title
7.2: Wolfram Elementary Cellular Automata - The Nature of Code

description
This video covers the basics of Wolfram's elementary 1D cellular automaton. (If I reference a link or project and it's not included in this description, please let me know!) Read along: http://natureofcode.com/book/chapter-7-cellular-automata/#chapter07_section2 A New Kind of Science: http://www.wolframscience.com/nksonline/toc.html Elementary Cellular Automaton: http://mathworld.wolfram.com/ElementaryCellularAutomaton.html https://github.com/shiffman/The-Nature-of-Code-Examples/ Help us caption & translate this video! http://amara.org/v/Qbvb/ 📄 Code of Conduct: https://github.com/CodingTrain/Code-of-Conduct

detail
{'title': '7.2: Wolfram Elementary Cellular Automata - The Nature of Code', 'heatmap': [{'end': 391.566, 'start': 339.153, 'weight': 0.743}, {'end': 444.898, 'start': 412.921, 'weight': 0.976}, {'end': 510.583, 'start': 493.911, 'weight': 0.723}, {'end': 673.259, 'start': 646.823, 'weight': 0.728}, {'end': 793.441, 'start': 776.628, 'weight': 0.883}, {'end': 888.755, 'start': 848.232, 'weight': 0.704}], 'summary': "Introduces the history of cellular automata and stephen wolfram's concepts, emphasizing the relevance of computational thinking in science. it explores the defining characteristics and computation of wolfram elementary ca, involving 256 possible rule sets and achieving uniformity, oscillation, randomness, and complexity. additionally, it delves into one-dimensional cellular automata, including rules, visual representations, and examples like uniformity, repetition, and the sierpinski triangle, using code examples.", 'chapters': [{'end': 104.08, 'segs': [{'end': 58.556, 'src': 'embed', 'start': 34.559, 'weight': 0, 'content': [{'end': 43.189, 'text': "So we're oddly going to start kind of towards the end of this kind of history of cellular automata and we're going to look at the work of Stephen Wolfram.", 'start': 34.559, 'duration': 8.63}, {'end': 48.305, 'text': "We're going to stop this discussion right here and point you to.", 'start': 45.262, 'duration': 3.043}, {'end': 53.15, 'text': "if you're really interested in kind of diving deep into the science behind this stuff,", 'start': 48.305, 'duration': 4.845}, {'end': 58.556, 'text': "I would encourage you to take a look at Wolfram's book A New Kind of Science, which you can read the entire book online.", 'start': 53.15, 'duration': 5.406}], 'summary': "An overview of cellular automata history and recommendation of stephen wolfram's book a new kind of science for in-depth study.", 'duration': 23.997, 'max_score': 34.559, 'thumbnail': 'https://coursnap.oss-ap-southeast-1.aliyuncs.com/video-capture/W1zKu3fDQR8/pics/W1zKu3fDQR834559.jpg'}, {'end': 92.651, 'src': 'embed', 'start': 68.288, 'weight': 2, 'content': [{'end': 74.696, 'text': "Anyway, it's a lot of material and there's a lot of controversy about this material and this sort of big question is nature discrete,", 'start': 68.288, 'duration': 6.408}, {'end': 75.778, 'text': 'or is it continuous??', 'start': 74.696, 'duration': 1.082}, {'end': 77.079, 'text': 'does this?', 'start': 76.378, 'duration': 0.701}, {'end': 77.619, 'text': 'but what?', 'start': 77.079, 'duration': 0.54}, {'end': 84.725, 'text': "Wolfram's central point here, or principle, I think, is that this way of thinking, this type of computational way of thinking,", 'start': 77.619, 'duration': 7.106}, {'end': 86.486, 'text': 'is relevant to all forms of science.', 'start': 84.725, 'duration': 1.761}, {'end': 92.651, 'text': "Now I'm not here to answer that question or even pretend to know the answer to that question,", 'start': 86.546, 'duration': 6.105}], 'summary': 'Wolfram emphasizes the relevance of computational thinking in all forms of science.', 'duration': 24.363, 'max_score': 68.288, 'thumbnail': 'https://coursnap.oss-ap-southeast-1.aliyuncs.com/video-capture/W1zKu3fDQR8/pics/W1zKu3fDQR868288.jpg'}], 'start': 2.782, 'title': 'Introduction to cellular automata', 'summary': "Introduces the history of cellular automata, from the work of john von neumann and stanislaw ulam in the 1950s to stephen wolfram's