Difference between revisions of "Conversational AI"
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*** [[Semi-Supervised Learning with Generative Adversarial Network (SSL-GAN)]] | *** [[Semi-Supervised Learning with Generative Adversarial Network (SSL-GAN)]] | ||
*** [[Context-Conditional Generative Adversarial Network (CC-GAN)]] | *** [[Context-Conditional Generative Adversarial Network (CC-GAN)]] | ||
| − | * [[Natural Language Processing (NLP)]] ...[[Natural Language Generation (NLG)|Generation]] | + | * [[Large Language Model (LLM)]] ... [[Natural Language Processing (NLP)]] ...[[Natural Language Generation (NLG)|Generation]] ... [[Natural Language Classification (NLC)|Classification]] ... [[Natural Language Processing (NLP)#Natural Language Understanding (NLU)|Understanding]] ... [[Language Translation|Translation]] ... [[Natural Language Tools & Services|Tools & Services]] |
| − | Conversational AI refers to technologies, like chatbots or virtual agents, which users can talk to. They use large volumes of data, machine learning, and natural language processing to help imitate human interactions, recognizing speech and text inputs and translating their meanings across various languages. Conversational AI can simulate human conversation and is made possible by | + | Conversational AI refers to technologies, like chatbots or virtual agents, which users can talk to. They use large volumes of data, machine learning, and natural language processing to help imitate human interactions, recognizing speech and text inputs and translating their meanings across various languages. Conversational AI can simulate human conversation and is made possible by [[Natural Language Processing (NLP)]], a field of AI that allows computers to understand and process human language. |
| − | Some examples of conversational AI include chatbots, virtual assistants, text-to-speech software, and speech recognition software . Conversational AI works by using a combination of | + | Some examples of conversational AI include chatbots, virtual assistants, text-to-speech software, and speech recognition software . Conversational AI works by using a combination of NLP and machine learning (ML). Conversational AI systems are trained on large amounts of data, such as text and speech. This data is used to teach the system how to understand and process human language. The system then uses this knowledge to interact with humans in a natural way. It’s constantly learning from its interactions and improving its response quality over time . |
Some benefits of using conversational AI include reducing costs and increasing productivity and operational efficiency through automation. It can also deliver better customer experience, achieve higher customer engagement and satisfaction . | Some benefits of using conversational AI include reducing costs and increasing productivity and operational efficiency through automation. It can also deliver better customer experience, achieve higher customer engagement and satisfaction . | ||
Revision as of 16:36, 28 April 2023
YouTube ... Quora ...Google search ...Google News ...Bing News
- Generative AI ... Conversational AI ... OpenAI's ChatGPT ... Perplexity ... Microsoft's Bing ... You ...Google's Bard ... Baidu's Ernie
- Singularity ... Moonshots ... Emergence ... Explainable / Interpretable AI ... AGI ... Inside Out - Curious Optimistic Reasoning ... Automated Learning
- In-Context Learning (ICL) ... LLMs understand to encode learning algorithms implicitly during their training processes
- Assistants ... Agents ... Negotiation ... HuggingGPT ... LangChain
- Development ...AI Pair Programming Tools ... Analytics ... Visualization ... Diagrams for Business Analysis
- Case Studies
- AI Solver
- Generative Pre-trained Transformer (GPT)
- Generative Query Network (GQN)
- Data Augmentation, Data Labeling, and Auto-Tagging
- Python ... Generative AI with Python ... Javascript ... Generative AI with Javascript ... Game Development with Generative AI
- Generative AI for Business Analysis
- Natural Language Generation (NLG)
- Demo, summarizing, priority listing, & analysis...
- Three main types:
- Autoencoder (AE) / Encoder-Decoder
- Sequence Models
- Adversarial Networks
- Large Language Model (LLM) ... Natural Language Processing (NLP) ...Generation ... Classification ... Understanding ... Translation ... Tools & Services
Conversational AI refers to technologies, like chatbots or virtual agents, which users can talk to. They use large volumes of data, machine learning, and natural language processing to help imitate human interactions, recognizing speech and text inputs and translating their meanings across various languages. Conversational AI can simulate human conversation and is made possible by Natural Language Processing (NLP), a field of AI that allows computers to understand and process human language.
Some examples of conversational AI include chatbots, virtual assistants, text-to-speech software, and speech recognition software . Conversational AI works by using a combination of NLP and machine learning (ML). Conversational AI systems are trained on large amounts of data, such as text and speech. This data is used to teach the system how to understand and process human language. The system then uses this knowledge to interact with humans in a natural way. It’s constantly learning from its interactions and improving its response quality over time .
Some benefits of using conversational AI include reducing costs and increasing productivity and operational efficiency through automation. It can also deliver better customer experience, achieve higher customer engagement and satisfaction .
