Best AI tools for< Increase Activation >

Orango AI is an AI application that provides AI agents for support and onboarding, guiding users through product usage. It offers autonomous UX testing, AI data extraction, and RPA solutions. The application helps increase user activation, reduce churn, and improve user experience by providing real-time guidance and suggestions based on user context and expertise.

Demand Spring is a strategic AI implementation platform for B2B marketing leaders. They offer services such as AI advisory for revenue acceleration, AI activation & growth services, training & enablement for AI-first mindset teams, and marketing automation & AI workflow agents. The platform helps B2B marketing leaders leverage AI and marketing automation platforms to transform operations, increase productivity, and create personalized customer engagement. Demand Spring aims to make AI and automation accessible, actionable, and impactful for their clients.

Kampfire is an AI-powered platform that transforms event photos into engaging, shareable content to enhance attendee engagement and brand reach. It offers personalized photo sharing, sponsor opportunities, event promotion, lead generation, and conditional actions. With features like facial recognition technology, personalized photo albums, interactive activations, and comprehensive event analytics, Kampfire helps event professionals create lasting memories and increase ROI.

Fini is a customer support AI chatbot that helps businesses resolve customer queries, increase retention, revenue, and activation. It integrates with various platforms like Zendesk, Slack, and Discord, and can be customized to match the tone and character of the business. Fini uses machine learning to learn from customer interactions and improve its responses over time. It offers features such as seamless human routing, multi-channel deployment, and feedback-based learning.

Humanic is an AI-powered marketing platform designed to help marketers create tailored content for micro-cohorts, drive higher activation and adoption rates, and optimize email campaigns. It uses advanced agentic AI to assist in building marketing campaigns and generating personalized content for different user segments. Humanic aims to help companies realize the potential of customer behaviors captured by PLG companies, improve user engagement, and increase revenue through targeted marketing strategies.

Neuwo is a leading contextual AI engine for content classification and automated tagging. It advocates that organizations of any size should have access to cutting-edge yet cost-effective contextual AI technology for meaningful automated content categorization and customization. The platform enables users to transition seamlessly from Oracle Grapeshot to Neuwo, offering advanced AI-driven algorithms for more precise targeting and increased engagement. Neuwo's technology ensures reaching the right audience at the right time, without the need for contracts. The platform enriches valuable data through intelligent content processing, brand safety, and suitability, and content activation, adding value to digital properties and businesses.

The Trend Video Idea Generator is an AI-powered tool designed to help users create engaging video ideas for social media platforms. By leveraging daily trends and AI technology, the tool assists users in generating unique and trending video concepts. Users can access the platform to spark creativity, enhance their social media presence, and stay up-to-date with the latest trends in the digital landscape. The tool aims to streamline the video ideation process and provide users with valuable insights to optimize their content strategy.

Persado is a leading provider of Generative AI (GenAI) solutions for marketing and customer engagement. Its Motivation AI platform leverages advanced AI, deep learning models, and a vast knowledge base of marketing communications to generate personalized language that motivates customers to engage and act. Persado's AI-powered solutions have been proven to drive significant revenue growth and conversion rate improvements for its customers across various industries, including retail, financial services, travel, and telecommunications.

Center AI is a local marketing platform that helps businesses optimize their online visibility, manage customer reviews, and drive foot traffic to physical stores. It offers features such as multiple location management, SEO monitoring, reputation management, review insights, and competitor tracking. Center AI has been proven to increase conversions, visibility, and positive interactions for businesses across various industries.

Growth Suite is an AI-powered buying intention targeting and smart discounts app for Shopify stores. It helps businesses understand each visitor's buying intention in real-time and offer them irresistible deals when their interest peaks. The app seamlessly integrates with Shopify stores, offering a native-like experience that enhances brand image while boosting conversions.

