Causation vs. Correlation - Revision history

BPeat at 20:24, 28 April 2024

2024-04-28T20:24:11Z

BPeat at 00:09, 9 September 2023

2023-09-09T00:09:16Z

BPeat: /* Multivariate Additive Noise Model (MANM) */

2023-07-14T01:03:42Z

‎Multivariate Additive Noise Model (MANM)

BPeat at 22:13, 11 July 2023

2023-07-11T22:13:01Z

BPeat: /* Retrocausality */

2023-07-04T18:32:16Z

‎Retrocausality

BPeat at 15:31, 3 July 2023

2023-07-03T15:31:31Z

BPeat: /* Retrocausality */

2023-07-01T02:20:44Z

‎Retrocausality

BPeat at 16:06, 30 June 2023

2023-06-30T16:06:27Z

BPeat: /* The Delayed Choice Quantum Eraser, Debunked */

2023-06-09T19:52:56Z

‎The Delayed Choice Quantum Eraser, Debunked

BPeat: /* Causality vs Retrocausality */

2023-06-09T19:51:44Z

‎Causality vs Retrocausality

@@ Line 20: / Line 20: @@
 [https://www.bing.com/news/search?q=Causal+AI+Causation+Correlation&qft=interval%3d%228%22 ...Bing News]
-* [[In-Context Learning (ICL)]] ... [[Context]] ... [[Causation vs. Correlation]] ... [[Autocorrelation]] ... [[Out-of-Distribution (OOD) Generalization]] ... [[Transfer Learning]]
+* [[Causation vs. Correlation]] ... [[Autocorrelation]] ...[[Convolution vs. Cross-Correlation (Autocorrelation)]]
-* [[Convolution vs. Cross-Correlation (Autocorrelation)]]
+* [[Perspective]] ... [[Context]] ... [[In-Context Learning (ICL)]] ... [[Transfer Learning]] ... [[Out-of-Distribution (OOD) Generalization]]
 * [[Math for Intelligence]] ... [[Finding Paul Revere]] ... [[Social Network Analysis (SNA)]] ... [[Dot Product]] ... [[Kernel Trick]]
 * [[Strategy & Tactics]] ... [[Project Management]] ... [[Best Practices]] ... [[Checklists]] ... [[Project Check-in]] ... [[Evaluation]] ... [[Evaluation - Measures|Measures]]

@@ Line 24: / Line 24: @@
 * [[Math for Intelligence]] ... [[Finding Paul Revere]] ... [[Social Network Analysis (SNA)]] ... [[Dot Product]] ... [[Kernel Trick]]
 * [[Strategy & Tactics]] ... [[Project Management]] ... [[Best Practices]] ... [[Checklists]] ... [[Project Check-in]] ... [[Evaluation]] ... [[Evaluation - Measures|Measures]]
-* [[Singularity]] ... [[Artificial Consciousness / Sentience|Sentience]] ... [[Artificial General Intelligence (AGI)| AGI]] ... [[Inside Out - Curious Optimistic Reasoning| Curious Reasoning]] ... [[Emergence]] ... [[Moonshots]] ... [[Explainable / Interpretable AI|Explainable AI]] ...  [[Algorithm Administration#Automated Learning|Automated Learning]]
+* [[Artificial General Intelligence (AGI) to Singularity]] ... [[Inside Out - Curious Optimistic Reasoning| Curious Reasoning]] ... [[Emergence]] ... [[Moonshots]] ... [[Explainable / Interpretable AI|Explainable AI]] ...  [[Algorithm Administration#Automated Learning|Automated Learning]]
 * [https://nickchk.com/causalgraphs.html Causal Inference Animated Plots | Nick Huntington-Klein]
 * [https://sites.google.com/view/causality-reading-group Causal Inference | Causal-Inference.org]

@@ Line 100: / Line 100: @@
 <youtube>Ue27icanbS4</youtube>
-= Multivariate Additive Noise Model (MANM) =
+= <span id="Multivariate Additive Noise Model (MANM)"></span>Multivariate Additive Noise Model (MANM) =
 * [https://www.sciencedirect.com/science/article/pii/S0893608018301060?via%3Dihub A multivariate additive noise model for complete causal discovery | P. Parida, T. Marwala, S. Chakraverty - ScienceDirect]
 Model for general causality that identifies multiple causal connections without time-sequence data. "Uniquely, the model can identify multiple, hierarchical causal factors. It works even if data with time sequencing is not available. The model creates significant opportunities to analyse complex phenomena in areas such as economics, disease outbreaks, climate change and conservation," says Prof Tshilidzi Marwala, a professor of artificial intelligence, and global AI and economics expert at the University of Johannesburg, South Africa. "The model is especially useful at the regional, national or global level where no controlled or natural experiments are possible," adds Marwala. "MANM is based on [[Directed Acyclic Graph (DAG)]], which can identify a multi-nodal causal structure. MANM can estimate every possible causal direction in complex feature sets, with no missing or wrong directions." The use of DAGs is a key reason MANM significantly outperforms models previously developed by others, which were based on [https://www.cs.helsinki.fi/u/ahyvarin/whatisica.shtml Independent Component Analysis (ICA)], such as [https://www.cs.helsinki.fi/u/ahyvarin/papers/JMLR06.pdf Linear Non-Gaussian Acyclic Model (ICA-LiNGAM)], [https://archive.org/details/arxiv-1104.2808/page/n15 Greedy DAG Search (GDS)] and [https://auai.org/uai2017/proceedings/papers/250.pdf Regression with Sub-sequent Independent Test (RESIT)], he says. "Another key feature of MANM is the proposed Causal Influence Factor (CIF), for the successful discovery of causal directions in the multivariate system. The CIF score provides a reliable indicator of the quality of the casual inference, which enables avoiding most of the missing or wrong directions in the resulting causal structure," concludes Chakraverty. Where an existing dataset is available, MANM now makes it possible to identify multiple multi-nodal causal structures within the set. As an example, MANM can identify the multiple causes of persistent household debt for low, middle and high-income households in a region. [https://phys.org/news/2018-06-artificial-intelligence-causation.html Artificial intelligence trained to analyze causation | University of Johannesburg]
@@ Line 108: / Line 108: @@
 <youtube>_kFcZqv9PnA</youtube>
 <youtube>LN0xtUuJsEI</youtube>
 = Causal Reasoning Approaches =

