?? The Future of AI Evaluation: LLM Judges vs. Human-in-the-Loop As generative AI continues to revolutionize industries, one critical question remains: How do we evaluate AI systems at scale without compromising on trust and quality? In our latest article, we explore the balance between LLM Judges and Human-in-the-Loop (HITL) evaluation approaches. ?? LLM Judges bring unparalleled scalability, speed, and consistency to the table, while ???? Human-in-the-Loop offers nuanced judgment, contextual understanding, and ethical oversight. But what if you didn’t have to choose? Platforms like RagMetrics combine the strengths of both to create a scalable, reliable, and trustworthy evaluation framework that meets the growing demands of modern AI systems. ?? What’s in the article? The unique challenges of evaluating RAG systems and LLMs. How LLM Judges and HITL solve different parts of the puzzle. Why a hybrid approach is essential for industries like healthcare, finance, and defense. ?? Read the full article here: https://lnkd.in/dRSjSKRm ?? What’s your take? Are you team LLM Judge or HITL? Let us know in the comments! #AI #LLM #RAG #ArtificialIntelligence #AIEvaluation #TechInnovation
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The European Union's new AI Act is the world’s first comprehensive artificial intelligence and machine learning (collectively, AI) focused law. It will have a sweeping impact on many businesses, including those operating outside the EU, that currently design, develop, integrate, or use AI systems or models or plan to do so in the future. So, what do you need to know about this landmark new law? Here, we've outlined 10 key takeaways for business and legal leaders: https://bit.ly/3LMwZVU #AI #artificialintelligence
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our work with AI21 Labs directly addresses and aligns with OECD.AI's AI Principles for trustworthy AI. amazing to see responsibility, safety, and functionality coupled together so naturally!
?? How can we ensure that large language models (LLMs) align with ethical principles while delivering meaningful outputs? ?? In this blog post, Shanen Boettcher, PhD of AI21 Labs, explores the intersection of AI development and the OECD AI Principles—specifically focusing on how to train LLMs to adhere to a code of conduct. He provides actionable insights into embedding ethical codes into LLMs and integrating overarching principles into the workplace. Ulrik Vestergaard Knudsen Jerry Sheehan Audrey Plonk Karine Perset?Celine Caira?Luis Aranda?Jamie Berryhill??Lucia Russo?Noah Oder?John Leo Tarver ????Rashad Abelson?Angélina Gentaz?Valéria Silva?Bénédicte Rispal?Johannes Leon Kirnberger Eunseo Dana Choi?Sara Fialho Esposito Nikolas S. Sarah Bérubé Guillermo H. Sara Marchi #artificialintelligence #oecd #LLM #trustworthyai #responsibleai
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?? Trustworthy #EnterpriseAI: How to train an LLM to follow a code of conduct Training large language models to follow a code of conduct isn’t just a technical challenge—it’s an ethical imperative. At?AI21 Labs, we’re building LLMs that align with human values, business needs and societal expectations. We’ve partnered with the OECD.AI to ensure that AI21 Labs' #Jamba models align with our Business Code of Conduct, mapped directly to the?OECD.AI?principles for trustworthy AI. Curious about our approach? Read the full whitepaper by Shanen Boettcher, PhD here:?https://lnkd.in/eRWV4huA #AI #LLM #ResponsibleAI #Innovation
?? How can we ensure that large language models (LLMs) align with ethical principles while delivering meaningful outputs? ?? In this blog post, Shanen Boettcher, PhD of AI21 Labs, explores the intersection of AI development and the OECD AI Principles—specifically focusing on how to train LLMs to adhere to a code of conduct. He provides actionable insights into embedding ethical codes into LLMs and integrating overarching principles into the workplace. Ulrik Vestergaard Knudsen Jerry Sheehan Audrey Plonk Karine Perset?Celine Caira?Luis Aranda?Jamie Berryhill??Lucia Russo?Noah Oder?John Leo Tarver ????Rashad Abelson?Angélina Gentaz?Valéria Silva?Bénédicte Rispal?Johannes Leon Kirnberger Eunseo Dana Choi?Sara Fialho Esposito Nikolas S. Sarah Bérubé Guillermo H. Sara Marchi #artificialintelligence #oecd #LLM #trustworthyai #responsibleai
