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Misc. GPT-3 Information (click to expand)

Are Prompts Effective?

• Analyzing The Problem GPT-3 Is Trying To Solve: GPT-3 provides a probablistic solution to a problem - it doesn't succeed all the time, or fail all the time either. The debate over GPT-3's effectiveness is based on whether this probablistic solution is enough. Skeptics of GPT-3 believe that it should solve prompts all the time, not just a few cherry-picked exmaples...while GPT-3 supporters are content with it solving prompts some of the time or even once (moving most of the "burden" of problem-solving over to the prompt-design phase).
  • Commentary: If GPT-3 is to be practically useful, it must be able to solve a problem correctly at least 50% of the time. That way, if GPT-3 produces a "wrong" answer, you can keep rerolling until you get the correct answer.
• [Is GPT-3 Few-Shot Ready?](https://www.

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Quote, Unmodified From Original

Input JSON:

{
    "quote": "We’re changing the way people share around the world with our
               Global Community and 1.4 billion pieces of content under our
               simple, easy-to-use open licenses.",
    "source": "https://creativecommons.org",
    "license": "CC-BY",
    "license_url": "https://creativecommons.org/licenses/by/4.0/",

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Basics

1. Write a function that squares a number

;square : number -> number
(define (square number)
    (* number number) 
  )

(square 5)

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• base2048
• Ecoji (encoji came first, but Ecoji is more popular and is more robust)
• base65536
• Emojisum

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Julia was twenty-six years old. She lived in a hostel with thirty other girls ('Always in the stink of women! How I hate women!' she said parenthetically), and she worked, as he had guessed, on the novel-writing machines in the Fiction Department. She enjoyed her work, which consisted chiefly in running and servicing a powerful but tricky electric motor.

She was 'not clever', but was fond of using her hands and felt at home with machinery. She could describe the whole process of composing a novel, from the general directive issued by the Planning Committee down to the final touching-up by the Rewrite Squad. But she was not interested in the finished product. She 'didn't much care for reading,' she said. Books were just a commodity that had to be produced, like jam or bootlaces.

...

'What are these books [produced by Pornosec] like?' said Winston curiously.

'Oh, ghastly rubbish. They're boring, really. They only have six plots, but they swap them round a bit. Of course I was only on the kaleidoscopes. I wa

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/*
Copyright 2019 Tariq Ali

Licensed under the Apache License, Version 2.0 (the "License");
you may not use this file except in compliance with the License.
You may obtain a copy of the License at

    http://www.apache.org/licenses/LICENSE-2.0

Unless required by applicable law or agreed to in writing, software

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Note: The passage came from http://www.gutenberg.org/files/829/829-h/829-h.htm

The first professor I saw, was in a very large room, with forty pupils about him. After salutation, observing me to look earnestly upon a frame, which took up the greatest part of both the length and breadth of the room, he said, “Perhaps I might wonder to see him employed in a project for improving speculative knowledge, by practical and mechanical operations. But the world would soon be sensible of its usefulness; and he flattered himself, that a more noble, exalted thought never sprang in any other man’s head. Every one knew how laborious the usual method is of attaining to arts and sciences; whereas, by his contrivance, the most ignorant person, at a reasonable charge, and with a little bodily labour, might write books in philosophy, poetry, politics, laws, mathematics, and theology, without the least assistance from genius or study.” He then led me to the frame, about the sides, whereof all his pupils stood in ranks.

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August

Introduction

From a 2017 comment:

Usual critiques of story generators tend to be some variant of "Yes, you can produce short evocative text snippets, but without structure, you can't scale your generator upwards". It seems approaches that require planning and outlines (story compilers, simulations, etc.) are an inverse of that, providing the structure to scale upwards, but are unable to generate the short evocative text snippets on their own.

This may not actually be a problem to worry about though - a human probably need to be in the loop somewhere (at least, if the story is to be enjoyable or useful to other humans).

>But if it does become an issue, maybe we need to have two generators -- use a Markov chain or RNNs to generate short evocative paragraphs for individual topics, and then a large-scale planner to pick paragraphs from those individual topics.

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Fog Computing

In a traditional IoT architeture, you have your normal "device" that transmit messages to the cloud and receive a response. However, this approach is "slow" (high latency) - the device must wait for the following steps to occur:

1. the data being transmitted across the Internet to the cloud provider

2. the cloud provider doing its own processing of the data

3. the cloud provider transmitting the data back to the device

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#Copyright 2018 Tariq R. Ali

#Licensed under the Apache License, Version 2.0 (the "License");
#you may not use this file except in compliance with the License.
#You may obtain a copy of the License at

#    http://www.apache.org/licenses/LICENSE-2.0

#Unless required by applicable law or agreed to in writing, software
#distributed under the License is distributed on an "AS IS" BASIS,