Today, the average company's workforce is not able to continuously refresh the knowledge and skill levels needed to capitalize on new business opportunities. This situation threatens to worsen over time. Here's a different approach: machine learning and artificial intelligence solutions can proactively offer the workforce an entirely new, future-oriented learning experience across devices and channels--one that is customized, personalized, dynamic and predictive. Business leaders know that thriving in the digital age requires them to take on the disruptive forces changing their industry--with speed, confidence and bold new bets. Nothing less than a similarly bold approach to "new skilling" will prepare the workforce to support continuous innovation and growth.

Automated Machine Learning helps streamline your processes and inspire predictive analytics within your organization. Built for technical and non-technical business leaders, Data-Core's "Citizen Scientists" can perform Machine Learning to use Microsoft Azure Auto ML literally within 1-hour on a best fitted model generated by training the data-set and in a very minimum budget. Automated Machine Learning expects data to be cleaned, feature engineered and labeled. You share your domain expert with us, who explains your business and expectation from your historical data, and we do rest for you. Step 1: We feed your historical data-set (in csv format) in Azure AutoML Platform Step 2: Our "Citizen Scientists" will train the data-set in Azure AutoML to generate the best fitted model.

When was the last time to you read a WhatsApp message that was longer than the screen space? Or spent an extra minute reading a LinkedIn post that was two paragraphs? We live in a world of soundbites, but details still matter--especially when it comes to your cover letter. The biggest challenge on a two-page resume is explaining your past work experience crisply and concisely. In fact, many companies use AI-based programs and algorithms to parse out the basic details of your resume.

The Frontier hub is a tech-enabled, creative space allowing local businesses, clients and staff the opportunity to collaborate and experience the power of technology.

"This (AI) is about augmenting human intelligence. When you step back and look at AI, yes there is hype, it will replace all jobs. We say look that's not the right way to approach it. The correct way to say is that this set of artificial intelligence technologies will augment and assist humans to do their work better," Ashvin Vellody, Partner, Deloitte India told indianexpress.com during an interaction. According to a new report by Deloitte and the Confederation of Indian Industry (CII), AI could prove to be most beneficial in areas like agriculture, manufacturing, education and health care services in India.

The Accenture AI report suggests several ways customers can push on with AI scaling. The consultant's examination of top-performing organizations identified a strong data foundation, multi-disciplinary AI teams and C-suite commitment to an enterprise-wide AI rollout as the key success factors. Ninety-five percent of the survey's respondents cited the importance of data as the bedrock for AI scaling. The top performers, however, "are more intentional and focused on ensuring the right, relevant data assets are in place to underpin their AI efforts," according to the Accenture AI report. Tacking the AI challenge in an integrated way also contributes to scaling.

You've heard of machine learning and seen what it can do, but how exactly do machines learn? We feed algorithms, which are sets of rules used to help computers perform problem-solving operations, large volumes of data from which to learn. Generally, the more data a machine learning algorithm is provided the more accurate it becomes. Machine learning algorithms are split into two main categories based on how they interact with data: Supervised and unsupervised. Due to their differences when analyzing data, these two machine learning categories are better suited for solving different problems.

Today, we're at an inflection point in how we engage with customers to better meet their needs. According to a PwC report, 73% of all people point to customer experience as an important factor in their purchasing decisions. Yet only half of the U.S. consumers say companies are meeting their expectations. In this experience-driven economy, companies who understand the meaning behind customers' needs, listen and learn in every interaction, and consistently create engaging and personal experiences, will win. Companies should adopt AI to get the desired success.

Accenture (NYSE:ACN) has opened a new innovation hub for mining and energy in Perth, Australia. The hub gives mining and energy companies access to "technology innovations including cloud computing, artificial intelligence, the internet of things, virtual and augmented reality, quantum computing, blockchain and drones". Ann Burns, who leads Accenture's Resources sector in Australia and New Zealand, commented: "With this new innovation hub, we are helping raise the innovation profile of Western Australia and Australia overall. We believe that the Western Australian energy and mining sectors can become world leaders in digitalization. Crucial to this is a focus on what we refer to as'triple zero': ideas, design and technologies that help achieve zero harm to workers and machines, zero loss across the value chain, and zero waste for sustainability."

Artificial Intelligence (AI) is having a transformative impact on the financial markets. While delivering enormous efficiencies and lowering barriers to entry, the technology also brings challenges and risks with it – and particularly so when it comes to the overall stability of the market. Distilling insights from the 15 sources including Accenture, Deloitte, HFS Research, McKinsey, Thomson Reuters & PWC, this Impact Brief provides time-poor professionals with insights that are easy-to-read and digest, and can be read in less than 10 minutes.