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|keywords=ChatGPT, artificial, intelligence, machine, learning, GPT-4, GPT-5, NLP, NLG, NLC, NLU, models, data, singularity, moonshot, Sentience, AGI, Emergence, Moonshot, Explainable, TensorFlow, Google, Nvidia, Microsoft, Azure, Amazon, AWS, Hugging Face, OpenAI, Tensorflow, OpenAI, Google, Nvidia, Microsoft, Azure, Amazon, AWS, Meta, LLM, metaverse, assistants, agents, digital twin, IoT, Transhumanism, Immersive Reality, Generative AI, Conversational AI, Perplexity, Bing, You, Bard, Ernie, prompt Engineering LangChain, Video/Image, Vision, End-to-End Speech, Synthesize Speech, Speech Recognition, Stanford, MIT |description=Helpful resources for your journey with artificial intelligence; videos, articles, techniques, courses, profiles, and tools
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[https://www.bing.com/news/search?q=Generative+AI&qft=interval%3d%228%22 ...Bing News]
 
[https://www.bing.com/news/search?q=Generative+AI&qft=interval%3d%228%22 ...Bing News]
  
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* [[Generative AI]] ... [[Conversational AI]] ... [[OpenAI]]'s [[ChatGPT]] ... [[Perplexity]] ... [[Microsoft]]'s [[Bing]] ... [[You]] ...[[Google]]'s [[Bard]] ... [[Baidu]]'s [[Ernie]]
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* [[Conversational AI]] ... [[ChatGPT]] | [[OpenAI]] ... [[Bing/Copilot]] | [[Microsoft]] ... [[Gemini]] | [[Google]] ... [[Claude]] | [[Anthropic]] ... [[Perplexity]] ... [[You]] ... [[phind]] ... [[Grok]] | [https://x.ai/ xAI] ... [[Groq]] ... [[Ernie]] | [[Baidu]] ... [[DeepSeek]]
 +
* [[What is Artificial Intelligence (AI)? | Artificial Intelligence (AI)]] ... [[Generative AI]] ... [[Machine Learning (ML)]] ... [[Deep Learning]] ... [[Neural Network]] ... [[Reinforcement Learning (RL)|Reinforcement]] ... [[Learning Techniques]]
 
** [[ChatGPT#Integration| ChatGPT Integration]]
 
** [[ChatGPT#Integration| ChatGPT Integration]]
−
* [[Assistants]] ... [[Hybrid Assistants]]  ... [[Agents]]  ... [[Negotiation]] ... [[Hugging_Face#HuggingGPT|HuggingGPT]] ... [[LangChain]]
+
* [[Agents]] ... [[Robotic Process Automation (RPA)|Robotic Process Automation]] ... [[Assistants]] ... [[Personal Companions]] ... [[Personal Productivity|Productivity]] ... [[Email]] ... [[Negotiation]] ... [[LangChain]]
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* [[Development]] ...[[Development#AI Pair Programming Tools|AI Pair Programming Tools]] ... [[Analytics]] ... [[Visualization]] ... [[Diagrams for Business Analysis]]
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* [[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]]
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* [[Case Studies]]  
+
* [[Artificial General Intelligence (AGI) to Singularity]] ... [[Inside Out - Curious Optimistic Reasoning| Curious Reasoning]] ... [[Emergence]] ... [[Moonshots]] ... [[Explainable / Interpretable AI|Explainable AI]] ... [[Algorithm Administration#Automated Learning|Automated Learning]]
−
** [[Neeva]]
+
* [[Perspective]] ... [[Context]] ... [[In-Context Learning (ICL)]] ... [[Transfer Learning]] ... [[Out-of-Distribution (OOD) Generalization]]
−
** [[Alpaca]] | Stanford
+
* [[Causation vs. Correlation]] ... [[Autocorrelation]] ...[[Convolution vs. Cross-Correlation (Autocorrelation)]]  
−
** [https://medium.com/@nkz.0814/generative-ai-100-usecase-d37a4ef42dad Generative AI 100 use case | Shunsuke Nakaji - Medium]
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* [[Development]] ... [[Notebooks]] ... [[Development#AI Pair Programming Tools|AI Pair Programming]] ... [[Codeless Options, Code Generators, Drag n' Drop|Codeless]] ... [[Hugging Face]] ... [[Algorithm Administration#AIOps/MLOps|AIOps/MLOps]] ... [[Platforms: AI/Machine Learning as a Service (AIaaS/MLaaS)|AIaaS/MLaaS]]
−
** [https://www.enterpriseappstoday.com/news/generative-ai-statistics.html Generative AI Statistics By Industry, Sector, Revenue and Facts | Barry Elad  - Enterprise Apps Today]
+
* [[Generative AI#Hallucination|Hallucination]]
−
* [[Capabilities]]  
+
* [[Alpaca]] | Stanford
−
** [[Video/Image]] ... [[Vision]] ... [[Colorize]] ... [[Image/Video Transfer Learning]]
+
* [https://medium.com/@nkz.0814/generative-ai-100-usecase-d37a4ef42dad Generative AI 100 use case | Shunsuke Nakaji - Medium]
−
** [[End-to-End Speech]] ... [[Synthesize Speech]] ... [[Speech Recognition]]  
+
* [https://www.enterpriseappstoday.com/news/generative-ai-statistics.html Generative AI Statistics By Industry, Sector, Revenue and Facts | Barry Elad  - Enterprise Apps Today]
 +
* [https://www.analyticsinsight.net/nasa-is-working-on-a-chatgpt-like-chatbot-for-astronauts/ NASA Is Working on A ChatGPT-Like Chatbot for Astronauts | Parvin Mohmad - Analytics Insight]
 +
* [[Risk, Compliance and Regulation]] ... [[Ethics]] ... [[Privacy]] ... [[Law]] ... [[AI Governance]] ... [[AI Verification and Validation]]
 