Whatmore is an AI-powered video commerce platform that helps e-commerce stores create engaging and shoppable videos to increase conversion rates. With Whatmore, you can easily create short videos in seconds, transform product images into videos, and add music and trending effects to your videos. You can also use Whatmore to import videos from Instagram and TikTok, and add shoppable tags to your videos to make them interactive. Whatmore offers a variety of features to help you create and share your videos, including a drag-and-drop video editor, a library of pre-made video templates, and a built-in video player. Whatmore also provides detailed analytics to help you track the performance of your videos and see how they are impacting your sales.

Neexa is an AI-powered sales CRM tool that autonomously engages prospects, nurtures leads with consistent follow-ups, and converts inquiries into paying customers 24/7. It is designed to help businesses effortlessly increase sales by leveraging AI technology to handle customer interactions and sales processes. Neexa's unique features and capabilities make it a valuable tool for businesses looking to streamline their sales operations and drive revenue growth.

Sale Whale is an AI-powered sales rep chatbot that helps businesses increase their sales and deliver success. Our chatbots are designed to handle customer inquiries, provide personalized recommendations, and close sales – all in real-time. We also offer a customer support bot that can help ensure clients understand how to use your product or service, so they can get the most out of it and stay around longer.

Brain.fm is a website that offers scientifically proven music to increase focus and productivity. The music is designed to blend into the background and stimulate the brain with gentle rhythmic pulses that support sustained attention. Brain.fm's music is not binaural beats, but rather an updated understanding of neuroscience and auditory processing to create a more effective and powerful solution.

GrowASO is an AI-driven App Store Optimization (ASO) platform that helps app developers and marketers increase their app downloads, revenue, and rankings. It offers a range of features including AI-powered app listing optimization, app icon experiments, keyword traffic and difficulty estimates, keyword rank tracking, and competitor analysis. GrowASO supports both iOS and Android apps and provides cross-platform optimization.

Plugger is an AI-powered graphic design assistant that automates various design tasks to help businesses create high-quality marketing materials, social media graphics, e-commerce photography, and more. With diverse capabilities and expertise in hundreds of styles, Plugger simplifies the design process and offers data-driven designs in seconds. It saves time, improves design quality, and enhances consistency, making it a valuable tool for marketing teams, startups, and e-commerce businesses.

Fountain is an AI-powered frontline workforce management platform that offers effortless hiring, efficient onboarding, easy HR compliance, simplified sourcing, and intelligent targeting solutions. It helps businesses streamline their hiring processes, increase retention rates, and optimize workforce experiences. Fountain's AI products enhance recruitment efficiency and deliver high volume hiring results through automated workflows and advanced AI-enabled tools. The platform also provides tailored features, early access to new products, and discounted pricing for users. With a focus on frontline hiring, Fountain collaborates with customers to develop new features and products regularly, ensuring a user-friendly experience for all.

Userpilot is a product growth platform that offers a comprehensive set of solutions to help product teams activate more users, increase feature adoption, and drive expansion revenue. The platform includes features such as product analytics, user engagement tools, user feedback mechanisms, user onboarding solutions, churn prevention strategies, in-app support, and product launch capabilities. Userpilot aims to help companies improve their product growth by providing personalized user experiences and actionable insights based on user behavior.

Wizart is a comprehensive platform that provides AI-powered visualization solutions for businesses. It offers a range of tools and services to help companies create engaging and immersive product visualizations, including a visualizer, material cloud, and vision API. With Wizart, businesses can eliminate the imagination gap and increase customer engagement by providing high-quality product content, such as renders, videos, and interactive models.

Famewall is a testimonial collection tool that helps businesses gather and showcase customer testimonials on their websites. It offers features such as easy testimonial collection, video testimonials, social proof widgets, and testimonial management. With Famewall, businesses can build trust with potential customers, increase conversions, and stand out from the competition by leveraging the power of customer feedback.

Atom is an accurate low-bit weight-activation quantization algorithm that combines mixed-precision, fine-grained group quantization, dynamic activation quantization, KV-cache quantization, and efficient CUDA kernels co-design. It introduces a low-bit quantization method, Atom, to maximize Large Language Models (LLMs) serving throughput with negligible accuracy loss. The codebase includes evaluation of perplexity and zero-shot accuracy, kernel benchmarking, and end-to-end evaluation. Atom significantly boosts serving throughput by using low-bit operators and reduces memory consumption via low-bit quantization.

