The Union podcast

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100 Episodes WASTED! Fix These 4 Simple Podcast Blunders in Minutes 14:42

8 weeks yang lalu14:42

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Is your health and wellness podcast optimized for success, or are crucial oversights holding back your potential? I audited a doctor’s podcast recently and was shocked at what I found. This podcast had over 100 episodes—pretty impressive. However, the whole setup of the podcast had some brutal mistakes that I’m sure were holding this doctor back from seeing bigger results. How can optimizing your podcast's website links transform your show's reach? Are you missing out on SEO benefits that could elevate your visibility? Curious about the impact of professional collaboration on your podcast? Don't let simple mistakes hold you back. Tune in to find out how to turn your podcast into a lead-generating powerhouse! Today’s episode includes: How minor mistakes hinder podcast growth and engagement. Why directing podcast episode links on Apple, Spotify, etc to your own website is ideal. Why collaborating with professional teams can elevate your podcast impact and revenue. How maintaining high production standards enhances credibility, especially in the health and wellness space. How omitting crucial subscription links will limit your audience growth. Why owning a proper domain ensures long-term SEO benefits and authority with search engines. How missing social media links in your show notes makes it difficult for listeners to connect with you. Why understanding and avoiding common mistakes ensures maximum ROI from podcasting efforts. Are you pouring your heart into your podcast but still not seeing the growth you deserve? Download our free guide to unlock your podcast’s full potential and expand your impact: https://eastcoaststudio.com/5mistakes Our LinkedIn: https://www.linkedin.com/company/eastcoaststudio/ Our Instagram: https://www.instagram.com/ecpodcaststudio/…

The Union

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The Union is about the intersection between people, technology, and artificial intelligence. Get ready to be inspired and challenged as we ask questions, uncover insights, and share inspiring stories about digital ecosystems and automation.

59 episode

#Tech #Automation #Hyperautomation #Machine Learning #Artificial Intelligence #Krista #Aipaas #Ipaas #Orchestral #Conversational AI

The Union

updated sekitar setahun yang lalu

Beranda serial•Feed

59 episode

#Tech #Automation #Hyperautomation #Machine Learning #Artificial Intelligence #Krista #Aipaas #Ipaas #Orchestral #Conversational AI

Semua episode

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You DO Want AI Training on Your Data 36:08

5 weeks yang lalu36:08

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Most business leaders say they don’t want AI training on their data—but what they really mean is they don’t want to lose control. In this episode, we explain why the only way AI delivers real value is by learning your business: your documents, your processes, your language, and your priorities. We break down the difference between exposing data and improving outcomes, and why generic AI won't scale. You’ll hear how AI that understands your workflows can anticipate needs, suggest actions, and drive results—without writing endless prompts or building from scratch. If you’re still treating AI like a tool that needs babysitting, it’s time to rethink the strategy. Topics covered: Why blocking AI from learning limits your ROI The risks of generic intelligence in enterprise settings How to train AI like you train your people Real-world examples of AI reinforcing strategy by learning context Learn how to make AI work for your business—starting with your data. Listen now and subscribe for more episodes on making AI work in the enterprise. #AI #EnterpriseAI #Automation #BusinessIntelligence #AgenticPlatforms #AITraining #LLM #ProcessAutomation #DigitalTransformation More at krista.ai…

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Elevate Recorded Meetings to Enterprise Knowledge 23:54

8 weeks yang lalu23:54

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Tired of meeting recordings that lead nowhere? We explore why summaries and tasks aren’t enough for operations executives seeking real enterprise knowledge. It’s more than recordings—it’s about weaving in emails, Teams chats, CRM data, and documents for a complete picture. Learn how orchestration transforms these insights into automated workflows, boosting efficiency and outcomes. From tackling customer churn with full context to unifying data with Krista, this episode shows how to turn meetings into a strategic asset. Key Takeaways: Recordings alone don’t cut it—context is king Enterprise data (emails, chats, CRM) powers smarter decisions Orchestration automates action from unified knowledge Want to elevate your meetings? Check out Krista’s conversation agents, AI-led knowledge management, and orchestration at https://krista.ai/solutions/conversation-agent/ . Subscribe for more tips on turning data into results! #EnterpriseKnowledge #MeetingAutomation #Orchestration #AI #BusinessStrategy More at krista.ai…

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MCP – Hype, Risk, and Enterprise Reality 27:58

9 weeks yang lalu27:58

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In this episode, we break down the Model Context Protocol (MCP) — what it is, how it works, and why it’s generating so much hype in the AI world. But beyond the headlines, we explore the real enterprise implications. Is MCP secure? Can it be trusted to connect large language models to your internal systems? And what risks are developers and businesses ignoring in the rush to experiment? We draw parallels to past tech missteps (remember ActiveX?) and share firsthand insights from our own use of MCP tools. If you're leading AI strategy, running IT, or just trying to understand where this is all headed — this is the conversation you don’t want to miss. 👉 Subscribe for more deep dives on AI, automation, and enterprise tech. #MCP #AIintegration #EnterpriseAI #LLM More at krista.ai…

