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According to the old adage, “a picture is worth a thousand words!” This is an adage meaning that complex and sometimes multiple ideas can be conveyed by a single still image, which conveys its meaning more effectively than a mere verbal description. Now imagine a Motion Picture, a movie scene, how much is conveyed? Perhaps a 100X more than a picture!
The Future of AI in Communications
The future of AI in communications involves the integration of AI/ML for enterprise policy compliance, risk management, log analysis of operational systems, and predictive trend analysis. This can be achieved through platform providers like Accure.AI and will likely be part of the emerging Secure AI Services Edge (SAISE) solution. As advancements in AI, machine learning, conversational AI, and quantum computing continue, our digital infrastructures, devices, and services will become increasingly smarter and contextually aware.
The Concept of Sentient AI
To create Sentient AI, key elements include:
- Embodiment and sensorimotor experience with autonomous goal creation
- Self-awareness with mental maps
- Stream of consciousness for functional thought processes
- Sense of time, narrative, and memory
- Cognitive processes such as perception, memory, attention, decision-making, and problem-solving
- Symbolic reasoning, logic, and abstract thinking
- Higher-level creativity, ethics, morality, and philosophical reflection
In the context of edge computing and communications, envision a scenario where all forms of communication inherently possess hidden meanings and are subject to interpretation by an AI/ML engine. This engine could provide the following capabilities:
- Hidden Contextual Analysis
- Language Translation
- Sentiment Analytics
- Meeting Summaries
- Quick Storage/Retrieval
- Quality Enhancements like noise elimination and video augmented reality
- Meeting Suggestions such as supplementary documents or information
- Scheduling for follow-up meetings or task management
These features are already offered by some video conferencing engines and social media platforms with communication applications. In the near future, all communications might support real-time “Chat GPT”-like sessions for all chats, emails, and dialogues.
Can we leverage this for creating Sentient AI?
In an Ofcom report on 6G, co-authored by myself, we proposed Quantum X as a technology to aid in the creation of Sentient AI. Quantum X leverages quantum mechanical phenomena for computational and communications applications such as quantum computing, quantum networking, and quantum radio. Additionally, we identified Identity Management of Everything (IMoE) as a crucial technology concept for supporting identity and policy management across the emerging Internet of Everything, encompassing people, things, devices, places, and content/data, to create holistic trust.
The approach that is being considered is Hybrid Quantum Computing where on-prem solutions can be cheaper with conventional CPUs/GPUs, cheaper 3-bit Quantum Computers as needed for local processing, and Cloud-based 10-20 qubit systems accessed as needed for occasional training purposes, much like the following:
Hybrid AI Approaches to Achieve Sentient Computing
Quantum computing, combined with neural networks, is being explored to enhance perception through neural networks (NN) and cognition through fuzzy logic (FL). In our paper, “Hybrid Approaches to AI for Realizing Intelligent Networks in the 5G Era,” we discussed the importance of a hybrid approach to implementing ML in a trusted and fit-for-purpose manner while maintaining transparency through existing decision trees. This concept, initially proposed by CT Lin and C.S.G Lee in their 1991 IEEE paper, suggests that neural networks and fuzzy logic control can help systems adapt to events and changes by selecting and applying the appropriate algorithm, policy, or rule to achieve optimal outcomes.
The Role of Quantum Computational Intelligence (QCI)
Quantum Computational Intelligence (QCI) is an actively pursued field for its practical applications and potential solutions to real-life problems. However, it also poses cybersecurity risks, such as breaking encryption algorithms. Researchers like Chang-Sheng Lee have explored integrating Quantum CI with Generative AI to enhance co-learning and multimodal data transformation, suggesting a need for AI models that can process visual cues alongside text-based inputs to generate effective insights.
Leveraging LLM jailbreaks to create multi-modal LLMs for achieving sentient computing involves several steps and considerations. “Jailbreaking” in this context refers to techniques used to bypass the limitations and constraints of existing language models, allowing for greater flexibility and functionality to handle multi-modal visual streams and user “feelings” emoted. However, it’s important to note that ethical considerations and adherence to safety guidelines are paramount when developing such advanced systems.
“The needs of the one outweigh the needs of the many.” – Star Trek III: The Search for Spock
These pieces are being published as they have been received – they have not been edited/fact-checked by ThePrint