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Roko's basilisk - Wikipedia
Roko's basilisk is a thought experiment which states that an otherwise benevolent artificial superintelligence (AI) in the future would be incentivized to create a virtual reality simulation to torture anyone who knew of its potential existence but did not directly contribute to its advancement or development.[1][2] It originated in a 2010 post at discussion board LessWrong, a technical forum focused on analytical rational enquiry.[1][3][4] The thought experiment's name derives from the poster of the article (Roko) and the basilisk, a mythical creature capable of destroying enemies with its stare.
The Tower of Lire | Brilliant
Calculus has such a wide scope and depth of application that it's easy to lose sight of the forest for the trees. This course takes a bird's-eye view, using visual and physical intuition to present the major pillars of calculus: limits, derivatives, integrals, and infinite sums. You'll walk away with a clear sense of what calculus is and what it can do. Calculus in a Nutshell is a short course with only 19 quizzes. If you want to quickly learn an overview of calculus or review the foundational principles after a long hiatus from the subject, this course ought to be perfect. Calculus Fundamentals and Integral Calculus are the two courses that can follow next in the Calculus sequence. If/when you want to go into more depth and learn a wide spread of specific techniques in differential calculus and integral calculus respectively, that's where you should look. For example, integration techniques like "integration by parts" are only in the Integral Calculus course.
In physics, the center of mass of a distribution of mass in space (sometimes referred to as the balance point) is the unique point where the weighted relative position of the distributed mass sums to zero. This is the point to which a force may be applied to cause a linear acceleration without an angular acceleration. Calculations in mechanics are often simplified when formulated with respect to the center of mass. It is a hypothetical point where the entire mass of an object may be assumed to be concentrated to visualise its motion. In other words, the center of mass is the particle equivalent of a given object for application of Newton's laws of motion.
Radioactive decay - Wikipedia
Radioactive decay (also known as nuclear decay, radioactivity, radioactive disintegration, or nuclear disintegration) is the process by which an unstable atomic nucleus loses energy by radiation. A material containing unstable nuclei is considered radioactive. Three of the most common types of decay are alpha decay (α-decay), beta decay (β-decay), and gamma decay (γ-decay), all of which involve emitting one or more particles. The weak force is the mechanism that is responsible for beta decay, while the other two are governed by the electromagnetism and nuclear force.[1] A fourth type of common decay is electron capture, in which an unstable nucleus captures an inner electron from one of the electron shells. The loss of that electron from the shell results in a cascade of electrons dropping down to that lower shell resulting in emission of discrete X-rays from the transitions. A common example is iodine-125 commonly used in medical settings.
Lamarckism - Wikipedia
Lamarckism, also known as Lamarckian inheritance or neo-Lamarckism,[2] is the notion that an organism can pass on to its offspring physical characteristics that the parent organism acquired through use or disuse during its lifetime. It is also called the inheritance of acquired characteristics or more recently soft inheritance. The idea is named after the French zoologist Jean-Baptiste Lamarck (1744–1829), who incorporated the classical era theory of soft inheritance into his theory of evolution as a supplement to his concept of orthogenesis, a drive towards complexity.
Surface of revolution - Wikipedia
A surface of revolution is a surface in Euclidean space created by rotating a curve (the generatrix) around an axis of rotation.[1]
Examples of surfaces of revolution generated by a straight line are cylindrical and conical surfaces depending on whether or not the line is parallel to the axis. A circle that is rotated around any diameter generates a sphere of which it is then a great circle, and if the circle is rotated around an axis that does not intersect the interior of a circle, then it generates a torus which does not intersect itself (a ring torus).
