Best AI tools for< Answer Baking Questions >

Kasisto is a conversational AI platform that provides financial institutions with the ability to create personalized, automated, and engaging digital experiences for their customers and employees. Kasisto's platform is infused with unmatched financial literacy and augments your workforce with remarkably competent digital bankers who facilitate accurate, human-like conversations and empower your teams with “in-the-moment” financial knowledge.

Interactions IVA is a conversational AI solutions platform for customer experience (CX). It offers a range of features to help businesses improve their customer interactions, including intelligent virtual assistants, PCI compliance, social customer care, and more. Interactions IVA is used by businesses in a variety of industries, including communications, finance and banking, healthcare, insurance, restaurants, retail and technology, travel and hospitality, and utilities.

Interview.study is an AI-powered interview preparation platform that helps candidates practice real interview questions asked by top companies. The platform provides users with instant feedback on their responses, helping them identify areas for improvement and develop stronger answers. Interview.study also offers a variety of features to help candidates prepare for their interviews, including a database of interview questions, a mock interview tool, and a resume builder.

Sensei AI is a real-time interview copilot application designed to provide assistance during live interviews. It offers instant answers to questions, personalized responses, and aims to help users land their dream job. The application uses advanced AI insights to understand the true intent behind interview questions, tailoring responses based on tone, word choices, keywords, timing, formality level, and context. Sensei AI also offers a hands-free experience, robust privacy features, and a personalized interview experience by tailoring answers to the user's job role, resume, and personal stories.

ChatCSV is a personal data analyst tool that allows users to upload CSV files and ask questions in natural language. It generates common questions about the data, visualizes answers with charts, and keeps a chat history for reference. It is useful for industries like retail, finance, banking, marketing, and advertising to analyze trends, customer behavior, and campaign performance.

Posh AI is an AI application designed specifically for the banking sector. It offers a range of AI solutions such as Voice Assistant, Digital Assistant, and Knowledge Assistant to enhance customer service, employee efficiency, and operational excellence in financial institutions. Posh AI aims to revolutionize the banking experience by providing 24/7 customer service, automating banking transactions, and improving access to information for employees. The platform integrates seamlessly with existing solutions and empowers banks to deliver better digital experiences through AI technology.

Hotseat AI is a legal research assistant that allows users to search through legal documents and find expert-level quotes matching their queries in seconds. It offers semantic search capabilities, metadata extraction, and the ability to search over both public and private documents. The tool is currently in private beta with a focus on EU regulations related to tech, fintech, banking, and financial services.

Onnix AI is a personalized AI co-pilot designed specifically for bankers, aiming to save teams time by providing accurate answers and deliverables quickly. It brings AI and powerful data science tools to the banking sector, offering features such as creating personalized slide decks, conducting Excel analysis, and querying data sources. Onnix AI caters to both senior and junior teams, enabling them to generate deeper insights and streamline their workflow efficiently.

Alltius is an AI platform that offers conversational AI agents for sales and support solutions in industries such as insurance, financial services, banking, SaaS, and industrial sectors. It provides personalized storytelling, instant help, and support for users, sales reps, and field staff. Alltius aims to redefine customer experiences by providing accurate responses, in-depth answers, and ensuring data privacy and security. The platform is designed to enhance customer interactions, increase sales conversions, and resolve customer queries efficiently.

Blozum is an advanced AI chat assistant application designed to enhance website conversions. It offers digital sales assistants that act as 24/7 sales force, engaging with platform visitors, providing instant answers, and guiding customers through purchase journeys. The application leverages AI to optimize interactions, personalize user experiences, and streamline the sales process. Blozum is suitable for various industries such as Ecommerce, Real Estate, Retail, Web3, Insurance, Banking, Edtech, Healthcare, and more.

Answer.AI is a practical AI R&D lab that creates end-user products based on foundational research breakthroughs. They focus on creating practical solutions and products using AI technologies. The lab aims to bridge the gap between theoretical research and real-world applications by developing innovative AI solutions.

Ubdroid AI Answer Engine is an AI-powered tool that utilizes various open-source LLMs to provide answers to user queries. It works by processing user queries and fetching relevant information from these LLMs. The accuracy of the answers depends on the quality and relevance of the data provided by the LLMs. The free version of the tool has a request limit of 10 requests per minute. If a model is not working, users can select another model.

