├── .gitignore ├── screenshot.png ├── pyproject.toml ├── salience ├── __init__.py ├── salience.py └── static │ └── index.html ├── README.md ├── transcript.txt └── poetry.lock /.gitignore: -------------------------------------------------------------------------------- 1 | __pycache__ 2 | -------------------------------------------------------------------------------- /screenshot.png: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/mattneary/salience/HEAD/screenshot.png -------------------------------------------------------------------------------- /pyproject.toml: -------------------------------------------------------------------------------- 1 | [tool.poetry] 2 | name = "salience" 3 | version = "0.0.0" 4 | description = "" 5 | authors = ["Matt Neary "] 6 | license = "MIT" 7 | readme = "README.md" 8 | 9 | [tool.poetry.dependencies] 10 | python = "^3.11" 11 | flask = "^2.3.2" 12 | transformers = "^4.30.2" 13 | nltk = "^3.8.1" 14 | sentence-transformers = "^2.2.2" 15 | numpy = "^1.25.0" 16 | 17 | 18 | [build-system] 19 | requires = ["poetry-core"] 20 | build-backend = "poetry.core.masonry.api" 21 | -------------------------------------------------------------------------------- /salience/__init__.py: -------------------------------------------------------------------------------- 1 | from flask import Flask 2 | import numpy as np 3 | from .salience import extract 4 | import json 5 | 6 | app = Flask(__name__) 7 | 8 | with open('./transcript.txt', 'r') as file: 9 | source_text = file.read().strip() 10 | sentence_ranges, adjacency = extract(source_text) 11 | 12 | @app.route("/salience") 13 | def salience_view(): 14 | return json.dumps({ 15 | 'source': source_text, 16 | 'intervals': sentence_ranges, 17 | 'adjacency': np.nan_to_num(adjacency.numpy()).tolist(), 18 | }) 19 | -------------------------------------------------------------------------------- /README.md: -------------------------------------------------------------------------------- 1 | # salience 2 | 3 | > In short, a graph-based ranking algorithm is a way of deciding on the 4 | > importance of a vertex within a graph, by taking into account global 5 | > information recursively computed from the entire graph, rather than relying 6 | > only on local vertex-specific information ... In this paper, we introduced 7 | > TextRank – a graph-based ranking model for text processing. 8 | > 9 | > (Rada Mihalcea and Paul Tarau, "TextRank: Bringing Order into Texts", 2004) 10 | 11 | Extractive summarization should be preferred over abstractive summarization 12 | when nuance is essential and when the summary is meant as a companion to the 13 | source text. LLMs are effective at abstractive summarization, but they can also 14 | be leveraged in extractive summarization. Rather than solve this with a prompt, 15 | LLM embeddings can be combined with the TextRank algorithm to reliably yield 16 | high-quality extractive summaries. 17 | 18 | In other words, embeddings can be used to automatically generate highlights. The 19 | internal representation is an affinity matrix between sentences that can be used 20 | to find the most salient sentences in a text. 21 | 22 | ## Preview 23 | 24 | ![Screenshot of Salience Output](screenshot.png) 25 | 26 | ## How to Run 27 | 28 | ```sh 29 | $ poetry install 30 | $ poetry run flask --app salience run 31 | ``` 32 | 33 | This will kick off a flask server. You can access the output at `http://127.0.0.1:5000/static/index.html` 34 | -------------------------------------------------------------------------------- /salience/salience.py: -------------------------------------------------------------------------------- 1 | import numpy as np 2 | import torch 3 | from sentence_transformers import SentenceTransformer 4 | import nltk.data 5 | import nltk 6 | 7 | nltk.download('punkt') 8 | 9 | model = SentenceTransformer('all-mpnet-base-v2') 10 | sent_detector = nltk.data.load('tokenizers/punkt/english.pickle') 11 | 12 | def cos_sim(a, b): 13 | sims = a @ b.T 14 | a_norm = np.linalg.norm(a, axis=-1) 15 | b_norm = np.linalg.norm(b, axis=-1) 16 | a_normalized = (sims.T / a_norm.T).T 17 | sims = a_normalized / b_norm 18 | return sims 19 | 20 | def degree_power(A, k): 21 | degrees = np.power(np.array(A.sum(1)), k).ravel() 22 | D = np.diag(degrees) 23 | return D 24 | 25 | def normalized_adjacency(A): 26 | normalized_D = degree_power(A, -0.5) 27 | return torch.from_numpy(normalized_D.dot(A).dot(normalized_D)) 28 | 29 | def get_sentences(source_text): 30 | sentence_ranges = list(sent_detector.span_tokenize(source_text)) 31 | sentences = [source_text[start:end] for start, end in sentence_ranges] 32 | return sentences, sentence_ranges 33 | 34 | def text_rank(sentences): 35 | vectors = model.encode(sentences) 36 | adjacency = torch.tensor(cos_sim(vectors, vectors)).fill_diagonal_(0.) 37 | adjacency[adjacency < 0] = 0 38 | return normalized_adjacency(adjacency) 39 | 40 | def terminal_distr(adjacency, initial=None): 41 | sample = initial if initial is not None else torch.full((adjacency.shape[0],), 1.) 42 | scores = sample.matmul(torch.matrix_power(adjacency, 10)).numpy().tolist() 43 | return scores 44 | 45 | def extract(source_text): 46 | sentences, sentence_ranges = get_sentences(source_text) 47 | adjacency = text_rank(sentences) 48 | return sentence_ranges, adjacency 49 | 50 | def get_results(sentences, adjacency): 51 | scores = terminal_distr(adjacency) 52 | for score, sentence in sorted(zip(scores, sentences), key=lambda xs: xs[0]): 53 | if score > 1.1: 54 | print('{:0.2f}: {}'.format(score, sentence)) 55 | -------------------------------------------------------------------------------- /salience/static/index.html: -------------------------------------------------------------------------------- 1 | 2 | 3 | 4 | 5 | Salience 6 | 7 | 50 | 51 | 52 |