@@ Line 23: / Line 23: @@
 * [[Convolution vs. Cross-Correlation (Autocorrelation)]]
 * [[Math for Intelligence]] ... [[Finding Paul Revere]] ... [[Social Network Analysis (SNA)]] ... [[Dot Product]] ... [[Kernel Trick]]
-* [[Evaluation - Measures]]
+* [[Strategy & Tactics]] ... [[Project Management]] ... [[Best Practices]] ... [[Checklists]] ... [[Project Check-in]] ... [[Evaluation]] ... [[Evaluation - Measures|Measures]]
 * [[Singularity]] ... [[Artificial Consciousness / Sentience|Sentience]] ... [[Artificial General Intelligence (AGI)| AGI]] ... [[Inside Out - Curious Optimistic Reasoning| Curious Reasoning]] ... [[Emergence]] ... [[Moonshots]] ... [[Explainable / Interpretable AI|Explainable AI]] ...  [[Algorithm Administration#Automated Learning|Automated Learning]]
 * [https://nickchk.com/causalgraphs.html Causal Inference Animated Plots | Nick Huntington-Klein]

@@ Line 202: / Line 202: @@
 == <span id="Retrocausality"></span>Retrocausality ==
 * [[Time]] ... [[Causation vs. Correlation#Retrocausality| Retrocausality]] ... [[Quantum#Delayed Choice Quantum Eraser|Delayed Choice Quantum Eraser]] ... [[Quantum]]
 * [https://en.wikipedia.org/wiki/Retrocausality Retrocausality | Wikipedia]
 * [https://en.wikipedia.org/wiki/Two-state_vector_formalism Two-state vector formalism (TSVF) | Wikipedia]

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 |title=PRIMO.ai
 |titlemode=append
-|keywords=artificial, intelligence, machine, learning, models, algorithms, data, singularity, moonshot, Tensorflow, Google, Nvidia, Microsoft, Azure, Amazon, AWS
+|keywords=ChatGPT, artificial, intelligence, machine, learning, GPT-4, GPT-5, NLP, NLG, NLC, NLU, models, data, singularity, moonshot, Sentience, AGI, Emergence, Moonshot, Explainable, TensorFlow, Google, Nvidia, Microsoft, Azure, Amazon, AWS, Hugging Face, OpenAI, Tensorflow, OpenAI, Google, Nvidia, Microsoft, Azure, Amazon, AWS, Meta, LLM, metaverse, assistants, agents, digital twin, IoT, Transhumanism, Immersive Reality, Generative AI, Conversational AI, Perplexity, Bing, You, Bard, Ernie, prompt Engineering LangChain, Video/Image, Vision, End-to-End Speech, Synthesize Speech, Speech Recognition, Stanford, MIT |description=Helpful resources for your journey with artificial intelligence; videos, articles, techniques, courses, profiles, and tools
 |description=Helpful resources for your journey with artificial intelligence; videos, articles, techniques, courses, profiles, and tools
 }}
 [https://www.youtube.com/results?search_query=Causal+AI+Causation+Correlation YouTube]

← Older revision		Revision as of 19:52, 9 June 2023
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	== The Delayed Choice Quantum Eraser, Debunked ==		== The Delayed Choice Quantum Eraser, Debunked ==
		+	The delayed choice quantum eraser is one of the weirdest, if not THE weirdest, experiments in quantum mechanics. It supposedly rewrites the past because the choice of a measurement changes what happened in another measurement earlier. In this video I explain why this is not what's happening. The quantum eraser isn't remotely as weird as you may have heard.
		+
	<youtube>RQv5CVELG3U</youtube>		<youtube>RQv5CVELG3U</youtube>

@@ Line 186: / Line 186: @@
 = Causality vs Retrocausality =
-<b>Causality</b> is when an earlier event causes a later event, while <b>retrocausality</b> is when a later event affects an earlier one.
+<b>Causality</b> is when an earlier event causes a later event, while <b>Retrocausality</b> is when a later event affects an earlier one.
 * Causality is the relationship between an event (the cause) and a second event (the effect), where the second event is understood as a consequence of the first. In other words, causality is the concept that an action or event will produce a certain response to the action in the form of another event.