Ghost has a flexible organisational taxonomy called tags and the ability to create custom site structures using dynamic routes.
You can think of tags like Gmail labels. By tagging posts with one or more keyword, you can organise articles into buckets of related content.
When you create content for your publication you can assign tags to help differentiate between categories of content.
For example you may tag some content with News and other content with Podcast, which would create two distinct categories of content listed on
If you tag a post with both
Podcast - then it appears in both sections. Tag archives are like dedicated home-pages for each category of content that you have. They have their own pages, their own RSS feeds, and can support their own cover images and meta data.
Inside the Ghost editor, you can drag and drop tags into a specific order. The first tag in the list is always given the most importance, and some themes will only display the primary tag (the first tag in the list) by default.
News, Technology, Startup
So you can add the most important tag which you want to show up in your theme, but also add related tags which are less important.
Sometimes you may want to assign a post a specific tag, but you don't necessarily want that tag appearing in the theme or creating an archive page. In Ghost, hashtags are private and can be used for special styling.
For example, if you sometimes publish posts with video content - you might want your theme to adapt and get rid of the sidebar for these posts, to give more space for an embedded video to fill the screen. In this case, you could use private tags to tell your theme what to do.
Here, the theme would assign the post publicly displayed tags of News - but it would also keep a private record of the post being tagged with #video. In your theme, you could then look for private tags conditionally and give them special formatting.
You can find documentation for theme development techniques like this and many more over on Ghost's extensive theme docs.
Dynamic routing gives you the ultimate freedom to build a custom publication to suit your needs. Routes are rules that map URL patterns to your content and templates.
You may not want content tagged with
News to exist on:
example.com/tag/news. Instead, you want it to exist on
In this case you can use dynamic routes to create customised collections of content on your site. It's also possible to use multiple templates in your theme to render each content type differently.
There are lots of use cases for dynamic routing with Ghost, here are a few common examples:
Dynamic routing can be configured in Ghost using YAML files. Read our dynamic routing documentation for further details.
Work with all your favourite apps and tools using our integrations, or create your own custom integrations with webhooks.
We’re releasing an analysis showing that since 2012 the amount of compute needed to train a neural net to the same performance on ImageNet 1 classification has been decreasing by a factor of 2 every 16 months. Compared to 2012, it now takes 44 times less compute to train a neural network to the level of AlexNet 2 (by contrast, Moore’s Law 3 would yield an 11x cost improvement over this period). Our results suggest that for AI tasks with high levels of recent investment, algorithmic progress has yielded more gains than classical hardware efficiency.Read Paper
Algorithmic improvement is a key factor driving the advance of AI. It’s important to search for measures that shed light on overall algorithmic progress, even though it’s harder than measuring such trends in compute. 4
Algorithmic efficiency can be defined as reducing the compute needed to train a specific capability. Efﬁciency is the primary way we measure algorithmic progress on classic computer science problems like sorting. Efficiency gains on traditional problems like sorting are more straightforward to measure than in ML because they have a clearer measure of task difficulty. 
However, we can apply the efficiency lens to machine learning by holding performance constant. Efficiency trends can be compared across domains like DNA sequencing17 (10-month doubling), solar energy18 (6-year doubling), and transistor density3 (2-year doubling).
We are standardizing OpenAI’s deep learning framework on PyTorch. In the past, we implemented projects in many frameworks depending on their relative strengths. We’ve now chosen to standardize to make it easier for our team to create and share optimized implementations of our models.Browse Microscope
$ pip install procgen # install $ python -m procgen.interactive --env-name starpilot # human $ python <<EOF # random AI agent import gym env = gym.make('procgen:procgen-coinrun-v0') obs = env.reset() while True: obs, rew, done, info = env.step(env.action_space.sample()) env.render() if done: break EOF
We’ve designed all Procgen environments to satisfy the following criteria:
High Diversity: Environment generation logic is given maximal freedom, subject to basic design constraints. The diversity in the resulting level distributions presents agents with meaningful generalization challenges.
Fast Evaluation: Environment difficulty is calibrated such that baseline agents make significant progress after training for 200M timesteps. Moreover, the environments are optimized to perform thousands of steps per second on a single CPU core, enabling a fast experimental pipeline.
Tunable Difficulty: All environments support two well-calibrated difficulty settings: easy and hard. While we report results using the hard difficulty setting, we make the easy difficulty setting available for those with limited access to compute power. Easy environments require approximately an eighth of the resources to train.
Emphasis on Visual Recognition and Motor Control: In keeping with precedent, environments mimic the style of many Atari and Gym Retro games. Performing well primarily depends on identifying key assets in the observation space and enacting appropriate low level motor responses.
OpenAI builds free software for training,
benchmarking, and experimenting with AI.