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Time Business News
14-08-2025
- Business
- Time Business News
The Support Hallucination Trap: Why Even Great Models Fail
Photo by Benjamin White on Unsplash Imagine this: a customer reaches out to your AI-powered support bot to ask about a new product feature. The bot, trained on last quarter's documentation, confidently responds, but it's completely wrong. The feature changed two weeks ago, and the bot never got the memo. This isn't a failure of intelligence. It's a failure of communication. Large language models (LLMs) like GPT-4 aren't broken, they're just isolated. Without structured, real-time feedback loops, even the most advanced AI systems operate like support agents locked in a room with no updates, no coaching, and no way to learn from their mistakes. The result? Confident improvisation in a vacuum. Your AI isn't broken, it's just ignored. Even the best models hallucinate when they're forced to guess. This section explores how hallucinations stem from missing context, not model incompetence. In AI, 'hallucination' refers to when a model generates plausible-sounding but incorrect or fabricated information. But in support environments, these aren't random errors: they're structured improvisations based on outdated or incomplete data. For example, a bot might confidently state that your service-level agreement (SLA) is 72 hours, when in fact it was updated to 48 hours last week. The model isn't being 'stupid,' it's working with the best guess it can make from stale inputs. LLMs like GPT-4 or Cohere Command R+ don't inherently 'know' your product, policies, or workflows. They rely on grounding: the process of anchoring responses in external, up-to-date knowledge sources. Without this, they revert to probabilistic reasoning based on training data, which may be months or years old. Fine-tuning helps, but it's not a substitute for real-time awareness. Without feedback, models can't distinguish between what's true, what's changed, and what matters. Prompt engineering and fine-tuning are powerful tools, but they're static by nature. This section explains why they fall short in dynamic support environments. Prompts can encode rules, tone, and structure. Fine-tuning can teach a model your historical ticket data. But neither can adapt to change unless they're continuously updated. Without feedback loops, prompts become brittle. They reflect yesterday's reality, not today's needs. Consider a model trained on support tickets from Q1. In Q2, your refund policy changes, your product UI is redesigned, and your escalation process is streamlined. But the model still answers as if it's Q1 because no one told it otherwise. This is why hallucinations persist even in well-engineered systems. The model isn't misbehaving, it's uninformed, hence not helping much with understanding how AI support tools avoid generating hallucinations. To prevent hallucinations, we must treat AI support systems like living organisms, constantly learning, adapting, and evolving. This section introduces three essential feedback loops. Support agents are your first line of defense against hallucinations. Equip them with a structured interface to flag incorrect AI responses, explain why they're wrong, and categorize the error type (e.g., factual error, tone mismatch, outdated policy). Example: 'Bot said our refund window is 60 days — it's 30.' This feedback should be routed into a central system for review and retraining. Customers can also provide valuable signals if you ask the right questions. Instead of generic star ratings, use targeted prompts like: 'Was this response helpful and correct?' This lightweight feedback can highlight confusion, inaccuracies, or gaps in the model's understanding. The most overlooked and most powerful loop is system-level feedback. Integrate your AI with product release notes, CRM updates, and knowledge base changes. When a policy changes or a feature is deprecated, your model should know immediately. CoSupport AI offers frameworks for building these closed-loop systems. Feedback is only useful if it's actionable. This section outlines how to build a pipeline that turns feedback into learning. Hallucination Think of this as your AI's 'error inbox.' Don't wait for quarterly retraining cycles. Update your retrieval logic and prompts weekly or even daily. Automate the ingestion of new documents, with version control to track what changed and when. This keeps your model grounded in the present, not the past. Introduce safeguards based on feedback history. For example: If a response is flagged three times, route similar queries to a human. Use a 'confidence + feedback match' score to determine when to suppress or rephrase a response. These gates reduce the risk of repeated hallucinations and build trust over time. For implementation inspiration, see GitHub's AI Ops pipelines or LangChain's feedback