Smartphone and mobile chip manufacturers are participating in the wave of AI generation to bring this technology to phones in the near future.

AI generation has exploded over the past year, with a range of applications being released to generate text, images, music, and even versatile assistants. Smartphone and semiconductor companies are also building the latest hardware to not miss out on the wave. Leading the way is Google’s Pixel 8, while Qualcomm’s Snapdragon 8 Gen 3 processor is also set to be launched in the coming days.

The latest signs indicate that phone manufacturers are welcoming AI generation from Google. The Pixel 8 series is the first set of smartphones capable of operating and processing Google’s Foundation Models for AI generation directly on the device without the need for an internet connection. The company stated that the models on the Pixel 8 reduce many dependencies on cloud services, providing increased security and reliability as data is not readily available.

This has become a reality thanks to the Tensor G3 chip, with the Tensor (TPU) processor significantly improving over last year. The company usually keeps the operation of the AI chip secret but has revealed some information, such as the Pixel 8 having double the number of on-device machine learning models compared to the Pixel 6. The AI generation on the Pixel 8 also has the ability to compute 150 times faster than the largest model of the Pixel 7.

Google is not the only phone manufacturer applying AI generation at the hardware level. Earlier this month, Samsung announced the development of the Exynos 2400 chipset with AI computing performance increased by 14.7 times compared to the 2200 series. They are also developing AI tools for their new phone line using the 2400 chip, allowing users to run text-to-image applications directly on the device without an internet connection.

Qualcomm’s Snapdragon chip is the heart of many leading Android smartphones globally, which raises expectations for the AI generation capabilities on the Snapdragon 8 Gen 3 model.

Earlier this year, Qualcomm demonstrated a text-to-image application called Stable Diffusion running on a device using Snapdragon 8 Gen 2. This indicates that image generation support could be a new feature on the Gen 3 chipset, especially since Samsung’s Exynos 2400 also has a similar capability.

Qualcomm Senior Director Karl Whealton stated that upcoming devices can “do almost anything you want” if their hardware is powerful, efficient, and flexible enough. He mentioned that people often consider specific AI generation-related features and question whether the existing hardware can handle them, emphasizing that Qualcomm’s available chipsets are powerful and flexible enough to meet user needs.

Some smartphones with 24 GB of RAM have also been launched this year, signaling their potential for utilizing AI generation models. “I won’t name device manufacturers, but large RAM capacity brings many benefits, including performance improvement. The understanding capability of AI models is often related to the size of the training model,” Whealton said.

AI models are typically loaded and continuously reside in RAM, as regular flash memory would significantly increase application loading times.

“People want to achieve a rate of 10-40 tokens per second. That ensures good results, providing almost human-like conversations. This speed can only be achieved when the model is in RAM, which is why RAM capacity is crucial,” he added.

However, this does not mean that smartphones with low RAM will be left behind.

“On-device AI generation will not set a minimum RAM requirement, but RAM capacity will be proportional to enhanced functionality. Phones with low RAM will not be left out of the game, but the results from AI generation will be significantly better with devices that have larger RAM capacity,” commented Director Whealton.

Qualcomm’s Communications Director, Sascha Segan, proposed a hybrid approach for smartphones that cannot accommodate large AI models on the device. They can host smaller models and allow processing on the device, then compare and validate the results with the larger cloud-based model. Many AI models are also being scaled down or quantized to run on mid-range and older phones.

According to experts, AI generation models will play an increasingly important role in upcoming mobile devices. Currently, most phones rely on the cloud, but on-device processing will be the key to expanding security and operational features. This requires more powerful chips, more memory, and smarter AI compression technology.

Medical researchers in Canada have trained artificial intelligence (AI) to accurately diagnose type 2 diabetes in just 6 to 10 seconds, using the patient’s voice.

According to the Daily Mail, a research team at Klick Labs in the United States has achieved this breakthrough after their AI machine learning model identified 14 distinct audio characteristics between individuals without diabetes and those with type 2 diabetes.