* [[AI Solver]]
 
* [[AI Solver]]
−
* [[Discriminative vs. Generative]]
 
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** [https://en.wikipedia.org/wiki/Generative_model Generative Model | Wikipedia]
 
 
** [[Generative Pre-trained Transformer (GPT)]]
 
** [[Generative Pre-trained Transformer (GPT)]]
 
** [[Generative Query Network (GQN)]]
 
** [[Generative Query Network (GQN)]]
 
** [[Data Quality#Data Augmentation, Data Labeling, and Auto-Tagging|Data Augmentation, Data Labeling, and Auto-Tagging]]
 
** [[Data Quality#Data Augmentation, Data Labeling, and Auto-Tagging|Data Augmentation, Data Labeling, and Auto-Tagging]]
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** [[Python]]   ... [[Generative AI with Python]] ... [[Javascript]] ... [[Generative AI with Javascript]] ... [[Game Development with Generative AI]]
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** [[Python]] ... [[Generative AI with Python|GenAI w/ Python]] ... [[JavaScript]] ... [[Generative AI with JavaScript|GenAI w/ JavaScript]] ... [[TensorFlow]] ... [[PyTorch]]
 
** [[Generative AI for Business Analysis]]
 
** [[Generative AI for Business Analysis]]
 
** [[Natural Language Generation (NLG)]]
 
** [[Natural Language Generation (NLG)]]
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* [[Moonshots#Emergence from Analogies|Emergence from Analogies]]
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* [[Gaming]] ... [[Game-Based Learning (GBL)]] ... [[Games - Security|Security]] ... [[Game Development with Generative AI|Generative AI]] ... [[Metaverse#Games - Metaverse|Games - Metaverse]] ... [[Games - Quantum Theme|Quantum]] ... [[Game Theory]] ... [[Game Design | Design]]
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* Demos, generating...
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* [https://arxiv.org/abs/2202.03164 Conversational Agents: Theory and Applications | Mattias Wahde and Marco Virgolin]
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** Music: [https://colab.research.google.com/notebooks/magenta/piano_transformer/piano_transformer.ipynb  Generating Piano Music with Transformer | I. Simon, A. Huang, J. Engel, C. "Fjord" Hawthorne - Google on Colab] play with pretrained [[Transformer]] models for piano music generation, based on the [https://magenta.tensorflow.org/music-transformer Music Transformer model]
+
 
