MapR Technologies, Inc., the industry's leading data platform for AI and Analytics, announced today at Strata Data Conference six
new data science service offerings to help customers gain immediate
value from Machine Learning (ML) and Artificial Intelligence (AI) and
expand their competitive edge over competitors, no matter where the
customer is in their data science journey.
Because
AI and ML can be complex, organizations don't always have the capacity
to execute on AI and ML ideas. Those that do, may not be able to bring
those ideas to production. According to McKinsey Global Institute,
early adopters of ML have a 3 to 15% profit advantage across sectors.
Many say they achieve revenue increases by using AI in core processes.
Some organizations may lack the internal knowledge and expertise, but
this should not hold them back entirely.
"The
MapR Data Science team has helped dozens of organizations get to the
next stage in their AI journey," said Joe Blue, director data science,
MapR Technologies. "We've learned that there is no one-size fits all
approach that will work for every organization. When we engage with
organizations, we learn where they are in their AI maturity level and
what their objectives are to come up with a customized plan to get them
to the next level."
Details of New MapR Data Science Lifecycle Offerings:
- AI/ML Hack-a-thon.
In this offering, the MapR Data Science team works with the
organization to identify a business use case and rapidly prototype a
solution. This offering is targeted toward AI and ML contemplators, and
is meant to be a short, hands-on session that delivers a real ML and AI
solution that the organization will continue to improve and maintain
over time.
- Data Science Refinery Accelerator.
MapR's Data Science Refinery unlocks container and ML technologies and,
with this engagement, an expert will guide customers through
installation, best practices, and baseline models to ensure maximum
production success. For a limited time, a one-week engagement is
included when purchasing the MapR Data Platform, a $15k value.
- Cybersecurity Advanced Protection.
Network security vendors are usually effective at spotting known
patterns, but there are often "unknown" gaps that could allow evolving
hackers to gain entry or inflict damage. The MapR cybersecurity data
science offering orchestrates a real-time pipeline of logs (e.g.
application logs, transaction logs, etc.) and trains models based on the
unique signature of network sources and traffic. Ultimately, the
organization receives a visual, UI-based assessment showing suspicious
activity, allowing internal security experts to review and escalate
threats in real-time.
- ML Deployment.
Building ML solutions to solve business problems doesn't actually
address that problem until the model can make real decisions. The issue
is that many environments have limitations in using data and scaling
decisions. Intended for organizations that are further along in their ML
/ AI journey, the model deployment offering
maximizes a model's value by uploading the modeling process to the MapR
Data Platform. The solution is then poised to take advantage of all the
organization's data, utilize every ML library, and deliver results that
will scale and improve with the business.
- AI Enablement.
With this offering, the data science team combines the MapR ML
framework with Streaming events to deploy an AI engine that will begin
to find new opportunities for optimization through a continuous learning
and feedback loop. The team uses Machine Learning to bring order to the
chaotic nature of a system's behavior (e.g., a person, a car, a
pipeline, etc.), then apply reinforcement learning to teach the system
to adapt to identify and assess unusual cases to achieve generalization.
- ML Model Maintenance. ML
models degrade over time. In many cases, the arrival of performance
results lags behind the next model deployment. Designed for mature ML
processes, this offering enables organizations to monitor their ML
workflows for events that might impact their accuracy in lieu of
performance data. Having detected those impacts, the business will be
able to make more informed decisions, such as when the current model
should be replaced.
"Production
success with AI and ML depends on deploying and then evaluating models
over time," explained Ted Dunning, chief applications architect, MapR
Technologies. "The ML Model Maintenance offering streams diagnostics and
makes it easier to offers better model evaluation, and improves the
ability to respond, increasing the agility and effectiveness of an
organization's ML and AI deployment."
Availability
The new MapR data science offerings are immediately available.