Best AI tools for< Accelerate Computation >

Lilac is an AI tool designed to enhance data quality and exploration for AI applications. It offers features such as data search, quantification, editing, clustering, semantic search, field comparison, and fuzzy-concept search. Lilac enables users to accelerate dataset computations and transformations, making it a valuable asset for data scientists and AI practitioners. The tool is trusted by Alignment Lab and is recommended for working with LLM datasets.

Zapata AI is an Industrial Generative AI application that empowers enterprises to revolutionize their industry by building and deploying cutting-edge AI applications. It specializes in tackling complex business challenges with precision using quantum techniques and advanced computing technologies. The platform offers solutions for various industries, accelerates quantum research, and provides expert perspectives on Generative AI and quantum computing.

Cerebras is an AI tool that offers products and services related to AI supercomputers, cloud system processors, and applications for various industries. It provides high-performance computing solutions, including large language models, and caters to sectors such as health, energy, government, scientific computing, and financial services. Cerebras specializes in AI model services, offering state-of-the-art models and training services for tasks like multi-lingual chatbots and DNA sequence prediction. The platform also features the Cerebras Model Zoo, an open-source repository of AI models for developers and researchers.

Proscia is a leading provider of digital pathology solutions for the modern laboratory. Its flagship product, Concentriq, is an enterprise pathology platform that enables anatomic pathology laboratories to achieve 100% digitization and deliver faster, more precise results. Proscia also offers a range of AI applications that can be used to automate tasks, improve diagnostic accuracy, and accelerate research. The company's mission is to perfect cancer diagnosis with intelligent software that changes the way the world practices pathology.

Cradle is a protein engineering platform that uses machine learning to design improved protein sequences. It allows users to import assay data, generate new sequences, test them in the lab, and import the results to improve the model. Cradle can be used to optimize multiple properties of a protein simultaneously, and it has been used by leading biotech teams to accelerate new and ongoing projects.

Altair is a global leader in computational intelligence, offering software and cloud solutions in simulation, HPC, data analytics, and AI. The platform provides advanced technology for accelerating AI adoption, powering engineering processes, and enabling sustainability solutions across various industries. Altair's products and platforms cater to diverse sectors such as aerospace, automotive, healthcare, and more, with a focus on digital twin technology, generative AI, and cloud computing. The company also hosts events, webinars, and training programs to support users in leveraging their tools effectively.

Lavo Life Sciences is an AI-accelerated crystal structure prediction application that helps in drug development by providing accurate predictions for small molecule drugs. The application utilizes AI technology to optimize solid-state formulations, reduce turnaround time, mitigate risks, and discover novel polymorphs, ultimately streamlining the pharmaceutical research and development process.

Accio is a data modeling tool that allows users to define consistent relationships, metrics, and expressions for on-the-fly computations in reports and dashboards across various BI tools. It provides a syntax similar to GraphQL that allows users to define models, relationships, and metrics in a human-readable format. Accio also offers a user-friendly interface that provides data analysts with a holistic view of the relationships between their data models, enabling them to grasp the interconnectedness and dependencies within their data ecosystem. Additionally, Accio utilizes DuckDB as a caching layer to accelerate query performance for BI tools.

Owkin is a full-stack AI biotech company that integrates the best of human and artificial intelligence to deliver better drugs and diagnostics at scale. By understanding complex biology through AI, Owkin identifies new treatments, de-risks and accelerates clinical trials, and builds diagnostic tools to reduce time to impact for patients.

BizWith.AI is an AI-powered automation platform that helps businesses save time, cut costs, and outperform the competition. With BizWith.AI, businesses can create unique, plagiarism-free content, images, voice overs and transcriptions in a matter of seconds. They can also schedule posts, automate responses, and get insights to enhance their social media presence. BizWith.AI's AI-powered chatbot can handle customer queries effectively, reducing support costs and improving customer satisfaction. Businesses can also expand their team with 32 AI agents and coders, providing them with a diverse range of specialized assistance.

Trend Hunter is an AI-powered platform that offers a vast database of ideas and innovations, trend reports, consumer insights, advisory services, and training programs. It combines human researchers with AI to provide data-driven insights for innovators. The platform helps businesses accelerate innovation, identify trends, and stay ahead of the competition. Trend Hunter's AI capabilities include natural language processing, machine learning, image recognition, and consumer insights analysis.