integrations. What happens when you skip feedback loops? This section explores the hidden costs in productivity, trust, and customer satisfaction. A bot that resolves tickets quickly might look efficient until you realize it's causing a spike in reopen rates. Time saved in the moment can lead to time wasted in escalations and corrections. Fast isn't always right. And wrong answers cost more than slow ones. Support agents may silently rewrite AI-generated replies without reporting errors. Customers may stop using the bot altogether. These silent signals erode trust, and they're hard to detect without feedback instrumentation. To measure trust, track: Agent override rates Bot deflection vs. escalation ratios Customer re-engagement after bot interaction Hallucinations aren't a sign of model failure: they're a sign of system neglect. Even the smartest AI needs structured, real-time feedback to stay relevant, accurate, and trustworthy. The solution isn't smarter models. It's louder feedback. In this way, you don't need smarter AI, you need louder feedback. TIME BUSINESS NEWS
Yahoo
08-05-2025
- Entertainment
- Yahoo
Franklin has eye on the future while looking back, preserving its past
FRANKLIN, Tenn. (WKRN) — Inside the Moore-Morris History and Culture Center of Williamson County, TN is an immersive re-creation of White's Tavern, which was inside the city's first inn. It was established in 1803 by pioneer Benjamin White. 'If you're here for a room, that will be 8 cents. If you need me to stead your horse, it will be 12; my boy will fetch 'em and take 'em out back,' said an actor portraying White, who appears as a hologram behind the bar. You can also hear from other historical figures — including Freeman Thomas, who escaped slavery in Williamson County and joined the Union Army. 'This was the biggest thing that ever happened in my life,' said an actor portraying Thomas inside a portrait that seemed to suddenly come alive. 'I felt like a man with a uniform on and a gun in my hand.' NEWS 2 ON TOUR: What draws companies to Williamson County? 'These living portraits are our main teaching tool here,' the center's managing director, Nat Taylor, said. 'What I like about them as a historian is that the words that they say — we pulled them right from primary sourced historical records.' The building on Bridge Street was home to the county jail from 1905 until 1942; later, it was a restaurant and event venue. The non-profit Heritage Foundation of Williamson County purchased the building and opened the center in 2024 to share the area's rich stories with the community. 'It's clear Franklin really cares about its history and understanding it,' Taylor said. 'Franklin is a great mix of a historic community and a great preservation ethic of this beautiful historic downtown, but it's also a community that continues to grow and evolve,' Franklin City Administrator Eric Stuckey said. Stuckey said that downtown is the difference maker in what sets the city apart and draws in new residents and visitors. 'It feels like home when you're here on these streets,' Stuckey said. 'It's not just any place in America. It is a special place, and people just naturally sense that. That's not an accident. It's been lovingly preserved over many years.' Although it may seem like Franklin has grown exponentially, Stuckey said the city has had a consistent growth pattern since the 1980s. 'We've grown [by] right about 20,000 a decade, or 2,000 a year since that time frame,' Stuckey said. 'It's a sustainable, steady amount of growth.' Franklin is home to major corporations including Nissan, Mitsubishi and Community Health Systems. In-N-Out Burger is set to open its regional headquarters next year. Stuckey said the city focuses on land use planning to keep infrastructure and utility needs met. One of the biggest challenges is affordable housing. MORE ON TOUR: Williamson County greenways plan survey extended 'It is both a community characteristic, but it's also an economic vitality component to have housing options for people at different stages in their career — different workers,' Stuckey said. 'We want to strive to do that; it's a hard issue. We don't have an easy solution, but we're continuing to work on it and think about it and look at ways that we can make that happen.' Franklin is a city with an eye on the future while it also looks back and preserves its past. 'I think communities that really care about their history — it will only serve them for their future, so I think we're pretty well positioned here,' Taylor said. For National Travel and Tourism Week, the Moore-Morris History and Culture Center is offering free admission through May 10. For more information, follow this link. Copyright 2025 Nexstar Media, Inc. All rights reserved. This material may not be published, broadcast, rewritten, or redistributed. For the latest news, weather, sports, and streaming video, head to WKRN News 2.