controversial concepts, emphasizing the relevance of computational thinking in science.", 'chapters': [{'end': 104.08, 'start': 2.782, 'title': 'Introduction to cellular automata', 'summary': "Introduces the history of cellular automata, from the work of john von neumann and stanislaw ulam in the 1950s to stephen wolfram's controversial concepts, emphasizing the relevance of computational thinking in science.", 'duration': 101.298, 'highlights': ["The chapter introduces the history of cellular automata, from the work of John von Neumann and Stanislaw Ulam in the 1950s to Stephen Wolfram's concepts. The history of cellular automata is traced back to the work of John von Neumann and Stanislaw Ulam in the 1950s, and later, the controversial concepts of Stephen Wolfram are emphasized.", "Encouragement to explore Wolfram's book 'A New Kind of Science'. Encourages exploration of Wolfram's book 'A New Kind of Science' for a deeper understanding of the science behind cellular automata.", "Emphasis on the relevance of computational thinking in science. Stephen Wolfram's principle emphasizes the relevance of computational thinking in all forms of science, sparking controversy about the nature of science."]}], 'duration': 101.298, 'thumbnail': 'https://coursnap.oss-ap-southeast-1.aliyuncs.com/video-capture/W1zKu3fDQR8/pics/W1zKu3fDQR82782.jpg', 'highlights': ['The history of cellular automata is traced back to the work of John von Neumann and Stanislaw Ulam in the 1950s, and later, the controversial concepts of Stephen Wolfram are emphasized.', "Encourages exploration of Wolfram's book 'A New Kind of Science' for a deeper understanding of the science behind cellular automata.", "Stephen Wolfram's principle emphasizes the relevance of computational thinking in all forms of science, sparking controversy about the nature of science."]}, {'end': 600.49, 'segs': [{'end': 148.659, 'src': 'embed', 'start': 126.372, 'weight': 4, 'content': [{'end': 134.37, 'text': 'the simplest possible grid of cells would be a one-dimensional grid, a linear grid, so to speak, an array of cells.', 'start': 126.372, 'duration': 7.998}, {'end': 139.794, 'text': 'The simplest possible set of states would be a 0 or a 1.', 'start': 135.491, 'duration': 4.303}, {'end': 145.857, 'text': "I suppose the simplest possible set of states would be just 0, but we couldn't possibly get anything out of just having one state.", 'start': 139.794, 'duration': 6.063}, {'end': 148.659, 'text': 'So we at least need two states, 0 or 1.', 'start': 146.017, 'duration': 2.642}], 'summary': 'One-dimensional grid with two states, 0 or 1, is the simplest cell structure.', 'duration': 22.287, 'max_score': 126.372, 'thumbnail': 'https://coursnap.oss-ap-southeast-1.aliyuncs.com/video-capture/W1zKu3fDQR8/pics/W1zKu3fDQR8126372.jpg'}, {'end': 213.829, 'src': 'embed', 'start': 188.439, 'weight': 1, 'content': [{'end': 194.122, 'text': 'where we get the cell state is a function of its neighboring states in the previous generation?', 'start': 188.439, 'duration': 5.683}, {'end': 196.762, 'text': 'OK, so this is our project right now.', 'start': 194.721, 'duration': 2.041}, {'end': 201.244, 'text': "We need to walk through these rules, define them, and then see how they're implemented in code.", 'start': 196.822, 'duration': 4.422}, {'end': 203.005, 'text': 'And then, whoa, look at the results.', 'start': 201.304, 'duration': 1.701}, {'end': 210.248, 'text': "Have the results achieved anything interesting, or a value, or have they achieved complexity? So let's answer that question.", 'start': 203.345, 'duration': 6.903}, {'end': 212.469, 'text': "So I'm going to erase this.", 'start': 211.648, 'duration': 0.821}, {'end': 213.829, 'text': 'We can kind of remember this.', 'start': 212.509, 'duration': 1.32}], 'summary': 'Project involves defining rules, implementing in code, and evaluating results for achieving complexity.', 'duration': 25.39, 'max_score': 188.439, 'thumbnail': 'https://coursnap.oss-ap-southeast-1.aliyuncs.com/video-capture/W1zKu3fDQR8/pics/W1zKu3fDQR8188439.jpg'}, {'end': 391.566, 'src': 'heatmap', 'start': 339.153, 'weight': 0.743, 'content': [{'end': 