53 | Salience 54 | automatic sentence highlights based on their significance to the document 55 |

56 |

57 | 118 | 119 | 120 | -------------------------------------------------------------------------------- /transcript.txt: -------------------------------------------------------------------------------- 1 | Social reality might not be a video game, but there’s no point trying to imagine that. Crass realism obscures the rules. Besides, society converges upon a video game – or immersive ludic simulation – even if it isn’t one already. Such gamification is a trend to note. It has multiple drivers. 2 | 3 | As games get more convincing, they increasingly set the default perceptual frame. In technologically-advanced societies, game-like systems are becoming the obvious model for self-understanding. The reception for stories with this slant continuously improves. Even scientific theorizing is drawn to them. The topic might seem less than serious, even definitively so, but ultimately it isn’t. Alternatively, it might be said that there is a non-seriousness more serious than seriousness itself. Everything will be gamified. 4 | 5 | In the epoch of WMD deterrence, unlimited warfare is not allowed to happen. Instead, it is perpetually simulated. Every serious military establishment becomes a set of war-games in process. From the peak of virtual thermonuclear spasm, war-gaming cascades down through the apparatus of conventional war-fighting capability, and then spreads outwards – like a blast-wave – through every civilian forum of institutional planning. Eventually (but already) to have been ‘war-gamed’ just means to have been thought through. A war-game is less serious than a war, but it’s the most serious way to process things when war is off the table. It’s also – from its inception – the way to keep war off the table. Si vis pacem, para bellum, which means playing it out. 6 | 7 | That everything would be gamified was decided during the pre-history of computing, at the latest. The potential to simulate anything, which is only to say emerging artificial intelligence, leaves nothing that cannot be folded into a game, given time. 8 | 9 | In their take-off phase, at least, machines demand strict rules, responding well only to precise instructions. They dissipate fog or, more precisely, motivate its dissipation. The world adjusts to machine intelligence by sharpening its definition. Formalization acquires precise practical criteria. 10 | 11 | Anything that trains an AI has to function as a game. This is because playing games is the only thing AI can ever do. For synthetic intelligence to be applied to a problem, of any kind, it has to be gamified. Then strategies can be pursued, in strict compliance with rules, to maximize success. Optimization games are the only kind that exist, and inversely. 12 | 13 | While games are made, or adopted, for AI to play in, games incorporate AIs into themselves, as components. Simply making games that work requires computer game companies to nurture a semi-independent machine intelligence lineage of their own. Playing against AIs, and also alongside them, is ever increasingly what gamers do. This is what the ‘single player’ option abbreviates, most obviously. The antisocial path stimulates nonlinearity on the side of the machine. Machine intelligence escalation twists into an ever tighter loop, continually intensifying, as it plays games against itself, and against anyone else who wanders in to challenge it. 14 | 15 | The games that are relentlessly improving – the kind ‘gamers’ play – are competition for society. They provide an alternative to traditional modes of social involvement. Japanese ‘otaku’ pioneered these paths of departure. Wherever technology crests, the world follows them. Advance tends to exit. 16 | 17 | ‘Incel’ – or ‘involuntary celibate’ – is in some ways a misleading term for what is happening here. The condition of fundamental social alienation described is no more ‘involuntary’ than any other opt-out. The ‘incel gamer’ no longer finds the most basic of all traditional social relations worth it. There are better games. The revealed preference is evident regardless of what might be said. They grasp games as a way to leave. 18 | 19 | At the same time, the PUAs – or ‘pick-up artists’ – have been pulling everything apart from the opposite direction. If they have a bible it is Neil Strauss’s The Game. Rather than abandoning mating for games, the PUAs gamify mating. 20 | 21 | Turning it into a game is the first step to becoming good at it. In the same way, war is ‘the game of princes’. Everything is a game to those who are good at it, and as a condition of them coming to be good at it. This is the serious non-seriousness previously touched upon. Excellence has ludic foundations. Play or be played, as it is cynically said. 22 | 23 | How could it not become ever more obvious that ‘Gamergate’ had to happen? If non-Wokeness in the gaming industry had never been an issue, it would be a sign that nothing of importance was taking place there. In reality, it could not be left alone because it was destined to eat everything. The topic was seriously non-serious, as the GameStop short-squeeze was more recently. 