Oracle wants to keep a close eye on the cloud. 

The company filed a patent application for “health metrics associated with cloud services.” It pitches an observability service that tracks whether or not various services within a cloud environment are operating at their best capacity. 

“Cloud operators may monitor the operations and performance of the cloud environment, to gain insights into system health, detect operational issues, optimize resource allocation or utilization, and promptly respond to issues that may arise,” Oracle said in the filing. 

Each service available in a cloud environment is assigned what Oracle calls a “health metric.” This metric is influenced by different “alarms” linked to features within that specific service. For example, if one feature within an application is operating slowly, that’ll lower the health metric for the application as a whole.

If an alarm is triggered and a service’s health metric drops, Oracle’s system would consider how its health impacts “downstream” services that rely on it to function. If one service going down creates a domino effect, making others go haywire, that’ll impact its health metric even further.

All of this data is visualized on a user interface that allows system administrators to track outages in real time and trace the original source of a problem. 

Oracle has made a lot of cloud gains in the last several months. The company saw cloud earnings jump 21% in the most recent quarter. It also surpassed IBM in cloud market share, tying with Salesforce at around 3% in the second quarter, according to CRN. 

It’s not likely that the company will ever overtake the likes of AWS, Microsoft, or Google in this market, said Trevor Morgan, senior vice president of operations at OpenDrives. However, that’s not where the company’s strength lies, he said. 

Oracle’s sweet spot may be in providing a foundational service that’s adaptable to the data needs of its clients, said Morgan. This patent is evidence of that, said Morgan, and could help monitor the data-hungry AI services that are increasingly being built and deployed in cloud environments. 

AI has changed the cloud landscape drastically, increasing dependence on these services as computing needs exponentially increase. While other major cloud providers are busy building out AI tooling and foundational models, Oracle is providing a “water source, so to speak,” said Morgan. 

The company doesn’t have to be an AI trendsetter to benefit from the wave, he said. Rather than trying to be something it’s not, Morgan said, Oracle has positioned itself as a predictable business in an ever-changing market, offering “long-term stability for the shareholders.” 

“For Oracle to have to be the major information store means that wherever this goes, they’re a player in that — whether they’re leading the way in AI or they’re that data repository that the AI will then draw upon.”

AI comes with a lot of risks. IBM wants to track them down. 

The tech firm filed a patent application for “providing and comparing customized risk scores” for AI models. IBM’s tech assesses AI models for several different types of risk depending on how they’re put to use. 

“The consequences of a failure of an AI system can have substantial effects on individuals, organizations, or other entities that can range from inconvenient to extremely harmful,” IBM said in the filing. 

IBM’s patent aims to provide “domain specific” risk assessments, adapting the scores to their specific intended use, governing standards, or other regulations. For example, IBM noted, a model used in facial recognition for policing may have stricter requirements and lower risk tolerance than one used in a general security system. 

The context in which a model is used helps IBM’s tech determine which “dimensions” of risk it should focus on, such as fairness, explainability, or robustness, as well as the “metrics” by which to measure those dimensions, such as if a model’s risk factors impact different groups in different ways. 

All of this information is used to calculate customized risk scores for each model, which are then converted to “comparable,” or standardized, scores. This enables stakeholders to compare the risk of their AI models across different applications, allowing for better transparency and accountability. 

As AI development and deployment explode, so do the risks that these applications come with. The risks change depending on the context, and might entail data security, fairness and bias, or accuracy issues. And as IBM continues to focus on the enterprise AI market with data platforms and open source models built for business applications, paying attention to risk is crucial.

In enterprise contexts, models are often used for critical operations and applications in industries such as finance, healthcare, logistics, government, and beyond. Because of this, not understanding the risk that an AI model poses in its specific setting could present a huge liability. 

“The difference between enterprise and consumer is the liability rests on the enterprise,” said Arti Raman, founder and CEO of AI data security company Portal26. “In a business-to-business setting, both the [organization] that is providing the model as well as the one that’s consuming the model care about risk and liability.” 

And while the AI boom gave way to an initial flood of development, the return on investment for these products hasn’t quite hit the mark that the industry hoped for. That’s because “a large portion of experimentation is not going into production because of risk,” said Raman. 

“Now that you’re seeing that this flow of investment isn’t quite getting you all the returns you wanted — not because the tech doesn’t work, but because the risk isn’t accounted for — you’re going to see a focus on risk,” she added.

Meta wants to put a ring on it. 

The company filed a patent application for an “optical ring that enables thumb-to-index gestures.” Meta’s patent details a wearable used for controlling and interacting with mixed reality environments without having to make “large and apparent hand motions.” 

“This can be distracting and tiring for the wearer,” Meta said in the filing. “Moreover, existing XR input devices often require wearer-specific training data for underlying inference models to work effectively.” 

Meta’s ring is equipped with a miniature optical sensor to monitor nuanced, complex gestures made by the thumb and index finger. The camera captures “ultra low-resolution” images of a user’s fingers for minimal data processing (and therefore smaller form factor) while still allowing it to interpret gestures. 

Additionally, the ring would include electrodes to capture “bioimpedance measurements,” or changes in electrical currents throughout the hand, as well as a motion-tracking sensor to understand gestures in more detail. Taken together, the ring is able to capture what Meta calls “stateful” gestures, or layered inputs that give its system a better understanding of both motion and pressure. 

This could make things like menu selection or navigation more seamless in extended reality environments. It may also let Meta use “user-generalizable ML models,” foregoing the need to collect extra data from users. 

We’ve seen peripheral devices like this from Meta before. The company has filed several patents for smart watch tech, and its recently-debuted Project Orion AR glasses include a neural wristband for input tracking. 

While these devices are helpful for taking the burden of processing off of extended reality headsets, they add another layer of friction onto the experience that might turn off users, said DJ Smith, co-founder and chief creative officer at The Glimpse Group. 

“Any peripheral device at its core is a hindrance to adoption,” he said. “The overall experience may be better because the user input is smoother and quicker, but having to deal with clunky stuff is never good.” 

This is where Meta may want to take notes from Apple, said Smith. While the company’s device ecosystem is filled with peripherals, each comes with its own functionality that adds value. “If it’s not adding value, it’s going to be a chore,” said Smith.

And though Apple is fairly new to the extended reality market, the company may be pushing into Meta’s turf: The iPhone maker’s hardware division is planning to push into the smart glasses market, according to Bloomberg, starting with an internal study to gather feedback from employees for an initiative codenamed Atlas. 

Lots of things stand in the way of making glasses a viable form factor, Smith noted, both in terms of engineering and cost. But for Meta and Apple, “the long-range vision has always been a pair of glasses,” he said. Both the Vision Pro and Reality Labs, while incredibly costly endeavors, are likely a “test bed for AR glasses down the road.” 

Recouping those investments is going to be a matter of adoption, he said. “Getting the cost down, getting more people into it, creating more use cases — all of these things will happen over time.”