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AI Agents—What Lies Beneath 27:16

11 weeks yang lalu27:16

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Should AI agents really cost $20,000 per month? In this episode, we break down OpenAI’s reported pricing for specialized AI agents and why many companies will try (and fail) to build their own. 🔍 What’s Inside: ✅ The hidden costs of DIY AI—why it’s not just about training a model ✅ Why most AI agents fail without orchestration, security, and integration ✅ How businesses get trapped in an endless cycle of building, fixing, and rebuilding ✅ Why a platform approach is the key to deploying AI agents faster and at lower costs 💡 Instead of sinking millions into fragmented AI projects, companies need a smarter way to assemble, orchestrate, and scale AI agents. Krista is that platform. 📌 Subscribe for more insights on AI and automation! 📩 Want to learn more? Visit Krista.ai for smarter AI deployment. #AI #Automation #ArtificialIntelligence #AIAgents #BusinessTech More at krista.ai…

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Your TeenAGENTer 37:01

12 weeks yang lalu37:01

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Are AI agents the future of business—or just overhyped digital teenagers? In this episode, we break down why today’s AI agents promise big but need serious guidance to deliver. Think of them as teens on their first job: full of potential, but not ready to run the show. We explore: - The truth behind slick AI demos (spoiler: they’re not autonomous yet) - How AI can boost your business today—as a helper, not a boss - Why a solid platform is key to keeping AI in line - A quick-start checklist to make AI work for YOU Perfect for business leaders who want practical AI wins without the hype. Watch now to learn how to raise your AI agents into responsible business partners—and skip the growing pains! Subscribe for more no-BS takes on AI in business. Connect with Krista: Ready for AI that actually works? Visit https://krista.ai/ More at krista.ai…

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AI Agents—Security Asset or Hidden Risk? 38:40

16 weeks yang lalu38:40

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Are AI agents a security risk or a security enhancement? In this episode, John Michelsen breaks down the biggest concerns enterprises have about AI-driven automation. We discuss data privacy, internal and external threats, compliance, and how AI platforms like Krista can actually improve security posture. If you're deploying AI in your organization, this conversation is a must-listen. 🔹 Topics Covered: ✅ The biggest security risks with AI agents ✅ How to ensure compliance with regulations like GDPR & SOC 2 ✅ The real reason some AI platforms are "free" (and why you should be cautious) ✅ How AI can reduce human error and insider threats More at krista.ai…

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Chasing Agents 23:11

17 weeks yang lalu23:11

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The explosion of AI agents is transforming enterprise workflows, but it’s not without challenges. From integration hurdles to operational silos, businesses struggle to navigate the crowded ecosystem of hundreds and eventually thousands of agents. In this episode of The Union Podcast, Scott and Chris discuss risks of disconnected tools and how a platform approach like Krista’s agentic platform ensures seamless automation, scalability, and efficiency. Learn how to avoid repeating past mistakes with standalone apps and discover why enterprises are embracing platforms to future-proof their AI investments. If you’re exploring AI for your business, this episode is your essential guide to understanding the big picture. More at krista.ai…

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You Don't Have to Know Your Future 52:11

20 weeks yang lalu52:11

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In a world where technology evolves faster than ever, you don’t have to know your exact future to thrive—you just need to be on the path to it. This video explores how AI is reshaping industries, redefining work, and accelerating innovation in ways we couldn’t have imagined just a few years ago. John Michelsen shares insights into the rapid advancements of AI, emphasizing that while you can’t predict every step, embracing change and adopting AI iteratively are essential for staying competitive. Learn why small, practical steps can help you build the muscle for rapid technology adoption, and how leaders and organizations can align to create a culture of continuous learning and growth. From AI’s potential to elevate human roles to the pitfalls of waiting too long, this discussion highlights why it’s not about knowing the future—it’s about being prepared to meet it. Key Takeaways: Why you don’t need to know your future to start leveraging AI. How leadership alignment accelerates AI adoption and innovation. The importance of starting small, scaling fast, and building agility in your organization. Real-world examples of businesses turning AI into a competitive advantage. The future isn’t about replacing humans—it’s about unlocking their potential. Watch now to learn how to lead with confidence and thrive in an AI-driven world. #AI #FutureOfWork #Innovation #Leadership More at krista.ai…

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Mastering AI Outputs: A Review of Prompt Engineering Guides 24:33

