[S3E5] Learning Curve
The SGC agrees to an information exchange with the technologically advanced planet Orban, but the team discovers a sinister truth about what the Orbanians do with their children."Learning Curve" provides examples of the following tropes: Adorably Precocious Child: Merrin is eleven years old and an expert on naquadah reactors but has no understanding of concepts such as 'fun'.
Bittersweet Ending: Merrin is put through the Averium and her old personality is lost, but the knowledge that she gained on earth about having fun is absorbed by all the other Orbanians so that she and the rest of the children are now able to play games and think creatively.
Blue-and-Orange Morality: Calen genuinely doesn't see anything wrong with absorbing the knowledge of the children and can't understand why the team are outraged by it, as it's the only method of learning they know.
Child Prodigy: All of the chosen Orbanian children are this due to having nanites implanted in their brains in infancy that increase their capacity for learning.
Death of Personality: Because the children receive their nanites before their neural pathways have formed, the process of removing them during the Averium reduces them to an infant-like state where they have no memory of their former lives.
Friend to All Children: O'Neill is the most disgusted of all the characters after finding out just what exactly the Orbanians do with their children and decides to take Merrin to the surface to give her a taste of what she's missing out on.
Going Critical: Lampshaded when Carter tests the naquadah reactor she manages to build with Merrin's help. It doesn't do anything dangerous, but it emits a pulse of harmless energy that sets the base alarms off, something about which Hammond has a few choice words to say:Hammond: In the future, Major, before you activate any device that includes the word "reactor", I would appreciate it if you could notify me.
Ingesting Knowledge: When a child goes through their Averium, all the other Orbanians are given a nanite containing everything they learned.
The Kindnapper: O'Neill essentially kidnaps Merrin for her own good after finding out what will happen if she returns to Orban.
Military Maverick: O'Neill takes it upon himself to defy orders in taking Merrin from the base. Hammond does reprimand him for this, but he gets off pretty lightly all things considered.
Motor Mouth: Daniel launches into an overexcited, rambling spiel after discovering the significance of the culture the Orbanians may be descended from, something that confuses the hell out of Calen.
Nanomachines: The Orbanian children have large numbers of nanites in their brains to help them absorb vast amounts of knowledge quickly. When the children come of age, these nanites are removed in a ceremony called the Averium and distributed among the rest of the Orbanian people.
One-Steve Limit: An aversion; the Orbanian child that Teal'c befriends is called Tomin; another Tomin would show up much, much later as a recurring character throughout seasons nine and ten.
Parental Bonus:Carter: Merrin, you're eleven years old. Half the interesting things in my life didn't happen till I was fifteen. Merrin: What kind of interesting things? Carter: Oh. Um, just... stuff.
Powered by a Forsaken Child: The reason the Orbanians have managed to develop such an advanced society in a relatively short amount of time is because they use their children to absorb knowledge and then distribute the information throughout the rest of the population, leaving the children as little more than empty shells.
Romanticism Versus Enlightenment: Orbanian society sees the ideals of The Enlightenment run amok. O'Neill injects some well-needed Romanticism.
The Sleepless: Merrin claims that she rarely needs sleep, allowing her to work for over 24 hours straight, past the point at which Carter has crashed out on her desk from exhaustion.Carter: Okay, now I am jealous.
[S3E5] Learning Curve
SG-1 is impressed with the learning power of Orbanian children but soon learns that the children eventually go through a ceremony which removes the nanites from the children in order to take away what they learned. Colonel Jack O'Neill decides to take Merrin away from them and teach her how to become a true kid.
On Orban, Daniel realizes the Orbanians are not of Aztec but Teotihuacan descent, and theorizes that the arrival of the Goa'uld caused Teotihuacan's downfall. Daniel is directed by Kalan to explain this to Tomin. Back on Earth, Sam is having trouble understanding Merrin's explanation of the generator technology. She attempts to have Merrin simplify her explanations, but Dr. Janet Fraiser interrupts and asks to conduct "Follow-up tests" on Merrin. When the tests are complete, Fraiser calls a meeting with Major General George S. Hammond, Jack, and Sam, explaining that she has discovered Merrin has nanites in her bloodstream and brain, superseding her normal brain synapses. General Hammond quickly begins preparing for a crisis, but Merrin explains that the nanites were designed on Orban, that all Orbanians carry them as a means to gather information, and that each Urrone is given millions of nanites to assist them in learning large amounts of information very quickly, accounting for the high intelligence of the Urrone children that had been observed. Merrin also tells the group that each Urrone must undergo the Averium and that at each Averium all of the Orbanians are given one nanite, but does not explain any further. General Hammond is mollified and allows Carter to continue studying the Naquadah generator with Merrin's help.
