s1lv3rj1nx/ch2
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id int64 0 217 | title stringlengths 5 52 | date stringlengths 8 14 ⌀ | text stringlengths 404 75.5k |
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0 | The Age of the Essay | September 2004 | Remember the essays you had to write in high school? Topic sentence, introductory paragraph, supporting paragraphs, conclusion. The conclusion being, say, that Ahab in _Moby Dick_ was a Christ-like figure.
Oy. So I'm going to try to give the other side of the story: what an essay really is, and how you write one. Or a... |
1 | A Plan for Spam | August 2002 | _(This article describes the spam-filtering techniques used in the spamproof web-based mail reader we built to exercise [Arc](arc.html). An improved algorithm is described in [Better Bayesian Filtering](better.html).)_
I think it's possible to stop spam, and that content-based filters are the way to do it. The Achille... |
2 | The Trouble with the Segway | July 2009 | The Segway hasn't delivered on its initial promise, to put it mildly. There are several reasons why, but one is that people don't want to be seen riding them. Someone riding a Segway looks like a dork.
My friend Trevor Blackwell built [his own Segway](http://tlb.org/#scooter), which we called the Segwell. He also buil... |
3 | After Credentials | December 2008 | A few months ago I read a _New York Times_ article on South Korean cram schools that said
> Admission to the right university can make or break an ambitious young South Korean.
A parent added:
> "In our country, college entrance exams determine 70 to 80 percent of a person's future."
It was striking how old fashion... |
4 | High Resolution Fundraising | September 2010 | The reason startups have been using [more convertible notes](http://twitter.com/paulg/status/22319113993) in angel rounds is that they make deals close faster. By making it easier for startups to give different prices to different investors, they help them break the sort of deadlock that happens when investors all wait... |
5 | Where to See Silicon Valley | October 2010 | Silicon Valley proper is mostly suburban sprawl. At first glance it doesn't seem there's anything to see. It's not the sort of place that has conspicuous monuments. But if you look, there are subtle signs you're in a place that's different from other places.
**1\. [Stanford University](http://maps.google.com/maps?q=st... |
6 | Keep Your Identity Small | February 2009 | I finally realized today why politics and religion yield such uniquely useless discussions.
As a rule, any mention of religion on an online forum degenerates into a religious argument. Why? Why does this happen with religion and not with Javascript or baking or other topics people talk about on forums?
What's differe... |
7 | What Kate Saw in Silicon Valley | August 2009 | Kate Courteau is the architect who designed Y Combinator's office. Recently we managed to recruit her to help us run YC when she's not busy with architectural projects. Though she'd heard a lot about YC since the beginning, the last 9 months have been a total immersion.
I've been around the startup world for so long t... |
8 | Revenge of the Nerds | May 2002 | "We were after the C++ programmers. We managed to drag a lot of them about halfway to Lisp."
\- Guy Steele, co-author of the Java spec
In the software business there is an ongoing struggle between the pointy-headed academics, and another equally formidable force, the pointy-haired bosses. Everyone knows who the point... |
9 | The Python Paradox | August 2004 | In a recent [talk](gh.html) I said something that upset a lot of people: that you could get smarter programmers to work on a Python project than you could to work on a Java project.
I didn't mean by this that Java programmers are dumb. I meant that Python programmers are smart. It's a lot of work to learn a new progra... |
10 | Design and Research | January 2003 | _(This article is derived from a keynote talk at the fall 2002 meeting of NEPLS.)_
Visitors to this country are often surprised to find that Americans like to begin a conversation by asking "what do you do?" I've never liked this question. I've rarely had a neat answer to it. But I think I have finally solved the prob... |
11 | What I've Learned from Hacker News | February 2009 | Hacker News was two years old last week. Initially it was supposed to be a side project—an application to sharpen Arc on, and a place for current and future Y Combinator founders to exchange news. It's grown bigger and taken up more time than I expected, but I don't regret that because I've learned so much from working... |
12 | The List of N Things | September 2009 | I bet you the current issue of _Cosmopolitan_ has an article whose title begins with a number. "7 Things He Won't Tell You about Sex," or something like that. Some popular magazines feature articles of this type on the cover of every issue. That can't be happening by accident. Editors must know they attract readers.
W... |
13 | The Anatomy of Determination | September 2009 | Like all investors, we spend a lot of time trying to learn how to predict which startups will succeed. We probably spend more time thinking about it than most, because we invest the earliest. Prediction is usually all we have to rely on.
We learned quickly that the most important predictor of success is determination.... |
14 | Startups in 13 Sentences | February 2009 | One of the things I always tell startups is a principle I learned from Paul Buchheit: it's better to make a few people really happy than to make a lot of people semi-happy. I was saying recently to a reporter that if I could only tell startups 10 things, this would be one of them. Then I thought: what would the other 9... |
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YAML Metadata Warning:The task_categories "text2text-generation" is not in the official list: text-classification, token-classification, table-question-answering, question-answering, zero-shot-classification, translation, summarization, feature-extraction, text-generation, fill-mask, sentence-similarity, text-to-speech, text-to-audio, automatic-speech-recognition, audio-to-audio, audio-classification, audio-text-to-text, voice-activity-detection, depth-estimation, image-classification, object-detection, image-segmentation, text-to-image, image-to-text, image-to-image, image-to-video, unconditional-image-generation, video-classification, reinforcement-learning, robotics, tabular-classification, tabular-regression, tabular-to-text, table-to-text, multiple-choice, text-ranking, text-retrieval, time-series-forecasting, text-to-video, image-text-to-text, image-text-to-image, image-text-to-video, visual-question-answering, document-question-answering, zero-shot-image-classification, graph-ml, mask-generation, zero-shot-object-detection, text-to-3d, image-to-3d, image-feature-extraction, video-text-to-text, keypoint-detection, visual-document-retrieval, any-to-any, video-to-video, other
Dataset Card for Paul Graham Essay Collection Dataset
Dataset Description
This dataset contains a complete collection of essays written by Paul Graham, a renowned programmer, venture capitalist, and essayist. The essays cover a wide range of topics including startups, programming, technology, entrepreneurship, and personal growth. Each essay has been cleaned and processed to extract the title, date of publication, and the full text content.
Dataset Structure
The dataset is provided in a tabular format with the following columns:
title: The title of the essay.date: The date when the essay was originally published, in the format Month YYYY.text: The full text content of the essay.
Data Sources
The essays in this dataset have been sourced from Paul Graham's personal website at http://www.paulgraham.com/.
Data Preprocessing
The essays have undergone the following preprocessing steps:
- Extraction of title and publication date from the essay's metadata.
- Removal of promotional material unrelated to the essay's content.
- Conversion of the essay text to plain text format.
- Cleaning of the text to remove any extraneous whitespace or special characters.
Intended Use and Limitations
This dataset is intended for various natural language processing tasks such as question-answering, summarization, text generation, and text-to-text generation. The essays provide valuable insights and perspectives on a range of topics and can be used for training models or conducting analyses related to startups, technology, and personal growth.
However, it's important to note that the essays reflect the personal views and opinions of Paul Graham and may not be representative of a broader population. The content should be used with appropriate context and understanding of its subjective nature.
License and Attribution
This dataset is released under the MIT License. When using this dataset, please attribute it to Paul Graham and provide a link to his website at http://www.paulgraham.com/.
Contact Information
For any questions or inquiries about this dataset, please contact sgoel9@berkeley.edu.
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