![]() Personally, I’ve always used GitHub Pages and I’m still using it. To name a few: GitHub Pages or Netlify or Firebase Hosting. But how Hugo works is not the topic of this article, so if you are interested to know a bit more, I suggest you look over the documentation.Īs mentioned above, the final output of Hugo is a static website and there are many free solutions to host it. With Hugo, you can write articles or content with Markdown, and then Markdown pages are automatically transformed into HTML and CSS pages when you build the website. It is a powerful tool that lets you have a website up and running in just a few minutes. The site is built with Hugo, one of the most popular static site generator. A bit about tech stack #īefore speaking about the setup, I want to spend some words about the tech stack. I’m pretty confident I’ve ended up with something worth sharing. There’s no perfect solution and Future Me will most likely refactor and (over)re-engineer the current solution), I started to seek the “perfect” writing setup. After I finally landed on the “perfect” tech architecture (I know, I’m lying. After a short while spent on Medium, I decided I wanted to be the sole owner of my content, so I started experimenting with different solutions and ideas. OpenAI will continue building on the safety groundwork we laid with GPT-3-reviewing applications and incrementally scaling them up while working closely with developers to understand the effect of our technologies in the world.It’s been a few years since I started writing this blog, and I quite like sharing my thoughts and experiences. During the initial period, OpenAI Codex will be offered for free. We’re now making OpenAI Codex available in private beta via our API, and we are aiming to scale up as quickly as we can safely. But we know we’ve only scratched the surface of what can be done. We’ve successfully used it for transpilation, explaining code, and refactoring code. OpenAI Codex is a general-purpose programming model, meaning that it can be applied to essentially any programming task (though results may vary). The latter activity is probably the least fun part of programming (and the highest barrier to entry), and it’s where OpenAI Codex excels most. Once a programmer knows what to build, the act of writing code can be thought of as (1) breaking a problem down into simpler problems, and (2) mapping those simple problems to existing code (libraries, APIs, or functions) that already exist. OpenAI Codex empowers computers to better understand people’s intent, which can empower everyone to do more with computers. OpenAI Codex has much of the natural language understanding of GPT-3, but it produces working code-meaning you can issue commands in English to any piece of software with an API. GPT-3’s main skill is generating natural language in response to a natural language prompt, meaning the only way it affects the world is through the mind of the reader. It has a memory of 14KB for Python code, compared to GPT-3 which has only 4KB-so it can take into account over 3x as much contextual information while performing any task. OpenAI Codex is most capable in Python, but it is also proficient in over a dozen languages including JavaScript, Go, Perl, PHP, Ruby, Swift and TypeScript, and even Shell. OpenAI Codex is a descendant of GPT-3 its training data contains both natural language and billions of lines of source code from publicly available sources, including code in public GitHub repositories. ![]()
0 Comments
Leave a Reply. |
AuthorWrite something about yourself. No need to be fancy, just an overview. ArchivesCategories |