The Union

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 Jailbrea...

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 c...

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...

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 transfo...

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 b...

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...

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. W...

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...

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...

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 ana...

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 w...

Explore how AI orchestration is revolutionizing Third-Party Risk Management (TPRM). Learn how combining AI technologies, like document understanding, NLP, and generative AI, with process orchestration improves risk management practices. Discover how AI can read vendor documentation, complete assessments, identify risk outliers, and provide comprehensive data processing in minutes rather than weeks...

The Pressing Demand for Generative AI in Enterprise Generative AI (GenAI) is promising unparalleled advancements and efficiencies for many types of use cases.  Boards and CEOs continue to experiment with the technology and imagine how it can improve workforces and increase throughput. The Wall Street Journal highlights how CEOs are pressuring CIOs and technology leaders to urgently install generat...

In an era where Artificial Intelligence (AI) is transforming business processes, companies face a significant dilemma: whether to hire expensive AI specialists or pivot towards more cost-effective and scalable options. With industry giants like Netflix offering compensation packages as high as $900,000 for AI Product Managers, the perceived value of AI expertise is high. However, smaller companies...

Different LLMs have varying strengths and weaknesses. Understanding the strengths and weaknesses of different language models is crucial, as it allows you to select the most efficient tool for your specific needs. When you evaluate and test various LLMs, you are essentially comparing their ability to answer different types of questions, their performance, and their cost-effectiveness. This compari...

The prompt engineer. Do you need one? Can you train your people to generate prompts? Can this be automated? Well, it depends. LLMs, like BARD, OpenAI GPT-3.5 and 4, Llama, or Flan, require a diligent and persistent approach to testing and refining prompts. Their variable performance for different use cases reveals the critical need for consistent testing and evaluation to achieve accurate results....

To effectively limit LLM hallucinations, you need to treat LLMs more like journalists instead of storytellers. Journalists weave stories using factual, real-time information. Similarly, you need to feed your LLMs with real-time information to ensure their generated content aligns more closely with reality. Storytellers on the other hand don't require real-time information, since they are crea...

In this episode of The Union podcast, Chris and I review McKinsey &Co.'s "The state of AI in 2023: Generative AI’s breakout year," exploring its impact on various industries and job functions and how it's shaping the future of work. How High Performers Achieve Results with Generative AI McKinsey's report summarizes 1684 survey responses and highlights how companies are...

Companies evaluating AI want the most accurate machine learning models (ML) to predict or summarize business outcomes. However, many times achieving high levels of accuracy and confidence inflates expenses and erodes value versus adding to it. In this episode, Luther Birdzell and Scott King discuss what is and what is not AI, evaluating ML model accuracy against costs, and how to maximize your ROI...

Embracing Predictive Analytics in Decision-Making In this episode of The Union Chris and I discuss predictive analytics and how to use it to help you make better decisions. We explored how advanced analytics can help business process owners and IT professionals boost their decision-making prowess. The most important topic in this episode is using machine learning to build machine learning. It&apos...

There's a lot of AI buzz and businesses everywhere are feeling the pressure to integrate this exciting technology. However, amidst all the hype, there's a need to clarify a few things. First off, AI isn't a panacea for all business woes. It needs a foundation of sound data and processes to be effective and it's intended to assist rather than replace human decision-making. The p...

Generative AI is transforming how data and content are generated in many types of use cases. Its ability to quickly summarize data and enable people to interact with systems in a conversational manner is redefining what work is and the value associated with it. In a recent conversation with Chris Kraus, we reviewed McKinsey & Co.'s, "The economic potential of generative AI: The next...

Artificial intelligence (AI) has an immeasurable impact on various industries, from finance to healthcare to customer service. It can automate repetitive tasks, derive insights from massive data sets, and even help manage and govern data. However, effectively governing AI data requires a well-thought-out strategy and proper implementation. Chris Kraus and I discussed the importance of data governa...

Generative AI possesses great abilities to craft impressive content. Its capacities in generating text, photos, and videos, and engaging in conversational interactions are remarkable, yet they represent only one step in a customer's or employee's quest to complete a process. Imagine a customer reaching out to an organization for assistance. Generative AI can answer this person if its mod...

Implementing generative AI or any other form of AI within a business framework demands more than mere installation. Businesses need to be confident that their data remains secure and that there are role-based administrative procedures present in managing the least privilege. The AI should be capable of synchronizing with current systems in real-time to provide pertinent information and precise res...