Engineering: Personalization & AI
How to Achieve a 9ms Inference Time for Transformer Models
Interested in Moderation for your product? Check out Stream's Auto-Moderation Platform! It is crucial for the technology platforms to moderate any harmful content as early as possible. Most modern moderation tools take a few hundred milliseconds to a few seconds to detect harmful content. Often the action against detected harm is taken after the harm
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5 min read
Transformations in Machine Learning
On 8th September 2020, an article in the Guardian was written by a robot called GPT-3. They asked the robot to write an article about why humans should not be scared of robots and Artificial Intelligence. The human editors wrote the introduction for the article and instructed GPT-3 to generate the next possible sentences iteratively.
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17 min read
Activity Feed Personalization 101: Top Feed Features to Improve User Engagement
Personalization comes in many flavors, and the data science team at Stream can help you build your own feeds personalization engine based on your specific needs. In conjunction with our analytics client we recommend tracking every event for every user, such as clicking on a link) we use both engagement and feed data to power
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4 min read
Google Feed Personalization and Recommender Systems
Lately, I’ve been using Google’s feed on Android and it contains several interesting best practices for content discovery. Google’s feed strikes an effective balance between machine learning and follow relationships. With the recent advancements in AI, it can be hard to know when to apply AI and when to use a more manual method. This
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4 min read
Building an End-to-End Deep Learning GitHub Discovery Feed
There's hardly a developer who doesn’t use GitHub. With all those stars, pulls, pushes and merges, GitHub has a plethora of data available describing the developer universe. As a Data Scientist at Stream, my job is to develop recommender systems for our clients so that they can provide a better user experience for their customers. With that said, I wanted to see if I could build a recommendation
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11 min read
Moving Beyond EdgeRank for Personalized Newsfeeds
This blog post is broken into two parts and harkens back to learnings from a prior post. The sum of all these parts is altogether my best effort to provide you with a framework of how to take the creation of personalized news feeds to the next level. Part 1: Theory behind a very basic
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6 min read
Building Your Own Instagram Discovery Engine: A Step-By-Step Tutorial
Isn’t it great how Instagram’s “Explore” section displays content that matches your interests? When you open the application, the content and recommendations shown are almost always relevant to your specific likes, interests, connections, etc. While it may be fun to think we’re the center of the Instagram universe, the reality is that personalized, relevant content
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7 min read
Follow Recommendations in Social Networks
Social media is a series of networks connecting individuals, companies, organizations, and groups to one another. These networks can transcend local, national, and international borders connecting people to networks far and wide. With all those connections, how can a user find the ones that they want to connect with? That’s where follow suggestions come in.
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4 min read