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"Trustworthy AI for the enterprise: How to train an LLM to follow a code of conduct"
?? How can we ensure that large language models (LLMs) align with ethical principles while delivering meaningful outputs? ?? In this blog post, Shanen Boettcher, PhD of AI21 Labs, explores the intersection of AI development and the OECD AI Principles—specifically focusing on how to train LLMs to adhere to a code of conduct. He provides actionable insights into embedding ethical codes into LLMs and integrating overarching principles into the workplace. Ulrik Vestergaard Knudsen Jerry Sheehan Audrey Plonk Karine Perset?Celine Caira?Luis Aranda?Jamie Berryhill??Lucia Russo?Noah Oder?John Leo Tarver ????Rashad Abelson?Angélina Gentaz?Valéria Silva?Bénédicte Rispal?Johannes Leon Kirnberger Eunseo Dana Choi?Sara Fialho Esposito Nikolas S. Sarah Bérubé Guillermo H. Sara Marchi #artificialintelligence #oecd #LLM #trustworthyai #responsibleai
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Recommended read for policy makers and researchers with an interest in ethical AI: OECD report on embedding ethical codes in LLM’s. Especially useful for those who look into AI in workplace and Education.
?? How can we ensure that large language models (LLMs) align with ethical principles while delivering meaningful outputs? ?? In this blog post, Shanen Boettcher, PhD of AI21 Labs, explores the intersection of AI development and the OECD AI Principles—specifically focusing on how to train LLMs to adhere to a code of conduct. He provides actionable insights into embedding ethical codes into LLMs and integrating overarching principles into the workplace. Ulrik Vestergaard Knudsen Jerry Sheehan Audrey Plonk Karine Perset?Celine Caira?Luis Aranda?Jamie Berryhill??Lucia Russo?Noah Oder?John Leo Tarver ????Rashad Abelson?Angélina Gentaz?Valéria Silva?Bénédicte Rispal?Johannes Leon Kirnberger Eunseo Dana Choi?Sara Fialho Esposito Nikolas S. Sarah Bérubé Guillermo H. Sara Marchi #artificialintelligence #oecd #LLM #trustworthyai #responsibleai
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Fascinating article from the Financial Times on AI model collapse, something Das Rush has written about for our N2 Communications AI series. In short: Large Language Models need a LOT of content data to train on. Human-created content data (sometimes known as "good writing") is getting more expensive--licensing fees, lawsuits, etc. The alternative is to train new LLMs on "synthetic" content data that is created by other LLMs. But researchers are finding that this leads very quickly to model collapse, which Das calls "the AI equivalent of a copy of a copy of a copy, each instance a slightly lower resolution than the previous one, until the audience has no idea what they’re looking at." If you want to get Classical, think of it as an Ouroboros Problem--the snake eating its own tail. All of this has huge implications for the future of GenerativeAI, and is one more point of evidence against the idea that human creatives will be replaced any time soon. The follow-up question I've been asking is "how much is content data worth?" And its sub-questions, how much more is good writing worth than mediocre writing, and how do you systematically tell the difference? I've started a research project on this for future articles, if anyone has been wondering similar things and wants to brainstorm, hit me up! FT article here: https://lnkd.in/gn8xkyKp Nature article it is based on here: https://lnkd.in/g_Q4iRac
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?? **Meet RAG: The Future of AI** ??? ?? **Retrieval-Augmented Generation (RAG)** is transforming AI by combining real-time data retrieval with language models, delivering accurate, up-to-date responses.? ?? **Why RAG?**?? Traditional AI models struggle with outdated info and lack context. RAG solves this by pulling fresh, relevant data from external sources—perfect for healthcare, legal, education, and customer support.? ?? **How it works:**?? 1?? **Retrieves** real-time info using semantic search.?? 2?? **Generates** precise answers by blending retrieved data with pre-trained knowledge.? ? **Benefits:**?? ? Reduces false info (hallucinations).?? ? Improves accuracy and transparency.?? ? Always up-to-date with real-time insights.? ?? Learn more: https://lnkd.in/gEykMzRb #AI #RAG #TechInnovation #FutureOfAI