This repository contains the training code of MobileLLM, a language model optimized for on-device use cases with fewer than a billion parameters. It integrates SwiGLU activation function, deep and thin architectures, embedding sharing, and grouped-query attention to achieve high-quality LLMs. MobileLLM-125M/350M shows significant accuracy improvements over previous models on zero-shot commonsense reasoning tasks. The design philosophy scales effectively to larger models, with state-of-the-art results for MobileLLM-600M/1B/1.5B.

The 'create-million-parameter-llm-from-scratch' repository provides a detailed guide on creating a Large Language Model (LLM) with 2.3 million parameters from scratch. The blog replicates the LLaMA approach, incorporating concepts like RMSNorm for pre-normalization, SwiGLU activation function, and Rotary Embeddings. The model is trained on a basic dataset to demonstrate the ease of creating a million-parameter LLM without the need for a high-end GPU.

RealtimeSTT is an easy-to-use, low-latency speech-to-text library for realtime applications. It listens to the microphone and transcribes voice into text, making it ideal for voice assistants and applications requiring fast and precise speech-to-text conversion. The library utilizes Voice Activity Detection, Realtime Transcription, and Wake Word Activation features. It supports GPU-accelerated transcription using PyTorch with CUDA support. RealtimeSTT offers various customization options for different parameters to enhance user experience and performance. The library is designed to provide a seamless experience for developers integrating speech-to-text functionality into their applications.

QServe is a serving system designed for efficient and accurate Large Language Models (LLM) on GPUs with W4A8KV4 quantization. It achieves higher throughput compared to leading industry solutions, allowing users to achieve A100-level throughput on cheaper L40S GPUs. The system introduces the QoQ quantization algorithm with 4-bit weight, 8-bit activation, and 4-bit KV cache, addressing runtime overhead challenges. QServe improves serving throughput for various LLM models by implementing compute-aware weight reordering, register-level parallelism, and fused attention memory-bound techniques.

This repository contains the source code for a GEMM & deep learning hardware accelerator system used to validate proposed systolic array hardware architectures implementing efficient matrix multiplication algorithms to increase performance-per-area limits of GEMM & AI accelerators. Achieved results include up to 3× faster CNN inference, >2× higher mults/multiplier/clock cycle, and low area with high clock frequency. The system is specialized for inference of non-sparse DNN models with fixed-point/quantized inputs, fully accelerating all DNN layers in hardware, and highly optimizing GEMM acceleration.

This project focuses on implementing Sparse Autoencoders (SAEs) for mechanistic interpretability in Large Language Models (LLMs) like Llama 3.2-3B. The SAEs aim to untangle superimposed representations in LLMs into separate, interpretable features for each neuron activation. The project provides an end-to-end pipeline for capturing training data, training the SAEs, analyzing learned features, and verifying results experimentally. It includes comprehensive logging, visualization, and checkpointing of SAE training, interpretability analysis tools, and a pure PyTorch implementation of Llama 3.1/3.2 chat and text completion. The project is designed for scalability, efficiency, and maintainability.

LLM Steer is a Python module designed to steer Large Language Models (LLMs) towards specific topics or subjects by adding steer vectors to different layers of the model. It enhances the model's capabilities, such as providing correct responses to logical puzzles. The tool should be used in conjunction with the transformers library. Users can add steering vectors to specific layers of the model with coefficients and text, retrieve applied steering vectors, and reset all steering vectors to the initial model. Advanced usage involves changing default parameters, but it may lead to the model outputting gibberish in most cases. The tool is meant for experimentation and can be used to enhance role-play characteristics in LLMs.

The 'fms-fsdp' repository is a companion to the Foundation Model Stack, providing a (pre)training example to efficiently train FMS models, specifically Llama2, using native PyTorch features like FSDP for training and SDPA implementation of Flash attention v2. It focuses on leveraging FSDP for training efficiently, not as an end-to-end framework. The repo benchmarks training throughput on different GPUs, shares strategies, and provides installation and training instructions. It trained a model on IBM curated data achieving high efficiency and performance metrics.

