Remove AI Tools Remove Conversational AI Remove Prompt Engineering
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AI courses to boost your skills and stay ahead

AI News

Learners gain insights into conversational AI tools, the differences between Natural Language Understanding (NLU) bots and rule-based bots, and best practices in conversation flow analysis. For business analysts, the course provides essential skills to guide AI initiatives that deliver real business value.

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Advancing AI trust with new responsible AI tools, capabilities, and resources

AWS Machine Learning Blog

Responsible AI builds trust, and trust accelerates adoption and innovation. Used alongside other techniques such as prompt engineering, RAG, and contextual grounding checks, Automated Reasoning checks add a more rigorous and verifiable approach to enhancing the accuracy of LLM-generated outputs.

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When ‘Chatbot’ Is a Dirty Word: 3 Misconceptions Business Leaders Have About Conversational AI

Unite.AI

Today’s “chatbots,” on the other hand, are more frequently referring to conversational AI, a tool with much broader capabilities and use cases. And because we now find ourselves in the midst of the generative AI hype cycle, all three of these terms are being used interchangeably.

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Prompt Engineering Hacks for ChatGPT & LLM Applications

Topbots

Harnessing the full potential of AI requires mastering prompt engineering. This article provides essential strategies for writing effective prompts relevant to your specific users. Let’s explore the tactics to follow these crucial principles of prompt engineering and other best practices.

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This AI Paper from IBM and MIT Introduces SOLOMON: A Neuro-Inspired Reasoning Network for Enhancing LLM Adaptability in Semiconductor Layout Design

Marktechpost

Semiconductor layout design is a prime example, where AI tools must interpret geometric constraints and ensure precise component placement. Researchers are developing advanced AI architectures to enhance LLMs’ ability to process and apply domain-specific knowledge effectively.

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Generative AI use cases for the enterprise

IBM Journey to AI blog

The quality of outputs depends heavily on training data, adjusting the model’s parameters and prompt engineering, so responsible data sourcing and bias mitigation are crucial. Imagine training a generative AI model on a dataset of only romance novels. Existing content can be reimagined and edited using AI tools.

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Enterprise LLM APIs: Top Choices for Powering LLM Applications in 2024

Unite.AI

The race to dominate the enterprise AI space is accelerating with some major news recently. This incredible growth shows the increasing reliance on AI tools in enterprise settings for tasks such as customer support, content generation, and business insights. Key Features Advanced Models : With access to GPT-4 and GPT-3.5-turbo,

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