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?? **Meet RAG: The Future of AI** ?? ?? **Retrieval-Augmented Generation (RAG)** is transforming AI by combining real-time data retrieval with language models, delivering accurate, up-to-date responses. ?? **Why RAG?**? Traditional AI models struggle with outdated info and lack context. RAG solves this by pulling fresh, relevant data from external sources—perfect for healthcare, legal, education, and customer support. ?? **How it works:**? 1?? **Retrieves** real-time info using semantic search.? 2?? **Generates** precise answers by blending retrieved data with pre-trained knowledge. ? **Benefits:**? ? Reduces false info (hallucinations).? ? Improves accuracy and transparency.? ? Always up-to-date with real-time insights. ?? Learn more: https://lnkd.in/d4-DCQHf #AI #RAG #TechInnovation #FutureOfAI
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?? How can we ensure that large language models (LLMs) align with ethical principles while delivering meaningful outputs? ?? In this blog post, Shanen Boettcher, PhD of AI21 Labs, explores the intersection of AI development and the OECD AI Principles—specifically focusing on how to train LLMs to adhere to a code of conduct. He provides actionable insights into embedding ethical codes into LLMs and integrating overarching principles into the workplace. Ulrik Vestergaard Knudsen Jerry Sheehan Audrey Plonk Karine Perset?Celine Caira?Luis Aranda?Jamie Berryhill??Lucia Russo?Noah Oder?John Leo Tarver ????Rashad Abelson?Angélina Gentaz?Valéria Silva?Bénédicte Rispal?Johannes Leon Kirnberger Eunseo Dana Choi?Sara Fialho Esposito Nikolas S. Sarah Bérubé Guillermo H. Sara Marchi #artificialintelligence #oecd #LLM #trustworthyai #responsibleai
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Doing digital right! Managing Director Swiss Digital Initiative & f0t1 GmbH; foraus Policy Fellow Science & Tech / Security; CIDOB-Santander 35 under 35
"By translating the OECD’s AI Principles into 60 operationalised statements and subsequently stress-testing each of those 60 statements with 1,000 attack prompts, researchers could identify exactly where the Jamba models held up—and where they fell short—just as a Code of Conduct should. But, as we mentioned earlier, a Code of Conduct is not there just to identify misaligned behaviour. It also offers a framework for improvement.???? In our own process, we use the results of this testing to inform the training and alignment of future model versions. All responses carry over into the next round of training: those aligned with our AI Code of Conduct are used for positive reinforcement. In contrast, responses that violate the Code of Conduct are reviewed by human evaluators and used as negative feedback. Through this iterative process, we are able to build a model that is aligned with our AI Code of Conduct and the OECD’s AI Principles and ready for responsible and trustworthy use in the enterprise." This idea of #Constitutional #AI is very interesting and promising. But this approach also comes with its own limitations as my thought experiment with the #Swiss #Constitution shows https://lnkd.in/dr8PcDaV
?? How can we ensure that large language models (LLMs) align with ethical principles while delivering meaningful outputs? ?? In this blog post, Shanen Boettcher, PhD of AI21 Labs, explores the intersection of AI development and the OECD AI Principles—specifically focusing on how to train LLMs to adhere to a code of conduct. He provides actionable insights into embedding ethical codes into LLMs and integrating overarching principles into the workplace. Ulrik Vestergaard Knudsen Jerry Sheehan Audrey Plonk Karine Perset?Celine Caira?Luis Aranda?Jamie Berryhill??Lucia Russo?Noah Oder?John Leo Tarver ????Rashad Abelson?Angélina Gentaz?Valéria Silva?Bénédicte Rispal?Johannes Leon Kirnberger Eunseo Dana Choi?Sara Fialho Esposito Nikolas S. Sarah Bérubé Guillermo H. Sara Marchi #artificialintelligence #oecd #LLM #trustworthyai #responsibleai
