AI has been a host of surprises! And, it has also been a flagbearer of ‘Smart Tech’ ubiquitously! No denial there! But, recently with On device AI, it is onto rolling out what we can fairly term as a ‘Smarter facelift’ for your everyday use. Where you get on the device with a facelift but at the same time you get off too many (ex) main characters like the internet, cloud and ofc human interaction. And, as smart as it gets, tech giants like Apple Inc. and Samsung are already putting their chips on it.
Also, did you ever think your device can roll out personalized outputs without waiting or always relying on human interaction or the internet connection or even cloud computing for that matter. No, we’re not simply making wild expectations here. Because, with On device AI we can probably get our hands on that in no time. It’s more like the users get a personal AI running on their smartphones without any external contemporaries while producing tailored results in real time. Again, not just that! Gadgets can now deeply learn your choices and map thoroughly your preferences via machine learning.
But, amongst it all the best part is it is trained locally. That too, on your own device and without the back and forth of reliance on cloud infrastructure and major latency issues. Here it is safe to say that you can expect something more rapid, secured and particularly personalized with On-device AI. Although, having said that, scratching off the surface and skimming through the buzz around smarter devices is imperative.
What is On Device AI?
Firstly, On Device AIs are also known as Edge AI. Considering its swift growth every year and a humongous shit on edge devices, the technology AI is yet again here with an even smoother roll-out and a productivity leap. It's not like as a technology AI has not elevated the whole landscape for its user base. But this is the first time around where it simplifies tasks for them in a peculiar approach.
But, with On Device AI. We can probably sense that this time around the productivity, simplicity and rapid responses extensions are quite beyond the lines of usual fines. However, one has to take the bitter with the sweet. And, while On device AI is a tapestry of trailblazing rollouts. It has a few turn-offs, such as cost, could be associated with hyper-stellar dynamism. However, as technology progresses towards efficiently automating functionality, it may also be reduced to a manageable extent.
Two Core Principles
It is basically a mini cluster of specific/distinct chipset and a smart set of processors hosting multiple algorithms. Subsequently, producing personally tailored outputs via being locally trained right there on your device. Without rerouting to separate AI driven solutions fetching outcomes.
In toto, On device AI is a seamless AI chipset integrated on your gadgets, this could be your smartphone, PC, tablet or any smart device for that matter. Now about its technicality It is more like a chipset trained using LLM placed integrated to your personal device. It fetches datasets, chunking it into personalized responses instantly at the same time marching between the apps on your device.
To understand it better; Take it as a sifter and Mixer:
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Your data is pooled-in on the device
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The personal data is then sifted and relevant information is captured.
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AI Algorithms then pitch in via the AI powered Chipset to further assess and analyze the data.
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The next phase is to predict your every pattern regarding your every activity as a user.
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Recommends and with your permission actions the proactive approach for you. Hence It can also be termed as Actionable AI model
For Example:
Shopping online is no less than running a sprint. Rummaging through brands, products and apps to get that specific ‘Black Tote bag’ or those ‘Chelsea boots’. Running frequent checks all through the digital display time and again. Cut to you having On-device AI integrated. It brings algorithms like machine learning and deep learning to use. From mapping your preferences, to skimming down the products falling on the lines of your choices to recommending products, skimming offers. And, and, and throwing it into the cart, covering all the order placing shenanigans, to detailed payment processes. It does it all, to roll out a holistic and circumspect user experience!
Adding to that: For this entire proactive shopping experience. You don't necessarily have to be clubbed to a thick internet connection, and you do not need to worry about your personal credentials traversing through multiple cloud platforms. Do you know why? Because edge AI trains locally. Which means, it fetches data sets from your device, runs it through AI algorithms again on your device itself. So, you can finally bid adieu to those external cloud reliance, the hassle of high latency. Besides all of that, you get a personal AI rolling out secured, seamless and instant responses tailored to your choice.
Thus, it would not be an overstatement or an exaggeration to say that devices are getting smarter. And, application developers and businesses can expect this affair of smarter devices adoption to take up a notch. Especially as early adopters expect it to be a boon for users and app developers. Well, we understand, this brings you to ponder on how On device AIs impact businesses across the globe? And, bugging questions like what about the toll that it would initially take on the battery life for the device? There’s a mini curveball there.
How Could On Device AI Impact Businesses & Early Adopters?
Businesses are hardwired to cater users as promptly as possible. Like if the businesses are already pacing at rolling out services in microseconds; Panning out results and even tailored results in nanoseconds is the next thing on their radar. Mobile app developers are to be the first to dive in the trajectory of smart devices getting an even smarter facelift. I mean being close to their targeted users they are surely expected to take center stage.
However, to know how On device AI or edge AI would impact the businesses. One needs to know what to expect from On-device AI?
On-device AIs have the following potential but then what are the downsides?
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Accelerates the device capabilities.
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Fixates a LLM on a personal device.
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AI Aspects integrated on the Device.
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AI Algorithms can seamlessly intertwine with the applications.
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Productivity booster.
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Faster personalized outputs.
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Stapled Security.
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No Human interaction and third party data processing-storing reliance.
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Low Latency.
Considering this as a bigger picture, you as a business owner or a mobile app developer also need to keep an eye on the downsides. On-device AI may not be the best when it comes to controlling the cost margins and budgets. Plus, we do not know how it will help the devices to not run out of juice, all the time. The battery life and complex task simplifier, with aspects like NLP etc. can be a problem.
While masses across the globe bank on AI assistants like Siri and Google unanimously, there is a certainty for On-device AI integration to rule and reign supreme in the times to come. But, is it just for the tech giants? Well, we believe it can be a boon for businesses like eCommerce, Manufacturers and even Fintech for that matter. Because we do live in an app ecosystem and more skimmed, seamless and far more secured device integration. These AI-powered chipsets can be resource intensive for the businesses. They are like a rabbit hole ready to explore for the mobile app developers but require a drive of huge research backed growth.
Though On-Device AI for mobile apps is still at a nascent stage yet tech giants like Samsung are already reigning in with a fresh push in this genre. Like its R1, a personal AI smartphone with some flashy features and outlook too. Then, what do you say? Is Edge AI a smart brain for smart devices?
To Wrap up
AI Innovations are not the ultimate answer to a question but it is an equation formulated full of unknown variables". One might even ask what are the variables then. On that we say our effort to recognize the potential of the technology and investing in a bigger step towards the future.
Since the introduction of AI people have been rattled and industry-leading giants are looking for that power-up to make it to the other side of the spectrum. Then maybe after proper implementation of an end-to-end automated ecosystem, on-device AI for mobile apps can be the best thing that ever happened. However, it's still in the early stage and we need to learn, explore and discover every possibility before introducing those AI-enabled mobile app-based solutions in the market. Nevertheless, it is a sturdy roll out with potential. However, picking a side here and claiming a say for the future is a bit too early considering it is a fresh roll out in the market space, still.