RAVE is a variational autoencoder for fast and high-quality neural audio synthesis. It can be used to generate new audio samples from a given dataset, or to modify the style of existing audio samples. RAVE is easy to use and can be trained on a variety of audio datasets. It is also computationally efficient, making it suitable for real-time applications.

GPTQModel is an easy-to-use LLM quantization and inference toolkit based on the GPTQ algorithm. It provides support for weight-only quantization and offers features such as dynamic per layer/module flexible quantization, sharding support, and auto-heal quantization errors. The toolkit aims to ensure inference compatibility with HF Transformers, vLLM, and SGLang. It offers various model supports, faster quant inference, better quality quants, and security features like hash check of model weights. GPTQModel also focuses on faster quantization, improved quant quality as measured by PPL, and backports bug fixes from AutoGPTQ.

Awesome-LLM-Quantization is a curated list of resources related to quantization techniques for Large Language Models (LLMs). Quantization is a crucial step in deploying LLMs on resource-constrained devices, such as mobile phones or edge devices, by reducing the model's size and computational requirements.

Minuet AI is a Neovim plugin that integrates with nvim-cmp to provide AI-powered code completion using multiple AI providers such as OpenAI, Claude, Gemini, Codestral, and Huggingface. It offers customizable configuration options and streaming support for completion delivery. Users can manually invoke completion or use cost-effective models for auto-completion. The plugin requires API keys for supported AI providers and allows customization of system prompts. Minuet AI also supports changing providers, toggling auto-completion, and provides solutions for input delay issues. Integration with lazyvim is possible, and future plans include implementing RAG on the codebase and virtual text UI support.

ceLLama is a streamlined automation pipeline for cell type annotations using large-language models (LLMs). It operates locally to ensure privacy, provides comprehensive analysis by considering negative genes, offers efficient processing speed, and generates customized reports. Ideal for quick and preliminary cell type checks.

This repository is a work in progress that contains first-principle implementations of groundbreaking AI algorithms using various deep learning frameworks. Each implementation is accompanied by supporting research papers, aiming to provide comprehensive educational resources for understanding and implementing foundational AI algorithms from scratch.

This repository contains a hand-curated list of great machine (deep) learning resources for Natural Language Processing (NLP) with a focus on Generative Pre-trained Transformer (GPT), Bidirectional Encoder Representations from Transformers (BERT), attention mechanism, Transformer architectures/networks, Chatbot, and transfer learning in NLP.

The LLM course is divided into three parts: 1. 🧩 **LLM Fundamentals** covers essential knowledge about mathematics, Python, and neural networks. 2. 🧑‍🔬 **The LLM Scientist** focuses on building the best possible LLMs using the latest techniques. 3. 👷 **The LLM Engineer** focuses on creating LLM-based applications and deploying them. For an interactive version of this course, I created two **LLM assistants** that will answer questions and test your knowledge in a personalized way: * 🤗 **HuggingChat Assistant**: Free version using Mixtral-8x7B. * 🤖 **ChatGPT Assistant**: Requires a premium account. ## 📝 Notebooks A list of notebooks and articles related to large language models. ### Tools | Notebook | Description | Notebook | |----------|-------------|----------| | 🧐 LLM AutoEval | Automatically evaluate your LLMs using RunPod |  | | 🥱 LazyMergekit | Easily merge models using MergeKit in one click. |  | | 🦎 LazyAxolotl | Fine-tune models in the cloud using Axolotl in one click. |  | | ⚡ AutoQuant | Quantize LLMs in GGUF, GPTQ, EXL2, AWQ, and HQQ formats in one click. |  | | 🌳 Model Family Tree | Visualize the family tree of merged models. |  | | 🚀 ZeroSpace | Automatically create a Gradio chat interface using a free ZeroGPU. |  |

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