News

Google’s medical AI was super accurate in a lab. Real life was a different story.

Wi-Fi Alliance® delivers more value from Wi-Fi® in 6 GHz

Facebook AI, AWS partner to release new PyTorch libraries

Facebook AI and AWS have partnered to release new libraries that target high-performance PyTorch model deployment and large scale model training. As part of the broader PyTorch community, Facebook AI and AWS engineers have partnered to develop new libraries targeted at large-scale elastic and fault-tolerant model training and high-performance PyTorch model deployment. These libraries enable the community to efficiently productionize AI models at scale and push the state of the art on model exploration as model architectures continue to increase in size and complexity.

Demolishing Wallhacks with VALORANT’s Fog of War

Anti-cheat lead Paul Chamberlain walks us through the technical guts of Fog of War, VALORANT’s anti-wallhack system. From the very beginning of VALORANT development, we made it a priority to build out cheating resistance to ensure competitive integrity. In this article, I’ll walk you through one of these anti-cheat systems – Fog of War.

Nanosensor can alert a smartphone when plants are stressed

MIT engineers have developed a way to closely track how plants respond to stresses such as injury, infection, and light damage, using sensors made of carbon nanotubes. These sensors can be embedded in plant leaves, where they report on hydrogen peroxide signaling waves. Plants use hydrogen peroxide to communicate within their leaves, sending out a distress signal that stimulates leaf cells to produce compounds that will help them repair damage or fend off predators such as insects.

State of the Machine Learning and AI Industry

From 2012 to 2018, blue-chip technology companies implemented custom-built ML platforms for internal use (i.e., Facebook’s FBLearning, Uber’s Michelangelo, Twitter’s Cortex, AirBnB’s BigHead), many of these platforms are primarily based on open-source packages and have been deeply tailored for the specific use cases of their respective companies. Since then, the industry has seen a strong evolution of Enterprise-grade ML platform solutions, including those from incumbent vendors (e.g., Amazon Sagemaker, Microsoft Azure ML, Google Cloud ML, etc.) and the challengers in the space (e.g., DataRobot, H2O, BigML, Dataiku). Incumbent vendors follow an incremental strategy approach, with their ML services offering sitting on top of their existing cloud services as another application layer vs. the MLnativeapproach taken by the challengers.

Your Guide to Natural Language Processing (NLP)

This extensive post covers NLP use cases, basic examples, Tokenization, Stop Words Removal, Stemming, Lemmatization, Topic Modeling, the future of NLP, and more. Everything we express (either verbally or in written) carries huge amounts of information. The topic we choose, our tone, our selection of words, everything adds some type of information that can be interpreted and value extracted from it.

Introducing the Plato Research Dialogue System: A Flexible Conversational AI Platform

Extractive Text Summarization using Glove Vectors

Text summarization is one of famous NLP application which had been researched a lot and still at its nascent stage compared to manual summarization. In simple terms, the objective is to condense unstructured text of an article into a summary automatically. There are two types of summarization techniques.

Text Classification: Best Practices for Real World Applications

Most text classification examples that you see on the Web or in books focus on demonstrating techniques. This will help you build a pseudo usable prototype. If you want to take your classifier to the next level and use it within a product or service workflow, then there are things you need to do from day one to make this a reality.