23 weeks yang lalu24:33

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In this episode of The Union Podcast, Scott King and Chris Kraus review AI prompting guides from Microsoft, OpenAI, and Google. They discuss the challenges of crafting effective prompts, the limitations of teaching prompt engineering to everyone, and why automation should take center stage for business users. Highlights include: ✅ The differences between Google’s business-focused approach and Microsoft/OpenAI’s developer-centric guides. ✅ Privacy concerns and the complexities of integrating tools like Google Workspace or Azure. ✅ Why prompt engineering is both an art and a science—and not always the best use of time. ✅ How automation can eliminate repetitive tasks, improve customer support, and free your team to focus on what matters most. Join the conversation and learn how to navigate the world of generative AI without wasting time on unnecessary complexities. 📎 Links to prompting guides mentioned in the video: Microsoft Prompting Guide OpenAI Prompting Guide Google Gemini Prompting Guide More at krista.ai…

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You Can Buy Half the AI You Need; the Other Half is Unique to You 30:30

25 weeks yang lalu30:30

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AI is no longer optional—it’s a competitive necessity. But what does it take to implement AI effectively for your business? In this episode, we break down why half of the AI you need is readily available in generative models, but the other half must be tailored to your unique processes, data, and goals. Join Scott King, Chris Kraus, and John Michelsen as they explore the challenges of traditional machine learning, the limitations of generative AI, and how Krista’s automated machine learning framework builds machine learning for you. Learn how Krista enables businesses to deploy AI quickly and cost-effectively without needing expensive data science teams. Discover how to identify high-ROI processes, streamline operations, and let machines handle repetitive tasks, so your team can focus on high-value work. Ready to get started? Visit Krista.ai to learn more about building AI solutions tailored to your business. #AI #Automation #MachineLearning #GenerativeAI #KristaAI #DigitalTransformation #BusinessInnovation More at krista.ai…

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What is an Agentic Platform, and Its Essential Capabilities? 24:29

27 weeks yang lalu24:29

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Agentic platforms are essential for AI-driven automation. Join John Michelsen and Chris Kraus as they discuss how agentic platforms empower organizations by enabling autonomous AI agents to perform complex tasks and make intelligent decisions. Discover the key capabilities that set agentic AI apart, including low-code configuration, robust security guardrails, and seamless multi-channel engagement. If you're looking to transform your business operations with cutting-edge AI, this conversation will show you how agentic platforms can deliver real organizational value. More at krista.ai…

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There's No I in LLM 27:11

28 weeks yang lalu27:11

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Are large language models (LLMs) like ChatGPT truly automating work? John Michelsen unpacks the misconception that LLMs alone can drive business transformation. Join us as Michelsen shares real-world examples, revealing why relying solely on LLMs leads to slow, manual workflows. Learn how true automation requires orchestration across systems and processes, integrating AI into a seamless workflow to deliver meaningful outcomes at machine speed. Tune in to understand how to maximize the power of AI and avoid the pitfalls of superficial automation. More at krista.ai…

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Document Understanding and the Power of Entity Extraction 27:54

30 weeks yang lalu27:54

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In this episode, we John Michelsen and Chris Kraus explain the limitations of traditional document processing methods like Intelligent Document Processing (IDP) and Optical Character Recognition (OCR) and how they struggle with unstructured data and unforeseen questions. Listen in as they discuss how flexible, context-driven Natural Language Processing (NLP) is transforming document understanding, enabling businesses to extract information accurately and efficiently—even in complex scenarios. They detail the benefits of NLP techniques such as lexical matching, entity extraction, and context-aware data sorting, which help technology leaders move beyond rigid rules and regular expressions. Discover how NLP allows organizations to identify essential data points, streamline workflows, and reduce human error, all while improving the accuracy of information extraction. Learn how Krista integrates these NLP advancements to simplify document processing, freeing your team from complex rules and enabling faster, more reliable decision-making. Ready to take your document processing to the next level? Watch now to see how NLP is revolutionizing data extraction with the power of context. More at krista.ai…

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Moving Beyond Traditional IDP and OCR to AI-Driven Solutions 30:05

33 weeks yang lalu30:05

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AI is redefining document processing, moving beyond the limitations of traditional methods like Intelligent Document Processing (IDP) and Optical Character Recognition (OCR). As business demands become more complex, old solutions fall short—especially when dealing with unstructured content like diverse invoice formats and sales orders. Discover how AI's advanced capabilities can adapt to varying document types, improve accuracy over time, and significantly reduce manual intervention. In this episode, John Michelsen shares real-world insights, including a case study from a European healthcare organization that improved its document processing accuracy from 65% to 82.5% by implementing AI. Learn why businesses must act now to adopt these technologies, streamline workflows, and stay ahead of the competition. This episode offers actionable steps for using AI to automate repetitive tasks, enhance data extraction, and unlock new growth opportunities. Like, subscribe, and share to stay informed about how AI is transforming the future of business operations. More at krista.ai…

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How AI Delivers Real-Time Answers to Unforeseen Questions 38:14