346.036, 'text': 'Number with a zero or one in it, or we have two to the third power Possible way configurations or eight possible configurations one, two, three, four,', 'start': 339.153, 'duration': 6.883}, {'end': 347.297, 'text': 'five, six, seven, eight.', 'start': 346.036, 'duration': 1.261}, {'end': 352.079, 'text': "so it's interesting to note Is there only eight possible ways that neighborhood could be configured?", 'start': 347.297, 'duration': 4.782}, {'end': 357.122, 'text': "so if there's only eight possible ways? Why don't we just define an outcome for every possible way?", 'start': 352.079, 'duration': 5.043}, {'end': 362.724, 'text': 'meaning if the neighborhood is configured like so the resulting new? State should be a zero.', 'start': 357.122, 'duration': 5.602}, {'end': 364.805, 'text': "if it's configured like so it should be a zero.", 'start': 362.724, 'duration': 2.081}, {'end': 367.026, 'text': "if it's configured like so it should be a one.", 'start': 364.805, 'duration': 2.221}, {'end': 374.946, 'text': "Then let's say a zero, then a 1, then a 1, then a 1, and then a 0..", 'start': 367.026, 'duration': 7.92}, {'end': 378.367, 'text': 'So I made up an arbitrary rule here.', 'start': 374.946, 'duration': 3.421}, {'end': 383.369, 'text': 'But in a Wolfram elementary CA, this is what is known as a rule set.', 'start': 378.607, 'duration': 4.762}, {'end': 391.566, 'text': 'Somewhere in my magical annotation system to this video, you will see the decimal equivalent of this.', 'start': 386.303, 'duration': 5.263}], 'summary': 'There are eight possible configurations in the neighborhood, prompting the idea of defining outcomes for each configuration.', 'duration': 52.413, 'max_score': 339.153, 'thumbnail': 'https://coursnap.oss-ap-southeast-1.aliyuncs.com/video-capture/W1zKu3fDQR8/pics/W1zKu3fDQR8339153.jpg'}, {'end': 449.8, 'src': 'heatmap', 'start': 412.921, 'weight': 2, 'content': [{'end': 420.003, 'text': 'Now, how many possible rule sets are there? Well, a rule set requires eight binary numbers.', 'start': 412.921, 'duration': 7.082}, {'end': 423.564, 'text': 'Two to the eighth power is 256.', 'start': 421.583, 'duration': 1.981}, {'end': 428.625, 'text': 'That I do happen to know by heart or have memorized or somehow calculated in my head.', 'start': 423.564, 'duration': 5.061}, {'end': 429.425, 'text': "I'm not sure which one.", 'start': 428.645, 'duration': 0.78}, {'end': 434.567, 'text': 'So interestingly enough, there are only 256 possible ways a Wolfram Elementary CA can be defined.', 'start': 430.746, 'duration': 3.821}, {'end': 444.898, 'text': "Which means we can look at very easily if you've got like 15 minutes.", 'start': 439.676, 'duration': 5.222}, {'end': 446.899, 'text': "we can look at if you're not too busy.", 'start': 444.898, 'duration': 2.001}, {'end': 449.8, 'text': 'we can look at all the possible configurations.', 'start': 446.899, 'duration': 2.901}], 'summary': 'There are 256 possible rule sets for wolfram elementary ca, easily viewable in 15 minutes.', 'duration': 47.009, 'max_score': 412.921, 'thumbnail': 'https://coursnap.oss-ap-southeast-1.aliyuncs.com/video-capture/W1zKu3fDQR8/pics/W1zKu3fDQR8412921.jpg'}, {'end': 520.789, 'src': 'heatmap', 'start': 493.911, 'weight': 0.723, 'content': [{'end': 499.595, 'text': 'So you might imagine getting the first two components, the first two classifications.', 'start': 493.911, 'duration': 5.684}, {'end': 506.52, 'text': 'If we look at this and we look at, OK, well, 0, 1, 0 in this system, 0, 1, 0 means you get a 1.', 'start': 499.795, 'duration': 6.725}, {'end': 510.583, 'text': "And let's look at 0, 0, 1 here would give us this value.", 'start': 506.52, 'duration': 4.063}, {'end': 510.964, 'text': '0, 0, 1 gives us a 0.', 'start': 510.603, 'duration': 0.361}, {'end': 511.604, 'text': 'And then 1, 0, 0 gives us a 1.', 'start': 510.964, 'duration': 0.64}, {'end': 513.105, 'text': 'Hey, look at that.', 'start': 511.604, 'duration': 1.501}, {'end': 520.789, 'text': 'We got 0, 1, 1.', 'start': 513.125, 'duration': 7.664}], 'summary': 'Analyzing binary classifications yields 1, 0, 0, 1, and 0, 1, 1 results.', 