AWS Startups Blog

AWS Editorial Team

Author: AWS Editorial Team

Amazon Web Services

How Startups Deploy Pretrained Models on Amazon SageMaker

For most machine learning startups, the most valuable resource is time. They want to focus on developing the unique aspects of their business, not managing the dynamic compute infrastructure needed to run their applications. Productionizing machine leaning should be easier, and that’s where AWS comes in. In this blog post and corresponding GitHub repo, you will learn how to bring a pre-trained model to Amazon SageMaker to have production-ready model serving in under 15 minutes.

Understanding the New World of Office Space with Basking

Overnight, the COVID-19 pandemic reshaped how and where Americans work. By June, according to a survey from Stanford researchers, 42% of the U.S. labor force was working from home full time, with millions more not working at all. For employers, that shift has led to new challenges as they navigate an unprecedented economy. One big question: what to do with all the empty offices?

tips for funding startups

Settld: Finding Grant Funding for your Startup

There are different ways of securing early startup cash, aside from personal bank loans or begging family and friends. One option is grant funding. Whilst there are caveats of relying upon this approach, the cash comes with no equity dilution and can offer a pre-revenue lifeline. Here is what Settld has learnt from going through the process so far.

Enabling AI and Machine Learning Model Training with Teraki

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.