Qualcomm has aggressively developed and integrated generative AI capabilities across its extensive semiconductor line for the past few years. For those few people who are completely left out of the information grid, AI uses intelligent algorithms to produce new and original content, such as photos, illustrations, movies and music, based on pre-existing data. .
Qualcomm’s Generative AI strategy leverages this technology to improve various aspects of its products and services. The company says its technologies can execute a wide range of exceptional use cases, but doing so locally on a smartphone adds far more value, especially from a cost-per-query and scalability perspective .
With that as a backdrop, let’s discuss Qualcomm’s ability to create hybrid AI functions that extend from device to cloud.
Talks about this capability were started by Qualcomm earlier this year at Mobile World Congress. This approach requires specific, specialized hardware modifications and substantial software adjustments, resulting in a deep-learning text-to-image model known as Stable Diffusion in 2022.
The main application of static diffusion is to generate detailed images based on text description. Nevertheless, stationary diffusion can also be used for other tasks such as image repair (inpainting) and for modifying AI-generated images outside the boundaries of the original image (outpainting).
It is important to note that parameters are the fundamental foundation of machine learning algorithms that enable functional Gen-AI applications. They form part of a model trained using past data. In general, the relationship between the number of parameters and the sophistication holds surprisingly well in the domain of languages. The estimated amount needed in the past for Zen-AI-style apps was in the 10 billion parameter region.
Qualcomm’s AI silicon brings artificial intelligence capabilities to edge devices, including mobile phones, tablets and PCs. (Image credit: Qualcomm)
Steady Diffusion for On-Device AI
According to Qualcomm, the implementation of Stable Diffusion requires only 1 billion parameters which squeezes into a device the size of a smartphone. This static diffusion feature enables users to enter a text query and create a picture locally without using the Internet capability of a smartphone.
Since Qualcomm’s display was operating in Airplane mode, all the data needed to create that image from the text query was stored on the device. Steady Diffusion is the go-to model for Qualcomm because of its sheer size and training from huge amounts of data – it can really understand concepts that are incredibly vast in scope and can be applied to a particular or small set of topics are not limited.
Currently, Qualcomm claims to be the only firm to enable this model to work on Android-based devices. Parametric models are getting smaller and smaller, enabling compelling Gen-AI apps to operate on just a single device. If you continue with this idea, comparable generative AI use cases can be demonstrated on all types of mobile devices.
From a platform perspective, scalability is the name of the game for Qualcomm, as few other businesses have a comparable legacy in devices in the end-user device ecosystem. Qualcomm’s “installed” Snapdragon base is now more than 2 billion devices, many without internet connectivity.
Gen AI can now run on mobile devices without internet connectivity. (Image credit: Qualcomm)
Benefits of Qualcomm’s Generative AI Approach
Qualcomm has distinct advantages thanks to its history in the smartphone industry, even though Nvidia often dominates the news in the AI sector.
Qualcomm can use its generative AI to create more immersive and realistic content to improve the user experience. For example, augmented reality (AR) applications can create high-quality photos and videos, enhance the user experience and make it more interactive.
Additionally, Qualcomm’s capabilities provide businesses with essential advantages for product testing and development. Qualcomm can simulate and build realistic models for testing and development using generative AI, which can speed up the design process, save costs, and increase the effectiveness of product development.
In addition, Qualcomm’s OEMs can benefit from the untapped potential of personalization in the realm of AI, while Qualcomm solutions can provide consumers with tailored experiences that leverage generative AI.
It’s easy to see how Qualcomm’s solutions could contribute by creating specialized suggestions, unique user interfaces, or customizable answers based on individual preferences and behavior patterns.
Qualcomm should tell us more
As most of my readers know, I have been raising awareness of the ethical issues surrounding using general artificial intelligence. A number of ethical issues are raised by generative AI, particularly in light of deepfakes and the potential exploitation of AI-generated content. Qualcomm must ensure that users of its generative AI technology act ethically and within the limits of the law.
There are reasons to worry.
When I recently asked a CEO of a text-to-image Gen-AI program whether company terms and conditions mandated that created content include permanent watermarks or metatag fingerprints, he shrugged and answered in the negative. Gave.
At a recent technology conference, a prominent CEO touted the possibility of General-AI-style applications handling performance assessments of “laborious” employees. The number of lawsuits that followed is unimaginable.
Still, on a recent analyst call with Qualcomm, the company seemed to understand that it needs to take on an ethical leadership role in this area, suggesting that it will be discussing the topic significantly more in subsequent conferences. Will reveal information.
The company acknowledges that it wants consumers to maximize the Gen-AI capabilities on its devices. Yet, it also asserts how important it is to differentiate between original content and content modified by General AI.
It’s not hard to imagine that facial authentication, for example, could play an important role in mitigating the issue on this front. However, there are biometric hardware features that can also be useful.
a brave new world. But will we be safe?
It’s undeniable that Qualcomm’s emphasis on AI and continued work to integrate this capability into the company’s extensive silicon portfolio has the potential to completely transform the tech landscape as we know it. The productivity and time-saving benefits are real, significant, and practically inconceivable.
The potential is enormous because Qualcomm can now robustly run these types of apps on smartphones and other mobile devices, including PCs, without an internet connection. The potential for information extortion and privacy invasion is also clearly evident.
Qualcomm must protect user data and comply with strict privacy laws to mitigate these concerns, and ensure that the data used in developing or deploying generative AI models prevent personal identification. Any personally identifiable information (PII) is appropriately anonymized.
In addition, before collecting or using user data for generative AI purposes, Qualcomm must obtain the user’s explicit consent. Open communication about data use, sharing and collection processes is essential to maintaining users’ trust.
Safety and Ethical Challenges
Qualcomm must implement robust security measures to protect user data from unwanted access, breaches and potential misuse, especially in the context of generative AI. Access restrictions, encryption, and regular security audits are all part of this. Qualcomm can increase user trust and ensure that its Zen-AI solutions respect user privacy by including a thorough privacy plan.
I also advocate that Qualcomm mandates its OEM partners, who incorporate next-generation artificial intelligence solutions into their consumer goods, to disclose to consumers when AI creates any content from such devices. Is.
There would be a tendency to put the burden for this disclosure entirely on the equipment manufacturers, who would then expect end users to bear that obligation. Still, I’d like to see Qualcomm take a public leadership position on this topic.
Sadly, over-reliance on generative AI technology may lead to an undervaluation of human creativity and intuition.
I am horrified by the prospect of images and videos created by generative AI likely to be used by both sides of the aisle in the upcoming presidential election because they will make it nearly impossible to tell fact from fiction.
Qualcomm must strike a balance between automation and human engagement to ensure the creation of novel and valuable solutions. This aspect of General AI is an opportunity for Qualcomm.