24 | 25 | Good or well-constructed games have a number of characteristic features. 26 | 27 | Firstly, they can only be played by the rules. Cheating is forbidden less than it is made impossible. Physics is like this. It proscribes nothing that can be done (as Crowley notoriously noticed). Rules that can be broken are a failure of game design. The more impractical it is to cheat, the better the game. 28 | 29 | Secondly, they have an implicit meta-rule that strictly prohibits changing the rules. To change the rules is to invent a new game, which cannot be done during play. Different games, with different rules, coexist simultaneously, rather than replacing each other successively. 30 | 31 | Thirdly, rule sets permit outcomes, without ever dictating them. Rules and strategies are mutually independent. Strategies compete within the rules, rather than over them. Strategic modification of rules, or the adaptation of rules to strategy, is essentially corrupt. 32 | 33 | Fourthly, each is fully enveloped by some consistent incentive structure. This renders success and failure unambiguous, grading performance. The players always know how it went. 34 | 35 | The ‘games’ favored by game theorists, such as variants of the prisoner’s dilemma, compose a small subset of such well-constructed games. They cannot be transcended by cheating. Game modification is never a permitted move. They permit no legislative power. Each has a single reward dimension. 36 | 37 | The breadth of application suggests these constraints are not difficult to meet. It might even seem that any alternative to a well-constructed game is anomalous in its degeneracy. 38 | 39 | To be a progressive is to be in favor of changing the rules. There is one ‘arc of history’ and it is made of reforms. Old rules and structures of oppression are considered broadly identical. 40 | 41 | A conservative is against changing the rules. If they are changed, they stay changed, because changing them back would still count as change. Thus the much derided function of conservatism as anchor for the progressive ratchet. 42 | 43 | A reactionary holds that the rules should never have been changed. Reaction would delight in restoring old rules, were it ever in a position to do so. It never is, and will never be. 44 | 45 | A neoreactionary accepts experimental variation in rules only when rule sets are multiplied. New rules are to be tolerated only alongside, in addition to, and as a concurrent alternative to old rules. They are legitimated only by hard forks. Anything else is progress, which is in all cases misfortune. 46 | 47 | Progress is reform without schism. While wrapping itself in the mantle of science, it incarnates a drastic violation of scientific method. Positive or negative characterizations of ‘progressive experiments’ are equally misleading. Progressive change is not experimental, but rather something closer to the opposite. It substitutes for testing, and disdains controls. Synchronic comparison is deliberately suppressed, and the more thorough the suppression the more progressive it is. Multiplication without difference is bad, but difference without multiplication is worse. 48 | 49 | In a corrupt society, or bad social game, the ruling class makes rules. There is nothing natural about this, regardless of what we are told. It is only in the wake of a radical socio-cultural calamity that it happens. 50 | 51 | In any well-constructed game, winning is entirely distinct from re-writing the rules. For instance, a speculative investor – however successful – does not modify the functioning of the stock market, any more than a chess master takes advantage of each victory to change the way pieces move. 52 | 53 | Capitalism, as a game, works well when businesses follow economic rules they have no role in formulating. Even in the political sphere, comparatively stable constitutional principles and norms are expected to conserve themselves resiliently through vicissitudes of party conflict. This point might confidently be strengthened. Invulnerability of political rules-of-the-game to party fortune is regime stability. The contrary condition, in which party dominance overwhelms political rules and permits the dictation of new ones, defines revolution. Competition within rules is politics, but competition to set rules is war. When politics seems more like war than it used to, this is why. 54 | 55 | The common law tradition permits no legislation. Laws are discovered, never made. The notion of law-making is abominable, and inconsistent with the existence of a free people. According to the only truly English position, legislation is always and essentially tyranny. 56 | 57 | Optimally, the rule of law is a pleonasm. It means only that the rules rule. Nothing could be more inevitable. 