This year’s AWS re:Invent was full of new releases and updates, cutting-edge tools, innovative products, and valuable resources to help take advantage of the rapid pace of growth and development in cloud services. For us at Intellify, we were most excited by the focus on building out Machine Learning tools and environments. SageMaker has gotten many new updates, making optimisation, recommendation systems, reinforcement learning (RL) and forecasting models deployable by more users than ever. Tellingly, much of Andy Jassy’s keynote was dedicated to announcing the massive new focus on Machine Learning and AI from AWS, and we are gearing up to help our customers take full advantage of the benefits.
5 Key Takeaways
While we continue to digest the content coming from re:Invent – it is a huge week after all – and begin to work with the expansions to SageMaker, Reinforcement Learning, Elastic Inference, Marketplace, and other ML-based toolkits, here are some of the major takeaways we had from the keynote presentations:
New SageMaker offerings: Ground Truth, Neo, Reinforcement Learning. We have been developing and deploying for our customers on SageMaker (see here, and here) since its first release and have found it a powerful environment for ML projects. AWS is expanding SageMaker even more, including:
Ground Truth: adding the capability to outsource data labelling to either human agents through Mechanical Turk, third parties, or in-house; or a combination of human and intelligent systems. Accurate labelling of data is crucial to successful implementation and integration of data sets for ML, and we can see ourselves taking advantage of this new service to ensure solution accuracy.
Reinforcement Learning (RL): a new environment dedicated to RL algorithms and compute power allowing deployment of RL-based ML solutions, which have much different requirements to supervised and unsupervised learning techniques.
Allowing ML vendors to share their cutting-edge ML algorithms and solutions in AWS Marketplace. Not only will this greatly expand the options available to those seeking pre-built ML solutions, it will also enable us to share some of our expertise on the platform, and more rapidly deploy flexible customer solutions using an array of customisable tools.
Significant expansions on Elastic Inference, and the arrival of AWS’ specialised ML chip: Inferentia. This is particularly exciting for us to see the expansion of flexible compute power for ML. Inference requires significant power when running our models, but for relatively sparse periods of time. The advantage of elastic inference will be in providing that high compute when it is needed, rather than paying for the availability of high compute all month. We’re sure this will make our future inference-based ML projects more cost-effective, while retaining the compute power we need for successful deployment.
The Introduction of DeepRacer and DeepRacer League.We loved this! Based on the new RL environment in AWS, watch out for an Intellify team flexing their ML and data science muscles in the League!
Amazon Textract, Personalize, and Forecast. This past year, customers have shown a lot of interest in document recognition/parsing; recommender systems, especially in ecommerce and customer experience-focused businesses; and time series modelling and forecasting. There are so many vital applications of these ML-based tools, and we can’t wait to get on board with Textract, Personalize, and Forecast to take them to a whole new realm of customers seeking the benefits of AI/ML.
AI and ML are hugely on the rise for both organisations and individuals. AWS’ new suite of releases and expansions to SageMaker, RL, Inference, and Marketplace will only help this field grow at an even faster rate. We’ve been deploying on SageMaker since its release, and these tools will only help us expand what we can offer to customers in terms of cutting edge, competitive AI/ML solutions.
Get in Contact
If you or your organisation are looking to take advantage of AI/ML and its enormous opportunities to boost revenue, create operational efficiency, and enhance competitiveness, please get in contact via phone (02 8089 4073) or email (email@example.com). We are AWS Consulting partners for Machine Learning, with a range of projects already completed across SageMaker and AWS cloud services.