Artwork Flow is an AI-powered artwork management software that helps streamline compliance checks, proofreading, and automation processes for packaging artwork. It empowers brand and marketing teams to achieve faster time to market by providing unified and intelligent creative management. The software offers features such as online proofing, smart tagging, workflow automation, and brand compliance checks. Artwork Flow is trusted by global packaging artwork teams and has received positive feedback for its effectiveness and user-friendly interface.

GapScout is a market research software powered by AI technology that helps businesses dominate their market by analyzing customer reviews to identify gaps and opportunities. It provides actionable insights based on real market feedback, enabling users to improve their products, spy on competitors, and accelerate sales growth. With a focus on extracting valuable information from reviews, GapScout aims to position brands for success and establish long-term dominance in the market.

The Deepfake Detection Challenge Dataset is a project initiated by Facebook AI to accelerate the development of new ways to detect deepfake videos. The dataset consists of over 100,000 videos and was created in collaboration with industry leaders and academic experts. It includes two versions: a preview dataset with 5k videos and a full dataset with 124k videos, each featuring facial modification algorithms. The dataset was used in a Kaggle competition to create better models for detecting manipulated media. The top-performing models achieved high accuracy on the public dataset but faced challenges when tested against the black box dataset, highlighting the importance of generalization in deepfake detection. The project aims to encourage the research community to continue advancing in detecting harmful manipulated media.

ytRank.ai is an AI-powered tool designed to help YouTube creators optimize their content strategy, outsmart the competition, and accelerate channel growth. It offers a range of powerful features such as discovering trending keywords, analyzing SEO scores, generating compelling titles, and creating optimized tags. By leveraging AI technology, ytRank.ai aims to boost channel rankings, visibility, and attract more viewers. With a focus on increasing visibility, engagement, and long-term growth, ytRank.ai is a valuable tool for YouTubers seeking to enhance their online presence.

PLEASEDONTCODE is an AI Code Generator specifically designed for Arduino and ESP32 embedded systems. It simplifies the coding process for users, helping them overcome common obstacles in programming such as compilation errors, syntax confusion, and logic issues. By automating code generation, the tool ensures error-free, syntactically correct, and logically sound code with clear comments for easy understanding. It aims to streamline project execution, increase productivity, and accelerate the development of prototype projects.

Adjust is an AI-driven platform that helps mobile app developers accelerate their app's growth through a comprehensive suite of measurement, analytics, automation, and fraud prevention tools. The platform offers unlimited measurement capabilities across various platforms, powerful analytics and reporting features, AI-driven decision-making recommendations, streamlined operations through automation, and data protection against mobile ad fraud. Adjust also provides solutions for iOS and SKAdNetwork success, CTV and OTT performance enhancement, ROI measurement, fraud prevention, and incrementality analysis. With a focus on privacy and security, Adjust empowers app developers to optimize their marketing strategies and drive tangible growth.

Tidio is an AI-powered customer service solution that helps businesses automate support, convert more leads, and increase revenue. With Lyro AI Chatbot, businesses can answer up to 70% of customer inquiries without human intervention, freeing up support agents to focus on high-value requests. Tidio also offers live chat, helpdesk, and automation features to help businesses provide excellent customer support and grow their business.

Tidio is an AI-powered customer service solution that helps businesses automate their support and sales processes. With Lyro AI Chatbot, businesses can solve up to 70% of customer problems without human intervention. Tidio also offers live chat, helpdesk, and automation features to help businesses provide excellent customer service and grow their revenue.

EarnBetter is an AI-powered platform that offers assistance in creating professional resumes, cover letters, and job search support. The platform utilizes artificial intelligence to rewrite and reformat resumes, generate tailored cover letters, provide personalized job matches, and offer interview support. Users can upload their current resume to get started and access a range of features to enhance their job search process. EarnBetter aims to streamline the job search experience by providing free, unlimited, and professional document creation services.

MInference is a tool designed to accelerate pre-filling for long-context Language Models (LLMs) by leveraging dynamic sparse attention. It achieves up to a 10x speedup for pre-filling on an A100 while maintaining accuracy. The tool supports various decoding LLMs, including LLaMA-style models and Phi models, and provides custom kernels for attention computation. MInference is useful for researchers and developers working with large-scale language models who aim to improve efficiency without compromising accuracy.

