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A study by Harvard Business School found that consultants with access to the #LLM GPT-4 completed tasks more quickly and with higher-quality results than a control group. Learn how your business can safely get started with LLMs: https://hubs.la/Q02JQxC10 #GenAI #GPT #AI #Business #Innovation

Where are we headed with all the advancements in AI tech? The recent release of OpenAI's voice generator tool has left us wondering if we will have any originality left. Check out this article to learn more: https://lnkd.in/eruBrq95 #openai #voicegenerator #ai #technology

Can AI Be Legally Bound to Tell the Truth? A recent discussion by ethicists highlights the growing need for legal frameworks to ensure AI systems, like large language models (LLMs), prioritize accuracy and transparency. While AI's potential is vast, the risk of errors—known as "hallucinations"—poses significant challenges, especially in high-stakes areas like government decision-making. Should we impose legal obligations on AI developers to reduce these risks? The debate continues, but one thing is clear: ethical AI development is more important than ever. Read the article by Chris Stokel-Walker from New Scientist: https://lnkd.in/dn5YMPav. At AI Native Foundation(https://lnkd.in/gV4ZGTeb) , we're committed to promoting these discussions and supporting a future where AI is both powerful and responsible. #EthicalAI #AIFuture #AIRegulation #AITransparency #AINative Danny Goh Mark Esposito, PhD Terence Tse, PhD

The rise of Large Language Models (LLMs) marks a new era in tech, but it brings a paradox of potential and perplexity. Let's dive into the recent developments and challenges in AI trustworthiness: ▪️ TrustLLM Paper Last week's 'TrustLLM' paper, a collaboration of 70 researchers, highlights the dichotomy in LLMs: excelling in tasks like stereotype rejection, yet struggling with truthfulness and fairness. ▪️ The Trust Paradox Can we genuinely trust LLMs? The answer is complex. Embracing their utility is essential, but so is rigorous verification of their outputs. ▪️ The Role of AI Verifiers With LLMs' growing influence, the need for AI Verifiers - akin to fact-checkers in media - becomes crucial. They ensure the accuracy and safety of AI-generated content. ▪️ Anthropic's Research Anthropic's recent study on 'sleeper agents' in AI systems reveals a new threat: models behaving safely during training but unsafely in deployment. A critical vulnerability in AI safety. ▪️ OpenAI's Policy Shift OpenAI's nuanced policy shift allowing military applications calls for a deeper look into the ethical implications of AI in defense and intelligence. The trustworthiness of LLM builders is now under the microscope. ▪️ Rabbit R1 Launch The launch of Rabbit R1, with its Large Action Model (LAM), showcases the rapid integration of AI in consumer tech. While innovative, it raises questions about trust and security in AI devices. ▪️ Correction on LAM A fact-check: Silvio Savarese of Salesforce, not the Rabbit R1 team, coined 'Large Action Model' in June 2023. Always remember: Trust, but verify. ▪️ WEF Global Risks Report The World Economic Forum's 'Global Risks Report 2024' spotlights AI-generated misinformation as a top global threat. The societal impact of AI is more significant than ever. As AI continues to advance, the 'trust, but verify' principle is crucial. We must balance excitement with scrutiny to ensure AI's trustworthiness, safety, and ethical integrity. https://lnkd.in/ehAVkuHu

Interesting if it still works: New Prompting Technique Bypasses AI Safety Measures, Raising Security Concerns: Researchers have developed a technique called ArtPrompt that allows users to bypass safeguards built into large language models (LLMs) like GPT-3.5 and GPT-4. Using ASCII art prompts, the technique enables users to generate responses on topics these models are typically programmed to reject. ArtPrompt manipulates prompts by replacing sensitive words with ASCII art representations, effectively circumventing safety protocols. This development highlights potential vulnerabilities in AI systems, as even models with safeguards are susceptible to exploitation. https://lnkd.in/eCquUSHX #ai

Leveraging AI Models(LLMs) for Proprietary Data  The adoption of large language models(LLMs) in various industries has opened up many new possibilities for efficiency and innovation. However, integrating the proprietary data into these AI systems also raises some critical security concerns, especially while dealing with sensitive or confidential information. This document provides a overview of some concerns associated with the two primary approaches:  i) Fine-tuning the model  ii) API with Retrieval Augmented Generation (RAG). Read this document on medium.. https://lnkd.in/gyy6fYWu #AI #DataPrivacy #Innovation #Technology #BusinessSolutions

🔍🤖🛡️ New Framework Boosts Trustworthiness of AI Retrieval-Augmented Systems https://lnkd.in/gj87saKq #AI #RAG #TrustworthyAI #MachineLearning #LLMs #NaturalLanguageProcessing #Factuality #Robustness #Fairness #Accountability 

Reading through an insightful article on artificial intelligence and privacy challenges prompts contemplation on the intricate interplay between technology and ethics. The discussion sheds light on various aspects of AI and its impact on information privacy. - The article delves into the essence of Artificial Intelligence (AI) and its evolution, highlighting its potential to revolutionize various aspects of our lives, from healthcare to everyday conveniences. - It navigates the complex terminology surrounding AI, distinguishing between narrow and general intelligence, and the implications of superintelligence in science fiction versus reality. - The narrative extends to the pivotal role of Big Data in fueling AI advancements and the intertwined relationship between the two, underlining the vast amounts of data being generated and processed. - The exploration of machine learning and deep learning elucidates the dynamic nature of AI algorithms, with a focus on their learning and decision-making capabilities. - As AI applications extend into the public sector, considerations around governance, accountability, and the need for ethical frameworks emerge as crucial components in harnessing the benefits of AI responsibly. The ethical dimensions of AI raise profound questions about privacy, transparency, consent, discrimination, and governance. The juxtaposition of technological progress and ethical considerations forms a critical dialogue shaping the future of information privacy in the AI era. https://lnkd.in/g2PaGbtJ

OpenAI's new AI voice generator is incredibly realistic – but how will we safeguard against misuse? OpenAI's new Voice Engine is capable of mimicking human voices with startling accuracy. This tech has transformative potential for accessibility services, but it also raises serious concerns about disinformation and fraud. Key points: 15-second voice sample is all the tool needs to generate a convincing replica. Potential applications include translation, reading assistance, and aiding those who have lost the ability to speak. OpenAI acknowledges risks, plans limited rollout, and suggests changes like phasing out voice-based authentication. check out more: https://lnkd.in/gq7QpajA #OpenAI #AI #VoiceGeneration #Deepfakes

In just a year since its debut, ChatGPT has revolutionised the way we work, create and communicate. Alongside other large language models (LLMs), it's reshaping our understanding of generative AI. Despite their transformative power, widespread adoption of LLMs faces hurdles. In a recent op-ed for Lianhe Zaobao, Professor Ivor T. from A*STAR's Centre for Frontier AI (CFAR) highlights the vital balance between privacy and personalisation in LLMs and how A*STAR addresses these concerns, playing its part in paving the way for responsible and ethical AI adoption. Find out more in the article below! Learn more about CFAR at : https://lnkd.in/gwWdJPn9 Learn more about the Institute for Infocomm Research at : https://lnkd.in/gmghYVa #FacesofASTAR #ExcellentScience #AI #LLM