Summary: Too many solutions. We are at an inflection point where too many vendors are offering too many solutions for moving our AI/ML models to production. The very real risk is duplication of effort, fragmentation of our data science resources, and incurring unintended new technical debt as we bind ourselves to platforms that have hidden assumptions or limitations in how that approach problems.
Added by William Vorhies on November 25, 2019 at 9:44am — No Comments
Summary: AI/ML itself is the next big thing for many fields if you’re on the outside looking in. But if you’re a data scientist it’s possible to see those advancements that will propel AI/ML to its next phase of utility.
What is RPA?
Robotic Process Automation (RPA) is the utilization of programming with machine learning and AI capacities to deal with high-volume, repeatable tasks, and transactions. RPA is an innovation planned for computerizing business forms. Robotic Process Automation conveys direct productivity and improves accuracy transforming an organization’s workflow. Empowering RPA allows flexibility within the enterprise. Programming robots are easy to…Continue
Added by Vinod Saratchandran on September 10, 2019 at 3:00am — No Comments
Summary: Based on a McKinsey study we reported that 47% of companies had at least one AI/ML implementation in place. Looking back at the data and the dominance of RPA as the most widely reported instance makes us think that the number is probably significantly lower.
Summary: Digital Decisioning Platforms is a new segment identified by Forrester that marries Business Process Automation, Business Rules Management, and Advanced Analytics. For platform developers it’s a new way to slice the market. For users it eases integration of predictive models into the production environment.
Added by William Vorhies on October 30, 2018 at 8:30am — No Comments
For people working in Artificial Intelligence, the term “Human-in-the-Loop” is familiar i.e. a human in the process to validate and improve the AI. There are many situations where it applies, as many as there are AI applications. However. there are still some distinct different ways it can be deployed even within the same application.
Contact Center Example
Let’s take for example the automation of a contact center. A…Continue
Added by Dan Somers on April 19, 2018 at 5:30am — No Comments
Much of the recent AI revolution has been focused on automation through big data and/or sensors and feedback into neural networks. The resulting applications are highly valuable to businesses and consumers. They improve quality of life by optimizing labor and resources. However, these applications fall short when it comes to handling human reasoning. Much of the rationale behind the operation of these systems are implicitly embedded in the data.…Continue
Added by Sing Koo on June 22, 2017 at 11:30am — No Comments
Summary: What are the real threats of job loss from real and AI enhanced virtual robots? How do we position ourselves and our children to succeed in this new environment?
Added by William Vorhies on April 25, 2017 at 8:09am — No Comments
Return on Investment (ROI) is defined as the ratio of a return (benefit or net profit) over the investment of resources that generated this return. Both the return and the investment are typically expressed in monetary units, whereas the ROI is calculated as a percentage.
ROI formula: (Return – Investment)/Investment
It’s typically expressed as a percentage, so multiply your results by 100.…Continue
Added by Amy Porras on August 12, 2016 at 2:30am — No Comments
There has been a lot of activity recently around revenue attribution - marketers want to develop a better understanding of their customer acquisition funnel and be able to measure progress against it. Most of this attention has been focused on the B2C space. However, less work has been done measuring the performance of B2B marketing activities.
Certainly the marketing automation segment is very vibrant with a large number of vendors (both big and small) providing solutions that…Continue
Added by Gregory Thompson on May 23, 2016 at 4:33pm — No Comments
All businesses are at the mercy of data quality challenges. From the moment you capture your first lead, you’ll be fighting a battle against data decay. The bigger the database gets, the more problems the business can encounter, and it isn’t easy to single out a…
We return this week for Part II of our blog with astrophysicist and data scientist, Kirk Borne, Ph.D. Formerly a NASA scientist, he’s one of the foremost experts in big data and its applications in business, government and science − from exploration of space to economic growth. Here again he speaks with Anametrix CEO Pelin Thorogood, this time identifying the areas where he thinks business will benefit most from big data.…
Added by Ryan Montano on May 23, 2014 at 6:30am — No Comments