The Radicalbit AI Monitoring Platform provides a comprehensive solution for monitoring Machine Learning and Large Language models in production. It helps proactively identify and address potential performance issues by analyzing data quality, model quality, and model drift. The repository contains files and projects for running the platform, including UI, API, SDK, and Spark components. Installation using Docker compose is provided, allowing deployment with a K3s cluster and interaction with a k9s container. The platform documentation includes a step-by-step guide for installation and creating dashboards. Community engagement is encouraged through a Discord server. The roadmap includes adding functionalities for batch and real-time workloads, covering various model types and tasks.

WebLLM is a modular and customizable javascript package that directly brings language model chats directly onto web browsers with hardware acceleration. Everything runs inside the browser with no server support and is accelerated with WebGPU. WebLLM is fully compatible with OpenAI API. That is, you can use the same OpenAI API on any open source models locally, with functionalities including json-mode, function-calling, streaming, etc. We can bring a lot of fun opportunities to build AI assistants for everyone and enable privacy while enjoying GPU acceleration.

New AI Drug Discovery is a repository focused on the applications of Large Language Models (LLM) in drug discovery. It provides resources, tools, and examples for leveraging LLM technology in the pharmaceutical industry. The repository aims to showcase the potential of using AI-driven approaches to accelerate the drug discovery process, improve target identification, and optimize molecular design. By exploring the intersection of artificial intelligence and drug development, this repository offers insights into the latest advancements in computational biology and cheminformatics.

TriForce is a training-free tool designed to accelerate long sequence generation. It supports long-context Llama models and offers both on-chip and offloading capabilities. Users can achieve a 2.2x speedup on a single A100 GPU. TriForce also provides options for offloading with tensor parallelism or without it, catering to different hardware configurations. The tool includes a baseline for comparison and is optimized for performance on RTX 4090 GPUs. Users can cite the associated paper if they find TriForce useful for their projects.

Awesome LLM compression research papers and tools to accelerate LLM training and inference.

InfLLM is a training-free memory-based method that unveils the intrinsic ability of LLMs to process streaming long sequences. It stores distant contexts into additional memory units and employs an efficient mechanism to lookup token-relevant units for attention computation. Thereby, InfLLM allows LLMs to efficiently process long sequences while maintaining the ability to capture long-distance dependencies. Without any training, InfLLM enables LLMs pre-trained on sequences of a few thousand tokens to achieve superior performance than competitive baselines continually training these LLMs on long sequences. Even when the sequence length is scaled to 1, 024K, InfLLM still effectively captures long-distance dependencies.

AITreasureBox is a comprehensive collection of AI tools and resources designed to simplify and accelerate the development of AI projects. It provides a wide range of pre-trained models, datasets, and utilities that can be easily integrated into various AI applications. With AITreasureBox, developers can quickly prototype, test, and deploy AI solutions without having to build everything from scratch. Whether you are working on computer vision, natural language processing, or reinforcement learning projects, AITreasureBox has something to offer for everyone. The repository is regularly updated with new tools and resources to keep up with the latest advancements in the field of artificial intelligence.

MaskLLM is a learnable pruning method that establishes Semi-structured Sparsity in Large Language Models (LLMs) to reduce computational overhead during inference. It is scalable and benefits from larger training datasets. The tool provides examples for running MaskLLM with Megatron-LM, preparing LLaMA checkpoints, pre-tokenizing C4 data for Megatron, generating prior masks, training MaskLLM, and evaluating the model. It also includes instructions for exporting sparse models to Huggingface.

Reinforcement Learning from AI Feedback (RLAIF) is a concept that describes a type of machine learning approach where **an AI agent learns by receiving feedback or guidance from another AI system**. This concept is closely related to the field of Reinforcement Learning (RL), which is a type of machine learning where an agent learns to make a sequence of decisions in an environment to maximize a cumulative reward. In traditional RL, an agent interacts with an environment and receives feedback in the form of rewards or penalties based on the actions it takes. It learns to improve its decision-making over time to achieve its goals. In the context of Reinforcement Learning from AI Feedback, the AI agent still aims to learn optimal behavior through interactions, but **the feedback comes from another AI system rather than from the environment or human evaluators**. This can be **particularly useful in situations where it may be challenging to define clear reward functions or when it is more efficient to use another AI system to provide guidance**. The feedback from the AI system can take various forms, such as: - **Demonstrations** : The AI system provides demonstrations of desired behavior, and the learning agent tries to imitate these demonstrations. - **Comparison Data** : The AI system ranks or compares different actions taken by the learning agent, helping it to understand which actions are better or worse. - **Reward Shaping** : The AI system provides additional reward signals to guide the learning agent's behavior, supplementing the rewards from the environment. This approach is often used in scenarios where the RL agent needs to learn from **limited human or expert feedback or when the reward signal from the environment is sparse or unclear**. It can also be used to **accelerate the learning process and make RL more sample-efficient**. Reinforcement Learning from AI Feedback is an area of ongoing research and has applications in various domains, including robotics, autonomous vehicles, and game playing, among others.