−
** Faces: [https://colab.research.google.com/github/tensorflow/hub/blob/master/examples/colab/tf_hub_generative_image_module.ipynb TF-Hub generative image model | The TensorFlow Hub Authors - Google] use of a [https://www.tensorflow.org/hub TF-Hub] module based on a generative adversarial network (GAN). The module maps from N-dimensional vectors, called latent space, to RGB images.
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** 3D Objects: [https://colab.research.google.com/github/tensorflow/lucid/blob/master/notebooks/differentiable-parameterizations/style_transfer_3d.ipynb 3D Style Transfer | Google] uses Lucid to implement style transfer from a textured 3D model and a style image onto a new texture for the 3D model by using a [https://distill.pub/2018/differentiable-parameterizations/#section-style-transfer-3d Differentiable Image Parameterization]
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= Conversational [[Generative AI]] =
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* Demo, summarizing, priority listing, & analysis...
+
 
 +
* [[Bing]] | [[Microsoft]]
 +
* [[Bard]] | [[Google]] 
 +
* [https://aws.amazon.com/q/ Q] | [[Amazon]]
 +
* [https://www.caktus.ai/caktus_student Caktus AI]
 +
* [https://chai.ml/ Chai]
 +
* [[Character.AI|Character.AI ... Chat with your favorite Characters, discover millions of user-created AIs, each with their own personality  ... iOS and Android]]
 +
* [https://neuroflash.com/chatflash/ ChatFlash | Neuroflash] ... Templates and personalities help you make your chat more targeted and effective
 +
* [[ChatGPT]] | [[OpenAI]]
 
** [https://www.chatpdf.com/ ChatPDF]  
 
** [https://www.chatpdf.com/ ChatPDF]  
−
* Three main types:
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** [https://huggingface.co/spaces/ysharma/ChatGPT4 ChatGPT4 |] [[Hugging Face]]
−
** [[Autoencoder (AE) / Encoder-Decoder]]
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* [https://writesonic.com/chat Chatsonic | Writesonic]
−
** Sequence Models
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* [[Claude]] | [[Anthropic]]
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*** [[Transformer]]
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* [https://www.msn.com/en-us/money/markets/tech-giant-baidu-unveils-ernie-chinas-answer-to-chatgpts-ai-tech/ar-AA18LhNm Ernie | Baidu] ... 'Enhanced Representation of Knowledge Integration'
−
*** [[Recurrent Neural Network (RNN)]]
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* [https://www.forefront.ai/ Forefront AI]
−
*** [[Sequence to Sequence (Seq2Seq)]]
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* [https://www.pandorabots.com/mitsuku/ Mitsuku]
−
** Adversarial Networks
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* [https://librechat.ai/ LibreChat] ... [https://docs.librechat.ai/ documentation]
−
*** [[Conditional Adversarial Architecture (CAA)]]
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* [https://www.moveworks.com Moveworks]
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*** [[Generative Adversarial Network (GAN)]]
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* [https://www.netomi.com/ Netomi]
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*** [[Semi-Supervised Learning with Generative Adversarial Network (SSL-GAN)]]
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* [https://www.notion.so/product/ai Notion AI | Notion]
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*** [[Context-Conditional Generative Adversarial Network (CC-GAN)]]
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* [https://open-assistant.io/dashboard Open Assistant is an open-source AI assistant that uses and trains advanced language models to understand and respond to humans.]
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* [[Natural Language Processing (NLP)]]  ...[[Natural Language Generation (NLG)|Generation]] ...[[Large Language Model (LLM)|LLM]] ...[[Natural Language Tools & Services|Tools & Services]]
+
* [https://ora.ai/ Ora]
−
 
+
* [[Perplexity]] | Perplexity.ai  ... current information, including footnotes with links to the sources of the data
 +
* [[Pi]] | Inflection AI
 +
* [[PoE (Platform for Open Exploration)]]  ... takes all chatbots and puts them in one place; access [[ChatGPT]], [[Claude]]+, and [[GPT-4]] [[Large Language Model (LLM)|LLM]]  
 +
* [https://powervirtualagents.microsoft.com/en-us/ Power Virtual Agents |] [[Microsoft]]
 +
* [[Replika]] ... creates a digital representation of you
 +
* [https://novelai.net/ NovelAI] ... [[Silly Tavern]]
 +
* [https://techcrunch.com/2023/02/27/snapchat-launches-an-ai-chatbot-powered-by-openais-gpt-technology/ My AI | Snapchat]
 +
* [https://www.soundhound.com/ Soundhound] ... speech-to-meaning
 +
* [[You]] | You.com  ... the AI search engine you control; YouChat, YouCode, YouWrite, YouImagine, YouStudy, & YouSocial
  
