Metaverse for Teaching

Meta Immersive Learning project is creating 10 “metaversities,"  digital campuses affiliated with real universities in the United States. In the last academic year, nine classes were offered to about 400 students in the metaverse. They ranged from journalism to biology, English to history. Next falll, the metaverse course offerings will increase to 15.

For Most of Us, AI is a Feature of a Product

For suppliers of artificial intelligence infrastructure, AI is a direct revenue source. For most of the rest of us, AI is a feature of some other product we buy or use. Amazon, for example, uses AI to drive its $222 billion e-commerce business plus its $103 billion third-party merchant revenues.

AI also underpins Amazon Web Services, subscriptions and advertising. 

source: Mozilla 

Digital Twins are Representations of the Real World, But Beyond That We do Not Yet Agree on Value

Any new technology brings new definitions. But to replace an existing technology, it also has to bring business or consumer value. Consider digital twins. How does a digital twin add value over existing monitoring and sensing systems, for example? Throw in new internet of things sensors and the definitions and use cases are even more complicated. 

Most definitions of digital twins involve the virtual representation of some real-world process. But that might be the only thing observers agree upon. 

If we assume the value of IoT is the ability to know what is happening, in real time, with processes and machines, we can understand the difference between real-time monitoring and non-real-time simulations, for example. The former tells you what is happening; the latter what could happen. 

Most proponents of digital twins emphasize its value over a “simulation.”

“A simulation replicates what could happen to a product, but a digital twin replicates what is happening to an actual specific product in the real world,” says TWI Global. “A digital twin creates a virtual environment able to study several simulations, backed up with real-time data and a two-way flow of information between the twin and the sensors that collect this data.”

source: TWI Global 

But we might also say a digital twin is a three-dimensional representation of “what is happening.” In that sense it is closer to the idea of a monitoring or sensing system able to fully represent many real-world conditions. 

Some might say that “simulations refer to digital models that imitate the operations or processes within a system.” Others might emphasize the more-static nature of a simulation, versus dynamic nature of a twin. 

But even those definitions are fuzzier than one might think. Digital twins can also be used for simulations, albeit with more realism and dynamism, even if most observers say the primary value is operations visibility. For some enterprises, the issue might be the amount of incremental value from a digital twin, compared to a robust IoT monitoring system. 

source: Softserve 

Others might focus on the difference between “intent” and “status.” 

“Simulations are created by the imagination of the designer, who will use them to analyze the cause and effect of different scenarios, mostly offline,” says Ericsson, also noting that the variety of definitions is “overwhelming.”

For example, a digital twin can be defined as software representation of assets and processes, which is enhanced with capabilities that are not present in the real-world entity. A digital twin “is a virtual copy of something, and processes associated with it, that can be used to predict or interact with reality,” Ericsson also says. 

Again, note the complexity of the concept. A digital twin is a virtual copy of something. But its uses can range from monitoring to simulation to process control. 

Some might argue that, in most cases, a simulation is a snapshot of a one-time task, which is then used to support design and analysis studies. But a digital twin might also support real-time simulations, in addition to monitoring and process control.

Digital twins, on the other hand, are driven by timely synchronization of information between the real and virtual worlds, and therefore adapt with changes in either world. Simulations are predominantly theoretical, whereas digital twins are specific and actual, some might say. 

Similarly, digital twins share some similarities with metaverses: digital spaces where people can interact virtually. But metaverses are built intentionally, typically representing virtual realms.

Digital twins only have value as replicas of the real world. That is about the only definition we might all agree upon. The value and use cases will be matters of interpretation.

Intel Struggles with Movement into Adjacencies, Just Like Telcos

Intel is not immune from the general trend to turn products into services. Nor is Intel protected from initiatives that do not develop as fully as expected. Sometimes it works; often it does not. That is the risk firms take with innovation.  

And, as always, questions are raised about strategy: stick on the core business or diversify. Telcos face the same problem as Intel does, in one important respect: acquisitions in growth areas mean spending a growth multiple to acquire the assets. In other words, Intel and ISPs have to buy high-value assets using low-value currencies.  

So the typical problem for tier-one telcos is debt, which more than anything else causes telcos to reverse course quite often. 

Analysts and advisors often disagree sharply about what telcos ought to do about their “growth” initiatives. Some favor “sticking to core connectivity” while others emphasize “diversifying beyond connectivity.”  

Service providers have tried both approaches, sometimes alternating between them, as competitive opportunities and threats come and go. 

Some service providers are fortunate to operate in markets with high profit margins. In such markets the advice to “stick to connectivity” can make sense. Others have fewer chances to grow if they stick to connectivity. In those cases diversification makes sense. 

But almost every service provider explores some growth opportunities outside the core connectivity business. How to do so remains the challenge. Growth initiatives are risky, expensive and often do not move the revenue needle very much. 

And such initiatives almost always are fueled by debt. In almost all cases, such efforts are reversed when priorities shift back to core business investment and debt reduction. 

The other approach is to try to grow new capabilities organically. That can reduce the danger of debt, but at the risk of not being able to scale quickly. 

It’s a huge issue, for Intel or ISPs.