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Effectively monitoring and optimizing your #LLMs is extremely crucial without which you are signing up for sub-optimal outputs at best & #legal, #compliance issue at worst. Here are latest takeaways from some very interesting researches: ✅ Review LLM inputs and outputs DAILY. Don't let those sneaky #failure modes catch you off guard. ✅ Multiple agents can be used to improve the performance of LLM's. Embrace the power of ensemble learning. More agents = better performance. Scale up and watch your accuracy soar! ✅ AI can label data multiple times faster than humans. Considering messy, #unlabelled data is a massive problem. Unlock the hidden potential in your #enterprise data with purpose-built models like Refuel's LLM-2. Label data 100x faster than humans. ✅ Continuously monitor, evaluate, and fine-tune your LLMs. It's the secret sauce to building your AI moat. Remember, your perception of "good" and "bad" outputs will evolve as you interact with more data. Embrace the journey and keep refining your LLMs. #ai #llm #data

For Community Banks, Credit Unions, and SMBs, AI represents a significant opportunity to innovate and enhance operational efficiency. However, the key to successfully adopting AI lies in establishing a strong governance framework. By outsourcing AI capabilities, protecting data confidentiality, aligning AI initiatives with business strategy, and ensuring ethical practices, businesses can leverage the benefits of AI while minimizing risks.

Compliance is already a major focus for many financial organisations. However, can we expect AI to raise more compliance challenges, or resolve existing ones? While there is considerable excitement around the opportunities AI will bring, the issues around AI governance and the ethical use of the technology are still a major topics for debate. After all, in such highly regulated industries, how can you make sure AI is used in a way that doesn't compromise compliance? How do you turn AI from a potential risk, into a major opportunity? If these are questions that have come to mind recently, we are hosting a breakfast roundtable at 8am on 21st of May with Informatica to dive into these exact issues and discover how clean, reliable, accurate data can help unlock the transformative potential of AI. Fancy joining us? https://lnkd.in/gXZ58s86 #AI #FinancialServices #GenerativeAI #DataManagement #MDM #governance

[Exploring AI Governance with IBM] 📆 Tuesday May 21st @12pm CT Join Steven Eliuk, VP AI & Governance at IBM, for a 45-minute virtual talk and group discussion on the critical need for AI governance to future proof solutions and protect your investments. Steven invites you in his own words! Register using the event link below 🔗⬇️. Group discussion: Why are regulators heavily focused on AI? How do you establish a robust 'AI baseline' aligned with evolving regulations? How do you plan for Ethical Debt and model builder transparency risks? Explore the answers to these questions and ask you own! Connect & Follow us: FromTheExperts (FTE)™ - The FTE Show #AI #datagovernance #enterpriseai #innovation #management #technology #riskmanagement #aiethics #CAIO

Unlock the Potential of AI: Best Practices for Governance in SMBs and Financial Institutions Artificial Intelligence (AI) offers incredible opportunities to automate tasks, improve decision-making, and enhance customer service. But with these opportunities come risks—data security, compliance, and ethical concerns. For SMBs and financial institutions, the key to unlocking AI’s potential lies in robust AI governance. Discover how outsourcing AI capabilities, protecting data confidentiality, and aligning AI initiatives with business goals can help your organization stay ahead in the AI game. Read our latest article to learn more about the best practices in AI governance. Ready to explore AI for your business? Reach out to us with any questions. #AI #AIGovernance #SmallBusiness #FinancialInstitutions #DataSecurity #Automation #EthicalAI #BusinessStrategy #GovernanceFramework https://lnkd.in/gGSYif_p

𝐏𝐫𝐨𝐩𝐨𝐬𝐞𝐝 𝐆𝐮𝐢𝐝𝐞 𝐨𝐧 𝐒𝐲𝐧𝐭𝐡𝐞𝐭𝐢𝐜 𝐃𝐚𝐭𝐚 𝐆𝐞𝐧𝐞𝐫𝐚𝐭𝐢𝐨𝐧 The published "Proposed Guide on Synthetic Data Generation" by the PDPC (Singapore's Data Protection Authority) offers valuable insights and helps organizations understand Synthetic Data generation techniques and their potential use cases, especially in AI. It covers: 💡 Explanation of synthetic data and its benefits for AI model training and data analysis. 📊 Covers various use cases. From fraud detection, bias reduction in AI, safeguarding patient data all the way to data collaborations. 🔒 A 5-step approach to minimize re-identification risks and ensure strong data governance. 📚 Case studies and real-world applications from J.P. Morgan, Mastercard, and Johnson & Johnson. Home: https://lnkd.in/gg5WbSaS #AI #GenAI #LLM #Regulations #DataPrivacy #SyntheticData #AI #DataSecurity

🤖 AI Regulation Is Coming. Fortune 500 Companies Are Bracing for Impact ✔️ 27% cited AI regulation as a risk in recent filings with the Securities and Exchange Commission, one of the clearest signs yet of how AI rules could affect businesses. ✔️ The White House’s Executive Order on AI and the EU AI Act point to a global trend toward more comprehensive and nuanced regulation, requiring compliance developments or enhancements. ✔️ Financial services and insurance companies accustomed to working with regulators may have an easier time navigating AI laws. An insightful analysis delivered by The Wall Street Journal 💡 #DigitalTransformation #AI #GenAI #IPA #Automation #RPA #SmartAutomation #FutureOfWork #FinancialServices #Organization #Bankingsector #BusinessTransformation

🚨 The Importance of Data in AI for Financial Services 🚨 AI and machine learning models are powerful tools—but only when fueled by high-quality, well-governed data. Without proper data governance, AI results become unreliable, especially in areas like fraud detection and credit scoring. This can lead to faulty risk assessments and costly financial losses. 💡 Deloitte reports that financial services firms can reduce fraud losses by up to 25% using AI models—if the data is accurate and well-managed. Investing in strong #DataGovernance and ensuring your data is reliable is key to unlocking the full potential of AI. 🔑 How is your organization ensuring data quality for AI success? #AI #MachineLearning #FraudDetection #DataQuality #FinancialServices #Innovation #RiskManagement #DataScience

Tackling AI Bias and Ensuring Fairness We all know AI models are only as good as the data they’re trained on. But what happens when that data contains biases? 🤔 Ensuring fairness in AI is one of the biggest governance challenges we face today. From my perspective, bias mitigation should be a proactive, not reactive, part of every organisation’s AI strategy. Whether through synthetic data, continuous testing, or regular audits, organisations must be vigilant. If we don’t address bias now, we risk eroding trust and facing potential legal issues. 💡 What steps is your organisation taking to ensure fairness in AI? How do you mitigate bias? I’d love to hear your thoughts! ⬇️ #AIBias #AIethics #AIgovernance #FairnessInAI

A 2023 KPMG survey reveals that 77% of business executives expect generative AI to have the largest impact on their business, while 92% believe its implementation poses moderate to high-risk concerns. Is your team working on a generative AI project and concerned about sensitive data leakage in #GenAI tools? Want to control how your enterprise data is processed? Check Anonos Prompt Protector – our solution to protect enterprise data  in  all your Gen AI use cases: 🔵 Protect trade secrets and IP in untrusted AI environments 🔵 Unlock desired GenAI use cases Find out more: https://lnkd.in/dzjx6bkk #GenerativeAI #DataProtection #AI #EnterpriseData #AIPrivacy #UseCases #TechInnovation #PromptProtector #Anonos