Chinese room - Wikipedia
The Chinese room argument holds that a digital computer executing a program cannot have a "mind," "understanding" or "consciousness,"[a] regardless of how intelligently or human-like the program may make the computer behave. The argument was presented by philosopher John Searle in his paper, "Minds, Brains, and Programs", published in Behavioral and Brain Sciences in 1980. Similar arguments were presented by Gottfried Leibniz (1714), Anatoly Dneprov (1961), Lawrence Davis (1974) and Ned Block (1978). Searle's version has been widely discussed in the years since.[1] The centerpiece of Searle's argument is a thought experiment known as the Chinese room
Philosophy of mind - Wikipedia
Philosophy of mind is a branch of philosophy that studies the ontology and nature of the mind and its relationship with the body. The mind–body problem is a paradigmatic issue in philosophy of mind, although a number of other issues are addressed, such as the hard problem of consciousness and the nature of particular mental states.[1][2][3] Aspects of the mind that are studied include mental events, mental functions, mental properties, consciousness and its neural correlates, the ontology of the mind, the nature of cognition and of thought, and the relationship of the mind to the body
Theory of mind - Wikipedia
In psychology, theory of mind refers to the capacity to understand other people by ascribing mental states to them (that is, surmising what is happening in their mind). This includes the knowledge that others' mental states may be different from one's own states and include beliefs, desires, intentions, emotions, and thoughts.[1] Possessing a functional theory of mind is considered crucial for success in everyday human social interactions. People use such a theory when analyzing, judging, and inferring others' behaviors. The discovery and development of theory of mind primarily came from studies done with animals and infants.[2] Factors including drug and alcohol consumption, language development, cognitive delays, age, and culture can affect a person's capacity to display theory of mind.
![#84 LAURA RUIS - Large language models are not zero-shot communicators [NEURIPS UNPLUGGED]](https://rdl.ink/render/https%3A%2F%2Fi.ytimg.com%2Fvi%2F5Yd28ssDutA%2Fmaxresdefault.jpg?width=350&height=&ar=16:9&mode=crop&format=avif&dpr=2)
#84 LAURA RUIS - Large language models are not zero-shot communicators [NEURIPS UNPLUGGED]
In this NeurIPSs interview, we speak with Laura Ruis about her research on the ability of language models to interpret language in context. She has designed a simple task to evaluate the performance of widely used state-of-the-art language models and has found that they struggle to make pragmatic inferences (implicatures). Tune in to learn more about her findings and what they mean for the future of conversational AI.
Pod: https://anchor.fm/machinelearningstreettalk/episodes/84-LAURA-RUIS---Large-language-models-are-not-zero-shot-communicators-NEURIPS-UNPLUGGED-e1rri6k
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Laura Ruis
https://www.lauraruis.com/
https://twitter.com/LauraRuis
BLOOM
https://bigscience.huggingface.co/blog/bloom
Large language models are not zero-shot communicators [Laura Ruis, Akbir Khan, Stella Biderman, Sara Hooker, Tim Rocktäschel, Edward Grefenstette]
https://arxiv.org/abs/2210.14986
[Zhang et al] OPT: Open Pre-trained Transformer Language Models
https://arxiv.org/pdf/2205.01068.pdf
[Lampinen] Can language models handle recursively nested grammatical structures? A case study on comparing models and humans
https://arxiv.org/pdf/2210.15303.pdf
[Gary Marcus] Horse rides astronaut
https://garymarcus.substack.com/p/horse-rides-astronaut
[Gary Marcus] GPT-3, Bloviator: OpenAI’s language generator has no idea what it’s talking about
https://www.technologyreview.com/2020/08/22/1007539/gpt3-openai-language-generator-artificial-intelligence-ai-opinion/
[Bender et al] On the Dangers of Stochastic Parrots: Can Language Models Be Too Big?
https://dl.acm.org/doi/10.1145/3442188.3445922
[janus] Simulators (Less Wrong)
https://www.lesswrong.com/posts/vJFdjigzmcXMhNTsx/simulators
Reality Is A Strange Loop - The Beauty Of Paradox + GRAPHICS
Strange Loops - A guided tour through Douglas Hofstadter's paradoxical concept of 'strange loops', and what they reveal about the ultimate nature of existence and consciousness.
