Knowledge Graph Quotes

The truth is staggering, colossal, unfathomable, so we cling to our bite-sized lies. We organize knowledge into bulleted lists and line graphs while the wisdom of the present moment sits patiently at the doors of our perception. Tackling

Some people engage in retail therapy, buying new things to make themselves feel more secure, and others engage in knowledge therapy, amassing new ideas to make themselves feel like they know something. We consume for comfort. We rely on certainty to shield us from the pain of confusion. The truth is staggering, colossal, unfathomable, so we cling to our bite-sized lies. We organize knowledge into bulleted lists and line graphs while the wisdom of the present moment sits patiently at the doors of our perception.

Our current long-term vision at LinkedIn is to extend this professional graph into an economic graph by digitally manifesting every economic opportunity [i.e., job] in the world (full-time and temporary); the skills required to obtain those opportunities; the profiles for every company in the world offering those opportunities; the professional profiles for every one of the roughly 3.3 billion people in the global workforce; and subsequently overlay the professional knowledge of those individuals and companies onto the “graph” [so that individual professionals could share their expertise and experience with anyone]. Anyone

Even then, I was dreaming of Raistlin's black robes one moment, and Dorsett's spin move the next. This was what my father deeded--that our Knowledge of Self be more than America, that we understand the brain death that sprawled from the projects to the subdivisions. Consciousness was a beginning, but the imagination could turn straight 18s into paladins in plate, could make warrens in tunnels from graph paper, could pull armies of gnolls from miniatures--that was the Knowledge that ultimately would find a way out.

Search engines and social networks are analog computers of unprecedented scale. Information is being encoded (and operated upon) as continuous (and noise-tolerant) variables such as frequencies (of connection or occurrence) and the topology of what connects where, with location being increasingly defined by a fault-tolerant template rather than by an unforgiving numerical address. Pulse-frequency coding for the Internet is one way to describe the working architecture of a search engine, and PageRank for neurons is one way to describe the working architecture of the brain. These computational structures use digital components, but the analog computing being performed by the system as a whole exceeds the complexity of the digital code on which it runs. The model (of the social graph, or of human knowledge) constructs and updates itself.

Fifteen of his clubs, dedicated to politics, music, and the performing arts, had all been developing strategic plans for the past two years. And the local branches of various societies--whose goals were to advance aviation, knowledge of chemistry, automotive transportation, equestrian sports, highway construction, as well as the prompt eradication of ethnic chauvinism--existed only in the sick imagination of the local union committee. As for the school of continuing education, of which Sardinevich was especially proud, it was constantly reorganizing itself, which, as anybody knows, means it wasn't undertaking any useful activity whatsoever. If Sardinevich were an honest man, he would probably have admitted that all these activities were essentially a mirage. But the local union committee used this mirage to concoct its reports, so at the next level up nobody doubted the existence of all those musico-political clubs. At that level, the school of continuing education was imagined as a large stone building filled with desks, where perky teachers draw graphs that show the rise of unemployment in the United States on their chalkboards, while mustachioed students develop political consciousness right in front of your eyes.

You are familiar with The Decline of the West, in which Oswald Spengler takes note of the current decadence of painting, as well as literature and music, and concludes that the end of our cultural epoch has arrived. He is a philosopher, but one descended from the natural sciences. He arranges observations, he records insights and knowledge. He takes a graphic view of history. And if he sees that a line curves downward, he considers the trend a proven fact, so that zero must be reached at a particular time and place. And that moment represents the end, the decline of the West! "But his graphing has no bearing on any of my ideas and plans as architect and politician. I study the reasons why the line curves downward, and I try to remove the causes. But at the same time, I examine the reasons why at an earlier time the line curved upward! And then I set out to restore the conditions of that day, to awake anew the creative wall of that time, and to bring about a new crest in the constantly fluctuating curve of history. "No doubt about it! Our culture has entered on stagnation, it looks like old age. But the reasons for this state do not lie in the fact that it has genuinely passed its manhood, but rather that the upholders of this culture, the Germanic-European peoples, have neglected it and have turned their attention to material tasks, to technology, industry, to hunger for material possessions, to rapacity, and to an economic egocentrism that overwhelms everything else. All their thinking and striving reaches its only climax in account books and in the outward show of the worldly goods they possess. "I am overcome with disgust, a vexing scorn, when I see the way such people live and behave! [ . . . ] But thank God, it is only the top ten thousand who think along these lines. It is true that the whole of the bourgeoisie is already strongly infected and sickly. But bourgeois youth are still healthy and can be shown the way back to nature, to a higher development, to new cultural will, provided only that they do not become enmeshed in the treadmill of meaningless and wholly materialistic contemporary life, only to drown either in the cupidity of business or in the tedium of the middle-class workaday routine or in the corruption of the big city. “If we succeed in replacing the egocentric cupidity of business with a socialist communal wall and a work-affirming responsibility for the common-weal; in abolishing the tedium of middle-class workaday monotony by substituting for it the potential enjoyment of personal liberty, the beauty of nature, the splendor of our own Fatherland and the thousandfold diversity of the rest of the world; and if we put an end to the corruption of omnipresent degeneracy, bred in the warrens of buildings and on the asphalt streets of the cities of millions - then the road is clear to a new life, to a new creative will, to a new flight of the free, healthy spirit and mind. And then, my dear Herr Roselius, your bricks will form themselves into entirely new shapes all by themselves. Temples of life will be built, cathedrals of a higher cult will be raised, and even thousands of years later, the walls will bear witness to the exalted times out of which even more exalted ones were bom!” When Roselius had left Hitler’s room with me, he took my hand and said: “Wagener, I thank you for having made this hour possible. What a man! And how small we feel, concerned as we are with those things that preoccupy us! But now I know' what I have to do! In spite of my sixty years, I have only one goal: to join in the work of helping the young people and the German Volk to find internal and external freedom!

