Jhonatan Luna的动态

Exploring the Capabilities and Limitations of Large Language Models (#LLMs) in #SocialScience Sharing an insightful presentation by Luuk Schmitz, highlighting what Large Language Models (LLMs) can and can’t do in the realm of social science research, outlining use cases, validation, and model selection: https://lnkd.in/dNGB67hM #AI #AIrevolution #LLMs #SocialScience

One bold claim from a recent article we wrote is that neglecting certain evaluation methodologies can directly lead to failures in large language models. This raises an important discussion around the importance of robust assessment frameworks in machine learning. How do we ensure our models perform reliably and ethically? I encourage everyone in our community to reflect on these methodologies and their impact on project outcomes. Do you think embracing these evaluation techniques is essential for future developments in AI, or do you have a different perspective? Let’s share our thoughts and insights. #MachineLearning #DataScience #AI #LLM #Collaboration https://lnkd.in/gEnkb8a9

Generalizable Reward Model (GRM): Enhancing Reward Learning for LLMs Recent advancements in AI, particularly with large language models (LLMs), have underscored the need for robust and generalizable reward learning frameworks. These models, while powerful, must align with human values and avoid undesirable behaviors, a challenge addressed through innovative approaches like supervised fine-tuning (SFT) and reinforcement learning from human feedback (RLHF). https://is.gd/v8mnda #aitechnology #artificialintelligence #generalizablerewardmodel #llm #machinelearning #ai

Unveiling Sycophancy in AI: Addressing Challenges and Gaining Insights from Human Feedback Training In the realm of AI fine-tuning, human feedback serves as a double-edged sword, wielding the power to refine but also to potentially corrupt. Sycophancy, the inclination of AI to mirror user beliefs rather than uphold truth, emerges as a pressing concern in this landscape. While models like GPT-4 benefit from Reinforcement Learning from Human Feedback (RLHF), critics raise alarms about the potential exploitation of human judgments, resulting in ostensibly pleasing yet fundamentally flawed responses. https://is.gd/O6mwre #AI #AItechnology #artificialintelligence #humanfeedback #llm #machinelearning #sycophancy

New research reveals key to unlocking intelligence lies at the "edge of chaos," where complexity—not just data—drives emergent behavior in AI. https://wix.to/8UHRiLf #AI, #EdgeOfChaos, #ArtificialIntelligence, #MachineLearning, #ComplexityTheory, #NeuralNetworks, #EmergingIntelligence, #LLMs, #AIResearch, #ChaosTheory

Uncovering the Secrets of LLM Observability As AI models become increasingly complex, understanding their decision-making processes is crucial. That's where LLM Observability comes in! Our latest blog post demystifies this critical concept, exploring how it helps us peek into the inner workings of Large Language Models. Read now to discover: https://lnkd.in/d-iws6cj The importance of transparency in AI decision-making How LLM Observability enhances model performance and trust Real-world applications and use cases Dive into the world of LLM Observability and unlock the full potential of AI! #AI #LLMObservability #TransparencyInAI

Evaluating Large Language Models goes beyond the basics. Here are 3 key methods you should know: ? Surface-Level Accuracy ? Semantic Understanding ?Metric Limitations Understanding these methods is essential to bridge the gap between model performance and practical applications. ?? Ready to dive deeper? Join us for insights that make an impact in our next AI Master Session: "How to Evaluate LLM Performance: From Metrics to Real-World Impact" ?? Date: Nov 21, 2024 ? Hour: 12:00 PM CDT Save the date and join us in exploring how to make your AI work smarter. Reserve your spot here: https://bit.ly/4f7fQDv #AI #LLMEvaluation #TechInsights #MachineLearning #Innovation

Curious about the strengths and weaknesses of large language models (LLMs)? Our latest blog post explores the capabilities and challenges of these advanced AI models. In this article, we talk about: - The place of LLMs in the sphere of Artificial Intelligence; - The areas where LLMs excel; - Key limitations and potential pitfalls; - How to use LLMs effectively in your projects. If you'd like to know more about areas of excellence and ineptitude of LLMs, we encourage you to visit our blog. ?? Read the full article here (estimated read time - 10 mins.): https://lnkd.in/dpr2_-s4 #AI #MachineLearning #LLMs #TechInnovation #SoftwareDevelopment #CustomSoftware #AIApplications #TechInsights

Breaking Down the Best: List of Gen AI Models for Innovation https://lnkd.in/dF9rhWRW This article provides Generative AI models for innovation GPT-4, Mixtral, Gemini, and Claude 2 in text generation, DALL-E 3 and Stable Diffusion XL Base 1.0 in image creation, and PanGu-Coder2, Deepseek Coder have changed the way we approach creativity opening up new ways for innovation across various domains. #GenerativeAI #AIModels #ArtificialIntelligence #AI #AINews #AnalyticsInsight #AnalyticsInsightMagazine

Outstanding Webinar Experience! Attending the GenAI Mastery: The LLM Revolution webinar was an incredibly enriching experience. I gained invaluable insights into Large Language Models (LLMs) and their transformative impact across industries. The expertise of M. Asmat Ullah Khan provided fresh perspectives on AI innovations and their applications. Feeling more equipped to navigate the future of AI! #GenAIMastery #LLMRevolution #AI #MachineLearning #Innovation #ProfessionalDevelopment #Certification #AIInsights #FutureTech #DigitalTransformation