'duration': 26.878, 'max_score': 493.911, 'thumbnail': 'https://coursnap.oss-ap-southeast-1.aliyuncs.com/video-capture/W1zKu3fDQR8/pics/W1zKu3fDQR8493911.jpg'}, {'end': 606.145, 'src': 'embed', 'start': 576.461, 'weight': 0, 'content': [{'end': 578.682, 'text': 'We also achieve complexity.', 'start': 576.461, 'duration': 2.221}, {'end': 582.383, 'text': 'We achieve this sort of ordered pattern that is unpredictable.', 'start': 578.722, 'duration': 3.661}, {'end': 586.445, 'text': "It's not pure random, but it's also not pure repetition either.", 'start': 582.944, 'duration': 3.501}, {'end': 588.766, 'text': 'We get this intelligent behavior.', 'start': 587.025, 'duration': 1.741}, {'end': 600.49, 'text': 'And this is really interesting, that this really highly computational system produces the type of result that we find in nature.', 'start': 589.086, 'duration': 11.404}, {'end': 606.145, 'text': "So I suppose there's a good argument for why we're looking at this stuff in the first place.", 'start': 601.502, 'duration': 4.643}], 'summary': 'Highly computational system produces intelligent, unpredictable patterns resembling nature.', 'duration': 29.684, 'max_score': 576.461, 'thumbnail': 'https://coursnap.oss-ap-southeast-1.aliyuncs.com/video-capture/W1zKu3fDQR8/pics/W1zKu3fDQR8576461.jpg'}], 'start': 104.08, 'title': 'Cellular automaton characteristics and computation', 'summary': 'Explores the defining characteristics of a cellular automaton, including the simplest scenarios for a one-dimensional grid, set of states, neighborhood, and rules for elementary ca. it also delves into the computation of the next generation in a wolfram elementary ca, involving 256 possible rule sets and achieving uniformity, oscillation, randomness, and complexity.', 'chapters': [{'end': 256.379, 'start': 104.08, 'title': 'Defining characteristics of cellular automaton', 'summary': 'Explores the defining characteristics of a cellular automaton, discussing the simplest possible scenarios for a one-dimensional grid, the set of states, the neighborhood, and the rules for the elementary ca, aiming to achieve complexity through the implementation in code.', 'duration': 152.299, 'highlights': ['The simplest possible scenario for a cellular automaton is a one-dimensional grid with a set of two states, 0 or 1.', 'The simplest possible neighborhood for a cell is defined as the three adjacent cells: the cell itself and its left and right neighbors.', 'The project involves defining the rules for the elementary CA, implementing them in code, and evaluating the achieved complexity in the results.']}, {'end': 600.49, 'start': 256.92, 'title': 'Wolfram elementary ca computation', 'summary': 'Explores the computation of the next generation in a wolfram elementary ca, involving 256 possible rule sets and achieving uniformity, oscillation, randomness, and complexity in the outcomes.', 'duration': 343.57, 'highlights': ['There are 256 possible ways a Wolfram Elementary CA can be defined, involving 256 possible rule sets. The system involves 256 possible rule sets, allowing for a wide range of configurations and outcomes.', "The outcomes are categorized into uniformity, oscillation, randomness, and complexity, showcasing the system's ability to produce intelligent behavior. The outcomes exhibit uniformity, oscillation, randomness, and complexity, demonstrating the system's capability to generate diverse and intelligent patterns.", 'The neighborhood could be configured in eight possible ways, leading to eight possible configurations. The neighborhood offers eight possible configurations, providing a basis for the subsequent computation of outcomes.']}], 'duration': 496.41, 'thumbnail': 'https://coursnap.oss-ap-southeast-1.aliyuncs.com/video-capture/W1zKu3fDQR8/pics/W1zKu3fDQR8104080.jpg', 'highlights': ["The outcomes exhibit uniformity, oscillation, randomness, and complexity, demonstrating the system's capability to generate diverse and intelligent patterns.", 'The project involves defining the rules for the elementary CA, implementing them in code, and evaluating the achieved complexity in the results.', 'There are 256 possible ways a Wolfram Elementary CA can be defined, involving 256 possible rule sets. The system involves 256 possible rule sets, allowing for a wide range of configurations and outcomes.', 'The neighborhood offers eight possible configurations, providing a basis for the subsequent computation of outcomes.', 'The simplest possible scenario for a cellular automaton is a one-dimensional grid with a set of two states, 0 or 1.']