34 weeks yang lalu38:14

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In this episode, we explain how AI-powered solutions like Krista are transforming the way businesses answer unforeseen questions. Join us as we explore the challenges of handling unknown inquiries in complex workflows, the role of real-time data, and how AI can integrate dynamic systems to provide instant, accurate responses. We also discuss use cases for customer support, sales, and standard operating procedures, and provide actionable steps for implementing AI to boost efficiency and streamline operations. Whether you’re looking to fill knowledge gaps or enhance decision-making, this episode offers valuable insights on how AI can drive real business value. More at krista.ai…

The Union

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How AI is Improving Document Understanding 31:51

35 weeks yang lalu31:51

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In this episode of The Union Podcast , we discuss how AI is revolutionizing document understanding and business operations. Join hosts Scott King, Chris Kraus, and John Michelsen as they explore real-world AI use cases that help businesses extract insights, automate workflows, and manage unstructured data more effectively. They discuss: Three key document understanding use cases that can transform how your organization manages data Real-world examples of AI speeding up invoice processing and handling complex documents The role of NLP (Natural Language Processing) in automating workflows and improving efficiency Whether you’re looking to streamline operations, reduce manual work, or better leverage the data within your organization, this episode provides actionable insights to get started with AI-driven document understanding. 🔔 Subscribe to The Union Podcast for more episodes on AI and business technology! More at krista.ai…

The Union

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AI and HR: Insights from SHRM 24 that Every HR Professional Needs to Know 20:35

47 weeks yang lalu20:35

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Michael Haske, CEO of Krista, shares his experiences and insights from attending the SHRM 24 conference. The event, which brought together HR professionals from around the globe, focused on major transformations in the workplace, particularly the integration of AI, the skills gap, and the need for enhanced civility. AI Integration in HR: A Hot Topic One of the central themes of the SHRM 24 conference was the role of artificial intelligence (AI) in transforming HR functions. Michael highlighted the enthusiasm and curiosity among attendees regarding AI's potential to revolutionize various HR processes. Popular use cases discussed at the conference included AI-driven talent acquisition, employee engagement, and predictive analytics to foresee employee turnover. The overarching message was clear: AI can automate repetitive tasks, freeing HR professionals to focus on strategic initiatives that enhance the employee experience. The Evolving Role of HR Professionals Traditionally, HR roles have not been heavily tech-centric. However, the integration of AI into HR functions is changing this dynamic. Michael noted that HR professionals now need to become experts in AI technologies and be involved in every AI-related conversation, especially those impacting people. Effective AI integration in HR involves using AI to enhance roles, streamline processes, and make data-driven decisions. Standardized, validated approaches to assessing and matching skills with job opportunities are also essential. SHRM and Krista: A Strategic Partnership A highlight of the conference was the announcement of a strategic partnership between SHRM and Krista to deploy AI solutions for SHRM members. Michael provided insights into this partnership, explaining how Krista was chosen as the AI vendor to build SHRM's member-facing AI engine. This AI tool aims to leverage SHRM's extensive knowledge base, accumulated over 75 years, to provide members with advanced capabilities such as document analysis, understanding, comparison, and drafting. The partnership is set to empower SHRM members with AI-driven superpowers, enhancing their efficiency and effectiveness in various HR tasks. Key Takeaways for HR Professionals The SHRM 24 conference provided insightful knowledge for HR professionals. Michael Haske emphasized several key takeaways: Embrace AI : HR professionals should not shy away from AI but instead embrace it as a tool to enhance their roles and improve organizational efficiency. Focus on Upskilling : With rapid technological advancements, continuous learning and development are crucial. HR professionals should prioritize upskilling and reskilling to stay relevant. Be at the Forefront : HR should be involved in all AI-related decisions within the organization, ensuring that AI implementations are human-centric and aligned with organizational goals. The SHRM 24 conference highlighted the transformative potential of AI in HR and the importance of addressing the skills gap. With strategic partnerships like that of SHRM and Krista, the future of HR looks promising, with AI playing a central role in driving efficiency and innovation. As Michael aptly put it, "It's time for HR to have a seat at the table on an enterprise-wide basis when it comes to AI decision-making." More at krista.ai…

The Union

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The Art of the Possible: Practical AI and Automation Use Cases for HR 26:52