A learning curve is a graphical representation of the relationship between how proficient people are at a task and the amount of experience they have. Proficiency (measured on the vertical axis) usually increases with increased experience (the horizontal axis), that is to say, the more someone, groups, companies or industries perform a task, the better their performance at the task.[1]
The common expression "a steep learning curve" is a misnomer suggesting that an activity is difficult to learn and that expending much effort does not increase proficiency by much, although a learning curve with a steep start actually represents rapid progress.[2][3] In fact, the gradient of the curve has nothing to do with the overall difficulty of an activity, but expresses the expected rate of change of learning speed over time. An activity that it is easy to learn the basics of, but difficulty to gain proficiency in, may be described as having "a steep learning curve".
Learning curve may refer to a specific task or a body of knowledge. Hermann Ebbinghaus first described the learning curve in 1885 in the field of the psychology of learning, although the name did not come into use until 1903.[4][5] In 1936 Theodore Paul Wright described the effect of learning on production costs in the aircraft industry.[6] This form, in which unit cost is plotted against total production, is sometimes called an experience curve.
The first known use of the term 'learning curve' is from 1903: "Bryan and Harter (6) found in their study of the acquisition of the telegraphic language a learning curve which had the rapid rise at the beginning followed by a period of slower learning, and was thus convex to the vertical axis."[5][3]
Psychologist Arthur Bills gave a more detailed description of learning curves in 1934. He also discussed the properties of different types of learning curves, such as negative acceleration, positive acceleration, plateaus, and ogive curves.[8]
In 1968 Bruce Henderson of the Boston Consulting Group (BCG) generalized the Unit Cost model pioneered by Wright, and specifically used a Power Law, which is sometimes called Henderson's Law.[9] He named this particular version the experience curve.[10][11]Research by BCG in the 1970s observed experience curve effects for various industries that ranged from 10 to 25 percent.[12]
The economic learning of productivity and efficiency generally follows the same kinds of experience curves and have interesting secondary effects. Efficiency and productivity improvement can be considered as whole organization or industry or economy learning processes, as well as for individuals. The general pattern is of first speeding up and then slowing down, as the practically achievable level of methodology improvement is reached. The effect of reducing local effort and resource use by learning improved methods often has the opposite latent effect on the next larger scale system, by facilitating its expansion, or economic growth, as discussed in the Jevons paradox in the 1880s and updated in the Khazzoom-Brookes Postulate in the 1980s.
The specific case of a plot of Unit Cost versus Total Production with a power law was named the experience curve: the mathematical function is sometimes called Henderson's Law. This form of learning curve is used extensively in industry for cost projections.[21]
Plots relating performance to experience are widely used in machine learning. Performance is the error rate or accuracy of the learning system, while experience may be the number of training examples used for learning or the number of iterations used in optimizing the system model parameters.[22] The machine learning curve is useful for many purposes including comparing different algorithms,[23] choosing model parameters during design,[24] adjusting optimization to improve convergence, and determining the amount of data used for training.[25]
Initially introduced in educational and behavioral psychology, the term has acquired a broader interpretation over time, and expressions such as "experience curve", "improvement curve", "cost improvement curve", "progress curve", "progress function", "startup curve", and "efficiency curve" are often used interchangeably. In economics the subject is rates of "development", as development refers to a whole system learning process with varying rates of progression. Generally speaking all learning displays incremental change over time, but describes an "S" curve which has different appearances depending on the time scale of observation. It has now also become associated with the evolutionary theory of punctuated equilibrium and other kinds of revolutionary change in complex systems generally, relating to innovation, organizational behavior and the management of group learning, among other fields.[26] These processes of rapidly emerging new form appear to take place by complex learning within the systems themselves, which when observable, display curves of changing rates that accelerate and decelerate. 041b061a72