The Ultimate Life Purpose Course - Create Your Dream Career:
https://www.actualized.org/life-purpose-course
Leo Reviews Top 200 Self Help Books
https://www.actualized.org/books
Leo's Blog:
https://www.actualized.org/insights
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https://www.actualized.org/forum/
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Special Thanks & Graphic Credits:
Turquoise Penrose Triangle:
Anton Kononov
http://www.antonkononov.com
Varios pictures & animations:
Wikimedia.org
Wikipedia.org
Twisted Donut animation:
Jacobo Zabludovsky
https://giphy.com/search/jacobo-zabludovsky
Rainbow Spiral animation & Strange Attractors animation:
David Szakaly
http://theinspirationgrid.com/hypnotic-animated-gifs-by-david-szakaly/
Waterfall animation:
Owen Chikazawa
https://dribbble.com/shots/2126205-Waterfall
Wheel Forever animation:
David Whyte
https://dribbble.com/beesandbombs
Swirling Dots animation:
Iain Acton
https://www.behance.net/iainoff
Drawing Hands & Relativity:
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http://www.mcescher.com
GEB Recursion:
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Unknown Artists:
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Riemann sum - Wikipedia
In mathematics, a Riemann sum is a certain kind of approximation of an integral by a finite sum. It is named after nineteenth century German mathematician Bernhard Riemann. One very common application is approximating the area of functions or lines on a graph, but also the length of curves and other approximations.
Naturalness (physics) - Wikipedia
In physics, naturalness is the property that the dimensionless ratios between free parameters or physical constants appearing in a physical theory should take values "of order 1" and that free parameters are not fine-tuned. That is, a natural theory would have parameter ratios with values like 2.34 rather than 234000 or 0.000234
Beyond Falsifiability: Normal Science in a Multiverse
Training language models to follow instructions with human feedback
Sentence-BERT: Sentence Embeddings using Siamese BERT-Networks
CICERO: An AI agent that negotiates, persuades, and cooperates with people
Neurogenesis - Wikipedia
Neurogenesis is the process by which nervous system cells, the neurons, are produced by neural stem cells (NSCs). It occurs in all species of animals except the porifera (sponges) and placozoans.[1] Types of NSCs include neuroepithelial cells (NECs), radial glial cells (RGCs), basal progenitors (BPs), intermediate neuronal precursors (INPs), subventricular zone astrocytes, and subgranular zone radial astrocytes, among others.[1]
Neurogenesis is most active during embryonic development and is responsible for producing all the various types of neurons of the organism, but it continues throughout adult life in a variety of organisms.[1] Once born, neurons do not divide (see mitosis), and many will live the lifespan of the animal
Binding problem - Wikipedia
The consciousness and binding problem is the problem of how objects, background and abstract or emotional features are combined into a single experience.[1]
The binding problem refers to the overall encoding of our brain circuits for the combination of decisions, actions, and perception. The binding problem encompasses a wide range of different circuits and can be divided into subsections that will be discussed later on. The binding problem is considered a "problem" due to the fact that no complete model exists.
The binding problem can be subdivided into four problems of perception, used in neuroscience, cognitive science and philosophy of mind. Including general considerations on coordination,the Subjective unity of perception, and variable binding
PROGRESSIVE DISTILLATION FOR FAST SAMPLING OF DIFFUSION MODELS
ChatGPT: Optimizing Language Models for Dialogue
We’ve trained a model called ChatGPT which interacts in a conversational way. The dialogue format makes it possible for ChatGPT to answer followup questions, admit its mistakes, challenge incorrect premises, and reject inappropriate requests. ChatGPT is a sibling model to InstructGPT, which is trained to follow an instruction in
We trained this model using Reinforcement Learning from Human Feedback (RLHF), using the same methods as InstructGPT, but with slight differences in the data collection setup. We trained an initial model using supervised fine-tuning: human AI trainers provided conversations in which they played both sides—the user and an AI assistant. We gave the trainers access to model-written suggestions to help them compose their responses. We mixed this new dialogue dataset with the InstructGPT dataset, which we transformed into a dialogue format.
We randomly selected a model-written message, sampled several alternative completions, and had AI trainers rank them. Using these reward models, we can fine-tune the model using Proximal Policy Optimization.
The Epigenotype annotated/explained version.
Prisoner's dilemma - Wikipedia
The Prisoner's Dilemma is an example of a game analyzed in game theory[citation needed]. It is also a thought experiment that challenges two completely rational agents to a dilemma: cooperate with their partner for mutual reward, or betray their partner ("defect") for individual reward.