−
Generative AI could improve the speed and accuracy of product research and [[development]]. Generative AI technology can also help with product engineering by allowing teams to simulate products in virtual environments. This allows for complex problems to be solved more quickly and efficiently, leading to improved design accuracy. - [https://www.forbes.com/sites/markminevich/2023/01/29/the-generative-ai-revolution-is-creating-the-next-phase-of-autonomous-enterprise/?sh=d98b66b1bc17 The Generative AI Revolution Is Creating The Next Phase Of Autonomous Enterprise | Mark Minevich - Forbes]
+
Conversational AI refers to technologies, like chatbots or virtual agents, which users can talk to. Conversational AI can also help you eliminate the [[Mental Block|blank sheet syndrome]] by providing prompting you with dialog and example content. They use large volumes of data, [[Machine Learning]], and [[Natural Language Processing (NLP)]] 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.
  
−
<hr><center><i>
 
−
Generative AI are predictive models, filtering available information to draw inferences on what should logically follow
 
−
</i></center><hr>
 
−
<i>[https://developers.google.com/machine-learning/gan/generative Background: What is a Generative Model? | Google]</i>
 
−
More formally, given a set of data instances X and a set of labels Y:
 
  
−
* <b>Generative</b> models capture the joint probability p(X, Y), or just p(X) if there are no labels.
+
<hr><center><b><i>
−
* <b>Discriminative</b> models capture the conditional probability p(Y | X).
 
  
−
A generative model includes the distribution of the data itself, and tells you how likely a given example is. For example, models that predict the next word in a sequence are typically generative models (usually much simpler than GANs) because they can assign a probability to a sequence of words.
+
Success is not about the absence of [[Mental Block|mental blocks]], but the ability to overcome them.
  
−
Informally:
+
</i></b></center><hr>
  
−
* <b>Generative</b> models can generate new data instances.
 
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* <b>Discriminative</b> models discriminate between different kinds of data instances.
 
−
<hr>
 
  
 +
Some examples of conversational AI include chatbots, virtual [[assistants]], [[Synthesize Speech|text-to-speech software]], and [[Speech Recognition]] software. 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 .
  
  
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<youtube>HyuBTMaKFmU</youtube>
 
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<youtube>L2TInyEUrCM</youtube>
 
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<youtube>reLhJnQd-Lo</youtube>
 
  
 +
= <span id="Chatbot"></span>Chatbot =
 +
[https://www.youtube.com/results?search_query=chatbot+build+QnA+artificial+intelligence+deep+machine+learning YouTube search...]
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[https://www.google.com/search?q=chatbot+build+QnA+artificial+intelligence+deep+machine+learning ...Google search]
 +
* [[Development]]  ... [[Development#AI Pair Programming Tools|AI Pair Programming Tools]]
 +
* [https://www.msn.com/en-us/video/money/chatgpt-artificial-intelligence-chatbots-and-a-world-of-unknowns-60-minutes/vi-AA18g6rj ChatGPT: Artificial Intelligence, chatbots and a world of unknowns | 60 Minutes]
 +
* [https://www.wordstream.com/blog/ws/chatbots 10 of the Most Innovative Chatbots on the Web | Dan Shewan - WordStream]
 +
* [https://www.zdnet.com/article/best-ai-chatbot/ The best AI chatbots: ChatGPT and other interesting alternatives to try | Sabrina Ortiz - ZDnet]
 +
* [https://www.engati.com/blog/types-of-chatbots-and-their-applications 6 types of chatbots - Which is best for your business? | Engati Team - Engati]
  
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== <span id="Roblox"></span>Roblox ==
+
Chatbot is a computer program that simulates conversation with human users, especially over the Internet. It can be used to provide customer service, answer questions, and help people find information quickly and easily. Chatbots are becoming increasingly popular as they become more sophisticated in their ability to understand natural language and respond appropriately. They can also be used for entertainment purposes, such as playing games or providing humorous responses.
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* [https://www.roblox.com/ Roblox]
+
[https://www.wikiwand.com/en/Chatbot Chatbot | Wikiwand]   ...[https://chrome.google.com/webstore/detail/wikiwand-wikipedia-modern/emffkefkbkpkgpdeeooapgaicgmcbolj Chrome Extension]
−
* [[Gaming]]
 