48 weeks yang lalu26:52

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Human resources are undergoing a significant transformation, thanks to advancements in AI and automation. Traditionally manual HR processes work, but many HR professionals wonder, "How can AI and automation technologies be applied to my everyday challenges?" Chris Kraus and I discuss several HR-specific AI and automation applications, offering practical insights into real-world use cases. Challenge: Navigating Complex Policies and Regulations How AI Can Help: AI-powered tools like Krista act as knowledgeable assistants, instantly providing accurate answers to employee questions about your company policies, benefits, and regulations. This not only saves time for HR staff but also ensures consistency and accuracy in responses. Employee Self-Service: Empowering Employees with Information How AI Can Help: AI-powered self-service portals allow employees to quickly access the information they need providing accurate answers and guiding them through complex processes like leave requests or benefit enrollment. This empowers employees and frees up HR staff to focus on strategic initiatives. Candidate Experience: Attracting and Hiring Top Talent How AI Can Help: AI-powered tools can automate job postings, applicant screening, and interview scheduling, making it easier for candidates to apply and for HR or local management to identify the best fit. Additionally, AI can help tailor the candidate experience based on individual preferences and communication channels like SMS or omnichannel. Recruiting and Tracking: Streamlining the Hiring Process How AI Can Help: Krista orchestrates processes across different systems, automating tasks like resume screening, interview scheduling, and progress tracking. Having software run the process instead of people ensures a smooth and efficient hiring process rather than manually keeping track of all of the steps. Employee Onboarding and Offboarding: Ensuring Smooth Transitions How AI Can Help: Krista automates onboarding and offboarding workflows, ensuring that tasks like systems access, equipment setup, and paperwork are automated and accounted for. This improves the onboarding experience and reduces the risk of data breaches when employees leave. Process Orchestration: Streamlining HR Operations How AI Can Help: Krista orchestrates complex HR processes, combining multiple tasks into a streamlined workflow. For example, an employee can request vacation, and Krista automatically handles approvals, calendar updates, and notifications. This improves efficiency, reduces errors, and frees up HR staff for more strategic work. Conclusion AI and automation can alleviate many common bottlenecks in HR processes. Leveraging tools like Krista can help HR professionals streamline operations, enhance the employee experience, and focus on strategic initiatives that drive business growth. Embracing AI is not just about efficiency; it's about empowering your workforce and adapting to the evolving landscape of work. As AI continues to advance, HR departments that leverage these technologies will be well-positioned to lead their organizations into the future. Ready to explore how AI can transform your HR processes? Contact us to discover the art of the possible for your organization. More at krista.ai…

The Union

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Protecting Your Company Data When Using LLMs 18:43

1 year yang lalu18:43

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While LLMs offer undeniable benefits, integrating them into the workplace poses significant risks to company data. Here’s why: Data Leakage: It’s easy for employees to paste confidential company information into LLM prompts inadvertently. This could include anything an employee can access: financial reports, trade secrets, customer data in text, documents, or even data in spreadsheets. Ownership Concerns: When company data is used to create content using LLMs, there’s a risk of losing ownership rights or control over intellectual property. Who owns the content created by LLMs? The company that provides the data or the LLM provider? Compliance Issues: The unregulated use of LLMs can lead to costly violations of data protection regulations like GDPR, CCPA, and others. Companies have a legal obligation to protect sensitive customer and employee data, and a breach caused by mishandling information within an LLM could have serious repercussions. Three LLM Usage Scenarios & Why You Should Be Worried The privacy and data security risks associated with LLMs vary depending on how your employees access and utilize the models and services. Three of the most common scenarios and the specific concerns they raise include: Scenario 1: Free GenAI/LLM Accounts Free and readily accessible GenAI tools and LLM interfaces are great at helping employees jumpstart content or edit existing text. However, this ease of use comes at a steep price. When employees turn to these free options for work-related tasks, often for convenience or out of unfamiliarity with company policy, sensitive data is put at extreme risk. Data Leakage at its Worst: Free LLM accounts offer minimal to no safeguards for your data. Anything pasted into these interfaces, from client emails to financial projections, is essentially out of your control. Training Future Models: Most alarmingly, many free LLM providers openly state they use user inputs to train their models. This means your confidential company information could become part of the knowledge base of a publicly accessible AI, potentially exposed to competitors or malicious actors. Scenario 2: Paid Enterprise LLM Accounts While paid enterprise accounts come with improved terms of service and stronger data protection promises, they do not guarantee absolute security. Risk of Leakage Persists: Even with contractual assurances, there remains a risk that your data could be unintentionally exposed due to human error or vulnerabilities in the provider’s systems. Training Concerns: Although many providers commit to not training their models on your data, there’s often no way to verify this claim independently. Your sensitive information could still be used to enhance the capabilities of LLMs, potentially benefiting your competitors. Scenario 3: Hosting Your Own LLMs This scenario represents the most security and control. By hosting open-source LLMs within a secure Krista tenant, you maintain absolute ownership and oversight of your data. No Data Leaves Your Account: Your company’s information never interacts with external LLM providers, eliminating the risk of data leakage or unauthorized use. Full Control: You have complete authority over how the LLM is configured, trained, and used, ensuring that it aligns perfectly with your organization’s specific security and compliance requirements. Peace of Mind: This approach provides the highest reassurance that your data remains confidential, secure, and entirely within your control. Implementing this technology within your organization is critical, and the risks associated with how you and your employees interact with LLMs vary depending on the use case. More at krista.ai…

The Union

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Understanding LLM Jailbreaking: How to Protect Your Generative AI Applications 23:03

