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AI is thriving on and driving the edge

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Connected devices and instant mobile access to data is a common facet of modern life, but the fact is that we’ve only just begun this transition to a digital universe. In the near future, autonomous cars will be buzzing through our streets, everything from our shoes to our eyeglasses and even our own body parts will be connected, and digital agents will be assisting us at every turn, and cataloging everything we do.

It sounds scary, and it will most certainly produce a number of thorny issues surrounding privacy, self-determination, and even what it means to be human. But underpinning all of it will be the edge, the layer of infrastructure currently under development that will provide much of the processing and storage needed by devices to carry out their real-time functions.

Automated and autonomous on the edge

By its nature, the edge will be widely distributed. Small nodes of compute and storage will exist in towns and neighborhoods, along highways and power lines, and virtually anywhere else they are needed. They will also be unmanned, for the most part, and will have to be enabled with a great deal of automation and autonomy to accommodate the massive and diverse requirements of a connected world.

This sounds like a job for artificial intelligence.

The edge, after all, is an ideal environment for AI, largely because it’s still in the greenfield stage of development. Unlike in the datacenter, there are no legacy systems to contend with, no processes to be reworked, or code to be altered. AI becomes the foundational element of an all-new data ecosystem. Dell Technologies, for one, is already churning out edge-specific AI solutions, many of them fully validated and integrated among compute, storage, network, software, and services for optimized AI workloads.

If anything, the pandemic has accelerated the drive to infuse AI into edge infrastructure, says IOT World Today’s Callum Cyrus. As remote work and ecommerce took off, organizations turned to machine learning and other tools to overcome the significant operational challenges they faced. But this only increased the data load at the edge, which now requires greater use of AI in order to maintain the speed and flexibility that emerging applications require. A key development is a new generation of intelligent chips, which will soon inhabit all levels of the edge processing spectrum, from general, entry-level machine learning cores to specialty A/V and graphics machines and advanced neural network microcontrollers.

Putting AI to good use on edge

A look at some use cases for AI on the edge shows just how powerful this new intelligent infrastructure can be, notes XenonStack’s Jagreet Kaur. Once you empower systems and devices with high-level decision-making capabilities, you can push a wide range of advanced applications to users. Among them are digital map projections, dual-facing AI dashcams, advanced security for shops and offices, and broader use of satellite imagery. Virtually every function that enters the digital ecosphere will be empowered by AI before long.

Organizations that are looking to strategize around these developments should keep three factors in mind, says Intel VP Brian McCarson. First, open source becomes a key enabler because AI thrives on ready access to as much data and as many resources as possible. Secondly, video will become a major asset as organizations evolve in the new economy. This means AI’s capability to leverage video at the edge will be a primary driver for success, and this will accelerate the need for greater investment in both AI platforms and infrastructure. And finally, change will take place rapidly on the edge as new systems and new applications eat the old ones. Whatever you deploy on the edge now, be prepared to revamp it sooner rather than later.

Note that AI development on the edge shouldn’t take place independently of development elsewhere on the enterprise data footprint. Interoperability among the datacenter, cloud, edge, and any other infrastructure that comes along will be crucial — again because AI is only as good as the data and resources it can leverage.

While it may be tempting to view the edge as simply an extension of legacy infrastructure, the reverse is true: the edge is the new foundation for the services that affect people’s lives. In this light, AI at the edge should be the driver for AI in the cloud and the datacenter, at least if your business model is centered on fulfilling user needs, not your own.

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Identity in the metaverse: Creating a global identity system

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With the advent of the metaverse, the need for a global identity system has become apparent. There are many different ways to create an identity in the metaverse, but no single system is universally accepted. 

The challenge is usually two-fold: first, how to create an identity that is accepted by all the different platforms and services in the metaverse, and second, how to keep track of all the different identities a person may have.

There are many proposed solutions to these challenges, but no clear consensus has emerged. Some believe that a single, global identity system is the only way to ensure interoperability between different platforms and services. Others believe that multiple identities are necessary to allow people to maintain their privacy and security.

The debate is ongoing, but it is clear that the need for a global identity system is becoming more urgent as the metaverse continues to grow.

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In this article, we will explore the various options for creating a global identity system in the metaverse. We will discuss the pros and cons of each option, and try to identify the best solution for the future.

Option 1: A single global identity

The simplest solution to the problem of identity in the metaverse is to create a single, global identity system. This would be a centralized system that would be responsible for managing all identities in the metaverse. 

