The latest developments in technology make it clear that we are on the precipice of a monumental shift in how artificial intelligence (AI) is employed in our lives and businesses.
First, let me address the misconception that AI is synonymous with algorithms and automation. This misconception exists because of marketing. Think about it: When was the last time you previewed a new SaaS or tech product that wasn’t “fueled by” AI? This term is becoming something like “all-natural” on food packaging: ever-present and practically meaningless.
Real AI, however, is foundational to supporting the future of how businesses and individuals function in the world, and a huge advance in AI frameworks is accelerating progress.
As a product manager in the deep learning space, I know that current commercial and business uses of AI don’t come close to representing its full or future potential. In fact, I contend that we’ve only scratched the surface.
Ambient computing
The next generation of AI products will extend the applications for ambient computing.
- Ambient = in your environment.
- Computing = computational processes.
We’ve all grown accustomed to asking Siri for directions or having Alexa manage our calendar notifications, and these systems can also be used to automate tasks or settings. That is probably the most accessible illustration of a form of ambient computing.
Ambient computing involves a device performing tasks without direct commands — hence the “ambient,” or the concept of it being “in the background.” In ambient computing, the gap between human intelligence and artificial intelligence narrows considerably. Some of the technologies used to achieve this include motion tracking, wearables, speech-recognition software and gesture recognition. All of this serves to create an experience in which humans wish and machines execute.
The Internet of Things (IoT) has unlocked continuous connectivity and data transference, meaning devices and systems can communicate with each other. With a network of connected devices, it’s easy to envision a future in which human experiences are effortlessly supported by machines at every turn.
But ambient computing is not nearly as useful without AI, which provides the patterning, helping software “learn” the norms and trends well enough to anticipate our routines and accomplish tasks that support our daily lives.
On an individual level, this is interesting and makes life easier. But as professionals and entrepreneurs, it’s important to see the broader market realities of how ambient computing and AI will support future innovation.
The truth is that ambient computing alone hasn’t been enough to catalyze major change. That’s because ambient computing devices lack a deeper understanding of the world, which brings us to the latest milestone: Multitask Unified Model (MUM).
Multitask Unified Model
In the summer of 2021, Google’s President of Search Pandu Nayak wrote a summary of the latest and greatest in complex task management, Multitask Unified Model (MUM). He explained that MUM uses the best-developed version of natural language processing in a T5 text-to-text framework, making it 1,000 times more powerful than Google’s previous search tech (BERT).
This is key because, with the advent of voice-based searches, people are asking questions that don’t have simple answers. What’s more, there is a demand for multimodal interpretation (understanding data across text, images, audio and video) and information sharing, and MUM is the first framework capable of tackling that.
MUM can handle information in different formats and isn’t limited to a single language. It is an immense leap for this technology to be able to facilitate complex ideas, handle multiturn logic and conditional exchanges, and then use AI to learn from and improve upon the user experience.
Ambient computing and MUM can change the game
The coordination of ambient computing and intelligence is sometimes referred to as ambient intelligence (AMI). For technology to qualify in this category, it must meet six criteria: It should be sensitive, responsive, adaptive, transparent, ubiquitous and intelligent. The goal is for technology to become sensitive and responsive to the presence of humans.
While the frameworks and mechanisms are inherent in ambient computing technology and data tools, all of the processes and information are ultimately made “personal” by AI.
AI is what makes technology feel human, and this is being developed in the market in a multitude of ways.
The ubiquity of machine assistance
In pretty much every iteration of ambient computing, the process involves embedding computational capacity into objects using microprocessors, sensors and similar tools. These objects can then communicate with people and perform tasks on their behalf without needing much (or any) input or direction.
Applications for this are cropping up everywhere.
Some have proposed that ambient computing is Amazon’s next big play. The behemoth’s ever-evolving suite of digital smart technology is pursuing real-world applications for ambient computing. Robots, drones, wearables, smart speakers and more are getting upgrades to detect custom sounds, visual changes and react to contingencies based on what the sensors pick up.
If the pizza guy shows up, the porch light turns on; if the dog barks, a recording of your voice can be played; if the video doorbell notices the door is open, it can clock that visual change and let you know.
In addition to developing MUM to make ambient computing useful, Google said it is working to integrate ambient computing into Volvo cars. It plans to implement deep integrations into vehicles already compatible with Android Auto. The plan is to provide a set of services that promote in-car experiences, including smart capabilities in the form of vehicle performance monitoring, remote feature use, automations, expanded digital car key capabilities and more.
A future of productivity supported by tech
We are in the early days of what it’s going to look like when we’re supported by ambient computing tools all the time. MUM will provide the information organization to verify, cross-check data and organize the experience, making all computations as real and relevant as possible.
Locks turning before we tell them to, keyboards that predict our next sentences, referential conversations with avatars in the metaverse, cursors that point toward our eyeline: All of this technology exists.
As each sector develops industry-specific tech, and IoT brings it all together, AI will continue to provide the foundational components for a future of tech-supported productivity.