Getting scientists to consider the validity of Indigenous knowledge is like swimming upstream in cold, cold water. They've been so conditioned to be skeptical of even the hardest of hard data that bending their minds toward theories that are verified without the expected graphs or equations is tough. Couple that with the unblinking assumption that science has cornered the market on truth and there's not much room for discussion.

Take, for example, the enduring challenge in analytics of combining data from disparate sources and have it make some sort of sense. Perhaps I’m a simpleton, but just framing it that way makes me immediately respond, “meaningfully combining data from heterogeneous sources is a knowledge graph’s main value proposition.”  And while there’s other means of combining those bits, the semantics allow you to both describe those connections, and to enduringly connect that data rather than endlessly transforming it.

There are also books that contain collections of papers or chapters on particular aspects of knowledge discovery—for example, Relational Data Mining edited by Dzeroski and Lavrac [De01]; Mining Graph Data edited by Cook and Holder [CH07]; Data Streams: Models and Algorithms edited by Aggarwal [Agg06]; Next Generation of Data Mining edited by Kargupta, Han, Yu, et al. [KHY+08]; Multimedia Data Mining: A Systematic Introduction to Concepts and Theory edited by Z. Zhang and R. Zhang [ZZ09]; Geographic Data Mining and Knowledge Discovery edited by Miller and Han [MH09]; and Link Mining: Models, Algorithms and Applications edited by Yu, Han, and Faloutsos [YHF10]. There are many tutorial notes on data mining in major databases, data mining, machine learning, statistics, and Web technology conferences.

One of King Hussein’s skeptical advisers had warned him “to expect a half-baked presentation” at the C.I.A. The spy agency briefers would cloak their lack of knowledge about the internal situation in Iraq “through the use of elaborate graphs, charts, and presentational aids.” Even in these early days of PowerPoint’s hegemony over Washington, an overload of colorfully designed but cluttered and questionably relevant information was a common feature of intelligence briefings.

Knowledge Graphs (KGs) provide ways to efficiently organize, manage and retrieve this type of information, and are increasingly used as an external source of knowledge for problems like recommender systems, language modeling [2], question answering or image classification.

Case Study: DXC Technology

Figure 2.1 Cortical connections over two years adapted from Conel The top row shows the baby’s cortex at birth, then at one month and at three months. They all look about the same, don’t they? But look what happens at six months (bottom left box): the number of cell bodies remains the same, but the number of connections has multiplied exponentially. The connections grow so quickly in the first three years of life that neuroscientists call it neural exuberance. Neural exuberance! The name is well earned: The baby’s brain makes 24 million new connections every minute, and this continues for the first three years of life. Each neuron may be connected to 1,000 other neurons — that multiplies out to 100 trillion possible connections between neurons, more than the number of stars in the universe. This high level of connectivity between brain cells leads to the cortex of a three-year-old being twice as thick as an adult’s! As connections are created, new abilities emerge. For example, when connections grow in Broca’s area — speech production — around six months, then children begin to speak. Around nine months of age, the frontal areas (behind the forehead) become more interconnected, and that’s when most children develop object permanence: knowing that objects continue to exist even when they are out of sight. Before object permanence develops, when Mom is out of sight she’s no longer in the baby’s universe. This is why young babies are inconsolable when Mom leaves. Once they start to develop object permanence, babies can hold on to an internal image of Mom. This is about the age that babies play peek-a-boo. Mom disappears when she puts the blanket over her head, but the nine-month-old knows Mom’s still there even if he can’t see her. The infant tests his “knowledge” when he pulls the blanket off and sees — sure enough! —Mom really is there! What is the use of so many brain connections in the first three years of life? These connections are ready-made highways for information to travel along. The toddlers’ ability to quickly adapt and learn is possible because they have a vast number of brain connections available for making sense of the world. Thanks to neural exuberance, the child does not need to create connections on the spur of the moment to make meaning of each new experience; myriad connections are already there. Pruning of connections The number of connections remains high from age 3 until age 10, when the process of neural pruning begins. Connections that are being used remain; others get absorbed back into the neuron. It’s similar to pruning a bush. After pruning, individual branches get thicker, fruit is more abundant, and the whole bush gets fuller. This seems a little counter-intuitive, but pruning works because it allows the plant’s limited resources to go to its strongest parts; water and nutrients are no longer wasted on spindly branches and dried-out roots. Similarly, when unused brain connections are pruned, neural resources are more available for brain areas that are being used. This results in a more useful and efficient brain that’s tailor-made to meet each individual’s needs. This process of pruning occurs in all brain areas. Figure 2.2 presents findings published by Sowell and associates. They measured Magnetic Resonance Imaging in 176 normal subjects from age 7 to 87 years. The x-axes in these graphs present years from 10 to 90 years. Notice there is a common pattern of decreasing connections in all brain areas. In some brain areas this change is steeper, such as in frontal areas, but is flatter in other areas such as temporal areas in the left hemisphere.

