We just released Diffbot API clients in 36 different programming languages, ranging from general purpose languages (Ruby/Python/Java), to systems languages (Go/C), to scripting languages (Bash), and even embedded (x86-64 anyone?). View them here: http://github.com/diffbot.
Previously, I wrote about how Amazon EC2 Spot Instances + Auto Scaling are an ideal combo for machine learning loads. In this post, I’ll provide code snippets needed to set up a workable autoscaling spot-bidding system, and point out the caveats along the way. I’ll show you how to set up an auto-scaling group with […]
Machine Learning Loads are Different than Web Loads One of the lessons I learned early is that scaling a machine learning system is a different undertaking than scaling a database or optimizing the experiences of concurrent users. Thus most of the scalability advice on the web doesn’t apply. This is because the scarce resources in machine […]
On June 25th, over 80 of Silicon Valley’s top hackers, designers, and students gathered at the Diffbot offices in Palo Alto in the hopes of building the next great Web 3.0 app. Over the next 13 hours, participants learned about data and analysis APIs, formed teams, and wrote code. At the end of the night, only […]
In a recent benchmark, Diffbot placed first overall among text extraction APIs on an academic evaluation set and one sampled from Google News. Tomaz Kovacic, a university student in artificial intelligence, recently conducted a comprehensive benchmark of text extraction methods as part of his thesis. Included in the study are commercial vendors as well as open-source APIs […]