}, {'end': 1177.956, 'segs': [{'end': 646.603, 'src': 'embed', 'start': 622.217, 'weight': 2, 'content': [{'end': 630.125, 'text': "I'm going to go over to the example for a second, and I'm going to open it up, and I'm going to run rule 222.", 'start': 622.217, 'duration': 7.908}, {'end': 632.468, 'text': 'So what do I mean when I say rule 222?', 'start': 630.125, 'duration': 2.343}, {'end': 637.153, 'text': 'A great resource that you should take a look at can be found by any Google search,', 'start': 632.468, 'duration': 4.685}, {'end': 642.379, 'text': "but is this page in Wolfram's Math World about elementary subtler automaton?", 'start': 637.153, 'duration': 5.226}, {'end': 646.603, 'text': "automata It's an automaton, and we're talking about many of them, they're automata.", 'start': 642.939, 'duration': 3.664}], 'summary': "Discusses rule 222 and refers to a resource on wolfram's math world about elementary subtler automaton.", 'duration': 24.386, 'max_score': 622.217, 'thumbnail': 'https://coursnap.oss-ap-southeast-1.aliyuncs.com/video-capture/W1zKu3fDQR8/pics/W1zKu3fDQR8622217.jpg'}, {'end': 675.459, 'src': 'heatmap', 'start': 646.823, 'weight': 0.728, 'content': [{'end': 649.225, 'text': 'But look, we can see here, here is a given rule set.', 'start': 646.823, 'duration': 2.402}, {'end': 654.43, 'text': 'If we have three black cells or three cells with a value of one, then we get a zero.', 'start': 649.805, 'duration': 4.625}, {'end': 656.231, 'text': 'If we have one, one, zero, we get a zero.', 'start': 654.71, 'duration': 1.521}, {'end': 657.332, 'text': 'You can see how this is modeled.', 'start': 656.271, 'duration': 1.061}, {'end': 665.336, 'text': 'Now, if we go down, We can see here, this, by the way, is the outcome of every single possible rule.', 'start': 657.372, 'duration': 7.964}, {'end': 673.259, 'text': 'So if we look at hey, rule 88, and again rule 88 is just simply the decimal representation of the binary number 88, which would be 0,, 0, 1, 0, 1,', 'start': 665.556, 'duration': 7.703}, {'end': 675.459, 'text': 'blah, blah, blah, blah.', 'start': 673.259, 'duration': 2.2}], 'summary': 'Modeling a rule set with specific conditions and outcomes.', 'duration': 28.636, 'max_score': 646.823, 'thumbnail': 'https://coursnap.oss-ap-southeast-1.aliyuncs.com/video-capture/W1zKu3fDQR8/pics/W1zKu3fDQR8646823.jpg'}, {'end': 764.361, 'src': 'embed', 'start': 732.209, 'weight': 0, 'content': [{'end': 735.652, 'text': 'The two-dimensional CA is really a grid of cells.', 'start': 732.209, 'duration': 3.443}, {'end': 739.175, 'text': "And each state we're going to look at as a different frame of animation.", 'start': 736.273, 'duration': 2.902}, {'end': 745.22, 'text': 'But this is one generation, right? In the 2D CA, this is a single generation right here.', 'start': 739.215, 'duration': 6.005}, {'end': 746.962, 'text': "Yes? I'm on camera.", 'start': 745.441, 'duration': 1.521}, {'end': 753.889, 'text': 'And this is a one-dimensional CA where each generation is a given row in this pattern.', 'start': 747.423, 'duration': 6.466}, {'end': 755.471, 'text': "So let's take a look.", 'start': 754.27, 'duration': 1.201}, {'end': 764.361, 'text': "And now if we go back to processing here, we're going to see, first of all, I'm representing.", 'start': 755.731, 'duration': 8.63}], 'summary': 'Explaining cellular automata in 1d and 2d grids for generations.', 'duration': 32.152, 'max_score': 732.209, 'thumbnail': 'https://coursnap.oss-ap-southeast-1.aliyuncs.com/video-capture/W1zKu3fDQR8/pics/W1zKu3fDQR8732209.jpg'}, {'end': 812.576, 'src': 'heatmap', 'start': 776.628, 'weight': 4, 'content': [{'end': 780.169, 'text': 'These are some rules I want to take a look at for the different