In recent computing, "Automation" is the most commonly used word.
This word often has a negative connotation, as it brings up worries related to job loss and job replacement, but here's the reality.
To analyze what we're trying to automate and how humans will evolve to create new forms of work, we need to:
This is the best time to participate in building the future of work solutions for the next 20 years.
The future is about “working along with robots” not “working against automation or robots."
This generation of humans will be become smarter and will evolve to create new solutions. There will be an increasing demand for those who can understand the future world and technologies like AI and Deep Learning.
Yes, the mundane, repetitive, recurring jobs will go away; but that is to be expected in any form of computing.
So why has the discussion around AI, Machine, Deep Learning and BOTS been significant during the last 2 years?
1. Infrastructure processing abilities have enabled voice based chat processing. This conversational interface integrates with applications and enables end users to interact in new ways. The cloud platform and infrastructure helps with design, development and integration of solutions.
2. We're bringing machines closer to human thinking. As we research contextual human working patterns, and natural interfaces, we're thinking of new ways to compute. The algorithms and data patterns are already available at data sets. The neural network, a programming architecture that can deal with multiple inputs and uses layers of nodes that model neurons, functions like the nervous system.
3. Robots have helped us build human pattern intelligence and algorithms to augment the future world.
4. The technology enablement of extending the five senses (see, hear, feel, touch, taste) in a unified solution is creating a new
world of application possibilities. The virtual, augmented and mixed reality world will change the customer experience.
Furthermore, emotional APIs are being built to augment human behavior. For example, CRM applications that understand how the customer is feeling about your service, without any paper form or discussion, are not far away.
5. With organizations examining productivity and customer cost pressures for business innovation, automation will become the norm with AI technologies. We need resources to enable, architect and execute the automation to determine which tasks are repetitive and mundane in order to continuously create new patterns of innovation.
Oracle is innovating within the the AI/Deep Learning space. These developments are very exciting and will generate a lot of interest in the future.
Adaptive Intelligent Apps are uniquely powered by enormous amounts of the following:
This will continuously improve outcomes as the system reacts, learns and adapts. There is a value exchange between the end user and the adaptive intelligent app: the more the end user interacts, the more value they receive.
Chat bots platform
According to the Oracle Mobile Platform Blog:
"Oracle positions its platform as an interface for enterprise apps. The chatbots will also work with apps like Facebook Messenger, Slack and so on. Chatbots employ a conversational interface that is both lean and smart, and if designed properly, is even charming. They can help people find the things they want and need, in real-time, without the hassle of searching online or navigating a complex customer service organization."
The Virtual Assistant “ChatBot” platform will enable Mobile Cloud Service to engage in conversations across chat channels: SMS, WhatsApp, Facebook Messenger and Slack.
According to the Amis Technology Blog:
"When the APIs invoked by the ChatBot have been implemented using predictive analytics and machine learning, the dialog
may appear smart and include recommendations, proactive responses and relevant warnings."
Oracle Management Cloud
"Oracle Management Cloud is a suite of IT infrastructure monitoring, management and analytics applications delivered as a service. Oracle Management Cloud’s log analytics service, for example, uses machine learning to cluster data and identify patterns in real-time log data to spot outliers and enable administrators to troubleshoot and resolve problems quickly."
According to Oracle.com,
"Another Oracle Management Cloud service,application performance monitoring, continuously learns the behavior of each
application component, such as a web server request, and detects anomalies in real time, reducing the need to manually manage threshold-based alerts across hundreds of metric streams."
IOT Analytics Platform
“The main goal is to provide an IoT analytics platform that combines data from devices and equipment as well as other data lakes or enterprise applications,” says Bhagat Nainani, Oracle Group Vice President of Engineering.
Oracle HCM using Machine Learning
According to Oracle.com,
"Oracle Human Capital Management Cloud’s recruiting feature uses machine learning algorithms to help HR departments sort through resumes. In the past, HR software would 'simply parse through the résumés looking for keywords—the big advantage being the ability to deal with large amounts of data,' says Mark Bennett, work-life and collaborative products strategy director at Oracle."
To build the right AI and deep learning skills, we need to have a deep understanding of database, programming and digital technologies.
A good starting point is to explore the oracle IAAS and PAAS technologies to learn how they can be used to develop augmented solutions on SAAS for the future.
There are multiple components in PAAS/IAAS which are provided as service. These can be used for developing solutions:
Explore Oracle Cloud Learning SAAS, IAAS and PAAS for professionals.
Consider Oracle Student Learning Subscriptions, which leverage the PAAS/IAAS platform.
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