The hottest Chatbots Substack posts right now

And their main takeaways
Category
Top Technology Topics

The Evolution Of Prompt Engineering

Cobus Greyling on LLMs, NLU, NLP, chatbots & voicebots • 0 implied HN points • 17 Apr 23
🕹 Technology AI NLP Generative AI Chatbots Prompt engineering
  1. Prompt engineering is important for getting the best responses from large language models. Users have to carefully design prompts to mimic what they want the model to generate.
  2. Static prompts can be turned into templates with placeholders that can be filled in later. This makes it easier to reuse and share prompts in different situations.
  3. Prompt pipelines allow users to create more complex applications by linking several prompts together. This helps organize how information is processed and improves user interaction with chatbots.

The Foundation Conversational AI Technologies: Version 3

Cobus Greyling on LLMs, NLU, NLP, chatbots & voicebots • 0 implied HN points • 13 Apr 23
🕹 Technology AI Chatbots Data Development NLP
  1. There's been a rise in chatbot development frameworks that now include large language models (LLMs). This means chatbots can do more complex tasks than before.
  2. LLMs are not just for generating responses anymore. They can help create entire conversation flows and assist developers more effectively.
  3. Future improvements will focus on better fine-tuning and supervision methods for LLMs, making them even smarter and more useful.

5 Things NLU Engines Are Really Good At

Cobus Greyling on LLMs, NLU, NLP, chatbots & voicebots • 0 implied HN points • 03 Apr 23
🕹 Technology AI NLP Chatbots Machine Learning Data Mining
  1. NLU engines make data entry super easy with no coding needed. You can just click and put in your data without worrying about complicated setups.
  2. Intents, or the goals of what users want, are flexible and can adapt to different classes or categories. This helps in understanding user requests better.
  3. Entities, which represent specific items or information, have improved a lot. Better detection of these lets chatbots gather information without having to ask the user again.

Prompt Engineering, OpenAI & Modes

Cobus Greyling on LLMs, NLU, NLP, chatbots & voicebots • 0 implied HN points • 17 Mar 23
🕹 Technology AI NLP Chatbots Data Programming
  1. Prompt engineering is really important for getting the most out of large language models. Good prompts can help the model give accurate and relevant responses.
  2. To prevent models from making things up or 'hallucinating,' prompts need to be carefully structured and put together. This helps keep the context clear and the information reliable.
  3. OpenAI is working on improving the safety and quality of responses using better prompt structures. This reduces risks like prompt injection attacks and helps ensure more consistent answers.

Adding A Moderation Layer To Your OpenAI Implementations

Cobus Greyling on LLMs, NLU, NLP, chatbots & voicebots • 0 implied HN points • 08 Mar 23
🕹 Technology AI API Moderation NLP Chatbots
  1. Adding a moderation layer to OpenAI implementations is essential to comply with usage policies. This helps avoid serious issues like account termination.
  2. The moderation endpoint is free to use and monitors for harmful content like hate, violence, and self-harm. Companies should check their API calls for inappropriate content.
  3. OpenAI is continually improving the moderation tools, but users need to frequently update their own policies to align with these changes. Regular checks can help ensure safe usage.
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NLU & NLG Should Go Hand-In-Hand

Cobus Greyling on LLMs, NLU, NLP, chatbots & voicebots • 0 implied HN points • 07 Mar 23
🕹 Technology AI NLP Chatbots Software Data
  1. Using NLU and NLG together can make chatbots work better. They can detect what users want and give accurate responses.
  2. Traditional NLU systems still have strong abilities in understanding user intent that shouldn’t be ignored. They're a valuable asset in chatbot design.
  3. Regularly checking and updating the prompts used by chatbots can help improve how they respond to users, making interactions more effective.

When Using The ChatGPT API, Users Will Have To Manage The Context

Cobus Greyling on LLMs, NLU, NLP, chatbots & voicebots • 0 implied HN points • 06 Mar 23
🕹 Technology AI APIs NLP Chatbots Conversational AI
  1. When using the ChatGPT API, users must provide context for the conversation because it doesn't remember past interactions. You need to include previous messages to keep the conversation clear.
  2. If the number of messages exceeds a limit, you can keep only the most recent ones to save space. This way, the model still understands the flow of the conversation.
  3. If you want better responses, you should be clear with your instructions and specify what type of answer you need. Changing how you ask questions can help improve the output.

Foundation Conversational AI Technologies Landscape

Cobus Greyling on LLMs, NLU, NLP, chatbots & voicebots • 0 implied HN points • 21 Feb 23
🕹 Technology AI NLP Chatbots Voicebots
  1. The conversational AI field is quickly evolving in three main areas: voicebots, agent assistance, and large language model (LLM) enablement.
  2. Many current AI systems focus on generating responses, but there's a missed opportunity to use predictive features effectively.
  3. Traditional natural language understanding systems still perform better in terms of cost and training compared to LLMs, especially for certain tasks.