1 year yang lalu23:03

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Generative AI, with its ability to produce human-quality text, translate languages, and write different kinds of creative content, is changing the way people work. But just like any powerful technology, it's not without its vulnerabilities. In this podcast, we explore a specific threat—LLM jailbreaking—and offer guidance on how to protect your generative AI applications. What is LLM Jailbreaking? LLM vandalism refers to manipulating large language models (LLMs) to behave in unintended or harmful ways. These attacks can range from stealing the underlying model itself to injecting malicious prompts that trick the LLM into revealing sensitive information or generating harmful outputs. More at krista.ai…

The Union

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Assembling AI: The Illusion of Simplicity 30:35

1 year yang lalu30:35

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Building your own GenAI system and app requires a deep understanding of the rapidly evolving technology and the complexities involved. It is not as simple as building traditional web or mobile apps. GenAI is constantly changing, with new models and updates being released frequently. This means that the frameworks, behaviors, and APIs used to interact with the models can change rapidly, requiring constant maintenance and upgrades. Additionally, the process of ingesting and understanding data, especially unstructured data like images and PDFs, is more complex than it seems. Assuming that maintaining the infrastructure and quality of GenAI apps is similar to your existing projects can lead to expensive costs and time-consuming maintenance cycles. Using a platform like Krista can provide the necessary tools and expertise to handle these complexities and allow businesses to focus on solving their specific business problems instead of maintaining a custom-built solution. Takeaways · Building your own GenAI system and app is not as simple as building traditional web or mobile apps. · GenAI technology is rapidly evolving, with new models and updates being released frequently. · The frameworks and APIs used to interact with the models can change rapidly, requiring constant maintenance and upgrades. · Ingesting and understanding unstructured data, like images and PDFs, is more complex than it seems. · Using a platform like Krista can provide the necessary tools and expertise to handle the complexities of building GenAI apps and automations. More at krista.ai…

The Union

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Unpacking the Shared Assessments Summit: How AI and Automation Can Revolutionize Risk Management 43:17

1 year yang lalu43:17

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Key Takeaways AI skepticism remains a hurdle: While interest in AI is high, doubts about accuracy, safety, and trust persist. This emphasizes the need for accurate, transparent, explainable AI models with validation and governance. Focus on time savings for overworked teams: A major draw of AI is automating repetitive tasks and finding pain points. This frees up Third Party Risk Management (TPRM) teams to reduce friction with the business and tackle the increasing burden of assessments, including Nth party risk. Contract risk: a critical area for AI application: AI's ability to analyze and extract data from complex contracts fills a significant gap, helping manage risks often overlooked by traditional risk management programs. Earning trust in AI is key: Risk management professionals crave solutions that are accurate and reliable. AI adoption depends on providing transparency, demonstrating explainability, and building confidence through meticulous validation. Strategic empowerment: AI isn't about replacing risk managers but enabling them to make proactive, informed decisions about risk. This transforms the profession and opens the door to embracing calculated risks for the organization's success. The journey starts with the basics: Organizations often need help finding where to begin. Understanding how AI automates assessments and pinpointing specific pain points is the first step toward targeted solutions. The Shared Assessments Summit, a leading risk management conference, brought together experts to discuss the latest trends and best practices. Sam Abadir, a risk management and governance, risk & compliance (GRC) solutions specialist, and Jason Eubanks, a risk consulting manager, were among those in attendance. In this article, we explore key takeaways from the conference, focusing on how artificial intelligence (AI) and automation can transform your approach to risk management. We explain how AI-powered tools, like Krista, can automate repetitive tasks, improve knowledge accessibility, and shift the focus of risk management professionals to strategic activities. We will also explore AI's potential to unlock new ways of approaching risk. By using AI and automation, risk management professionals can streamline processes, improve efficiency, and contribute more effectively to the success of their organizations. More at krista.ai…

The Union

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This is Your AI Copilot Speaking 24:16

1 year yang lalu24:16

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AI copilots are generative AI engines that assist users in point tasks such as writing emails, summarizing customer cases, and generating code. AI copilots can be used in a variety of business functions, including marketing, customer service, and software development. However, AI copilots assist one person with one task at a time. They improve personal productivity but are not effective at transforming business processes or using more powerful AI solutions like predictors and categorizers. Takeaways Definition and Scope of AI Copilots AI copilots are identified as tools based on generative AI technology, designed to assist in various tasks by generating or completing content based on given inputs. They are differentiated from other AI applications like predictors or categorizers. Applications and Benefits AI copilots can assist in coding by generating initial code drafts, helping to speed up the development process, though the generated code may require optimization for efficiency. In customer service, AI copilots can help draft email responses or summarize customer interactions inside of a single application. In legal applications, AI copilots can summarize meetings or draft documents, though it raises concerns about the skill development of junior lawyers. Challenges and Considerations The proliferation of AI copilots across different platforms and tasks (e.g., coding, customer service, email management) could lead to challenges in managing, governing, and integrating these tools effectively within organizations. There’s a risk of over-reliance on AI, potentially reducing human oversight and quality control, especially in critical tasks. There are concerns about AI’s potential for misuse, such as generating inappropriate or harmful content, though it was noted that current applications are not designed to act autonomously in such a manner. Perspectives on the Future of Work with AI Copilots The inevitable increase in the use of AI copilots across various job functions emphasizes the need for careful management to avoid overwhelming users. The potential for AI copilots to significantly reduce routine tasks and allow professionals to focus on more complex and creative aspects of their work was seen as a positive development. Adaptation and Learning A learning curve is associated with effectively utilizing AI copilots, including understanding how to prompt and interact with these tools for optimal results. Choosing the right AI tool for specific tasks is important to prevent inefficiency and confusion. More at krista.ai…

