Over the past three to four decades, the promise of Artificial Intelligence (AI) went from the tip of the iceberg (Expert Systems, Intelligent Tutoring Systems, Lisp, Prolog, A* algorithm, etc.) around mid-80s, to a dramatic crushing valley around mid-90s, only to raise once more as the AI wave is currently sweeping through practically every field in its path, including scientific, social, economic, and educational spheres. Currently, new AI-based terms like Quantum Computers, Deep Learning, Industry 4.0/5.0, Personalized Human-Machine Interaction models, Self-aware Systems, Cognitive management, etc., are replacing older ones like the 5th Generation computers and Robotics-factory.

Nowadays, AI-based systems are developed with confidence due to the high accuracy in training them using available data (Big/Huge Data, Large Datasets, Remote Sensing, Internet of Things) via Machine Learning (ML), at an incredible speed (5G/6G/7G). Advanced system integrations based on a variety of networks paradigms (Cloud, Slicing, NFV, SDN, etc.), UMV (Self-driving, Drones, Satellites, etc.), as well as the increase of computation power (miniaturization), contribute to this effort. As a result, new practical domains have emerged, such as Precision Medicine, Precision Agriculture, Artificial creativity, Personalized healthcare, Mobile Services, etc.

The inaugural AINOW 2025 conference serves as a meeting point for AI-adopters and practitioners to present and analyze various practical achievements and forecast the next trends.

Professionals from industry, government, and academia, researchers, engineers, practitioners, and students are invited to contribute. AINOW welcomes 1) full papers presenting significant research, development, application, position, or survey, 2) short papers on work-in-progress, 3) posters, 4) contributed talk presentations, as well as workshops, thematic sessions, and demos.

Prospective authors are invited to submit original, unpublished works, which are not under review in any other conference or journal. Topics of interest include, but are not limited to, the following.
Topics
AI analytics on advanced solutions

    Symbolic AI and Big AI hybrid solutions
    Machines Learning (ML) and supervised learning
    AI types (reactive, limited memory, theory of mind, and self-aware)
    AI-sensitivity to quality of data
    Deep Learning (DL) and reinforcement learning (RL) techniques
    Embedded intelligence (eAI) and hybrid-AI (hAI)
    Human-compatible AI, Conversational AI, and Human-like AI-thinking
    AI-thinking tools and knowledge engineering
    Self-aware computing and AI-driven applications
    AI pipelines and use cases
    AI technologies and mitigating approaches for echo chambers

Generative-AI basics and beyond

    Basics of generative-AI and impending services and applications
    Combination of counting occurrences vs predicting
    Generative pre-trained transformer models
    Combination of GPT models and Reinforcement learning models
    Creativity and originality in GPT-based tools
    Deep learning, Big Data, and Large Language Models (LLM)
    Autoregressive language models (like LLM) and Augmented LLMs
    From transformer architectures to specialized software
    Overfitting, underfitting, hallucinations, and unintended consequences
    Interpolation and extrapolation vs training data
    Danger of plausibility and fluency combination
    Guardrail for bias and toxicity

Experiences with generative-AI core activities

    Large Language Models (LLM) taxonomy and accurate data
    Capabilities of generative-AI (content generation, translation, interactive)
    Multi domain experiences (medical, legal, financial, education, etc.)
    Ethics and safeness (bias, fairness, filter, explainability)
    Generating forecasts in complex scenarios (financial, weather, real estate, etc.)
    Automating and personalized customer service
    Analyses of huge volumes of unstructured data
    Aggregated metrics of production systems
    Intelligent interactions
    Automated reports
    Personalized marketing
    Identify security threat patterns
    Optimizing pricing strategies
    Analyzing dangers on social networks
    Analysis user preferences, behaviors, contexts

AI-based support for new approaches

    Artificial life and future intelligence
    AI ethics, social inclusion, and accessibility
    Embodied and augmented cognition
    Heuristic tactile and haptic patterns
    AI-precision (medicine, agriculture, weather predictions)
    AI-based creativity
    AI-enabled creativity renaissance
    Managing AI-involving projects
    AI and visual data analysis
    AI-based remote sensing and signal processing
    AI-driven reasoning under uncertainty
    AI in emerging applications (market, gas&oil industry, crop Evaluation, etc.)
    AI/ML-based creative art (picture, music, novels, movies, virtual museums, etc.)
    Autonomous driving (drones, cars, underwater vehicles, etc.)
    Distributed deep learning (multi-node ML, increased parallelism, federated ML, GPUs/TPUs/servers, etc.)

AI-based complex systems and services

    AI for social networks and media
    AI, IoT, and wearable devices for medical applications
    AI, IoT, and remote sensing for agricultural and farming systems
    Mobile AI, on-device AI systems (eAI), Cloud AI, and Edge AI
    AI-based urban managing systems in smart cities
    AI-based Industry 4.0 and AI-based production and supply planning
    Native AI and 5G/6G Networks
    AI-approaches for small cells (4G) and massive MIMO (5G) technologies
    AI-based AR/VR systems
    AI-based harvesting space energy

Embodied-AI and Embedded-AI solutions

    Design of humanoid robots and interactive service robots (cobots)
    Mechanism for autonomous drones and self-driving cars
    Dedicated sensors and actuators for embodied-AI systems
    Embedded-AI capabilities in sensors, smart cameras, wearable devices, and IoT devices
    Latency and dependency on network connectivity control
    Applications of embedded-AI in IoT devices, wearable, consumer electronics. infrastructure.
    Solutions for health monitoring devices and home automation systems

AI-based specialized applications and systems

    AI-driven drones coordination systems
    AI-based predicting emergency events in 5G and 6G systems
    AI-based coordination of robot fleets and drone fleets
    AI-based neuroimaging for immersive virtual environments
    AI-based cognitive engines for self-driving in smart cities
    AI-based cognitive management in advanced networks (Slicing, Virtualization, SDN/NFV, virtual RAN, and Cloud-RAN)
    AI-based cyber systems resiliency
    AI human-centered cybersecurity
    AI-based network monitoring and management tools
    AI-support for legal aspects
    AI/ML-based system open interfaces
    AI-based maritime and transportation systems
    AI support for smart cities and urban decisions
    AI-driven automotive industry

Emerging AI social facets (sticky wicket)

    AI-driven accessibility for people with limited abilities
    AI-based personality distortion in social networks
    AI-based models for tracking citizen behavior
    AI dealing with fake news epidemic
    AI-based discovering disinformation patterns
    AI-based tampering multimedia content
    AI-based software for reality distortion (aging/de-aging, faking voice, image)
    AI-based cyber-crime prediction and detection
    Trust and credibility metrics in AI-based systems
    Responsible AI in serving pipelines
    Policies for designing, deploying, and maintaining AI-based complex systems
    International ethics standards for AI-based technology