Wolfram classifications.', 'start': 776.628, 'duration': 3.541}, {'end': 782.05, 'text': "So let's run this first one.", 'start': 780.47, 'duration': 1.58}, {'end': 784.971, 'text': 'And we can see, yes, this is what you would expect.', 'start': 782.39, 'duration': 2.581}, {'end': 793.441, 'text': "And in addition to stacking the generations, that I've talked about over here, what I'm doing in this particular scenario is letting them scroll by.", 'start': 785.051, 'duration': 8.39}, {'end': 795.946, 'text': 'So we could see this is uniformity.', 'start': 793.922, 'duration': 2.024}, {'end': 798.671, 'text': 'All the cells just tend to the same state.', 'start': 796.527, 'duration': 2.144}, {'end': 800.594, 'text': "Now let's look at repetition.", 'start': 799.292, 'duration': 1.302}, {'end': 804.069, 'text': 'which rule 190 is an example of.', 'start': 801.687, 'duration': 2.382}, {'end': 805.87, 'text': 'And we can see this.', 'start': 805.03, 'duration': 0.84}, {'end': 812.576, 'text': "Now it looks like, I don't know if you, maybe if I zoom in here a little bit, you can see there are these kind of diagonal lines it looks like.", 'start': 805.91, 'duration': 6.666}], 'summary': 'Wolfram classifications demonstrate uniformity and repetition, exemplified by rule 190, with observable diagonal lines.', 'duration': 35.948, 'max_score': 776.628, 'thumbnail': 'https://coursnap.oss-ap-southeast-1.aliyuncs.com/video-capture/W1zKu3fDQR8/pics/W1zKu3fDQR8776628.jpg'}, {'end': 853.193, 'src': 'embed', 'start': 824.245, 'weight': 5, 'content': [{'end': 826.367, 'text': 'So how is this stuff being calculated?', 'start': 824.245, 'duration': 2.122}, {'end': 828.428, 'text': 'So I want to look little bit.', 'start': 826.647, 'duration': 1.781}, {'end': 832.449, 'text': "I'm going to switch here to the kind of simpler example which is just showing.", 'start': 828.428, 'duration': 4.021}, {'end': 833.289, 'text': 'this is rule 90.', 'start': 832.449, 'duration': 0.84}, {'end': 838.57, 'text': 'I believe which is, by the way, kind of amazing that with this simple system, what is this pattern?', 'start': 833.289, 'duration': 5.281}, {'end': 840.03, 'text': 'this is the Sierpinski triangle.', 'start': 838.57, 'duration': 1.46}, {'end': 844.851, 'text': "it's a fractal pattern which we're going to get into more in future videos or previous videos.", 'start': 840.03, 'duration': 4.821}, {'end': 848.232, 'text': "if you're watching these out of order, okay.", 'start': 844.851, 'duration': 3.381}, {'end': 849.772, 'text': "so what's going on here?", 'start': 848.232, 'duration': 1.54}, {'end': 851.252, 'text': 'the, I you know.', 'start': 849.772, 'duration': 1.48}, {'end': 853.193, 'text': 'I just want to point out a few things.', 'start': 851.252, 'duration': 1.941}], 'summary': 'Discussion on calculating patterns in rule 90 and sierpinski triangle as examples of fractal patterns.', 'duration': 28.948, 'max_score': 824.245, 'thumbnail': 'https://coursnap.oss-ap-southeast-1.aliyuncs.com/video-capture/W1zKu3fDQR8/pics/W1zKu3fDQR8824245.jpg'}, {'end': 898.383, 'src': 'heatmap', 'start': 848.232, 'weight': 1, 'content': [{'end': 849.772, 'text': "so what's going on here?", 'start': 848.232, 'duration': 1.54}, {'end': 851.252, 'text': 'the, I you know.', 'start': 849.772, 'duration': 1.48}, {'end': 853.193, 'text': 'I just want to point out a few things.', 'start': 851.252, 'duration': 1.941}, {'end': 859.166, 'text': 'one is that the, the cells, are represented as an array of integers.', 'start': 853.193, 'duration': 5.973}, {'end': 866.312, 'text': 'so a given generation is an array of integers 0, 1, 0, 1, 1, 0, 1, whatever it is.', 'start': 859.166, 'duration': 7.146}, {'end': 870.235, 'text': 'that is the array that is that generation.', 'start': 866.312, 'duration': 3.923}, {'end': 873.357, 'text': 'this is not my best video.', 'start': 870.235, 'duration': 3.122}, {'end': 880.662, 'text': 'ok, this function here, generate, is the key function for how we get the next generation right.', 'start': 873.357, 'duration': 7.305}, {'end': 888.755, 'text': 'if we have an array of cells right, we have an array of