The Union

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What TPRM Professionals Think About AI 33:02

1 year yang lalu33:02

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In Third-Party Risk Management (TPRM), adopting Artificial Intelligence (AI) presents both an opportunity and a dilemma. One, if you should use AI , and second, for what tasks . I talked with TPRM experts Sam Abadir and Tom Garrubba about responses from a recent poll among approximately 1,000 risk management professionals. We reviewed the questions and responses and offered insights and opinions based on the results. More at krista.ai…

The Union

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Enhancing AI Precision with Retrieval Augmented Generation 28:05

1 year yang lalu28:05

28:05

Retrieval augmented generation (RAG) is revolutionizing AI by infusing language models with timely and relevant external data. This technique is pivotal in delivering not just intelligent but informed AI responses. In this podcast, Chris and I explain what RAG is, how it functions, its impact on AI’s performance, and the challenges it helps overcome. Key Takeaways Retrieval augmented generation works by integrating large language models (LLM) with real-time data retrieval to provide accurate, contextually relevant responses, which reduces computational and financial costs associated with inaccurate responses RAG fills knowledge gaps by using vector databases for better information retrieval and regularly updating knowledge libraries to maintain response accuracy, addressing the limitations of static data in AI models. The practical application of domain-specific augmented generation use in industries like retail and e-commerce, telecommunications, and manufacturing demonstrates improved service delivery. Unlocking LLM Potential with Retrieval Augmented Generation RAG is a method that significantly enhances the capabilities of LLMs. RAG functions as a prompt engineering technique, enriching the output of LLMs by integrating an information retrieval component into your systems of record and data sources like CRM, HR, and external knowledge bases. Doing so provides AI systems with timely, accurate, and domain-specific data - a marked improvement over conventional large language models that often operate with static or outdated training data. This improves the LLM’s ability to generate accurate responses and limit hallucinations. More at krista.ai…

The Union

1
2024 AI Outlook: What Business Leaders Need to Know 24:09

1 year yang lalu24:09

24:09

2024 AI Predictions What does the internet say about AI? What do the AI pundits think will happen? We were curious, too. In our quest to understand what was being predicted for AI in 2024, we reviewed a set of diverse sources to analyze and merge a myriad of predictions to provide a consolidated overview. This article cuts through the noise, delivering a straightforward perspective on AI trends. We've factored in common predictions and outliers, providing you with a balanced view of who predicts what when it comes to AI. The Sources Behind AI Predictions In our review of AI predictions, each source offered distinct insights reflecting their unique perspectives. I've linked each of the sources from Adobe, Forrester, Gartner, IBM, IDC, LA Times, NVIDIA, PWC, TechCrunch, and TechTarget that we reviewed and categorized. IBM emphasized predictions at an enterprise level, focusing on how AI would reshape business operations and strategies. Gartner and Forrester focused on the impact of AI on individual task levels, highlighting how AI could enhance personal efficiency and workplace dynamics. IDC provided a more IT-centric view, exploring how AI would aid IT professionals in their roles, with an emphasis on shifting outcomes and the emergence of conversations as the standard user interface. LA Times, PWC, and TechTarget brought attention to the coming of age of open-source AI, stressing the importance of ethical AI and the need for transparency in AI operations. NVIDIA presented a broader spectrum of insights, reflecting the diversity of opinions from the 17 experts they consulted, covering a wide range of AI applications and implications across various sectors and disciplines. The AI Landscape - A Consensus View Across the board, experts agree that generative AI is set to skyrocket this year, bolstering productivity and spurring innovation. Businesses are bound to see a significant shift towards multimodal AI, which invites a more natural interaction with technology using voice, images, and text. As these technologies advance, tight AI regulation is expected to emerge, guiding their integration into the market. The consensus is clear — AI is not just a fleeting trend but an innovation that is fueling economic growth and investments. Outliers - Unique Predictions and Their Significance Not all forecasts follow a common thread. Gartner casts a spotlight on AI's role as an emerging economic indicator of national power by 2027. Meanwhile, TechCrunch raises concerns about AI's potential misuse in the 2024 elections. NVIDIA equates the race for AI supremacy to a new space race. These outlier predictions, while not widely echoed, provide insights for businesses to consider, presenting both opportunities and warnings. More at krista.ai…