The advantages of this approach are obvious: It would be much easier to keep track of identities, and there would be no need to worry about different platforms and services accepting different identities. In addition, a centralized identity system would allow for better security and privacy controls, as well as the ability to track identity theft and fraud.

However, this approach also has several disadvantages. First, it would be very difficult to create a global identity system that is accepted by everyone. Also, a centralized system would be vulnerable to attack and could be used to track people’s movements and activities. Third, it would be difficult to protect the privacy of users in a centralized system.

Option 2: Multiple identities

Another solution to the problem of identity in the metaverse is to allow each person to have multiple identities. This would mean that each person could have one or more identities that they use for different purposes. 

One of the main advantages of this approach is that it would allow people to maintain their privacy and security. Each person could choose which identity to use for each situation, and they would not have to worry about their entire identity being exposed. In addition, this approach would be more resilient to attack, as it would be much harder to take down multiple identities than a single one.

The limitations of such an approach would be that it could be difficult to keep track of all the different identities, and there would be no guarantee that different platforms and services would accept all of them. In addition, multiple identities could lead to confusion and could make it more difficult for people to build trust with others.

Option 3: A decentralized identity system

A third solution to the problem of identity in the metaverse is to create a decentralized identity system. This would be an identity system that is not controlled by any one centralized authority but rather is distributed among many different nodes. 

This might seem like the ideal approach, since decentralization is a common theme in the metaverse. However, there are still some challenges that need to be overcome. For instance, it would need to be ensured that all the different nodes in the system are properly synchronized and that the system as a whole is secure. In addition, it might be difficult to get people to adopt such a system if they are used to the more traditional centralized approach.

One solution would be to get the nodes in the system to be run by different organizations. This would help to decentralize the system and make it more secure. Another advantage of this approach is that it would allow different organizations to offer their own identity services, which could be more tailored to their needs.

Another would be to incorporate an edge computing solution into the system. This would allow for more decentralized processing of data and could help to improve performance. It would also make the system more resilient to attack since there would be no centralized point of failure.

The best solution for the future of identity in the metaverse is likely to be a combination of these approaches. A centralized system might be necessary to provide a basic level of identity services, but it should be supplemented by a decentralized system that is more secure and resilient. Ultimately, the goal should be to create an identity system that is both easy to use and secure.

The ideal identity standards of the metaverse

Now that we have explored the various options for identity in the metaverse, we can start to identify the ideal standards that should be met by any future global identity system. 

It is no easy task to create a global identity system that meets all of the criteria, but it is important to strive for an ideal solution. After all, the metaverse is still in its early stages, and the decisions made now will have a lasting impact on its future. 

Current iterations of the metaverse have used very traditional approaches to identity, but it is time to start thinking outside the box. The ideal solution will be one that is secure, private, decentralized, and easy to use. It will be a solution that allows people to maintain their privacy while still being able to interact with others in the metaverse. 

Most importantly, it will be a solution that can be accepted and used by everyone. Only then can we hope to create a truly global identity system for the metaverse.

The bottom line on identity in the metaverse

The question of identity in the metaverse is a complex one, but it is an important issue that needs to be addressed. 

The challenges associated with creating an implementation that is secure, private and decentralized are significant, but they are not insurmountable. For one, it will be important to get buy-in from organizations that have a vested interest in the metaverse. These organizations can help to promote and support the adoption of identity standards. 

It is also important to keep in mind that the metaverse is still evolving, and the solution that is ideal today might not be ideal tomorrow. As such, it will be critical to have a flexible identity system that can adapt as the needs of the metaverse change. 

Ultimately, the goal should be to create an identity system that is both easy to use and secure. Only then can we hope to create a truly global identity system for the metaverse.

Daniel Saito is CEO and cofounder of StrongNode

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How to Eliminate Scheduling Inefficiencies in Your Business

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What do salons, consultancies, and home service providers all have in common? This question may seem like the prime setup for a joke, but there’s no punchline to look forward…

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Why You Should Start a Business Only While You Have a Job

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Opinions expressed by Entrepreneur contributors are their own.

Many people that I meet tell me that they dream of starting their own . I always ask them, “Then why don’t you?” They typically respond by saying that they have so many financial and personal responsibilities, that they can’t just quit their job to start a company, etc. Then I tell them my story …



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Related: How to Use Your Current Job to Start Your Next Business

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