cells, which is this here what do we need to do to get the next generation??', 'start': 880.662, 'duration': 8.093}, {'end': 890.576, 'text': 'We need to make a new array.', 'start': 888.955, 'duration': 1.621}, {'end': 892.979, 'text': 'We have an array of ints for that one generation.', 'start': 890.617, 'duration': 2.362}, {'end': 894.7, 'text': 'We need to make a new array of ints.', 'start': 893.199, 'duration': 1.501}, {'end': 895.541, 'text': 'Here we go.', 'start': 895.08, 'duration': 0.461}, {'end': 897.162, 'text': "We've got a new array of ints.", 'start': 895.741, 'duration': 1.421}, {'end': 898.383, 'text': 'And now, what do we need to do??', 'start': 897.322, 'duration': 1.061}], 'summary': 'Transcript discusses representing cells as an array of integers and generating the next generation.', 'duration': 50.151, 'max_score': 848.232, 'thumbnail': 'https://coursnap.oss-ap-southeast-1.aliyuncs.com/video-capture/W1zKu3fDQR8/pics/W1zKu3fDQR8848232.jpg'}, {'end': 1143.536, 'src': 'embed', 'start': 1119.278, 'weight': 3, 'content': [{'end': 1131.126, 'text': "But the fact that we can see this completely non-repeating pattern from such simple rules that just all you can think about is that we're going to get repetition from them is a really interesting result.", 'start': 1119.278, 'duration': 11.848}, {'end': 1138.735, 'text': 'And at the same time we can also see just from these simple rules, if we go to rule 110,', 'start': 1131.626, 'duration': 7.109}, {'end': 1143.536, 'text': "we can see that we're going to get something that has the properties of a complex system.", 'start': 1138.735, 'duration': 4.801}], 'summary': 'Simple rules produce non-repeating patterns, leading to complex systems.', 'duration': 24.258, 'max_score': 1119.278, 'thumbnail': 'https://coursnap.oss-ap-southeast-1.aliyuncs.com/video-capture/W1zKu3fDQR8/pics/W1zKu3fDQR81119278.jpg'}], 'start': 601.502, 'title': 'Cellular automata and code', 'summary': "Explores one-dimensional cellular automata, including rules, visual representations, and examples like uniformity, repetition, and the sierpinski triangle, using code examples. it also discusses the 'generate' function, updating arrays of cells, and simple rules generating complex patterns.", 'chapters': [{'end': 844.851, 'start': 601.502, 'title': 'Exploring cellular automata in code', 'summary': 'Explores the concept of one-dimensional cellular automata, including the rules, visual representations, and examples of different patterns such as uniformity, repetition, and the sierpinski triangle, utilizing code examples and explanations.', 'duration': 243.349, 'highlights': ['The chapter delves into the concept of one-dimensional cellular automata, discussing rules, visual representations, and patterns like uniformity, repetition, and the Sierpinski triangle. The discussion focuses on the concept of one-dimensional cellular automata, exploring rules, visual representations, and various patterns such as uniformity, repetition, and the Sierpinski triangle.', 'A detailed explanation of rule 222 and its visual representation is provided, demonstrating the application of the rule in the context of cellular automata. The chapter provides a detailed explanation and visual representation of rule 222, showcasing its application within the context of cellular automata.', 'The chapter presents the visual representation of rule 190, highlighting the concept of repetition and showcasing its pattern through a code example. The visual representation of rule 190 is presented, emphasizing the concept of repetition and demonstrating its pattern through a code example.', 'The chapter explores the pattern generated by rule 90, revealing the emergence of the Sierpinski triangle, a fractal pattern. The exploration of the pattern generated by rule 90 unveils the emergence of the Sierpinski triangle, a notable fractal pattern within the context of cellular automata.']