Remove Explainability Remove LLM Remove UX Design
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#45 Is Prompting a Future-Proof Skill?

Towards AI

Over the past few months, we have discussed the AI engineer’s toolkit for building reliable LLM products multiple times. Visrix is looking for an audio-video specialist to help with UI/UX design, AWS configurations, and scaling as the platform grows. Good morning, AI enthusiasts!

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Real-Real-World Programming with ChatGPT

O'Reilly Media

Our paper reinforces the growing consensus that LLM-based AI tools such as ChatGPT and GitHub Copilot can now solve many of the small self-contained programming problems that are found in introductory classes. What I needed at this time was a UX design consultant, so I wanted to see if ChatGPT could play this role.

ChatGPT 98
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Hallucinating Reality. An Essay on Business Benefits of Accurate LLMs and LLM Hallucination Reduction Methods

deepsense.ai

Just to explain what I mean by 3. The Truth Is Out There So, how to reduce hallucinations in LLMs? What are the techniques for minimizing LLM hallucinations? Design systems that support accurate LLM performance – use grounding to anchor outputs of a language model to a trusted source.

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The Future of Software Engineering: LLMs and Beyond

Heartbeat

After closely observing the software engineering landscape for 23 years and engaging in recent conversations with colleagues, I can’t help but feel that a specialized Large Language Model (LLM) is poised to power the following programming language revolution. The LLM Ecosystem The impact of LLMs extends beyond mere code generation.

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Redefining Conversational AI with Large Language Models

Topbots

After considering the market opportunities and the business value of conversational AI systems, we will explain the additional “machinery” in terms of data, LLM fine-tuning, and conversational design that needs to be set up to make conversations not only possible but also useful and enjoyable.

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Building AI Products With A Holistic Mental Model

Topbots

It aims to bring together the perspectives of product managers, UX designers, data scientists, engineers, and other team members. For example, if you are working on a virtual assistant, your UX designers will have to understand prompt engineering to create a natural user flow.

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Reinvent personalization with generative AI on Amazon Bedrock using task decomposition for agentic workflows

AWS Machine Learning Blog

We employ task decomposition, using domain / task adopted LLMs for content personalization (UX designer/personalizer), image generation (artist), and building (builder/front end developer) for the final delivery of HTML, CSS, and JavaScript files. The first part moves to the frontend developer LLM.