?? New Blog from Tod Famous The 85% Problem—The AI Gap Your Team Can’t Bridge Tempted to build your own generative AI for CX? Achieving 85% functionality may be within reach, but closing that final 15% gap can consume endless resources and budget. In The 85% Problem, Tod Famous reveals the hidden challenges of DIY AI—from constant maintenance to the risks of LLM unpredictability. Discover why working with a partner like Crescendo may be the key to reaching 100% and delivering the exceptional CX your customers expect. Read more to see if DIY AI is worth the leap. https://hubs.ly/Q02Y8r8d0 #CustomerExperience #AIinCX #CXLeadership
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Smaller Firms and The AI Scale Advantages of Big Enterprises! Smaller firms risk falling irretrievably behind the larger companies in the race to master AI due to limited resources. But many are unaware of the fact the powerful Open-source options are available to them. Several Open source generative AI models and other cloud-based AI resources are accessible at relatively low cost. Smaller enterprises have a lot to gain from improvements in customer experience, sales, marketing, operating efficiency and product innovation. They cannot afford to let the growth opportunities that AI offers pass them by. This is really a now or never moment for them. Ignoring AI is not an option. They must transform their business with Gen-AI for AI-driven insights and automation to remain competitive. We can help smaller firms unlock the full potential of Generative-AI. Whether it's enhancing decision-making, automating customer support, or conducting deep risk assessments, our tailored AI solutions ensure that every piece of data adds value to the strategic goals. Advanced techniques like Retrieval Augmented Generation (RAG) and fine-tuned Large Language Models (LLMs) are transforming how businesses are managed and run. Our approach integrates Open Source Large Language Models (LLMs) such as LlaMA-3, Mistral 8x7B, Falcon and others with your exhaustive data sets into one dynamic AI system that not only understands your business history but also responds to real-time data inputs. This means more accurate forecasting, enhanced customer service, optimized sales, marketing and production processes, and a profound understanding of market trends. Ready to redefine your business operations with AI? Let's connect and discuss how we can transform your data into your greatest asset. Contacts us at: [email protected] [email protected] https://lnkd.in/gvNQ8Y6P #AI #GenAI #DataDriven #Innovation #BusinessTransformation
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InRule is an AI decisioning platform that empowers organisations to quickly create, test, deploy, and manage business decisions critical to mission success.?Business users can use InRule as a self-serve platform to build low-code automated decision processes.? ? Learning the platform is fast, with most users gaining proficiency with InRule in weeks. A single business user can author decisions up to 10 times faster than traditionally coded logic created by an engineer and execute automated decisions independently. With improvements to business user productivity, data analysts and other technical users spend less time managing rule sets and handling exceptions.?? ? Get more information https://lnkd.in/gFY2pxYX #InRule #AI #DecisionMaking #BusinessRulesEngine
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"AI agents are intelligent software entities that can perform tasks, make decisions...Unlike chatbots or first-generation AI, these agents can proactively source information, analyze data, provide answers, and even initiate actions based on their roles and permissions." #digitaltransformation #aiagent #generativeai #ai #agentic #data #llm #lam #aiagents #aiux #futureofwork #aitransformation #aiproducts
AI Agents Are Accelerating Digital Transformation. Are You Ready?
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A customer recently asked me a thought-provoking question: "How can we ensure that LLMs like Claude provide consistent and accurate responses, especially when dealing with queries that weren't explicitly anticipated during the initial setup? What strategies can we employ to enhance the reliability of AI-generated answers?" This question touches on a crucial aspect of working with AI: consistency. The key to addressing this challenge lies in the art and science of prompt engineering. Why is prompt engineering so vital? It's about properly grounding the model in your specific context, reducing the cognitive load on both the AI and the end-user. By crafting well-structured prompts, we can: ?? Enhance consistency across responses ?? Improve accuracy within your domain ?? Reduce the need for users to repeatedly brief the AI on subject matter ?? Guide the AI to provide more relevant and tailored outputs To achieve these goals, I find COSTAR to be a useful mnemonic for remembering how to create robust prompts: C - Context: Provide essential background information O - Objective: Clearly define the task at hand S - Style: Specify the desired writing style T - Tone: Set the appropriate sentiment A - Audience: Identify who you're addressing R - Response: Outline the expected format (text, JSON, etc.) By incorporating these elements, you create a comprehensive prompt that acts as a guiding framework for the AI. This approach significantly improves the model's ability to generate consistent, accurate, and contextually appropriate responses - even for questions not explicitly covered in the initial prompt. Pro tip: Version control your prompts and test each iteration thoroughly! This approach allows you to refine and improve your prompts over time, leading to even better AI interactions and addressing consistency concerns head-on.
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?? Curious about AI agents and their impact on business? Check out Ann Maya's latest feature in AI Journal’s article "The Age of AI Agents: What to Know and How to Strategise." Learn how AI agents are revolutionizing business strategies, here https://okt.to/2hTksL
The age of AI agents: What to know and how to strategise | The AI Journal
aijourn.com
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?? Curious about AI agents and their impact on business? Check out Ann Maya's latest feature in AI Journal’s article "The Age of AI Agents: What to Know and How to Strategise." Learn how AI agents are revolutionizing business strategies, here https://okt.to/ycviEx
The age of AI agents: What to know and how to strategise | The AI Journal
aijourn.com
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Retrieval Augmented Generation (RAG) - Integrating Your Business Data into AI ?? Are you ready to take your AI capabilities beyond basic tools like ChatGPT? Our latest blog post dives into Retrieval Augmented Generation (RAG) and how it can help you integrate your business’s own data—whether it’s from databases, spreadsheets, or documents—into AI models tailored to your specific needs. ?? What you’ll learn: - How RAG can turn your AI into a specialized assistant - Practical steps for implementing RAG in your business - Tools like WatsonX and KnowNow’s Data Management Canvas to get you started AI doesn’t need to know the entire internet—just the data that matters to your business. Learn how to tailor AI for your industry and optimize its potential. ?? Read the full article here: https://lnkd.in/eJtbQpvg #AI #ArtificialIntelligence #RAG #BusinessData #AIIntegration #WatsonX #DataManagement #AIForBusiness
Retrieval Augmented Generation: Integrating Your Data into AI
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Co-Founder of Altrosyn and DIrector at CDTECH | Inventor | Manufacturer
1 周Tod's focus on the "85% Problem" assumes a linear progression towards AI maturity, neglecting the potential for disruptive innovations that could render current benchmarks obsolete. The recent emergence of open-source LLMs like BLOOM challenges the necessity of partnering with established players like Crescendo. Could a decentralized approach to AI development, leveraging community contributions and rapid iteration cycles, ultimately bridge the gap more effectively?