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Introducing the Inaugural AWS Machine Learning Competency Partners

by Joseph Spisak | on | Permalink | Comments |  Share

Out of all of the innovations that are being driven by cloud, the areas of artificial intelligence (AI) and machine learning (ML) are perhaps the most exciting. IDC, as an example, is forecasting that the market for AI systems to be $46 billion by 2020. This is up from $12.5 billion in 2017 and growing at a compound annual growth rate (CAGR) of 54.4%. Also, according to AngelList, there are over 3000 AI-focused startups.

AI/ML is being applied to every imaginable use case, including protecting us from fraud, helping us discover our entertainment easier, improving customer experience, and predicting when maintenance is needed in industrial equipment.  Perhaps most importantly, it is now being applied to the healthcare industry, where computer vision algorithms are automating radiology diagnosis, clinical data is being used to better predict patient health, precision medicine is tailoring treatments to individual patients, and ML just might discover the next lifesaving drug.

Even though there are aggressive growth projections for AI, there is some skepticism that it’s truly moving beyond research and creating real business value. However, on top of AWS today, a number of customers are already applying AI/ML at scale and solving a variety of problems in a number of segments.

AWS customers such as Arterys are applying computer vision to tackle medical imaging diagnosis. Other customers are using AI/ML in the following ways: Stitch Fix for fashion recommendations, Expedia for travel curation, Redfin for real estate valuation, Zendesk for customer support, 9fin for financial document analysis, and Signal Media for business intelligence. We also see companies building autonomous driving platforms using deep learning (DL) based perception algorithms. ML is even being applied to comb through legal documents.

Simply look to your favorite apps that recommend videos based on your individual tastes, or tag you in a photo automatically, or stream breaking news on a mobile app—all of this is powered by AI/ML.

Even with all of these amazing experiences, there are still challenges to overcome. For example, we continue to see customers with significant data but unfortunately not in a form that is prepared or annotated in a way that ML models can consume it. We also see a shortage of data scientists and ML practitioners that can mold this data into predictive models. And lastly, we see enterprises challenged to operationalize ML and take it to production scale.

What is the AWS Machine Learning Competency?

To help take the market forward and address these challenges, we are excited today to launch the inaugural AWS Partner Network (APN) Competency dedicated specifically to ML technology partners. We are also announcing the coming of a System Integrator and Consulting category that we plan to launch in 2018. We are excited that these leaders in their respective segments are joining AWS on its customer-obsessed quest to help our customers deliver ML at scale.

The ML Technology Competency Partners

The AWS ML Competency showcases industry-leading AWS Partners that provide proven technology and/or implementation capabilities for a variety of use cases including Data Services, Platform Solutions, and SaaS/API Solutions.

Data Services

Data scientists spend around 80% of their time preparing and managing data for analysis. This may include preparation, cleaning, parsing, annotation, and general data management. Partners in this category help data scientists and machine learning practitioners prepare and/or annotate their enterprise data for the eventual training of a predictive model. For example, the CrowdFlower platform is used by 9 out of the top 10 companies building autonomous driving platforms, and it is used by some of the world’s largest companies like EBay and Autodesk.

Including CrowdFlower here are the partners in this category that we believe are best positioned to help solve our customer’s data related challenges:

Platform Solutions

Data scientists and ML practitioners are in short supply so maximizing their effectiveness with efficient platforms, while avoiding time spent on tasks that can be automated, is paramount. The next generation of platforms provides environments where data scientists can take their data, train predictive models and make predictions on new data. These models can be deployed in a few clicks or even loaded onto IoT devices to do edge predictions. As an example, Databricks and C3 IoT provide hosted platforms that take care of the data science heavy lifting for customers like Viacom and Enel respectively.

Including C3 IoT here are our launch partners who provide the next generation platforms we believe will accelerate the next generation of data scientists and ML practitioners:

SaaS/API Solutions

Many of our customers don’t have data science teams or are looking for the most expedient solution without having to embark on developing an ML algorithm from scratch. This can be for reasons of resource constraints, time to market motivations, or simply opportunity cost making an off-the-shelf solution attractive. Examples of our partners that bring instant intelligence to applications include Luminoso (natural language processing), Anodot (time series anomaly detection) and SigOpt (ML model optimization).

Including Anodot, Luminoso, and SigOpt, here is a list of our partners who provide intelligent solutions for easy application workflow integration:

What does it mean to partner with AWS on Machine Learning?

We believe AWS is the pre-eminent place for partners to develop their production ML. Partners can go to market through and alongside our customer channel as well as directly monetize solutions all without ever leaving AWS.

Develop with Amazon AI: Whether you are a research scientist, data scientist, or an application developer, Amazon AI has tools and services to remove the heavy lifting and help you create machine intelligence faster. APN Partners can integrate with AI services such as Amazon Lex and Amazon Polly or just get started quickly using our deep learning Amazon Machine Images (AMIs) for fast prototyping.

Go to Market with APN: The AWS Partner Network (APN) is the global partner program for AWS that focuses on helping partners build successful AWS-based businesses or solutions by providing business, technical, marketing, and go-to-market support. As an APN Partner, you will receive business, technical, sales, and marketing resources to help enable you to grow your business and better support your customers.

Monetize on the AWS Marketplace: In addition to leveraging the Amazon AI services for development and APN as a sell-with channel, we believe AWS Marketplace provides our APN Partners with a unique and increasingly convenient channel for customers to find, subscribe, and deploy partner solutions. Partners can use AWS Marketplace as their go-to-market channel, reaching customers directly without having to build out capabilities for distribution, consumption, or invoicing capabilities.

What is a Competency Partner?

The AWS Competency Program is the global APN Partner program focused on providing our customers and sellers with guidance on the most qualified APN Technology and Consulting Partners. These partners have deep expertise and proven customer success in specific solutions areas, such as Big Data DevOps and IoT; in vertical markets such as Healthcare and Life Sciences, Financial Services, and Digital Media; and with enterprise business applications, including Microsoft Workloads and SAP. AWS Competencies help customers find APN Partners who can bring the right expertise for their specific business needs by quickly narrowing the search among the tens of thousands of partners in the APN network.

Next steps and Resources


About the Author

Joseph Spisak leads AWS’ partner ecosystem focused on Artificial Intelligence and Machine Learning. He has more than 17 years in deep tech working for companies such as Amazon, Intel and Motorola focused mainly on Video, Machine Learning and AI. In his spare time, he plays ice hockey and reads sci-fi.