This dilemma was originally framed by Merrill Flood and Melvin Dresher while working at RAND in 1950[citation needed]. Albert W. Tucker appropriated the game and formalized it by structuring the rewards in terms of prison sentences and named it "prisoner's dilemma".[1] William Poundstone in his 1993 book Prisoner's Dilemma writes the following version:Two members of a criminal gang are arrested and imprisoned. Each prisoner is in solitary confinement with no means of speaking to or exchanging messages with the other. The police admit they don't have enough evidence to convict the pair on the principal charge. They plan to sentence both to a year in prison on a lesser charge. Simultaneously, the police offer each prisoner a Faustian bargain.The possible outcomes are:
A: If A and B each betray the other, each of them serves 5 years in prison
B: If A betrays B but B remains silent, A will be set free and B will serve 10 years in prison
C: If A remains silent but B betrays A, A will serve 10 years in prison and B will be set free
D: If A and B both remain silent, both of them will serve 2 years in prison (on the lesser charge).
Rapid eye movement sleep - Wikipedia
After the deprivation is complete, mild psychological disturbances, such as anxiety, irritability, hallucinations, and difficulty concentrating may develop and appetite may increase. There are also positive consequences of REM deprivation. Some symptoms of depression are found to be suppressed by REM deprivation; aggression may increase, and eating behavior may get disrupted
Sleep in general aids memory. REM sleep may favor the preservation of certain types of memories: specifically, procedural memory, spatial memory, and emotional memory. In rats, REM sleep increases following intensive learning, especially several hours after, and sometimes for multiple nights. Experimental REM sleep deprivation has sometimes inhibited memory consolidation, especially regarding complex processes (e.g., how to escape from an elaborate maze).[103] In humans, the best evidence for REM's improvement of memory pertains to learning of procedures—new ways of moving the body (such as trampoline jumping), and new techniques of problem solving. REM deprivation seemed to impair declarative (i.e., factual) memory only in more complex cases, such as memories of longer stories.[104] REM sleep apparently counteracts attempts to suppress certain thoughts
After waking from REM sleep, the mind seems "hyperassociative"—more receptive to semantic priming effects. People awakened from REM have performed better on tasks like anagrams and creative problem solving.[73]
Sleep aids the process by which creativity forms associative elements into new combinations that are useful or meet some requirement.[74] This occurs in REM sleep rather than in NREM sleep
Rapid eye movement sleep - Wikipedia
Rapid eye movement sleep (REM sleep or REMS) is a unique phase of sleep in mammals and birds, characterized by random rapid movement of the eyes, accompanied by low muscle tone throughout the body, and the propensity of the sleeper to dream vividly.
The REM phase is also known as paradoxical sleep (PS) and sometimes desynchronized sleep or dreamy sleep,[1] because of physiological similarities to waking states including rapid, low-voltage desynchronized brain waves. Electrical and chemical activity regulating this phase seems to originate in the brain stem, and is characterized most notably by an abundance of the neurotransmitter acetylcholine, combined with a nearly complete absence of monoamine neurotransmitters histamine, serotonin and norepinephrine.[2]Experiences of REM sleep are not transferred to permanent memory due to absence of norepinephrine
A Gentle Introduction to Pooling Layers for Convolutional Neural Networks - MachineLearningMastery.com
Convolutional layers in a convolutional neural network summarize the presence of features in an input image. A problem with the output feature maps is that they are sensitive to the location of the features in the input. One approach to address this sensitivity is to down sample the feature maps. This has the effect of […]
Pooling layers provide an approach to down sampling feature maps by summarizing the presence of features in patches of the feature map. Two common pooling methods are average pooling and max pooling that summarize the average presence of a feature and the most activated presence of a feature respectively.
Service level indicator - Wikipedia
In information technology, a service level indicator (SLI) is a measure of the service level provided by a service provider to a customer. SLIs form the basis of service level objectives (SLOs), which in turn form the basis of service level agreements (SLAs);[1] an SLI is thus also called an SLA metric.
Service-level objective - Wikipedia
A service-level objective (SLO) is a key element of a service-level agreement (SLA) between a service provider and a customer. SLOs are agreed upon as a means of measuring the performance of the Service Provider and are outlined as a way of avoiding disputes between the two parties based on misunderstanding.