How to build a deep learning platform with open source components to handle tasks such as training data management and versioning, scalable model training, and deployment.
There is an incredibly common story playing out in countless enterprises in 2020.
With Determined you can cloud burst your deep learning training workloads on GCP’s cost-effective preemptible GPUs, in a way that is friendly to infrastructure teams and model developers alike.
Determined AI and AWS SageMaker are both platforms that accelerate these Machine Learning Engineering workflows, but with key differences that we compare, in detail.
A Response To Andreessen Horowitz’s “The New Business Of AI”
In this post, we explore the reasons behind it and suggest paths towards scalable training that have the potential to reliably work out of the box.
The environmental impact of artificial intelligence (AI) has been a hot topic as of late—and I believe it will be a defining issue for AI this decade.
Decades ago, Japan faced an unavoidable, long-term economic challenge. Even as its economy reached record highs in the late 1980s (fueled by strong auto sales, the rise of innovative companies like Nintendo, and real estate speculation), it was preparing for the coming day when more than a quarter of its population would be over age 65.
In the first of a series of posts, we share some thoughts on papers and blog posts that we’re reading right now that have generated some fiery internal discussion at Determined AI.
With the AI revolution solidly underway, tech’s top 5 companies are investing huge amounts of money into AI development and AI engineering talent.