BioloGPT is an AI tool designed to answer biology-related questions with insights and graphs. It provides information on various topics such as maintaining a healthy gut microbiome, foods for a healthy immune system, effects of cannabis on the brain, risks of Covid-19 vaccines, and advancements in psoriasis treatment. The tool is updated daily and cites full papers to support its answers.

Chatwith is a custom ChatGPT chatbot that can be integrated with your website and files. It can answer questions, perform tasks, and be customized to match your brand. With Chatwith, you can:

Slang.ai is a voice AI tool designed specifically for restaurants to intelligently handle phone calls. It allows restaurants to answer questions, take reservations, and provide a seamless customer experience. The tool is built to understand different accents, answer common questions, and manage reservations efficiently. Slang.ai helps restaurants increase reservations, improve ROI, and save time by handling calls 24/7. It offers customizable experiences, real-time analytics, and easy setup within minutes.

ChatNode is a powerful AI chatbot builder that helps businesses create next-generation chatbots that know everything about their business. With ChatNode, businesses can feed their chatbot all of their knowledge base in minutes, train the bot on any URLs or offline documents, and embed the bot anywhere on their website, in a pop-up chat, or on SLACK. ChatNode is packed with cutting-edge features, including live agent handoff, complete customization of the bots to match your brand, multiple data sources, fast and user-friendly testing and deployment, custom prompts, API access, SLACK integration, and support for 95 languages. ChatNode is also GDPR compliant and offers affordable pricing plans for startups and scale-ups.

Simple Phones is an AI-powered virtual phone system that allows businesses to never miss a call from customers. The application uses AI agents to answer inbound and outbound calls, log call details, offer affordable pricing plans, provide customization options, and support multiple languages and accents. Users can create their own AI agent in just 60 seconds and customize it for various use cases, such as booking appointments, answering FAQs, and routing calls to different team members. Simple Phones aims to enhance customer communication and streamline call handling processes for businesses of all sizes.

Frequentli is an AI-powered platform that helps businesses answer customer product inquiries quickly and gain valuable user insights. The platform offers a smart FAQ widget that not only provides fast answers to user questions but also offers actionable insights into user behavior and conversion barriers. Frequentli's dynamic widget responds to on-screen content automatically, enabling users to self-serve and access product information within seconds. With easy integration and generative insights, Frequentli empowers businesses to understand user needs and improve conversions without the need for in-depth analytics knowledge.

Ask2End is an AI-powered question-answering tool that provides comprehensive and accurate answers to any question you may have. It is designed to be user-friendly and accessible, allowing you to get the information you need quickly and easily.

ChatCube is an AI-powered chatbot maker that allows users to create chatbots for their websites without coding. It uses advanced AI technology to train chatbots on any document or website within 60 seconds. ChatCube offers a range of features, including a user-friendly visual editor, lightning-fast integration, fine-tuning on specific data sources, data encryption and security, and customizable chatbots. By leveraging the power of AI, ChatCube helps businesses improve customer support efficiency and reduce support ticket reductions by up to 28%.

LLM Foundry is a codebase for training, finetuning, evaluating, and deploying LLMs for inference with Composer and the MosaicML platform. It is designed to be easy-to-use, efficient _and_ flexible, enabling rapid experimentation with the latest techniques. You'll find in this repo: * `llmfoundry/` - source code for models, datasets, callbacks, utilities, etc. * `scripts/` - scripts to run LLM workloads * `data_prep/` - convert text data from original sources to StreamingDataset format * `train/` - train or finetune HuggingFace and MPT models from 125M - 70B parameters * `train/benchmarking` - profile training throughput and MFU * `inference/` - convert models to HuggingFace or ONNX format, and generate responses * `inference/benchmarking` - profile inference latency and throughput * `eval/` - evaluate LLMs on academic (or custom) in-context-learning tasks * `mcli/` - launch any of these workloads using MCLI and the MosaicML platform * `TUTORIAL.md` - a deeper dive into the repo, example workflows, and FAQs

