David Bach’s Post

The AI Safety Clock, created by IMD, is a tool designed to evaluate and communicate the risks posed by Uncontrolled Artificial General Intelligence (UAGI). The AI Safety Clock monitors three key factors to assess the risks posed by UAGI: 1️⃣ AI sophistication 2️⃣ Autonomy 3️⃣ Physical integration These factors are continuously monitored over 1,000 websites and 3,470 news feeds, providing real-time insights into technological progress and regulatory developments in the field of AI. https://lnkd.in/enMSCcnK #AI #Safety #AISafety #LLM #AGI #UAGI

Unlocking boundless possibilities of tomorrow. How does artificial intelligence content detection work, and how do you use Turnitin to detect AI writing and what is the best score is it 10-15 % or is it 15-20%. #AI #Annotation

Exploring the inner workings of AI: a milestone in AI safety and interpretability... I’ve just finished reading an eye-opening white-paper by Anthropic, "Mapping the Mind of a Large Language Model," which provides unprecedented insights into the organisation and functionality of AI models, particularly focusing on their Claude 3.0 Sonnet model. 4 Key Learnings: 1️⃣ Demystifying AI For the first time, we can see how millions of concepts are represented across a network of neurons within a state-of-the-art AI model. This transparency is a critical step towards validating the safety and reliability of AI systems. 2️⃣ Advanced Feature Detection: Using dictionary learning, researchers have identified complex features within the AI that correlate with a wide range of concepts, from simple geometric shapes to abstract ideas like ethical dilemmas. 3️⃣ Manipulating AI Responses: The study delves into how manipulating certain features within the AI can alter its behaviour, providing a fascinating glimpse into the potential for more controlled and predictable AI responses. 4️⃣ Towards Safer AI: This research paves the way for developing mechanisms to mitigate biases, ensure truthful interactions, and prevent misuse of AI technology. Implications for AI Development: The ability to map and understand the intricate feature networks within AI models not only enhances our ability to predict and control their behaviour but also establishes a foundation for developing more robust safety measures. It’s a step closer to creating AI systems that can truly be trusted. Reflecting on AI’s Future: The insights from this paper highlight the importance of interpretability in AI development. As we continue to integrate AI into various aspects of life, understanding the "how" and "why" behind its decision-making processes becomes crucial. This research not only sheds light on the current capabilities but also opens up new avenues for enhancing the ethical deployment of AI. 🔗 Read the full paper here: https://lnkd.in/efVknBie If you're as fascinated by these developments as I am, let’s connect and discuss how we can contribute to safer and more transparent AI! #AI #MachineLearning #ArtificialIntelligence #DataScience #TechForGood #EthicalAI

Adding generative AI to wargame training can improve realism, but not without risk https://buff.ly/48lVjqm

What's Next in AI: Why artificial intelligence didn't disrupt the election - Pittsburgh Post-Gazette: What's Next in AI: Why artificial intelligence didn't disrupt the election  Pittsburgh Post-Gazette http://dlvr.it/TG5sbv #ai #artificialintelligence

🚨 AI Detection Tools: Are They Reliable? 🤖 As AI-generated content continues to grow, so do the tools designed to detect it. However, recent discussions have raised concerns about the reliability of AI detection tools. While tools like Turnitin and Copyleaks are widely used in academic and professional settings, false positives and inaccuracies still pose challenges. 🔍 Many AI detectors analyze text patterns to flag machine-generated content, but evolving AI models are becoming harder to detect. Some tools are now incorporating "content credentials" to provide transparency around AI usage, but is that enough? 🔑 As AI technology advances, we need to consider how detection tools can improve and keep up with these advancements to maintain authenticity in our digital world. 👉 What are your thoughts on the reliability of AI detectors? Comment below! #AI #ArtificialIntelligence #AIDetection #TechTrends #DigitalTransparency

AI Isn’t Perfect: Artificial Intelligence is often seen as flawless. However, AI systems can inherit biases from their training data, leading to flawed outcomes. Always validate and monitor AI decisions. #ArtificialIntelligence #BiasInAI

AI/ML Beyond The Hype #3 What if AI hallucination was coming from a bad prompt? 🤔 In the world of generative AI, much of the blame for “hallucinations” – when AI outputs incorrect or nonsensical information – is placed on the model itself. But what if the issue lies in the input rather than the output? Just as clear communication is key to getting the right answers from a human expert, crafting precise prompts is essential for AI. A vague or overly complex prompt can lead to confusion, just as a poorly worded question might lead a person astray. As AI becomes a critical tool in industries ensuring that we understand the art of prompting is no longer optional—it’s a must. After all, the clearer the instructions, the better the results. Let’s reframe the narrative: instead of focusing solely on AI’s flaws, let’s take a closer look at how we interact with it. The problem might be less about AI hallucinating and more about us learning to speak its language effectively. Education is key 🔑 What do you think? Is it time we, as users, take more responsibility for our AI’s “hallucinations”? #ArtificialIntelligence #PromptEngineering #GenerativeAI #AIInnovation #Leadership

In today’s rapidly evolving AI landscape, mastering prompt engineering is key to unlocking the full potential of AI models. This certification has equipped me with skills to design effective prompts, optimize responses, and contribute to innovative projects in AI. #AI #PromptEngineering #LearningJourney #TechInnovation