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* [[Game Development with ChatGPT]]
 
  
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Roblox is a gaming platform and publishing system that allows users to create and play 3D games online. Some of the technologies used with Roblox are:
+
= <span id="D-ID"></span>D-ID =
 +
* [https://www.d-id.com/ D-ID]
  
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* Roblox Studio, a [[development]] environment that provides tools for creating and publishing games on Roblox
+
Meet the Natural User Interface (NUI) by D-ID. The interface that humanizes interactions with everything digital. Build interfaces that understand the needs of users and can be communicated with effectively. No typing, no clicking, just face-to-face conversation. D-ID is an AI company that has a tool called Creative Reality Studio, that creates some really impressive looking AI avatars.
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* Roblox VR, a virtual reality feature that enables users to enjoy the games in immersive 3D environments
 
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* Generative AI, a new technology that uses artificial intelligence to generate code, assets, and content for Roblox games
 
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* [[Amazon]] AWS, a cloud computing service that hosts Roblox’s servers and data centers
 
  
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<youtube>kh67Aa455VI</youtube>
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<youtube>U9BjpmBIkLA</youtube>
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<youtube>4tU7HXaLubU</youtube>
 
  
−
== Deep Generative Modeling ==
 
  
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<youtube>SYSmgrSPBtY</youtube>
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= HumanFirst =
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<youtube>Ly3GAnq2p34</youtube>
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[https://www.youtube.com/results?search_query=HumanFirst+natural+language YouTube search...]
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<youtube>JVb54xhEw6Y</youtube>
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[https://www.google.com/search?q=HumanFirst+natural+language ...Google search]
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<youtube>vEAq_sBf1CA</youtube>
 
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<youtube>R8fx2b8Asg0</youtube>
 
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<youtube>bJhV2C5KKZ4</youtube>
 
  
−
== Generative Modeling Language ==
+
* [https://www.humanfirst.ai/ HumanFirst]
 +
* [https://cobusgreyling.medium.com/the-cobus-quadrant-of-nlu-design-4b1654f21d70 The Cobus Quadrant™ Of NLU Design | Cobus Greyling - Medium]
  
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<youtube>KeJINHjyzOU</youtube>
+
Company that specializes in creating AI-powered conversational interfaces for businesses. Their platform allows companies to build and deploy chatbots and virtual [[assistants]] that can communicate with customers through natural language processing.
  
−
= SynthAI =
+
== Traditional ==
  
 +
This architecture consisted of a [[Natural Language Processing (NLP)#Natural Language Understanding (NLU)|NLU]] model (Intents & Entities), a dialog state machine and pre-defined bot messages. In this architecture, there is not much “AI” involved. The dialog flow structure is pre-determined and hard-coded with state machine logic. The bot responses are fixed or at best a response message is concatenated with variable values inserted. As is the status quo with IVRs. Hence many chatbots were actually more of a ITR system (interactive text response). Considering that specific intents are assigned to specific sections of the flow…the only “AI” portion was the trained [[Natural Language Processing (NLP)#Natural Language Understanding (NLU)|NLU]] model which extracts intents and entities from user input based on probability.  [https://cobusgreyling.medium.com/existing-rigid-chatbot-architecture-needs-large-language-model-llm-flexibility-3b766be82f9d Existing Rigid Chatbot Architecture Needs Large Language Model (LLM) Flexibility | Cobus Greyling - Medium]
  
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To date, generative AI applications have overwhelmingly focused on the divergence of information. That is, they create new content based on a set of instructions. In Wave 2, we believe we will see more applications of AI to converge information. That is, they will show us less content by synthesizing the information available. Aptly, we refer to Wave 2 as synthesis AI (“SynthAI”) to contrast with Wave 1. While Wave 1 has created some value at the application layer, we believe Wave 2 will bring a step function change. -[https://a16z.com/2023/03/30/b2b-generative-ai-synthai/ For B2B Generative AI Apps, Is Less More? | Zeya Yang and Kristina Shen - Andreessen Horowitz]
+
== [[Natural Language Processing (NLP)#Natural Language Understanding (NLU)|Natural Language Understanding (NLU)]] Design ==
  