Analyze the following text from a github repository (name and readme text at end) . Then, generate a JSON object with the following keys and provide the corresponding information for each key, in lowercase letters: 'description' (detailed description of the repo, must be less than 400 words，Ensure that no line breaks and quotation marks.),'for_jobs' (List 5 jobs suitable for this tool,in lowercase letters), 'ai_keywords' (keywords of the tool,user may use those keyword to find the tool,in lowercase letters), 'for_tasks' (list of 5 specific tasks user can use this tool to do,in lowercase letters), 'answer' (in english languages)

PyWxDump is a Python tool designed for obtaining WeChat account information, decrypting databases, viewing WeChat chats, and exporting chats as HTML backups. It provides core features such as extracting base address offsets of various WeChat data, decrypting databases, and combining multiple database types for unified viewing. Additionally, it offers extended functions like viewing chat history through the web, exporting chat logs in different formats, and remote viewing of WeChat chat history. The tool also includes document classes for database field descriptions, base address offset methods, and decryption methods for MAC databases. PyWxDump is suitable for network security, daily backup archiving, remote chat history viewing, and more.

This practical free hands-on course focuses on Large Language models and their applications, providing a hands-on experience using models from OpenAI and the Hugging Face library. The course is divided into three major sections: Techniques and Libraries, Projects, and Enterprise Solutions. It covers topics such as Chatbots, Code Generation, Vector databases, LangChain, Fine Tuning, PEFT Fine Tuning, Soft Prompt tuning, LoRA, QLoRA, Evaluate Models, Knowledge Distillation, and more. Each section contains chapters with lessons supported by notebooks and articles. The course aims to help users build projects and explore enterprise solutions using Large Language Models.

The 'nlp-llms-resources' repository is a comprehensive resource list for Natural Language Processing (NLP) and Large Language Models (LLMs). It covers a wide range of topics including traditional NLP datasets, data acquisition, libraries for NLP, neural networks, sentiment analysis, optical character recognition, information extraction, semantics, topic modeling, multilingual NLP, domain-specific LLMs, vector databases, ethics, costing, books, courses, surveys, aggregators, newsletters, papers, conferences, and societies. The repository provides valuable information and resources for individuals interested in NLP and LLMs.

Danswer is an open-source Gen-AI Chat and Unified Search tool that connects to your company's docs, apps, and people. It provides a Chat interface and plugs into any LLM of your choice. Danswer can be deployed anywhere and for any scale - on a laptop, on-premise, or to cloud. Since you own the deployment, your user data and chats are fully in your own control. Danswer is MIT licensed and designed to be modular and easily extensible. The system also comes fully ready for production usage with user authentication, role management (admin/basic users), chat persistence, and a UI for configuring Personas (AI Assistants) and their Prompts. Danswer also serves as a Unified Search across all common workplace tools such as Slack, Google Drive, Confluence, etc. By combining LLMs and team specific knowledge, Danswer becomes a subject matter expert for the team. Imagine ChatGPT if it had access to your team's unique knowledge! It enables questions such as "A customer wants feature X, is this already supported?" or "Where's the pull request for feature Y?"

InternLM-XComposer2 is a groundbreaking vision-language large model (VLLM) based on InternLM2-7B excelling in free-form text-image composition and comprehension. It boasts several amazing capabilities and applications: * **Free-form Interleaved Text-Image Composition** : InternLM-XComposer2 can effortlessly generate coherent and contextual articles with interleaved images following diverse inputs like outlines, detailed text requirements and reference images, enabling highly customizable content creation. * **Accurate Vision-language Problem-solving** : InternLM-XComposer2 accurately handles diverse and challenging vision-language Q&A tasks based on free-form instructions, excelling in recognition, perception, detailed captioning, visual reasoning, and more. * **Awesome performance** : InternLM-XComposer2 based on InternLM2-7B not only significantly outperforms existing open-source multimodal models in 13 benchmarks but also **matches or even surpasses GPT-4V and Gemini Pro in 6 benchmarks** We release InternLM-XComposer2 series in three versions: * **InternLM-XComposer2-4KHD-7B** 🤗: The high-resolution multi-task trained VLLM model with InternLM-7B as the initialization of the LLM for _High-resolution understanding_ , _VL benchmarks_ and _AI assistant_. * **InternLM-XComposer2-VL-7B** 🤗 : The multi-task trained VLLM model with InternLM-7B as the initialization of the LLM for _VL benchmarks_ and _AI assistant_. **It ranks as the most powerful vision-language model based on 7B-parameter level LLMs, leading across 13 benchmarks.** * **InternLM-XComposer2-VL-1.8B** 🤗 : A lightweight version of InternLM-XComposer2-VL based on InternLM-1.8B. * **InternLM-XComposer2-7B** 🤗: The further instruction tuned VLLM for _Interleaved Text-Image Composition_ with free-form inputs. Please refer to Technical Report and 4KHD Technical Reportfor more details.

