Commonsense question-answering (QA) methods combine the power of pre-trained Language Models (LM) with the reasoning provided by Knowledge Graphs (KG). A typical approach collects nodes relevant to the QA pair from a KG to form a Working Graph (WG) followed by reasoning using Graph Neural Networks(GNNs). This faces two major challenges: (i) it is difficult to capture all the information from the QA in the WG, and (ii) the WG contains some irrelevant nodes from the KG. To address these, we propose GrapeQA with two simple improvements on the WG: (i) Prominent Entities for Graph Augmentation identifies relevant text chunks from the QA pair and augments the WG with corresponding latent representations from the LM, and (ii) Context-Aware Node Pruning removes nodes that are less relevant to the QA pair. We evaluate our results on OpenBookQA, CommonsenseQA and MedQA-USMLE and see that GrapeQA shows consistent improvements over its LM + KG predecessor (QA-GNN in particular) and large improvements on OpenBookQA.

Pegasystems Inc., the low-code platform provider that builds agility into the world's leading organizations, announced its 2022 Pega Community Hackathon is now open for registration. In its third year, this global contest invites both professional and citizen developers to compete in building meaningful new apps that help solve real-world business and social problems that continue to emerge. Open to the entire Pega community, individuals and teams will leverage the intuitive, low-code Pega Platform environment throughout the development process -- from ideation and design to building and execution. Pega will offer extensive technology resources and mentorship, including office hours access with Pega experts for guidance and technical help. Registered participants can start building today and must complete their projects by October 7, 2022 with a solution concept and prototype that's ready for implementation.

UiPath Inc. has always been an unconventional company. It started with humble beginnings as essentially a software development shop. It then caught lightning in a bottle with its computer vision technology and simplification mantra, creating easy-to-deploy software robots for bespoke departments to automate mundane tasks. The company grew rapidly and was able to go public earlier this year. Consistent with its out-of-the-ordinary approach, while other firms are shutting down travel and physical events, UiPath is moving ahead with Forward IV, its annual user conference next week -- with a live audience at the Bellagio in Las Vegas. It's also "fast forwarding" as a company, determined to lead the charge beyond robotic process automation point tools and execute on a more all-encompassing enterprise automation agenda.

As we continue to move forward in digital transformation, an increasing number of companies are discovering the promise of robotic process automation (RPA). In a nutshell, RPA allows companies to gain efficiencies and (hopefully) save money by automating routine tasks. RPA is what I'd call the low-hanging fruit of artificial intelligence. It's governed by structured input. Its processes are mundane and rule-based.

This demo will show you how to leverage a machine learning service by running a churn model created externally and using its outputs in Pega Prediction Studio. The steps are similar to using other machine learning services such as Google AI Platform. Using a machine learning service instead of a model that runs locally may involve costs and possible down time of the service. However, for certain use cases such as churn or credit risk models, machine learning services can be the optimal choice. To showcase how to use a churn model created in Amazon SageMaker, let's first consider the high-level steps involved in creating a machine learning model.

It has started just 1 or 2 peoples out there … just few days you might not have used it … important, this is not new playing … must started 2020. We feel peoples will use #AI soon … but now it has become exactly to work with #Robots started soon!! I looked, at #UiPath and #PEGA … these might working well … Let use see how it worked!! They hope that things work automotive … that is the way company thinks will work … but in reality people have to know at lease now, may be it will be sleet after some time. At #UiPath will provide changes #free in will be done … but I think, some changes will be needed envoy … did you know home?

TTEC Holdings, Inc., a leading digital customer experience technology and services company focused on the design, implementation and delivery of transformative solutions for many of the world's most iconic and disruptive brands, announced a strategic partnership with Pegasystems, Inc., the software company empowering digital transformation at the world's leading enterprises. This partnership will empower clients with industry-leading digital transformation solutions to optimize customer experiences within their contact centers. With the partnership, Pega's world-class intelligent automation and customer engagement suite, combined with TTEC's Customer Experience as a Service platform, will provide the backbone of optimized, digitally driven employee and customer experiences managed by TTEC Digital. The two market leaders will leverage their decades of experience to deliver best-of-breed human and AI-powered intelligence across the customer lifecycle. Together, TTEC and Pega are uniquely positioned to remove the technical and operational obstacles that stand in the way of great experiences for a brand's customers and employees.

A new report released by Pega that examined consumer attitudes towards artificial intelligence indicates that despite the growing usage of AI technologies, consumers lack an understanding of how they can benefit from AI and are more likely to trust a real person to help make decisions. "Our study found that only 25% of consumers would trust a decision made by an AI system over that of a person regarding their qualification for a bank loan," said Dr. Rob Walker, vice president, decisioning and analytics at Pega. "Consumers likely prefer speaking to people because they have a greater degree of trust in them and believe it's possible to influence the decision, when that's far from the case. What's needed is the ability for AI systems to help companies make ethical decisions. To use the same example, in addition to a bank following regulatory processes before making an offer of a loan to an individual it should also be able to determine whether or not it's the right thing to do ethically." As a result of the survey's findings, Pega announced the launch of its Customer Empathy Advisor, an AI tool that seeks to incorporate empathy and ethical-decision making in the framework of AI technologies.

As we continue to move forward in digital transformation, an increasing number of companies are discovering the promise of robotic process automation (RPA). In a nutshell, RPA allows companies to gain efficiencies and (hopefully) save money by automating routine tasks. RPA is what I'd call the low-hanging fruit of artificial intelligence. It's governed by structured input. Its processes are mundane and rule-based.

To take care of all the mundane tasks employees currently handle, freeing their time to be more creative and perform the work that machines cannot. Today, the emerging technology is used mostly by large enterprises through machine learning and predictive analytics. Here's a look at the current state of AI and what lies ahead. But 31% said it is on the agenda for the next 12 months. Unsurprisingly, analysis of data is a key AI focus for businesses, with on-site personalization the second most commonly cited use case for AI.