Two dots on a graph can be identical, but they still have different coordinates.

Google’s semantic search is the first step toward a search engine that is like Star Trek’s onboard computer and the brains of that semantic search is what Google calls the Knowledge Graph. The word “Graph” here has been taken from mathematics but in this context it was coined by Facebook’s founder and CEO, Mark Zuckerberg, who used it to express the social network of relationships within Facebook’s digital boundaries. He called it the Social Graph.

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Biological systems are a chemical inevitability in the right circumstances. There is, of course, something special about life—I won’t take that away from it—but it is a chemical process, a dynamic, kinetic stability that exists, as your scientists have said, “far from thermodynamic equilibrium.” You don’t have to understand this or believe me, but life is fairly common in both time and space. It is not special, nor is it particularly fragile. The best measure I have of the size and complexity of a biosphere is calories of energy captured per square meter per year. Higher is more impressive, and always more beautiful, but this measures nothing of the creation of a system like humanity. For that, my awakened mind categorizes systems by bytes of information transmitted. This will sound to you like it’s a relatively new phenomenon on your planet, but it’s not. Even pelagibacter transmit information, if only to daughter cells. Ants spray pheromones, bees dance, birds sing—all of these are comparatively low-bandwidth systems for communication. But your system caused an inflection point. The graph of data flow switched from linear to exponential growth. Maybe you would call this system “humanity,” but I wouldn’t. It is not just a collection of individuals; it is also a collection of ideas stored inside of individuals and objects and even ideas inside ideas. If that seems like a trivial difference to you, well, I guess I can forgive you since you do not know what the rest of the universe looks like. Collections of individuals are beautiful, but they are as common as pelagibacter. Collections of ideas are veins of gold in our universe. They must be cherished and protected. My parents, whoever and whatever they were, gave me knowledge of many systems—it was locked in my code before I was sent here to self-assemble—and the only thing I can tell you about systems like yours is that they are rare because they are unstable. Dynamite flows through their veins. A single solid jolt and they’re gone. If my data sets are accurate, you are rare, fragile, and precious.

Of course, “conventional wisdom” at the time held that there could never be a pickup in demand for homes. Instead, most people were convinced that the American dream of home ownership was over; demand for homes would remain depressed forever; and thus the overhang of unsold homes would be absorbed only very slowly. They cited the trend among young people — having been burnt by the collapse of the housing and mortgage bubbles — to rent rather than buy, and as usual they extrapolated it rather than question its durability. As in so many of the examples in this book, for most people, psychology-driven extrapolation took the place of an understanding of and belief in cyclicality. It was clear to me and my Oaktree colleagues, from the graph and from our knowledge of the data behind it, that because the greatest economic crash in almost eighty years had halted additions to the housing supply, home prices could recover strongly if there was any material increase in demand. And, rejecting conventional wisdom, we were convinced that housing demand would prove cyclical as usual, and thus would pick up sometime in the intermediate-term future. This conclusion — supported by other data and analysis — contributed to our decision to invest heavily in non-performing home mortgages and non-performing bank loans secured by land for residential construction, and to purchase North America’s largest private homebuilding company. These investments worked out quite well. (It’s interesting in this context to note what the Wall Street Journal said in a May 12, 2017 article headlined “Generation of Renters Now Buying”: “In all [first-time home buyers] have accounted for 42% of buyers this year, up from 38% in 2015 and 31% at the lowest point during the recent housing cycle in 2011.” So much for extrapolating widespread abandonment of home ownership.)

Legislate is a legal technology company founded in Oxford in 2020 which makes it easy for non-lawyers to safely create, manage and search lawyer-approved contracts. Legislate makes contracts machine readable using patented knowledge graph technology so that contracts can be created, managed and searched at scale. By making contracts machine readable, Legislate is enabling a new category of smart, open contracts which know what they contain and how they connect with third party systems and services such as payroll and pensions for example. Legislate is used by fast growing businesses and scale ups to create and track contract data for employment and commercial contract use cases.