Solving For The Long Tail Of Intent Distribution

Cobus Greyling on LLMs, NLU, NLP, chatbots & voicebots • 0 implied HN points • 16 Feb 23
🕹 Technology AI Chatbots Machine Learning Data science
  1. The long tail of intent distribution has a lot of important customer conversations that can be often overlooked. These conversations are key to understanding what users really want.
  2. Using existing customer data like conversation transcripts and reviews can help identify these overlooked intents. Analyzing this data properly allows for better understanding and response design.
  3. Aligning chatbot intents with actual customer conversations is crucial for success. This ensures that the chatbot effectively meets user needs and improves overall interaction.

Existing Rigid Chatbot Architecture Needs Large Language Model (LLM) Flexibility

Cobus Greyling on LLMs, NLU, NLP, chatbots & voicebots • 0 implied HN points • 15 Feb 23
🕹 Technology AI NLP Chatbots Frameworks
  1. Current chatbot systems are too rigid and are mostly based on fixed rules and flows. They can't adapt easily to different conversations, making them less effective.
  2. Large language models (LLMs) have the potential to make chatbots more flexible and smarter. They can help chatbots understand and respond to a wider range of user inputs.
  3. Innovative new frameworks for conversational AI are emerging. These allow for more personalized interactions by combining different components based on user needs.

Bootstrapping A Chatbot With A Large Language Model

Cobus Greyling on LLMs, NLU, NLP, chatbots & voicebots • 0 implied HN points • 14 Feb 23
🕹 Technology AI Chatbots NLP Data science Programming
  1. To build a chatbot, you can organize unstructured data by clustering it into themes called intents. This helps make sense of lots of information and sets the stage for training the bot.
  2. Once the bot receives a user's message, it uses semantic search to match the message with the right intent. This helps in retrieving the most relevant information quickly.
  3. The bot then generates a response using the matched intent and the user's question. This process allows the chatbot to provide accurate and context-aware answers.

Foundation Conversational AI Technologies

Cobus Greyling on LLMs, NLU, NLP, chatbots & voicebots • 0 implied HN points • 10 Feb 23
🕹 Technology AI NLP Voicebots Chatbots Data Management
  1. Conversational AI (CAI) technologies are grouped by their areas, but sometimes it's tricky to fit them into just one category. Many technologies overlap.
  2. The focus is mainly on foundational technologies instead of specific products or solutions, which are too numerous to cover in detail.
  3. Feedback and suggestions for improvement are encouraged to make future versions better.

The Cobus Quadrant™ Of NLU Design

Cobus Greyling on LLMs, NLU, NLP, chatbots & voicebots • 0 implied HN points • 09 Feb 23
🕹 Technology AI NLP Chatbots Data Management
  1. Understanding customer intent is key to making chatbots work well. Starting with what customers want helps create better and more trusted AI experiences.
  2. NLU Design is about turning messy data into clear information for chatbots. It involves organizing unstructured data and using both human input and machine help to label and manage it.
  3. Improving chatbots requires ongoing evaluation and fine-tuning. Regularly checking their performance and making adjustments helps keep them responsive to users' needs.

NLP/NLU, Chatbots, Conversational UI/UX, Developer, Ubiquitous User Interfaces

Cobus Greyling on LLMs, NLU, NLP, chatbots & voicebots • 0 implied HN points • 01 Jun 21
🕹 Technology AI NLP Chatbots UI/UX Development
  1. NLP and NLU help machines understand human language better. This makes chatbots and voicebots more effective in conversations.
  2. Conversational UI/UX focuses on making user interactions with technology feel natural and engaging. Good design improves user satisfaction.
  3. Developers play a key role in building these technologies. Their skills help create seamless and intuitive interfaces for users.

Making minimalist chatbot iOS app so I don't have to pay $20/mo for premium LLM subscription

Expand Mapping with Mike Morrow • 0 implied HN points • 06 Dec 24
🕹 Technology Software Mobile Apps Chatbots AI Development
  1. If you use a chatbot a lot every month, paying a flat fee like $20 is worth it. But if your usage is unpredictable, it might be cheaper to use LLM APIs instead.
  2. Many chatbot apps ask for your API key, which can feel risky since your data could be misused. Building your own chatbot app can help you feel more secure.
  3. The author's app is very simple and needs to be more user-friendly. They are looking for better, secure chatbot apps for iOS that don't require a subscription.

Using AI Chatbots: A Gentle Introduction

Autonomy • 0 implied HN points • 22 Feb 25
🕹 Technology AI Chatbots Content Generation
  1. AI chatbots can help you find answers quickly, like having a smart teacher available all the time. They summarize complex information more effectively than traditional search engines.
  2. You can use AI to help create content, like writing emails or blog posts. It can generate ideas or even draft full pieces for you to tweak and finalize.
  3. Modern AI is now capable of reasoning through problems, which means it can help with complex tasks like legal arguments or decision-making processes. It suggests smart approaches based on its understanding of information.