AI Hardware & Edge AI

Introducing the Comprehensive AI Hardware & Edge AI Summit

The AI Hardware & Edge AI Summit offers a comprehensive platform covering the design and deployment of ML hardware and software infrastructure across the cloud-edge continuum.

For Enterprise ML Experts: This unique event is tailored for enterprise ML practitioners seeking both hardware and software tools and techniques for training, deployment, and serving machine learning. The program encompasses a blend of state-of-the-art topics and practical tutorials, equipping you with knowledge of the latest advancements and available resources. Join the 40% of our audience consisting of enterprise ML experts like yourself!

  1. Case Studies: A dedicated day focusing on case studies ranging from cloud to edge, encompassing generative AI, simulation & digital twins, computer vision, NLP, automotive AI, TinyML, and extreme edge. Gain insights into real-world applications and learn from practical experiences.
  2. MLOps and ML Software Infrastructure: Extensive coverage of MLOps, software tools, and ML software infrastructure, along with discussions on novel training methods such as federated learning, distributed learning, active learning, and multimodal learning. Stay up-to-date with the latest trends and advancements in ML technology.
  3. Product Launches and Showcases: Experience product launches, live demos, and showcases on the expanded exhibition floor. Witness firsthand the cutting-edge innovations and solutions shaping the AI landscape.

Aihub Team

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SK Telecom outlines its plans with AI partners

SK Telecom outlines its plans with AI partners

Razer and ClearBot are using AI and robotics to clean the oceans

Razer and ClearBot are using AI and robotics to clean the oceans

NHS receives AI fund to improve healthcare efficiency

NHS receives AI fund to improve healthcare efficiency

National Robotarium pioneers AI and telepresence robotic tech for remote health consultations

National Robotarium pioneers AI and telepresence robotic tech for remote health consultations

IBM’s AI-powered Mayflower ship crosses the Atlantic

IBM’s AI-powered Mayflower ship crosses the Atlantic

Humans are still beating AIs at drone racing

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How artificial intelligence is dividing the world of work

How artificial intelligence is dividing the world of work

Global push to regulate artificial intelligence

Global push to regulate artificial intelligence

Georgia State researchers design artificial vision device for microrobots

Georgia State researchers design artificial vision device for microrobots

European Parliament adopts AI Act position

European Parliament adopts AI Act position

Chinese AI chipmaker Horizon endeavours to raise $700M to rival NVIDIA

Chinese AI chipmaker Horizon endeavours to raise $700M to rival NVIDIA

AI Day: Elon Musk unveils ‘friendly’ humanoid robot Tesla Bot

AI Day: Elon Musk unveils ‘friendly’ humanoid robot Tesla Bot

AI and Human-Computer Interaction: AI technologies for improving user interfaces, natural language interfaces, and gesture recognition.

AI and Data Privacy: Balancing AI advancements with privacy concerns and techniques for privacy-preserving AI.

AI and Virtual Assistants: AI-driven virtual assistants, chatbots, and voice assistants for personalized user interactions.

AI and Business Process Automation: AI-powered automation of repetitive tasks and decision-making in business processes.

AI and Social Media: AI algorithms for content recommendation, sentiment analysis, and social network analysis.

AI for Environmental Monitoring: AI applications in monitoring and protecting the environment, including wildlife tracking and climate modeling.

AI in Cybersecurity: AI systems for threat detection, anomaly detection, and intelligent security analysis.

AI in Gaming: The use of AI techniques in game development, character behavior, and procedural content generation.

AI in Autonomous Vehicles: AI technologies powering self-driving cars and intelligent transportation systems.

AI Ethics: Ethical considerations and guidelines for the responsible development and use of AI systems.

AI in Education: AI-based systems for personalized learning, adaptive assessments, and intelligent tutoring.

AI in Finance: The use of AI algorithms for fraud detection, risk assessment, trading, and portfolio management in the financial sector.

AI in Healthcare: Applications of AI in medical diagnosis, drug discovery, patient monitoring, and personalized medicine.

Robotics: The integration of AI and robotics, enabling machines to perform physical tasks autonomously.

Explainable AI: Techniques and methods for making AI systems more transparent and interpretable

Reinforcement Learning: AI agents that learn through trial and error by interacting with an environment

Computer Vision: AI systems capable of interpreting and understanding visual data.

Natural Language Processing: AI techniques for understanding and processing human language.