}, {'end': 1177.956, 'start': 844.851, 'title': 'Cellular automata: rules and generations', 'summary': "Discusses the key function 'generate' for getting the next generation in a cellular automaton, the process of creating and updating arrays of cells, and the surprising results of simple rules generating complex and non-repeating patterns.", 'duration': 333.105, 'highlights': ["The 'generate' function is crucial for obtaining the next generation in a cellular automaton by creating a new array of integers based on the values of the current generation's cells. The 'generate' function is essential for determining the next generation in a cellular automaton by creating a new array of integers based on the current generation's cell values.", "The process involves creating a new array for the next generation, calculating new values for every cell based on its neighbors, and updating the cells array with the new generation's values. The process encompasses creating a new array for the next generation, computing new values for each cell based on its neighbors, and updating the cells array with the new generation's values.", "Simple rules in cellular automata can yield surprising results, such as generating complex and non-repeating patterns, showcasing the system's ordered yet unpredictable nature. Simple rules in cellular automata can produce unexpected outcomes, including complex and non-repeating patterns, demonstrating the system's ordered yet unpredictable nature."]}], 'duration': 576.454, 'thumbnail': 'https://coursnap.oss-ap-southeast-1.aliyuncs.com/video-capture/W1zKu3fDQR8/pics/W1zKu3fDQR8601502.jpg', 'highlights': ['The chapter explores the concept of one-dimensional cellular automata, discussing rules, visual representations, and patterns like uniformity, repetition, and the Sierpinski triangle.', "The 'generate' function is crucial for obtaining the next generation in a cellular automaton by creating a new array of integers based on the values of the current generation's cells.", 'A detailed explanation of rule 222 and its visual representation is provided, demonstrating the application of the rule in the context of cellular automata.', "Simple rules in cellular automata can yield surprising results, such as generating complex and non-repeating patterns, showcasing the system's ordered yet unpredictable nature.", 'The chapter presents the visual representation of rule 190, highlighting the concept of repetition and showcasing its pattern through a code example.', 'The exploration of the pattern generated by rule 90 unveils the emergence of the Sierpinski triangle, a notable fractal pattern within the context of cellular automata.']}], 'highlights': ["The outcomes exhibit uniformity, oscillation, randomness, and complexity, demonstrating the system's capability to generate diverse and intelligent patterns.", 'The history of cellular automata is traced back to the work of John von Neumann and Stanislaw Ulam in the 1950s, and later, the controversial concepts of Stephen Wolfram are emphasized.', 'The project involves defining the rules for the elementary CA, implementing them in code, and evaluating the achieved complexity in the results.', 'The chapter explores the concept of one-dimensional cellular automata, discussing rules, visual representations, and patterns like uniformity, repetition, and the Sierpinski triangle.', 'There are 256 possible ways a Wolfram Elementary CA can be defined, involving 256 possible rule sets. The system involves 256 possible rule sets, allowing for a wide range of configurations and outcomes.', 'The neighborhood offers eight possible configurations, providing a basis for the subsequent computation of outcomes.', "The 'generate' function is crucial for obtaining the next generation in a cellular automaton by creating a new array of integers based on the values of the current generation's cells.", "Stephen Wolfram's principle emphasizes the relevance of computational thinking in all forms of science, sparking controversy about the nature of science.", 'A detailed explanation of rule 222 and its visual representation is provided, demonstrating the application of the rule in the context of cellular automata.', "Simple rules in cellular automata can yield surprising results, such as generating complex and non-repeating patterns, showcasing the system's ordered yet unpredictable nature."]}