 +
Providing the full [[Natural Language Processing (NLP)#Natural Language Understanding (NLU)|NLU]] design end-to-end capabilities; with a pluggable data pipeline it allows teams to integrate different [[Natural Language Processing (NLP)#Natural Language Understanding (NLU)|NLU]] providers (for model training and evaluation) as well as ability to incorporate large language models to power the core ML-assisted workflows (like semantic search & clustering). [https://cobusgreyling.medium.com/the-cobus-quadrant-of-nlu-design-4b1654f21d70 NLU Design Landscape | Cobus Greyling - Medium]
  
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<img src="https://i2.wp.com/a16z.com/wp-content/uploads/2023/03/image1-2.png" width="1000">
 
  
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As we think through what Wave 2 might look like, we believe the use cases that will benefit most from synthesis AI will be when there is both:
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<img src="https://miro.medium.com/v2/resize:fit:1400/format:webp/1*yLwyX_HKYjwqFY0IkmesCw.png" width="800">
  
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A high volume of information, such that it’s not pragmatic for a human to manually sift through all the information.
 
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A high signal-to-noise ratio, such that the themes or insights are obvious and consistent. In the name of accuracy, you don’t want to task an AI model with deciphering nuance.
 
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In the diagram below, we categorize examples of common analysis and synthesis by these dimensions to help bring this to life.
 
  
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<img src="https://i0.wp.com/a16z.com/wp-content/uploads/2023/03/image4-1.png" width="1000">
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<youtube>aYbg0SodZcU</youtube>
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<youtube>kaOUO1-l3r4</youtube>

Latest revision as of 05:55, 30 January 2025

YouTube ... Quora ...Google search ...Google News ...Bing News


Conversational Generative AI

Conversational AI refers to technologies, like chatbots or virtual agents, which users can talk to. Conversational AI can also help you eliminate the blank sheet syndrome by providing prompting you with dialog and example content. They use large volumes of data, Machine Learning, and Natural Language Processing (NLP) 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.


Success is not about the absence of mental blocks, but the ability to overcome them.


Some examples of conversational AI include chatbots, virtual assistants, text-to-speech software, and Speech Recognition software. 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 .


Chatbot

YouTube search... ...Google search

Chatbot is a computer program that simulates conversation with human users, especially over the Internet. It can be used to provide customer service, answer questions, and help people find information quickly and easily. Chatbots are becoming increasingly popular as they become more sophisticated in their ability to understand natural language and respond appropriately. They can also be used for entertainment purposes, such as playing games or providing humorous responses. Chatbot | Wikiwand ...Chrome Extension

D-ID

Meet the Natural User Interface (NUI) by D-ID. The interface that humanizes interactions with everything digital. Build interfaces that understand the needs of users and can be communicated with effectively. No typing, no clicking, just face-to-face conversation. D-ID is an AI company that has a tool called Creative Reality Studio, that creates some really impressive looking AI avatars.


HumanFirst

YouTube search... ...Google search

Company that specializes in creating AI-powered conversational interfaces for businesses. Their platform allows companies to build and deploy chatbots and virtual assistants that can communicate with customers through natural language processing.

Traditional

This architecture consisted of a NLU model (Intents & Entities), a dialog state machine and pre-defined bot messages. In this architecture, there is not much “AI” involved. The dialog flow structure is pre-determined and hard-coded with state machine logic. The bot responses are fixed or at best a response message is concatenated with variable values inserted. As is the status quo with IVRs. Hence many chatbots were actually more of a ITR system (interactive text response). Considering that specific intents are assigned to specific sections of the flow…the only “AI” portion was the trained NLU model which extracts intents and entities from user input based on probability. Existing Rigid Chatbot Architecture Needs Large Language Model (LLM) Flexibility | Cobus Greyling - Medium

Natural Language Understanding (NLU) Design

Providing the full NLU design end-to-end capabilities; with a pluggable data pipeline it allows teams to integrate different NLU providers (for model training and evaluation) as well as ability to incorporate large language models to power the core ML-assisted workflows (like semantic search & clustering). NLU Design Landscape | Cobus Greyling - Medium



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