The likelihood of BrainChip's Akida technology being integrated into mobile phones is high, with strong indications of imminent commercialization.

According to www.iAsk.Ai - Ask AI:

BrainChip's neuromorphic AI processors, particularly the Akida NSoC, are designed for ultra-low power consumption and on-device processing, making them ideal for resource-constrained edge devices like smartphones [1] [2] [3]. The company has explicitly stated its intention to expand into consumer electronics, including mobile and embedded devices [3] [4].

Key points supporting this likelihood include:

• Neuromorphic Architecture: BrainChip's Akida chip mimics the human brain's processing, utilizing spiking neural networks (SNNs) for efficient, low-power AI tasks such as pattern recognition and continuous learning directly on the device [2] [5]. This contrasts with traditional AI that often relies on cloud connectivity, which is less suitable for mobile applications due to latency, privacy, and power concerns [2] [6].
• On-Device LLMs: BrainChip announced the release of advanced TENNs models that underpin real-time and private Generative AI capabilities for secure platforms, including on-device Large Language Models (LLMs) for mobile and embedded devices [3] [7]. This suggests a direct application for advanced AI features within smartphones.
• Partnerships and Industry Trends: A Qualcomm video reportedly boasted about a relationship with Prophesee and their anti-blur camera technology, which is expected to be in smartphones "very soon." Given Prophesee's CEO has praised Akida IP, this indirectly suggests BrainChip's technology could be integrated into devices supplied by Qualcomm, potentially including iPhones [4]. The broader industry trend also shows a concerted effort to integrate cost-effective Edge AI acceleration into consumer robots and intelligent appliances with intuitive human-machine interfaces, indicating a strong market demand for such solutions in mobile devices [5].
• Addressing Mobile Constraints: Mobile phones require efficient processing without constant cloud connectivity, minimal power consumption, and enhanced data privacy—all areas where BrainChip's Akida excels [1] [2] [6]. The ability to perform detection, recognition, and learning within the device itself, without sending images to a back-end system, is crucial for mobile privacy and efficiency [1].
• Upcoming Announcements: BrainChip's CEO, Sean Hehir, indicated that almost everything seen in the cloud for AI will soon be available on the edge, with significant announcements regarding functionality expected in late 2024 or early 2025 [2]. This timeline aligns with potential smartphone integration.