PATENT DROP: Intel’s greener AI
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PATENT DROP: Intel’s greener AI
Plus: Apple’s got hands; Snap brings the feels
Happy Monday and welcome to Patent Drop!
Today, a filing from Intel for a power-saving way to train AI; a wide-reaching Apple patent for a whole bunch of ways it can use your hand gestures; and tech from Snap to better understand your emotions in text.
Let's check it out.
Intel saves some power
Training AI can run up a company’s power bill. Intel may have found a way to save a few bucks.
The company is seeking to patent a system for conducting “power-efficient machine learning” for images and video. This system has to do specifically with decoding images and video in machine learning training — i.e., when an AI model translates the content of an image or video into a sentence, such as a caption.
Intel’s system works by weeding out “content that would otherwise result in unnecessary decoding.” As a result, Intel noted, “only a few images are decompressed and analyzed” by the system, thereby saving power.
To break it down: Intel’s system weeds out “irrelevant” images or videos from training datasets while they are compressed (meaning, while their file size is reduced) to save the time and effort it takes to decompress those images. After those images are picked out, the system tests whether the machine learning model can still accurately do its job. If the accuracy is impacted by the training data that was withheld, the system’s machine learning “software agent” takes note and tries again.
By only feeding the machine learning model the relevant data, the system saves tons of time and energy, as image decoding is “sequential and tend(s) to be the slowest operations in the machine learning pipeline,” Intel noted. Plus, the time it takes for conventional systems to decode content that isn’t relevant “may translate into a significant amount of wasted power usage in data centers.”
According to a Bloomberg report from March, training just one model can consume more energy than 100 US homes in a year, and Google researchers found that AI makes up 10% to 15% of the company’s energy usage each year (using roughly the same amount of annual electricity use as the city of Atlanta). Because the industry is so nascent, there’s little transparency into exactly how AI is impacting carbon emissions.
Since March, the industry has grown rapidly, and it’s showing no sign of stopping. Among big tech companies, Google, Microsoft, Meta and others are practically racing to outdo each other in the sector with AI integrations for both consumers and enterprises. AI startups are receiving outsized attention from a wave of VC investors looking to jump on the bandwagon. Finding ways to create AI models without burning through power could be a critical piece of the puzzle as the exponential growth gets, well … more exponential.
Intel has a lot of catching up to do if it wants to compete with the major players in AI. The company has sought to patent plenty of AI-related inventions, and has a good handful of AI offerings already on the market. But when it comes to AI chips, the company controls a tiny fraction of the market share – less than 1% compared to AMD’s 20% and Nvidia’s roughly 80%.
Every patent the company can secure, however, could help it better compete. Finding a way to train AI without burning up the earth could give Intel a leg up.
Apple takes you by the hand
Apple may be paying close attention to the way you move your hands.
The company filed a patent application for a system to interact with virtual objects “using hand gestures.” Essentially, Apple’s patent details a system that can pick up on hand gestures and controls in a “more efficient and intuitive” manner. It does so through sensors — many of which are already part of available Apple devices — ranging from motion-capture sensors to temperature sensors to “peripheral device” sensors (i.e., home appliance or smart speakers).
The 90-page filing details several ways that a user could control various Apple products with hand gestures, including with watches, TVs, laptops, tablets and head-mounted displays. The filing even mentions that these controls could be implemented in windshields and windows with “integrated display capability.”
One example that Apple’s filing details are different ways in which a smartwatch can integrate with several types of displays, such as guiding controls on a smart TV display, or controlling virtual objects on a tablet. The definition of a “virtual object” is also quite wide, noting that elements such as “digital images, video, text, icons, and control elements such as buttons and other graphics” fall under this umbrella.
Apple noted that conventional systems are often cumbersome and require complex inputs to achieve certain outcomes in augmented reality environments. These systems are often tedious and error-prone, Apple said, creating “a significant cognitive burden on a user, and detract(ing) from the experience.”
“In addition, these methods take longer than necessary, thereby wasting energy of the computer system,” Apple said. “This latter consideration is particularly important in battery-operated devices.”
As Apple noted in the filing, there are several use cases for advanced controls such as these, even hinting at integrations for the rumored Apple Car. But given the patent’s focus on the Apple Watch’s potential, the device could be a key component to the company’s wider connectivity plans.
Apple already offers some gesture recognition through the Apple Watch as part of an accessibility setting called Quick Actions, which allows users to respond to alerts with movements such as gripping a fist or making a pinching motion with your fingers. This patent may expand on already-existing capabilities.
