AWS Machine Learning - AI
NOVEMBER 26, 2024
AWS Trainium and AWS Inferentia based instances, combined with Amazon Elastic Kubernetes Service (Amazon EKS), provide a performant and low cost framework to run LLMs efficiently in a containerized environment. Adjust the following configuration to suit your needs, such as the Amazon EKS version, cluster name, and AWS Region.
TechCrunch
APRIL 28, 2022
But they share a common bottleneck: hardware. New techniques and chips designed to accelerate certain aspects of AI system development promise to (and, indeed, already have) cut hardware requirements. Emerging from stealth today, Exafunction is developing a platform to abstract away the complexity of using hardware to train AI systems.
This site is protected by reCAPTCHA and the Google Privacy Policy and Terms of Service apply.
AWS Machine Learning - AI
APRIL 10, 2025
As cluster sizes grow, the likelihood of failure increases due to the number of hardware components involved. Each hardware failure can result in wasted GPU hours and requires valuable engineering time to identify and resolve the issue, making the system prone to downtime that can disrupt progress and delay completion.
AWS Machine Learning - AI
NOVEMBER 26, 2024
Using vLLM on AWS Trainium and Inferentia makes it possible to host LLMs for high performance inference and scalability. Deploy vLLM on AWS Trainium and Inferentia EC2 instances In these sections, you will be guided through using vLLM on an AWS Inferentia EC2 instance to deploy Meta’s newest Llama 3.2 You will use inf2.xlarge
CIO
SEPTEMBER 10, 2024
In continuation of its efforts to help enterprises migrate to the cloud, Oracle said it is partnering with Amazon Web Services (AWS) to offer database services on the latter’s infrastructure. Oracle Database@AWS is expected to be available in preview later in the year with broader availability expected in 2025.
AWS Machine Learning - AI
NOVEMBER 14, 2024
of a red apple Practical settings for optimal results To optimize the performance for these models, several key settings should be adjusted based on user preferences and hardware capabilities. A photo of a (red:1.2) apple A (photorealistic:1.4) (3D render:1.2) Start with 28 denoising steps to balance image quality and generation time.
AWS Machine Learning - AI
MARCH 3, 2025
Although many customers focus on optimizing the technology stack behind the FM inference endpoint through techniques such as model optimization , hardware acceleration, and semantic caching to reduce the TTFT, they often overlook the significant impact of network latency. Next, create a subnet inside each Local Zone.
Expert insights. Personalized for you.
100 
Let's personalize your content