Published Jan 10, 2025

From NLP to LLMs: The Quest for a Reliable Chatbot

Explore the evolution and challenges of building reliable AI chatbots with Alan Nichol, as he delves into the integration of large language models with business logic, overcoming AI implementation hurdles, and transforming Rasa from an intent-based system to a leader in conversational AI. Uncover the intricate dance of deterministic logic and LLMs in crafting dynamic AI interactions.

Episode Highlights

Topics covered

Building AI Systems
01
AI Implementation Challenges
02
Conversational AI Approaches
03
Evolution of Rasa
04

Questions from this episode

- Is reinforcement learning a turning point for large language models (LLMs) and artificial intelligence (AI)?
  Asked by 7 people
- How can ChatGPT help in studying the concepts discussed in the episode Stephen Wolfram on AI’s rapid progress & the “Post-Knowledge Work Era” | E1711 and the clip Natural Language Processing?
  Asked by 3 people
- How is machine learning evolving as discussed in the episode Peter Norvig: Artificial Intelligence: A Modern Approach | Lex Fridman Podcast #42 and the clip AI Learning Paradigms?
  Asked by 2 people
- Do you use retrieval-augmented generation (RAG) or a chatbot?
  Asked by 2 people
- Do I get it right that a Retrieval Augmented Generation (RAG) system can retrieve data in addition to its training data?
  Asked by 2 people
- How is computing related to language?
  Asked by 2 people
- Can you give more examples of large language model applications in relation to the episode Stephen Wolfram: ChatGPT and the Nature of Truth, Reality & Computation | Lex Fridman Podcast #376 and the clip Computational Language Insights?
  Asked by 2 people
- What is the future of large language models (LLMs) as discussed in the episode GELU, MMLU, & X-Risk Defense in Depth, with the Great Dan Hendrycks and the clip MMLU Insights?
  Asked by 2 people
- How can AI summarize conversations?
  Asked by 1 person
- What kind of products or apps will you see that combine large language models (LLMs) for software engineering?
  Asked by 1 person
- What problems do developers face when building AI applications as discussed in the episode Augmenting Incident Response with LLMs and the clip Rethinking AI Applications?
  Asked by 1 person
- How do you use Retrieval-Augmented Generation (RAG) with a Language Model?
  Asked by 1 person
- What is the future of large language models (LLMs) as discussed in the episode OpenAI's Model (behavior) Spec, RLHF transparency, and personalization questions and the clip AI Model Flexibility?
  Asked by 1 person
- What was the biggest innovation that Perplexity achieved using large language models?
  Asked by 1 person
- What are the most recent developments and trends in AI, large language models (LLMs), retrieval-augmented generation (RAG), etc., as discussed in the episode Vector Databases and the Power of RAG and the clip Evolution of AI?
  Asked by 1 person

From NLP to LLMs: The Quest for a Reliable Chatbot

Topics covered

Popular Clips

Merging AI Worlds

Building AI Confidence

Conversational AI Challenges

LLMs in Production

Understanding Language Ambiguity

Intent-Free Chatbots

Integrating LLMs Effectively

Conversational AI Challenges

Evolving Language Interfaces

Prompting for AI

RAG Insights

Word Representations Revolution

Rasa's Evolution

Chatbot Evolution

Questions from this episode

Is reinforcement learning a turning point for large language models (LLMs) and artificial intelligence (AI)?

How can ChatGPT help in studying the concepts discussed in the episode Stephen Wolfram on AI’s rapid progress & the “Post-Knowledge Work Era” | E1711 and the clip Natural Language Processing?

How is machine learning evolving as discussed in the episode Peter Norvig: Artificial Intelligence: A Modern Approach | Lex Fridman Podcast #42 and the clip AI Learning Paradigms?

Do you use retrieval-augmented generation (RAG) or a chatbot?

Do I get it right that a Retrieval Augmented Generation (RAG) system can retrieve data in addition to its training data?

How is computing related to language?

Can you give more examples of large language model applications in relation to the episode Stephen Wolfram: ChatGPT and the Nature of Truth, Reality & Computation | Lex Fridman Podcast #376 and the clip Computational Language Insights?

What is the future of large language models (LLMs) as discussed in the episode GELU, MMLU, & X-Risk Defense in Depth, with the Great Dan Hendrycks and the clip MMLU Insights?

How can AI summarize conversations?

What kind of products or apps will you see that combine large language models (LLMs) for software engineering?

What problems do developers face when building AI applications as discussed in the episode Augmenting Incident Response with LLMs and the clip Rethinking AI Applications?

How do you use Retrieval-Augmented Generation (RAG) with a Language Model?

What is the future of large language models (LLMs) as discussed in the episode OpenAI's Model (behavior) Spec, RLHF transparency, and personalization questions and the clip AI Model Flexibility?

What was the biggest innovation that Perplexity achieved using large language models?

What are the most recent developments and trends in AI, large language models (LLMs), retrieval-augmented generation (RAG), etc., as discussed in the episode Vector Databases and the Power of RAG and the clip Evolution of AI?

Episode Highlights

Building AI Systems

AI Implementation Challenges

Conversational AI Approaches

Evolution of Rasa

From NLP to LLMs: The Quest for a Reliable Chatbot

Topics covered

Popular Clips

Questions from this episode

Episode Highlights

Building AI Systems

AI Implementation Challenges

Conversational AI Approaches

Evolution of RasaRasa's journey from an open-source NLP library to a leader in chatbot development highlights the evolution of AI tools. Alan Nichol shares insights into moving away from intent-based paradigms, paving the way for more scalable and flexible solutions.

Evolution of Rasa