Artificial Intelligence: Who Will Teach Ethics to Machines?
Esplora la sfida di insegnare l'etica all'intelligenza artificiale, proponendo un'algor-etica per garantire che le macchine servano l'umanità mentre la tecnologia avanza rapidamente.
Against Ethical Robots with Ron Chrisley
Explore AI ethics challenges, avoiding complacency and inflation while balancing reactive systems and robotic obligations in this thought-provoking seminar by Ron Chrisley.
Beyond LLMs - Agents, Emergent Abilities, Intermediate-Guided Reasoning, and BabyLM - Stanford CS25
Exploración de sistemas de IA autónomos, habilidades emergentes de LLMs, razonamiento guiado intermedio y modelos de lenguaje eficientes. Discusión sobre avances técnicos e implicaciones éticas en IA.
Stanford Seminar - Time Well Spent, Tristan Harris
Explore the impact of technology on attention and ethics with Tristan Harris, discussing AI, the attention economy, and strategies for responsible tech development.
Can You Trust a Computer Algorithm - How and Why
Experts discuss algorithmic trustworthiness, exploring AI benefits, challenges, ethical data management, and regulatory oversight for reliable outcomes in an era of increasing AI reliance.
The Collapse of Artificial Intelligence
Explore the potential downfall of AI systems, their limitations, and the challenges they face in achieving human-like intelligence with Melanie Mitchell's insightful analysis.
The Future of Artificial Intelligence
Demystifying AI: its current capabilities, true intelligence, and future prospects. Expert insights on expectations and concerns for near-term and long-term AI developments.
Epistemic Uncertainty - The AI Problem Understanding Gap and Structured Societal Context Knowledge
Exploring the AI Problem Understanding Gap and the need for structured societal context knowledge to develop safe, robust AI systems in high-stakes domains like healthcare.
Decoding the Law - What Will Large Language Models Mean Under the Law?
Explore the legal implications of large language models and their impact on law interpretation, enforcement, and societal norms with Professor Sonia Gipson Rankin's insightful analysis.
AI Trustworthiness Index and Sources Monitoring
Explore the critical perspectives on AI development and implementation in this 20-minute talk by Amandeep Singh, a senior research engineer at USC Information Sciences Institute. Delve into the importance of using artificial intelligence in moderation an…
Securing LLM-Powered Applications - Overcoming Security and Privacy Challenges
Explore the security and privacy challenges of LLM-powered applications in this 51-minute conference talk from Devoxx. Delve into common issues like prompt injection, key leakage, and misuse of private customer data for model training. Gain insights on l…
Exploring AWS AI/ML Services - Beyond the GenAI Hype
Dive deep into AWS AI/ML offerings, explore GenAI's position in the hype cycle, and understand ethical considerations with AWS Hero Vivek Raja. Includes SageMaker Studio demo.
AI for Developers: Real Talk on AI Capabilities and Limitations
Explore AI's current capabilities, limitations, and practical applications with insights from an AI solopreneur. Learn about getting started, useful tools, and the role of open source in AI development.
Exploring the Power of ChatGPT: Revolutionizing AI Applications
Unlock ChatGPT's potential in AI applications, from creative tasks to secure software development. Explore its capabilities, security implications, and transformative impact across various industries.
Generative AI: The Next Frontier for Cybersecurity and the Cloud
Explore the impact of generative AI on cybersecurity and cloud computing, uncovering potential risks and innovative solutions.
Scaling AI in Production with PyTorch
Learn to scale AI in production using PyTorch, covering resilient distributed platforms, TorchServe, and strategic partner initiatives for a robust ecosystem.
Is Your Machine Learning Model Trustworthy? Evaluating AI Quality and Reliability
Explore AI quality pillars, their importance, and evaluation methods to ensure trustworthy ML models. Learn automated techniques for assessing model performance, robustness, and explainability.
Safely Flying the Generative AI Skies - Managing Risks in AI Coding Tools
Explore risks and strategies for safely managing generative AI coding tools in organizations, supporting innovation while minimizing potential hazards.
Secure AI Transformation: What We Can Do Now and in the Future
Explore new threats, strategies, and best practices for securely transforming AI initiatives, focusing on safeguarding AI applications, development, data, and runtime environments.
Defining Open-Source AI: Challenges and Opportunities in the Evolving Landscape
Explore the complexities of defining Open-Source AI, balancing innovation with core open-source principles in the evolving AI landscape. Engage in shaping a definition that reflects technological progress.
The Turing Lectures - Can We Trust AI?
Explore AI biases, their impact on fairness, and efforts to address these issues. Gain insights into critical evaluation of AI technologies and the importance of rigorous testing and corporate accountability.