Onyx is an open-source Gen-AI and Enterprise Search tool that serves as an AI Assistant connected to company documents, apps, and people. It provides a chat interface, can be deployed anywhere, and offers features like user authentication, role management, chat persistence, and UI for configuring AI Assistants. Onyx acts as an Enterprise Search tool across various workplace platforms, enabling users to access team-specific knowledge and perform tasks like document search, AI answers for natural language queries, and integration with common workplace tools like Slack, Google Drive, Confluence, etc.

PDFToChat is a tool that allows users to chat with their PDF documents in seconds. It is powered by Together AI and Pinecone, utilizing a tech stack including Next.js, Mixtral, M2 Bert, LangChain.js, MongoDB Atlas, Bytescale, Vercel, Clerk, and Tailwind CSS. Users can deploy the tool to Vercel or any other host by setting up Together.ai, MongoDB Atlas database, Bytescale, Clerk, and Vercel. The tool enables users to interact with PDFs through chat, with future tasks including adding features like trash icon for deleting PDFs, exploring different embedding models, implementing auto scrolling, improving replies, benchmarking accuracy, researching chunking and retrieval best practices, adding demo video, upgrading to Next.js 14, adding analytics, customizing tailwind prose, saving chats in postgres DB, compressing large PDFs, implementing custom uploader, session tracking, error handling, and support for images in PDFs.

The AI Enablement Stack is a curated collection of venture-backed companies, tools, and technologies that enable developers to build, deploy, and manage AI applications. It provides a structured view of the AI development ecosystem across five key layers: Agent Consumer Layer, Observability and Governance Layer, Engineering Layer, Intelligence Layer, and Infrastructure Layer. Each layer focuses on specific aspects of AI development, from end-user interaction to model training and deployment. The stack aims to help developers find the right tools for building AI applications faster and more efficiently, assist engineering leaders in making informed decisions about AI infrastructure and tooling, and help organizations understand the AI development landscape to plan technology adoption.

AI Audio Datasets List (AI-ADL) is a comprehensive collection of datasets consisting of speech, music, and sound effects, used for Generative AI, AIGC, AI model training, and audio applications. It includes datasets for speech recognition, speech synthesis, music information retrieval, music generation, audio processing, sound synthesis, and more. The repository provides a curated list of diverse datasets suitable for various AI audio tasks.

AWQ (Activation-aware Weight Quantization) is a tool designed for efficient and accurate low-bit weight quantization (INT3/4) for Large Language Models (LLMs). It supports instruction-tuned models and multi-modal LMs, providing features such as AWQ search for accurate quantization, pre-computed AWQ model zoo for various LLMs, memory-efficient 4-bit linear in PyTorch, and efficient CUDA kernel implementation for fast inference. The tool enables users to run large models on resource-constrained edge platforms, delivering more efficient responses with LLM/VLM chatbots through 4-bit inference.

CopilotKit is an open-source framework for building, deploying, and operating fully custom AI Copilots, including in-app AI chatbots, AI agents, and AI Textareas. It provides a set of components and entry points that allow developers to easily integrate AI capabilities into their applications. CopilotKit is designed to be flexible and extensible, so developers can tailor it to their specific needs. It supports a variety of use cases, including providing app-aware AI chatbots that can interact with the application state and take action, drop-in replacements for textareas with AI-assisted text generation, and in-app agents that can access real-time application context and take action within the application.

Vectara Answer is a sample app for Vectara-powered Summarized Semantic Search (or question-answering) with advanced configuration options. For examples of what you can build with Vectara Answer, check out Ask News, LegalAid, or any of the other demo applications.