That said, likely the biggest piece of Apple news so far this year was the debut of its Vision Pro headset. The long-awaited device already boasts eye-tracking as a means of controlling your AR environment. Enabling hand tracking through a connection with the Apple Watch could be an added bonus.
Apple already has a deeply connected ecosystem of devices, but the ease of use and connectivity of this patent could lock in customers to the Apple brand even more than its devices already do. If all of a user’s devices are Apple, and all of those devices are connected with one another and can easily interact with one another, a user has less incentive to purchase, say, an Android phone, an Intel PC or a Meta headset.
“In the near term, I think Apple wants users to use all their devices together,” said Jake Maymar, VP of Innovation at The Glimpse Group. “The competitive advantage that Apple has over a lot of other companies is that all the devices will work seamlessly together.”
But this patent, added to Apple’s current line of devices and patents, could point to a larger goal from Apple, said Maymar: a fully connected ecosystem of devices controlled through spatial computing, or a way of interacting with computing in the space around you that was introduced in the Vision Pro. And because Apple has a large, core user base of dedicated customers, he noted, the company may have an easier time getting users to adopt this technology.
Snap gets emotional
Snap wants to give text-to-speech a little more flare.
The social media company is seeking to patent a system for “emotion-based text to speech.” Snap’s system uses AI to derive emotions from text, and uses that input to help its text-to-speech systems give more realistic output.
First, the system applies machine learning to the string of text to “compute a level of an emotion” associated with the words in that text string. This calculation helps the text-to-speech system decide how to mix and combine different emotions to get the appropriate output. For example, if the machine learning model decides some words in the sentence are neutral, and some are happy, it’ll meet somewhere in the middle.
While in some examples an AI model determines these emotions, in others, Snap notes that users are allowed to give input via an “emotion classification and emotion intensity module.”
Finally, all of this data is then fed to an “acoustic generator” and a neural network-based vocoder, which normalizes the text and generates the audio. That audio is then played back during the display of an image, video or augmented reality experience.
While text-to-speech systems are far from a new concept, conveying emotion through these systems and creating human-like speech from scratch can be difficult, Snap noted. “These systems can generate audio that speaks text in a neutral emotion which results in a cold, impassive and discouraging experience.”
Emotional understanding is an incredibly difficult barrier for AI to surpass, said Eldad Postan-Koren, co-founder and CEO of Winn.AI. This can be seen in speech recognition contexts, as companies like Amazon research how their smart speakers can better understand user requests by listening for emotion. Snap is essentially trying to solve the reverse, deriving emotion from text by breaking it down word by word, and translating it into a voiceover.
But several roadblocks stand in the way. For one, every person emotes differently, and many people struggle to convey emotion over text generally. (What did that extra exclamation point in your friend’s text really mean?)
Another obstacle is the cultural differences that exist in communication, Postan-Koren said. For example, he said, as someone that lives in Israel, he lives with different norms of communication than someone from the US. An AI that can nail all of the minute differences in global communication is practically “science fiction,” he said.
“In order to 100 percent understand you, I need to know,” said Postan-Koren. “I’d need to know the way you communicate, your personal background, your cultural background.”
This barrier may be why Snap’s patent specifies that it could get some direction from its users: In some implementations, the system allows users to pick which emotions they would like to convey in their text-to-speech, rather than making a socially inept machine learning model do it.
One last note: While this patent focuses on text-to-speech, understanding sentiment, whether it be from text or audio, can be a lucrative metric in advertising. Given that Snap’s Q2 revenues sunk even lower this past quarter, any tech that helps it better understand users could be to the company’s benefit.
Extra Drops
A few more before you scroll off.
Disney wants to make it easier to track fight scenes. The company wants to patent a system for “synergistic object tracking and pattern recognition” that uses AI to track when a body is “moving dynamically or in an atypical manner,” such as while dancing or fighting.
Google’s getting into optometry. The company wants to patent a system for determining placement and “display gazability” of a pair of glasses tried on virtually.
Walmart wants to find its bargain-hunters. The retailer is seeking to patent a system for identifying “value conscious users” by tracking user activity to find out who’s taking a closer look at better deals.
What else is new?
PayPal named Intuit’s Alex Chriss as its new CEO. Chriss, who ran Intuit’s unit focusing on small businesses, will take on the role starting Sept. 27.
Ford hired Peter Stern, a former Apple executive, to lead its new Ford Integrated Services unit. The unit will focus on creating software for customer experiences for its vehicles.
AI startup Anthropic raised $100 million in funding from South Korean mobile carrier SK Telecom, just three months after raising $450 million in its Series C round.
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