Take a look at voice applications. When applying a mindful AI approach, and leveraging the power of a global talent pool, developers can account for linguistic elements such as different dialects and accents in the data sets. Many of the people we rely on to crowdsource at Pactera EDGE are not full-time employees, but they develop expertise working regularly in our projects. We use modules and tests to identify and reward those with the strongest capabilities at translation and those that produce the best outcomes for our clients. Establishing a human-centered design framework from the beginning is critical.

Artificial intelligence (AI) must be inclusive to reach its potential. AI applications that solve problems for a small segment of the population will fail to achieve widespread adoption. So, it's important that AI applications be designed and prepared with data that reflects as many segments of the global population as possible. Many moving parts need to be managed well to do that, and one of them is language. The more languages an AI application can handle, the more inclusive it is.

Any AI-based product, ranging from Alexa to Netflix, needs reliable data to teach itself how to be more effective. But what happens when AI lacks enough real data to train itself? This is where synthetic data comes into play. Synthetic data consists of data generated with the assistance of AI. Synthetic data is based on a set of real data.

For example, when applying a mindful AI approach and leveraging the power of a global talent pool, developers can account for linguistic elements such as different dialects and accents in the data sets. At a recent Fortune Most Powerful Women Summit, speakers underscored the value of putting in place a diverse team of people. For instance, Lisa Edwards, president and COO of Diligent, said that having people from diverse backgrounds in data science governance positions prevents a situation where a group's bias simply reinforces the technology's bias. Mindful AI extends that notion to the resources that companies use to perform data collection and curation. Establishing a human-centered design framework from the beginning is critical.

Pactera EDGE, a world-class digital solutions provider for the data-driven, intelligent enterprise, announced the appointment of Vasudevan Sundarababu as a Senior Vice President, Head of Digital Engineering. Sundarababu, who has over 25-years of IT industry experience, most recently served as Global Head of Cloud Data Platforms for Capgemini Financial Services. He was previously Chief Technology Officer of CSS Corp. In his new role, Sundarababu will lead Pactera EDGE's global digital engineering practice, where he will be responsible for the identification and design of new products and solutions, the development of technology strategies and capabilities, and the inception of programs to bring these opportunities to Pactera EDGE's clients. Additionally, he will provide support to the sales team for client proposals and solutions.

Localizing content delivers strong business benefits. According to white paper released by Pactera EDGE and Nimdzi Insights, companies that localize the user experience see a 100%–400% increase in sales, and by localizing into just 10 languages, a brand's message will effectively reach 90% of online customers. As brands appreciate the business benefits of localization, they are increasingly turning to artificial intelligence to make localization more effective. This is true especially for large, complex, multinational businesses that need to adapt multiple products and services across hundreds of geographic markets and cultures. In fact, we believe AI can unlock hyperlocal and hyper-personalized experiences that are culturally aware, as my colleague Ilia Shifrin blogged recently.

Pactera Edge Technology Ltd. is a trusted consulting and technology services partner with proven global capabilities & over 2,300 employees worldwide committed to delivering Digital-themed consulting, Product & Digital Platform Engineering Services, Pactera creates business value for Fortune 2000 companies by accelerating business innovation, enabling new growth, improving operational efficiency and transforming the user experience. Its international presence, experience and teams provide an optimized balance of personalized and high-value service.

Machine-learning models trained on normal behavior are showing cracks --forcing humans to step in to set them straight. People weren't just searching, they were buying too--and in bulk. The majority of people looking for masks ended up buying the new Amazon #1 Best Seller, "Face Mask, Pack of 50". When covid-19 hit, we started buying things we'd never bought before. The shift was sudden: the mainstays of Amazon's top ten--phone cases, phone chargers, Lego--were knocked off the charts in just a few days.

When the U.S. began locking down to slow the spread of the coronavirus, Amazon, grocery stores, and wholesale stores like Costco saw an enormous uptick in consumers wanting to buy a few select items. On Amazon, during the week of April 12th to 18th, the top ten search queries were face masks and N95 masks, hand sanitizer, paper products like paper towels and toilet paper, and sanitizing solutions like Lysol spray and Clorox wipes. So many people bought face masks that April's new #1 selling product on Amazon was "Face Mask, Pack of 50". This trend occurred across every single consumer- and business-facing industry and vertical. Consumers started behaving erratically literally overnight, and they haven't stopped behaving abnormally, creating a massive problem for companies who employ artificial intelligence (AI) and machine learning models.