AI News, Advanced bioscience and AI: debugging the future of life
- On 2. januar 2020
- By Read More
AWS re: Invent 2019: Another year of madness and innovation
Who would have thought back in 2012 at the first AWS re: Invent that the conference would eventually grow to draw over 65,000 professionals worldwide and require over six venues in Las Vegas to conduct its agenda?
He accused other cloud providers of providing shallow capabilities and just being “checkbox monkeys.” Amazon is clear about its strategy to focus on transforming the enterprise and not just IT.
Solomon not only provided DJ entertainment to guests before the keynote but described how they worked with AWS to create a “bring your own key service” that allowed them to fully embrace the cloud and accelerate new market offerings.
Cerner, a healthcare technology company that manages 23 petabytes of health data for over 250 million people around the world across 30 countries, continues to explore ways to leverage this data for better care delivery and improved patient outcomes.
By migrating their privately-held data out to AWS and taking advantage of the machine learning services to build, train and deploy predictive models Cerner has been able to prevent costly, second episodes of care.
As if one set of chips was not good enough, AWS also announced Inferentia, the first custom ML chip that delivers up to 3x higher throughput and up to 40% lower costs per inference when compared to traditional GPU powered instances.
concept called root I/O virtualization tax where resources fight for I/O resources causes latencies and jitter and more compute power is consumed for virtualization management than the compute instance.
By moving certain processes to separate chips or cards, outside of the compute CPU’s, you can offload I/O operations, networking, security management, etc.
The announcement of AWS Redshift Advanced Query Accelerator (AQUA) provides a sophisticated hardware-accelerated caching that provides up to 10x better query performance than other cloud platforms on the market.
Existing data warehouse architectures with centralized storage require data to be moved to compute clusters where AQUA is moving the compute to the storage, limiting the amount of data movement required and enabling compute and storage to be scaled independently.
Several years ago, AWS announced SageMaker which was an abstraction service that allowed developers to rapidly build, train, and deploy machine learning models to simplify the infrastructure and avoid having to work at a framework level.
Now AWS has released SageMaker Studio which is an integrated development environment (IDE) for machine learning. You can perform all your steps for building, training, and deploying models in one visual environment.
You can create notebooks to manage experiments and perform debugging and profiling to detect model drift and other anomalies that may result from changing model assumptions.
These “studios” are in the early phases of adoption. While their true ease of use is still yet to be determined, it’s clear that for ML to go mainstream, the model technology needs to become more streamlined.
With Moore’s law finally reaching its limits of scaling chip densities, quantum computing is emerging as the next paradigm in application development at scale.
Amazon Braket is a newly announced, fully managed service that enables users to have access to quantum hardware provided by a variety of quantum computing hardware vendors (D-Wave, Rigetti, etc.) to allow rapid experimentation. Additionally, Amazon is providing access to quantum computing experts through its Amazon Quantum Solutions Lab to better understand the possibilities and practical applications of quantum computing within your business.
While the mainstream applications of quantum computing maybe five or more years away, this is an amazing way for businesses to both understand the potential as well as shape the future direction of quantum computing.
5G revolutionizes mobile computing across several dimensions such as 10 Gb/s peak data rates, 5ms low latency, 10 Tb/s data volumes per square kilometer, connection densities of 1 million devices per square kilometer, higher reliability, and lower energy consumption.
AWS Wavelength brings AWS services to the edge of a 5G network by allowing application traffic to reach servers running in wavelength zones without leaving a mobile provider’s network.