On a monthly basis, I will be rounding up key news associated with the Data Science Platforms space for Amalgam Insights. Companies covered will include: Alteryx, Amazon, Anaconda, Cambridge Semantics, Cloudera, Databricks, Dataiku, DataRobot, Datawatch, Domino, Elastic, H2O.ai, IBM, Immuta, Informatica, KNIME, MathWorks, Microsoft, Oracle, Paxata, RapidMiner, SAP, SAS, SnapLogic, Tableau, Talend, Teradata, TIBCO, Trifacta, TROVE.
Simulating Learning Processes in the Brain With AI/ML
Key Stakeholders: Chief Learning Officers, Chief Human Resource Officers, Learning and Development Directors and Managers, Corporate Trainers, Content and Learning Product Managers.
Why It Matters: The skills necessary for success in the corporate world are varied and include hard skills, people skills and situational awareness. While L&D is embracing the use of AI/ML to analyze learners’ data and to personalize learning paths, curate effective content, and attempt to better engage learners, what L&D has failed to embrace is the application of AI/ML to model each of these distinct learning systems, and their interactions.
Top Takeaway: Corporate learning vendors would be well served to develop AI/ML models that capture the processing characteristics of the three learning systems in the brain known to mediate hard skills, soft skills, and situational awareness learning. A comprehensive AI/ML model that captured the processing characteristics of each of these three distinct learning systems could be used to develop and test products and tools that optimize content curation, learning paths, engagement, and delivery processes that will differ substantially across systems and tasks to be learned.
Vendors with the Skillset and Expertise to Build this AI/ML Tool: Cornerstone, CrossKnowledge, IBM, Infor, LTG, Oracle, Saba, Salesforce, SAP, Workday, and likely many others.
Artificial Intelligence/Machine Learning and L&D
If you have a passion for learning then DevLearn is for you. DevLearn 2018 was quite the event. With excellent keynote addresses, breakout sessions, numerous vendors and great demos it was action-packed. I enjoyed every minute of DevLearn 2018 and I am already looking forward to 2019.
I took a few days to gather my notes and thoughts, and I have a number of observations on DevLearn 2018. I am sure that others who attended DevLearn 2018 will highlight different topics, and acknowledging that I was only able to speak in detail with a dozen or so vendors, here are my Top Four Scientific Observations.
Whether Talent, Behavioral or Data……The Impact of Science Continues to Grow
Relevant Vendors That I Spoke With: Adobe, Allego, EdCast, Inkling, iSpring, Learning Tribes, LEO Learning, MPS Interactive, Mursion, OttoLearn, Rehearsal, Schoox, STRIVR, Valamis
Note: This blog is a followup to Amalgam Insights’ visit to the “Change the Game” event held by IBM in New York City.
On September 19th, IBM announced its launch of a portfolio of AI trust and transparency capabilities. This announcement got Amalgam Insight’s attention because of IBM’s relevance and focus in the enterprise AI market throughout this decade. To understand why IBM’s specific launch matters, take a step back in considering IBM’s considerable role in building out the current state of the enterprise AI market.
IBM AI in Context
Since IBM’s public launch of IBM Watson on Jeopardy! in 2011, IBM has been a market leader in enterprise artificial intelligence and spent billions of dollars in establishing both IBM Watson and AI. This has been a challenging path to travel as IBM has had to balance this market-leading innovation with the financial demands of supporting a company that brought in $107 billion in revenue in 2011 and has since seen this number shrink by almost 30%.
In addition, IBM had to balance its role as an enterprise technology company focused on the world’s largest workloads and IT challenges with launching an emerging product better suited for highly innovative startups and experimental enterprises. And IBM also faced the “cloudification” of enterprise IT in general, where the traditional top-down purchase of multi-million dollar IT portfolios is being replaced by piecemeal and business-driven purchases and consumption of best-in-breed technologies.
Seven years later, the jury is still out on how AI will ultimately end up transforming enterprises. What we do know is that a variety of branches of AI are emerging, including
On a monthly basis, I will be rounding up key news associated with the Data Science Platforms space for Amalgam Insights. Companies covered will include: Alteryx, Anaconda, Cloudera, Databricks, Dataiku, DataRobot, Datawatch, Domino, H2O.ai, IBM, Immuta, Informatica, KNIME, MathWorks, Microsoft, Oracle, Paxata, RapidMiner, SAP, SAS, Tableau, Talend, Teradata, TIBCO, Trifacta.
This week, everybody is talking about Google Duplex, announced earlier this week at Google I/O. Based on previous interactions with IVRs from calling vendors for customer support, Duplex is an impressive leap forward in natural language AI, and offers future hope at making some clerical tasks easier to complete. Duplex will be tested further by a limited number of users in Google Assistant this summer, refining its ability to complete specific tasks: getting holiday hours for a business, making restaurant reservations, and scheduling appointments specifically at a hair salon.
So what does this mean for most businesses?
On February 21, 2018, MindBridge Ai announced updates to its Ai Auditor platform, which is designed to analyze financial data with machine learning and artificial intelligence tools for financial audits. These updates include
Key Takeaway: Amalgam believes that the go-live date of myEinstein will be the most important date for Enterprise AI in 2018 as it represents the day that AI will become practical and available to a broad business audience across industries, verticals, company sizes, and geographies.
On November 6, 2017, Salesforce [NYSE:CRM] announced the launch of myEinstein: services based on Salesforce’s Einstein machine learning platform to support point-and-click-based and codeless AI app development. This announcement was one of several new services that Salesforce built across platform (mySalesforce and myIoT), training (myTrailhead), and user interface development (myLightning).
myEinstein consists of two services:
When I represented Amalgam Insights at Inforum, I was wondering if I would be a fish out of water. After all, I am not an ERP analyst. I am not a retail analyst. I am not an HR technology analyst. And those are the first three things I think of when Infor comes to mind. As an analyst who focuses on technology consumption and bridging gaps between the CIO and CFO, I was wondering what would grab my attention other than Infor’s acquisition of Birst.
I was pleasantly surprised by the clarity of Infor’s vision of supporting industry-specific technology consumption. Infor ended up bringing up three key ideas that are core to the future of technology consumption and will end up being strategic considerations for the future of IT.
Based on Amalgam Insights’ discussions with over two dozen enterprise application solutions over the past six weeks, we believe that a new generation of applications is starting to emerge. Machine Learning has led to the evolution of a new generation of platforms that are transforming expert productivity by providing insights through self-guided logic that improves over time.
Amalgam Insights calls these solutions Role-Based Expert Enhancement Platforms (REEP), an emerging technology made possible by the increasing use of machine learning and artificial intelligence in the business world. We believe that, in the short-term, the emerging value of machine learning will come not from generalized platforms, but from these role-based solutions that will greatly simplify finance, compliance, and sales enablement tasks. As companies start thinking about the role of machine learning in enhancing their organizations, Amalgam recommends that they consider these four key areas of benefit: