How to get into digital transformation in 2020?

How to get into digital transformation in 2020?

Digital transformation is simply put – going paperless or hyper-converged, opting for cloud driven processes in operations of a business.

Its underlying efforts are fragmented. A business leader will need to learn, experience and understand its benefits.

In course of time and underlying complexity of digital transformation, the processes get deviated and losses control, consequently doomed to fail. In fact, more than 65  percent of digital transformation efforts fail.

To avoid this, digital transformation needs be strategic. There has to be a real reason for the change and not just for the sake of its glamour and fancy aspects.

In order to get ready with a strategic framework, you will need to read these points below, understand and get answers to the questions put forward.

  1. Understand your specific need. Why are you looking to go digital?
  1. Understand your capabilities. Detail as much as possible on what you’re capable of to avoid the risk of failure.
  1. Identify key stakeholders and seek input and feedback throughout the implementation process.
  1. Take one component at a time and go for implementation.
  1. Set regular benchmarks and check in regularly on your progress towards the goal.
  1. Seek for continuous improvement. Digital transformation is not a one-time process. It is a technology evolution that requires constant progression toward a fully integrated digital infrastructure.  

Want to know more, check-in at https://www.getredtie.com/

Data Analytics | AI Machine Learning

Do You Know The Difference Between Data Analytics And Artificial Intelligence AI Machine Learning?

The artificial intelligence AI industry has been leading the headlines consistently, and for good reason. It has already transformed industries across the globe, and companies are racing to understand how to integrate this emerging technology. Artificial intelligence is not a new concept. The technology has been with us for a long time, but what has changed in recent years is the power of computing, cloud-based service options and the applicability of AI to our jobs as marketers.

Marketing managers have readily engaged with data analytics, benefitting (and most likely suffering) from the mountains of data at their fingertips. This includes everything from user-tracking data on apps and websites, newsletter conversion rates and online advertising click-throughs, to CRM data analysis.

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Source: Forbes

 

HSBC | Google Cloud

HSBC looks to ramp up machine learning usage with Google Cloud

Global bank HSBC has taken its first pilot machine learning projects with Google Cloud Platform (GCP) into production and is now looking to ramp up the porting of applications and data workloads onto the vendor’s cloud infrastructure, once Google provides more granular encryption key controls in August. HSBC is a much-vaunted Google Cloud Platform customer

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Source: CIO

Quantum Computing | AI

How Quantum Computing Will Change The Face Of Artificial Intelligence

The new algorithms provide a general template, showing how quantum computers might be used to provide exponential speedups for central problems like clustering, pattern-matching, and principal component analysis. Clustering is an ML technique used to organise data into similar groups. Xanadu.ai is conducting considerable research in QC and believes that ML and Quantum Machine Learning (QML) will become more pervasive and will redefine the way researchers think about QC.

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Source: AnalyticsIndia

Apple | John Giannandrea

Apple, new AI chief now oversees Siri, Core ML, and machine learning teams

Apple has combined its various artificial intelligence divisions into a new structure led by recent hire John Giannandrea, formerly Google’s head of search and AI.  Apple confirmed the change with an update to its executive leadership page. Giannandrea will now be in charge of Apple’s machine learning division, its Siri team, and the Core ML team. Core ML is the machine learning API  launched last year to help native AI tasks and AI-focused apps and services from third-party developers run more efficiently on iOS devices.

The company lags behind in key AI areas like natural language processing and computer vision, both of which are necessary to power voice assistant features within Siri and new, more cutting-edge technology like augmented reality apps that rely on object recognition.

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Source: TheVerge

Formula 1 | Machine Learning

Formula 1 Uses Machine Learning To Deliver In-Race Predictions To Fans

Formula 1 plans to use cloud technology and machine learning to deliver more engaging statistic and even predictions to fans watching races on television and on its digital platforms. Cloud giant Amazon Web Services (AWS) has been signed up as an official technology partner, with its technology used to crunch the data and deliver it in a more meaningful way to fans and commentators.

Using the AWS platform, it will also be able to analyse data in real time, giving fans an idea of whether a driver is pushing themselves to the limit.

 

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Source: Forbes

AI | Machine Learning | Health

AI and health: Using machine learning to understand the human immune system

Microsoft announced a deal with Adaptive Biotechnologies, a health-tech and gene-sequencing company based out of Seattle. Adaptive Biotechnologies’ gene sequencers are currently used to detect residual myeloma — that is, cells that show a person who’s been treated for blood cancer isn’t entirely free of the disease.

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Source: ZDNet