The AI focused on a set of voice features, including subtle changes in pitch and intensity that are imperceptible to the human ear. This data was then combined with basic health information, including age, gender, height, and weight of the study participants.

The researchers found that gender played a determinant role: the AI could diagnose the disease with an accuracy rate of 89% for women, slightly lower at 86% for men.

This AI model holds the promise of significantly reducing the cost of medical check-ups. The research team stated that the Klick Labs model would be more accurate when additional data such as age and body mass index (BMI) of the patients are incorporated.

Mr. Yan Fossat, Deputy Director of Klick Labs and the lead researcher of this model, is confident that their voice technology product has significant potential in identifying type 2 diabetes and other health conditions.

Professor Fossat also teaches at the Ontario Tech University, specializing in mathematical modeling and computational science for digital health.

He hopes that Klick’s non-invasive and accessible AI diagnostic method can create opportunities for disease diagnosis through a simple mobile application. This would help identify and support millions of individuals with undiagnosed type 2 diabetes who may not have access to screening clinics.

He also expressed his hope to expand this new research to other healthcare areas such as prediabetes, women’s health, and hypertension.

Mo Gawdat, former Chief Business Officer of Google X, declares that the latest advancements in artificial intelligence could soon make sex dolls “lifelike,” and dating websites will be flooded with AI-generated profile pictures.

The former CEO of Google’s Research and Development department shared with the Impact Theory podcast channel that the convergence of AI, virtual reality, and augmented reality technologies could potentially reshape the very fabric of society and bring about a significant process of “reimagining love and relationships.”

When asked by host Tom Bilyeu about the short-term disruptions AI may cause, particularly in relation to sex, Gawdat pointed out that substitute sexual activities already exist, and all one needs is a virtual reality headset to witness how realistic simulated sexual experiences have become.

Gawdat stated, “Just think about all the fantasies that we can’t decode right now,” emphasizing that “ultimately, [the sensation of] sex happens in the brain, and its physical aspect is not difficult to simulate.”

The former Google executive further explained, “If we can convince you that this sex robot is lifelike or have a sexual experience in virtual reality or augmented reality headsets, then you would understand. Add a few more years and think about Neuralink (brain connectivity) and other ways to directly connect with your nervous system, why would you need another person?”

The former CBO argues that the pleasure of friendship and sex is “all the signals in your brain” and believes that such activities can be simulated, just as scientists can currently “very easily” simulate muscle movement and replicate other brain signals.

Gawdat continues to dismiss the “big debate” about the consciousness of AI or how people should interact with it. “What’s the problem if Morgan Freeman is talking to you on the screen, whether it’s really Morgan Freeman or an AI-generated avatar if you believe it’s Morgan Freeman?”

He also highlights the significant business incentives in further developing AI technology, especially in the dating industry, where applications like Replica – an AI chatbot that learns to mimic users’ writing styles to develop relationships with them – have amassed around 2 million users.

“Because it generates money, what would prevent the next dating app from providing you with an avatar for dating?” Gawdat raises the question. “Many people will try it.” However, he admits that he himself doesn’t know whether such “strange” advancements are better or worse.

According to CNET, a talking robot head equipped with the AI platform Harmony, sensors, and servo motors capable of moving its neck, jaw, mouth, and eyes, is priced at $10,000 and can be integrated into existing dolls as an upgrade.

Guile Lindroth, Director of Content and Artificial Intelligence at Realbotix, an AI robot company, stated, “We have plans for 15 AI layers, with each layer adding advancements on top of the previous one. We are currently at the fourth level.”

With a focus on developing applications and intelligent AI features for RealDolls products, Realbotix has long promised to bring the Harmony app to iOS users. However, doing so would require compliance with Apple’s App Store evaluation guidelines, which strictly prohibit “pornographic or explicit sexual materials.”