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The Technologies Every IT Professional Needs to Consider in 2021

Most organizations make annual predictions for the year ahead, but 2021 is different. The past 12 months obviously proved incredibly unpredictable, but this year we already know the world has changed. IT, in particular, has needed to move quickly to support a widespread shift to supporting remote workers. One month into 2021, and we're already seeing the trend continue, and it looks likely to be the same in the years to come.

Interview with AI Ethicist, Alice Thwaite

For our latest expert interview on our blog, we’ve welcomed Alice Thwaite to share her thoughts on the topic of artificial intelligence (AI) as well as the reasons behind founding technology ethics company Hattusia. Alice Thwaite is an AI ethics philosopher and ethicist who specialises in creating democratic information environments.

Incident Reporting and Crime Detection: The Role of Computer Vision

One of the most important uses of Artificial Intelligence (AI) and Machine Learning (ML) lies in the detection and prevention of criminal activities. Today, companies are widely using AI-powered computer vision devices to predict and detect crimes ranging from frauds and theft to violence and cybercrimes. The developments in computer vision technologies enabled authorities to simplify incident reporting and crime detection more efficiently.

6 Ways Artificial Intelligence Improves Software Development

Artificial intelligence is transforming software development. From the code to the deployment, AI is slowly but surely upping its game and helping us discover a brand new paradigm for inventing technology. Algorithm-based machine learning is being used to accelerate the software development lifecycle and AI is supporting developers to optimize software workflow at every stage of the development process.

Five Reasons To Choose Dell and Robin Cloud Native Platform For AI/ML (Blog series - Part 3 of 3)

In part 1 and part 2 of this series, we examined how AI/ML can help improve healthcare and the challenges faced by AI/ML teams in realizing the benefits respectively. In this part, we will explore how Robin and Dell can help overcome these challenges.

Four Key Challenges To Adopting AI/ML In Healthcare (Blog series - Part 2 of 3)

In part 1 of this series, we examined how AI/ML can help improve healthcare. AI/ML is an ambitious undertaking that promises to revolutionize healthcare. Getting excited is easy, but where do you start and why is it not just another empty promise? In fact, despite all these promises and futures, most AI/ML projects fail and don’t deliver. The failure rate of AI/ML projects is starting to make some wonder if this is real or hype.

Using AI and Automation to Enrich the Employee Service Experience

Artificial intelligence (AI) continues to take its place in the tech field. From virtual assistants to software capable of self-remediation, AI enhances everyday user experiences and increases the use of IT automation solutions in the workplace. Most of the tech workforce welcomes AI with open arms and understands the advances smart technology can bring and how it can improve business objectives.

Five Use Cases for AI/ML in Healthcare (Blog series - Part 1 of 3)

Technology has accelerated changes toward information-based healthcare delivery and management. Today’s multi-disciplinary approach to delivering better healthcare outcomes coupled with advanced imaging and genetic-based customized treatment models depend on AI/ML driven information systems. At Robin.io, we believe machine learning is the life-saving technology that will transform healthcare. AI/ML challenges the traditional, reactive approach to healthcare.

AI and machine learning streamline workflows at Coca-Cola

Coca-Cola is one of the most recognizable brands on the planet. That’s because wherever it’s produced, the quality, product, and design are the same. When three Coca-Cola companies merged in 2016 to create Coca-Cola European Partners, operational differences became apparent. The company needed a way to standardize platforms and processes across 13 Western European countries and 50 bottling plants. We had three systems in place, three ways of working, and multiple languages.

Bridge the gap in your OSS by adding an AI brain on top

Telecom companies monitor their network using a variety of monitoring tools. There are separate fault management and performance management platforms for different areas of the network (core, RAN, etc.), and infrastructure is monitored separately. Although these solutions monitor network functions and logic – something that would seem to make sense — in practice this strategy fails to produce accurate and effective monitoring or reduce time to detection of service experience issues.