The Union

1
The Future of TPRM 41:48

1 year yang lalu41:48

41:48

Most third-party risk lifecycles adhere to a similar pattern: planning, due diligence, contract negotiations, ongoing monitoring, and termination. However, the management and responsibility of these processes differ significantly across organizations. Traditionally, the information security department carried this burden, but recent events like Covid, regional wars, political changes, and socially-focused laws have broadened organizations' risk perception beyond just IT. They now include geographical, reputational, concentration, and compliance risks. Different departments, leveraging their unique expertise, now seek information from third parties to manage diverse risk types. Third-party risk management expert, Tom Garrubba, practical advice to assist companies in tailoring third-party risk management activities to their size, risk profile, and risk management necessities. Regardless of where the organization situates third-party risk management, the ultimate responsibility rests with the third-party risk manager and the business owner. They must identify the necessities and required documentation for each vendor, enabling a thorough assessment and due diligence or ongoing monitoring. The assessment process presents challenges for both the vendor and the risk manager, often requiring over 40 hours to complete and validate. Midsize companies dealing with dozens to hundreds of third parties quickly face the reality of these complications. Additionally, vendors often feel overwhelmed with assessment requests from their many customers and may instead issue a "customer assurance packet" containing broad information sets for you to sift through to identify potential risks. Third-party risk management is essential, even for industries not legally required to do so. Those lacking a robust strategy and supporting technology risk overloading their vendors with assessments and distracting internal teams. Furthermore, if you operate in a regulated industry, expect your strategy and technology to face scrutiny eventually. More at krista.ai…

The Union

1
AI Fear and Fear of Missing Out 17:32

1 year yang lalu17:32

17:32

Embracing technological change via automation and artificial intelligence (AI) is no longer optional; it's a necessity. Delaying AI use in your company can hinder progress and put you farther behind your competitors. However, embracing AI adoption is not without its apprehensions. Your concerns about unknown outcomes and hallucinations are valid but are easily overcome with the right security, accuracy, performance, and cost strategies to limit your risk and exposure. Integrating AI is about continual progress over perfection, focusing on the transformative power of automated processes, rather than the pursuit of unattainable perfection. We will show you how to overcome AI fear, build confidence, choose the right process for AI and guide you toward the first steps for adopting AI. More at krista.ai…

The Union

1
Generative AI for Agile Knowledge Management 48:11

2 years yang lalu48:11

48:11

Generative AI (GenAI) is influencing nearly all processes in our businesses and none so much as knowledge management. Employees want a better experience and they have found by already experimenting with GenAI; ask a question, and get an answer. But, the answers and the knowledge delivered to them via the public interfaces aren't always correct. Our guest speaker Julie Mohr is a principal analyst at Forrester covering IT service management and enterprise service management. Julie shares how knowledge management practices are evolving and how GenAI is accelerating change. Julie spotlights the shift from old-school waterfall techniques to agile knowledge management and describes how GenAI is set to overhaul how companies capture, update, and apply their knowledge. More at krista.ai…

The Union

1
GenAI is Great, But... 24:50

2 years yang lalu24:50

24:50

Generative AI vs Predictors and Categorizers Generative AI is hot and has ignited our imaginations. However, it's important to highlight that there are other AI capabilities, like predictors and categorizers, that can produce significantly more value, particularly in enterprise settings. But, these capabilities aren't new; they have been around for quite some time and have proven their worth in many business applications. Predictors, for instance, are excellent for forecasting numbers or categories based on historical data, while categorizers excel in sorting data into predefined groups. Both play a vital role in enhancing efficiency and decision-making in businesses, demonstrating that while generative AI is indeed captivating, it is not the most valuable AI player. Key Takeaways: Generative AI vs Other AI Models : While generative AI has garnered a lot of attention and hype, there are other AI models, such as predictors and categorizers, that can offer substantial value in enterprise settings. Practical Applications of Predictors and Categorizers : Predictors : Used for predicting numbers or categories based on historical data. Categorizers : Used for categorizing data into predefined categories. Bridging the Gap for Business Users : There is a need to make AI more accessible to business users, not just data scientists. Data Quality and Availability : Successful implementation of AI models requires good quality data. Building Trust in AI Models : For AI models to be successfully adopted, users need to trust their predictions and recommendations. Starting with AI in Business : Businesses looking to implement AI should start by identifying processes that can benefit from predictors and categorizers. Questions for Reflection: Identifying Opportunities for AI : In what areas of your business could predictors and categorizers be applied to improve efficiency or decision-making? Building Trust in AI : How can you involve business users in the AI implementation process to build trust and ensure the accuracy of the AI models? Data Quality and Preparation : What steps can you take to ensure that you have access to clean and relevant data for training your AI models? More at krista.ai…

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