Chaos theory

Fine-tuning

In theoretical physics, fine-tuning is the process in which parameters of a model must be adjusted very precisely in order to fit with certain observations. This had led to the discovery that the fundamental constants and quantities fall into such an extraordinarily precise range that if it did not, the origin and evolution of conscious agents in the universe would not be permitted. Theories requiring fine-tuning are regarded as problematic in the absence of a known mechanism to explain why the parameters happen to have precisely the observed values that they return. The heuristic rule that parameters in a fundamental physical theory should not be too fine-tuned is called naturalness. (Wikipedia).

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Tuning fork in water (slow motion)

Watch the amazing effect of a tuning fork in water!!!

From playlist Tuning forks in water-Amazing science experiment

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B04 Example problem of simple harmonic oscillation

Solving an example problem of simple harmonic oscillation, which requires calculating the solution to a second order ordinary differential equation.

From playlist Physics ONE

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B03 Simple harmonic oscillation

Explaining simple (idealised) harmonic oscillation, through a second-order ordinary differential equation.

From playlist Physics ONE

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C34 Expanding this method to higher order linear differential equations

I this video I expand the method of the variation of parameters to higher-order (higher than two), linear ODE's.

From playlist Differential Equations

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O'Reilly Webcast: When Times Get Tough, The Tough Get Tuning

Dee-Ann LeBlanc of Splunk shows how you can get better performance from your hardware without throwing dollars at it.

From playlist O'Reilly Webcasts

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C07 Homogeneous linear differential equations with constant coefficients

An explanation of the method that will be used to solve for higher-order, linear, homogeneous ODE's with constant coefficients. Using the auxiliary equation and its roots.

From playlist Differential Equations

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How to Fine-tune T5 and Flan-T5 LLM models: The Difference is? #theory

Introduction how to fine-tune T5 and FLAN-T5 models (LLM - Large Language Models). Then some detailed videos how to code, step-by-step, fine tuning in real time on T5 and Flan T5 models. Fine tune Flan T5. Theory how to fine-tune T5 LLMs. Next video is on coding examples (JupyterLab, Cola

From playlist Flan-T5 Large Language Model (LLM)

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What's Fine-Tuning in Physics? | Episode 1903 | Closer To Truth

What is fine-tuning in physics? Why do the “constants of nature” — masses of subatomic particles and strengths of forces like gravity and electromagnetism — have the values they do? Does fine-tuning “cry out” for explanation? Featuring interviews with Bernard Carr, Luke Barnes, Geraint Lew

From playlist Closer To Truth | Season 19

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What's Fine-Tuning in Cosmology? | Episode 1902 | Closer To Truth

What is fine-tuning in cosmology? Here’s the claim: cosmic conditions that allow complex structures — galaxies, stars, planets, people — depend on a few “constants of nature” lying within tight ranges of values. But is fine-tuning valid? Featuring interviews with Geraint Lewis, Luke Barnes

From playlist Closer To Truth | Season 19

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Fine-tune ChatGPT w/ in-context learning ICL - Chain of Thought, AMA, reasoning & acting: ReAct

Prompt engineering was yesterday. New insights into in-context learning to achieve significant better results w/ all autoregressive LLMs (like ChatGPT, BioGPT or PaLM540B). Latest research on Chain-of-Thought Prompting (CoT) and ReAct, combining reasoning and action (agent receives externa

From playlist Large Language Models - ChatGPT, GPT-4, BioGPT and BLOOM LLM explained and working code examples

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Efficient Transfer Learning with Null Prompts

Notion Link: https://ebony-scissor-725.notion.site/Henry-AI-Labs-Weekly-Update-July-15th-2021-a68f599395e3428c878dc74c5f0e1124 Chapters 0:00 Introduction 3:15 Efficient Transfer Learning 5:13 GPT-J Demo 6:48 Two Approaches to Prompting 9:54 Null Prompting 11:20 Results Thanks for watchin

From playlist AI Weekly Update - July 15th, 2021!

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Does Cosmic Fine-Tuning Demand Explanation? | Episode 1208 | Closer To Truth

The universe works for us because of deep physical laws. But if the values of these laws change much, then all we see and know could not exist. If small changes to the laws of physics would make life impossible, does fine-tuning require an explanation? Featuring interviews with Bernard Car

From playlist Closer To Truth | Season 12

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Does a Fine-Tuned Universe Lead to God? | Episode 502 | Closer To Truth

We human beings sit roughly midway between atoms and galaxies, and both must be so perfectly structured for us to exist. It's called "fine tuning" and it's all so breathtakingly precise that it cries out for explanation. To some, fine-tuning leads to God. To others, there are non-supernatu

From playlist Big Questions About God - Closer To Truth - Core Topic

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Dream Job Alert: AI Prompt Engineer - $335K | AI Prompt Design: A Crash Course

Anthropic AI offers you a job as prompt engineer. Go and get a new Job in AI, if you know about prompt engineering. Short Introduction to prompt engineering and continuous prompt design, plus prefix tuning vs fine-tuning for LLMs. Hint: all my viewers, who read recommended research arxiv

From playlist Large Language Models - ChatGPT, GPT-4, BioGPT and BLOOM LLM explained and working code examples

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Is Life and Mind Inevitable in the Cosmos? | Episode 902 | Closer To Truth

Our universe must be "just so" in order for life and mind-for us-to exist. "Just so" is called "fine-tuning," and it cries out for explanation. Featuring interviews with J. Gott, Frank Wilczek, Robert Laughlin, Raymond Kurzweil, Robert Russell, and Peter van Inwagen. Season 9, Episode 2 -

From playlist Closer To Truth | Season 9

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Stanford CS330 Deep Multi-Task & Meta Learning - Transfer Learning, Meta Learning l 2022 I Lecture 3

For more information about Stanford's Artificial Intelligence programs visit: https://stanford.io/ai To follow along with the course, visit: https://cs330.stanford.edu/ To view all online courses and programs offered by Stanford, visit: http://online.stanford.edu​ Chelsea Finn Computer

From playlist Stanford CS330: Deep Multi-Task and Meta Learning I Autumn 2022

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