Tag: AI

Founded in 2015, Emedgene has built an AI-based platform to automatically surface insights from genomics data. Previously, this data would need to be analyzed by genomics experts, of which there are only a few thousand around the world. Emedgene applies machine learning algorithms to generate these insights on the fly, essentially teaching computers how to be genetic researchers.

The Teraki platform, built by AI startup Teraki, automatizes intelligent sensor processing for telematics, video, and 3D point cloud data. The platform is developed with a single ideological concept/goal: Deliver scalability to manage the increasing need to handle sensor data from vehicles and devices in high volumes. Here’s how the team is leveraging AWS IoT services to do it.

Education startup Honorlock has innovated exam integrity by introducing a browser extension rather than a software download, launching exam content protection technology (Search & Destroy™), detecting secondary devices during exams (Multi-Device Detection™), and providing human voice detection. They have also deployed a hybrid approach to exam proctoring, combining both AI and ML), with live human proctors (Live Proctor Pop-In™). Here’s how they’re doing it.

Utkarsh Gupta, Lead Data Scientist at 1mg.com walks us through how the healthcare startup is building a patient-centric digital health repository. In part 2 of this series, he discusses how the infrastructure described above can be used for large scale machine learning applications and the ways to deploy them in production.

Utkarsh Gupta, Lead Data Scientist at 1mg.com walks us through how the healthcare startup is building a patient-centric digital health repository.

The mass digitization of information has made finding the right thing online difficult to say the least. This is precisely the problem Yewno was founded to solve. Leveraging sophisticated AI, built with AWS, the startup analyzes millions of information sources in real-time. Rather than simply hunting for keywords, the startup’s algorithms read text, understand context and meaning, and explain why things are connected.

San Francisco-based Synthesis AI has developed technology that generates vast quantities of photorealistic images and pixel-perfect labels to optimize computer vision training. “The world is exploding with cameras,” says Synthesis AI CEO Yashar Behzadi. “As we look at the new world of autonomous vehicles, augmented reality, and virtual reality, we’ve been fundamentally limited by traditional approaches.”

Being able to choose really powerful instances to reduce your training time on demand, paying only for the seconds you use them, and at the same time having the choice of your notebook instances in your favorite tooling opens large opportunities for cost savings and productiveness across startups. AWS Startup Solutions Architect Manager Daniel Bernao walks us through how to do it.

Founded in 2019, Tecton is on a mission to simplify the process of building and productizing data for machine learning, in an effort to make the technology accessible to any company. Instead of having data scientists and data engineers operating in silos and spending months implementing data pipelines, Tecton automates the complete lifecycle of data for ML.

These days it seems like artificial intelligence and machine learning are being applied to everything. What’s been lost in the rapid popularization of the technologies is the ability to easily explain how they work. That’s where Fiddler comes in.