me I'm a knight not a berserker. Sorry Okay, oh, I think that about does it for this for this map discussion. I think that's going to do it for for this week's episode Um, jillie. Do you have anything you wanted to add? Uh, I think that's everything that I have for now I'm quickly like scrolling through the images to make sure that I didn't miss anything But yeah, I mean it looks incredible If I guess the biggest thing is that somebody pointed out in the discord is if this is what their first map looks like Where what's the potential for future maps if they have it? Yeah, I didn't think about it. Um, if they end up doing an arena mode What what's the potential for that to look like like this if this is your your trial run basically I can't wait to see what they do further on that wise words wise words So jillie, you got anything to plug this week? A whole slew of youtube videos that it will actually come out this time Yeah, yeah, I reported them all today. They're just a matter of editing and posting so About the fun facts about the q&a about my thoughts about the map things More kind of going more in-depth on each image than that we really have time for here um, but I lots of videos Right. Oh man I'm looking forward to watching those. I can't really do too many videos right now myself. But yeah, cool right on dude I especially want to see that q&a video you did because I really don't remember what all was said to her in that It took a while to go through and and make sure I have the answers right and all that stuff I can imagine Uh This week. I'll plug. Uh, I did my blue kalia drink on tiktok drink inspired by kalia So, uh, you check that out if you want to it's in the links and shares in uh The ethereal discord, but I think that is About all I have to plug so next week a super intoxicated for enter the ether. You know why Yeah, I'm just like my third one.  They're a little sweet and fruity and then uh, you don't realize how much gin you're drinking so Good times all around All right, so guys, I hope nobody was put off too much by the changes in the map I hope if anything you were inspired by that overhead image because that certainly um Rearranged how I was thinking about ethereal. So Even if they do change one of their core concepts or something we can still see that it's still a very ambitious and um Just next level moba and then I hope you all come to enjoy with us So, uh, I hope you all join us as we all enter the ether I almost did your sign off, but I was like, wait a second. I have my own thing that I do Man