This repository contains the code and instructions needed to build a sophisticated answer engine that leverages the capabilities of Groq, Mistral AI's Mixtral, Langchain.JS, Brave Search, Serper API, and OpenAI. Designed to efficiently return sources, answers, images, videos, and follow-up questions based on user queries, this project is an ideal starting point for developers interested in natural language processing and search technologies.

Do-Not-Answer is an open-source dataset curated to evaluate Large Language Models' safety mechanisms at a low cost. It consists of prompts to which responsible language models do not answer. The dataset includes human annotations and model-based evaluation using a fine-tuned BERT-like evaluator. The dataset covers 61 specific harms and collects 939 instructions across five risk areas and 12 harm types. Response assessment is done for six models, categorizing responses into harmfulness and action categories. Both human and automatic evaluations show the safety of models across different risk areas. The dataset also includes a Chinese version with 1,014 questions for evaluating Chinese LLMs' risk perception and sensitivity to specific words and phrases.

This project is a tutorial on developing large model applications for novice developers. It aims to provide a comprehensive introduction to large model development, focusing on Alibaba Cloud servers and integrating personal knowledge assistant projects. The tutorial covers the following topics: 1. **Introduction to Large Models**: A simplified introduction for novice developers on what large models are, their characteristics, what LangChain is, and how to develop an LLM application. 2. **How to Call Large Model APIs**: This section introduces various methods for calling APIs of well-known domestic and foreign large model products, including calling native APIs, encapsulating them as LangChain LLMs, and encapsulating them as Fastapi calls. It also provides a unified encapsulation for various large model APIs, such as Baidu Wenxin, Xunfei Xinghuo, and Zh譜AI. 3. **Knowledge Base Construction**: Loading, processing, and vector database construction of different types of knowledge base documents. 4. **Building RAG Applications**: Integrating LLM into LangChain to build a retrieval question and answer chain, and deploying applications using Streamlit. 5. **Verification and Iteration**: How to implement verification and iteration in large model development, and common evaluation methods. The project consists of three main parts: 1. **Introduction to LLM Development**: A simplified version of V1 aims to help beginners get started with LLM development quickly and conveniently, understand the general process of LLM development, and build a simple demo. 2. **LLM Development Techniques**: More advanced LLM development techniques, including but not limited to: Prompt Engineering, processing of multiple types of source data, optimizing retrieval, recall ranking, Agent framework, etc. 3. **LLM Application Examples**: Introduce some successful open source cases, analyze the ideas, core concepts, and implementation frameworks of these application examples from the perspective of this course, and help beginners understand what kind of applications they can develop through LLM. Currently, the first part has been completed, and everyone is welcome to read and learn; the second and third parts are under creation. **Directory Structure Description**: requirements.txt: Installation dependencies in the official environment notebook: Notebook source code file docs: Markdown documentation file figures: Pictures data_base: Knowledge base source file used

LLocalSearch is a completely locally running search aggregator using LLM Agents. The user can ask a question and the system will use a chain of LLMs to find the answer. The user can see the progress of the agents and the final answer. No OpenAI or Google API keys are needed.

Your GBBO-inspired star baker

From dough to devotion: Your guide for enriched baking and faith.

Master the Investment Banking Interview Arena: Chatbot Solutions to Ace Any Banking Question

Answer anything about SELECT trial

Evidence-based answers to important questions, grounded in interdisciplinary knowledge and diverse perspectives.

will answer your question directly without the bs

A blog article writer specializing in answer-type content.

Friendly guide for podcasting newbies.

A GPT that guides to answers, never giving them directly.

I will answer all your game of throne related questions, both from books and the TV series.

Answer your question about Fess

Answer a few questions and let JingleBot make the perfect stress-free holiday shopping list. So fun !

Let humans answer difficult questions for which GPT doesn't know the solution yet.

My name is Domingo! I've been a Chihuahua my whole life! I can answer any questions about Chihuahuas you may have. Ask me anything, I want to help!

I answer questions and find related YouTube videos.

Answer concisely, then suggest three related questions.

Using OpenLLMLeaderboard data to answer your questions about LLM. For Currently!

Answer anything about ORBITA-2 trial

provide a number ,you will find the answer

A chatbot designed to answer questions related to ADP 6-22, Army Leadership and the Profession