58 | 59 | ‘Algorithmic governance’ says roughly the same. Yet under conditions of fundamental social corruption the ‘rule of law’ appears closer to an oxymoron. Is it not always men who in fact rule, with rules as their instrument? If so, formal procedure is mostly mystique. Yet this question is itself an index of decadence. Only when a game is already broken does it appear so lacking in authoritative constraint. 60 | 61 | America is a game so badly broken the world is positively awe-struck by it. Its hegemony ensures that everyone has to care. Most of the planet finds itself sucked into a game whose formal rule set is a chaotic cancerous mess. 62 | 63 | When America had a frontier, it was a land of real experiments. New games of all kinds were explored, in parallel. The national heritage of schismatic religion meant different rules applied in different places. From the mid- to late-Nineteenth Century, hardening of the Union and the closing of the frontier brought religious, moral, and political consolidation. American experiments entered their twilight, and The American Experiment was celebrated, integrally, which was no experiment at all, but only progress. 64 | 65 | ‘Never change the rules’ is an example of a good meta-rule. What, then, exemplifies a bad one? ‘We should all be playing the same game’ is probably the very worst. At least, nothing more sinister can easily be conceived. 66 | 67 | We don’t like the same games. More particularly, we don’t all like the kind of domination game that requires everyone to play the same game, even if some like it a lot. The ‘game industry’ has an abundance of practical evidence on ludic preference diversity, far exceeding what is required to make the basic point. We want to play different games is the basic point. Despite its overwhelming obviousness, getting it installed as a default is surprisingly difficult. In part, this is Social Domination game-play at work. 68 | 69 | There are people who dislike chess. There are many more who don’t like it enough to play it continuously, and exclusively. Chess, nevertheless, is a well-constructed game. No one is disgraced by their dedication to it. 70 | 71 | Social Domination is a contender for the worst-constructed game in history. “Let’s keep changing the rules until everybody likes it,” it suggests tacitly. It simultaneously makes other suggestions which directly contradict this, but never to the point of ensuring its retraction. As if this were not already bad enough, it also mandates universal cheating. Its rules are so numerous, unstable, and poorly-formulated that they are both theoretically and practically unintelligible. The latitude with which rule-violations are to be avoided or penalized has become a strategic consideration. Players in weak positions have to scrupulously avoid gross rule-violations and are increasingly terrorized by trivial, absurd, and informal norms. Players in strong positions get to ignore any rules they don’t like. 72 | 73 | The best Social Domination players get to decide whether to permit opt outs from Social Domination. The incentive effects here are entirely predictable. However much you hate the game, you have to win it to escape. Those who like it are far more likely to do well at it. On the rare occasions when those who don’t like it do well, they suddenly find they like it more than they had thought, or have invested too much in it to quit. To escape it means fighting it, which means playing it, which means investing in it. Getting out involves putting people into a position from which they can get you out, and that position turns out to be a lot more comfortable than either getting out, or letting anyone else out. These dynamics are clear to everyone. 74 | 75 | As it all becomes ever more obvious, cynicism explodes. No one is any longer really fooled by the thinly-stretched, saccharine, hysterical idealism. It’s all power and who-whom, as the practitioners of Cultural Revolution are the first to admit. “We’re fucking you, and we get to call it good, because we’re winning, and you’re not.” That’s the whole of it. For anyone who thinks Social Domination is a great game to play, it makes more sense than it ever has. There are many such people. They’re not going away. 76 | 77 | “Is it time yet?” 78 | 79 | “It’s a bit later actually.” 80 | 81 | “It’s a bit later than now? Or now’s a bit later than it?” 82 | 83 | It’s time to war-game getting the hell out, and away from them. The technological platforms for it are almost in place. Begin to use them, and they’ll arrive faster. It’s all been set up in a way that can’t be stopped. The games industry is the template. 84 | 85 | Any exit ramp that looks serious is fake. Social Domination manages serious threats easily, making them actually non-serious. Such ‘challenges’ fall under its rules, dialectically, and merely make it bigger. There’s no way to seriously oppose it without playing into it. 86 | 87 | Any real exit has to be seriously non-serious. Game it out. Play another, different game on the side, shifting everything steadily to the side. Migrate intelligence-capital onto a million ludic frontiers, where exit hatches. No one will take it seriously until it’s too late. 88 | 89 | It’s getting ever easier to try things out inside games. Any kind of plotting that doesn’t take this route will soon seem obsolete. 90 | 91 | The means of simulation do not need to be seized, but they do need to be proliferated. 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