PEFT (Parameter-Efficient Fine-Tuning) is a collection of state-of-the-art methods that enable efficient adaptation of large pretrained models to various downstream applications. By only fine-tuning a small number of extra model parameters instead of all the model's parameters, PEFT significantly decreases the computational and storage costs while achieving performance comparable to fully fine-tuned models.

Open-ChatGPT is an open-source library that enables users to train a hyper-personalized ChatGPT-like AI model using their own data with minimal computational resources. It provides an end-to-end training framework for ChatGPT-like models, supporting distributed training and offloading for extremely large models. The project implements RLHF (Reinforcement Learning with Human Feedback) powered by transformer library and DeepSpeed, allowing users to create high-quality ChatGPT-style models. Open-ChatGPT is designed to be user-friendly and efficient, aiming to empower users to develop their own conversational AI models easily.

DashInfer is a C++ runtime tool designed to deliver production-level implementations highly optimized for various hardware architectures, including x86 and ARMv9. It supports Continuous Batching and NUMA-Aware capabilities for CPU, and can fully utilize modern server-grade CPUs to host large language models (LLMs) up to 14B in size. With lightweight architecture, high precision, support for mainstream open-source LLMs, post-training quantization, optimized computation kernels, NUMA-aware design, and multi-language API interfaces, DashInfer provides a versatile solution for efficient inference tasks. It supports x86 CPUs with AVX2 instruction set and ARMv9 CPUs with SVE instruction set, along with various data types like FP32, BF16, and InstantQuant. DashInfer also offers single-NUMA and multi-NUMA architectures for model inference, with detailed performance tests and inference accuracy evaluations available. The tool is supported on mainstream Linux server operating systems and provides documentation and examples for easy integration and usage.

A curated list of high-quality papers on resource-efficient Large Language Models (LLMs) with a focus on various aspects such as architecture design, pre-training, fine-tuning, inference, system design, and evaluation metrics. The repository covers topics like efficient transformer architectures, non-transformer architectures, memory efficiency, data efficiency, model compression, dynamic acceleration, deployment optimization, support infrastructure, and other related systems. It also provides detailed information on computation metrics, memory metrics, energy metrics, financial cost metrics, network communication metrics, and other metrics relevant to resource-efficient LLMs. The repository includes benchmarks for evaluating the efficiency of NLP models and references for further reading.

Easy-Translate is a script designed for translating large text files with a single command. It supports various models like M2M100, NLLB200, SeamlessM4T, LLaMA, and Bloom. The tool is beginner-friendly and offers seamless and customizable features for advanced users. It allows acceleration on CPU, multi-CPU, GPU, multi-GPU, and TPU, with support for different precisions and decoding strategies. Easy-Translate also provides an evaluation script for translations. Built on HuggingFace's Transformers and Accelerate library, it supports prompt usage and loading huge models efficiently.

The 'machine-learning-research' repository is a comprehensive collection of resources related to mathematics, machine learning, deep learning, artificial intelligence, data science, and various scientific fields. It includes materials such as courses, tutorials, books, podcasts, communities, online courses, papers, and dissertations. The repository covers topics ranging from fundamental math skills to advanced machine learning concepts, with a focus on applications in healthcare, genetics, computational biology, precision health, and AI in science. It serves as a valuable resource for individuals interested in learning and researching in the fields of machine learning and related disciplines.

TornadoVM is a plug-in to OpenJDK and GraalVM that allows programmers to automatically run Java programs on heterogeneous hardware. TornadoVM targets OpenCL, PTX and SPIR-V compatible devices which include multi-core CPUs, dedicated GPUs (Intel, NVIDIA, AMD), integrated GPUs (Intel HD Graphics and ARM Mali), and FPGAs (Intel and Xilinx).

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.

DuoAttention is a framework designed to optimize long-context large language models (LLMs) by reducing memory and latency during inference without compromising their long-context abilities. It introduces a concept of Retrieval Heads and Streaming Heads to efficiently manage attention across tokens. By applying a full Key and Value (KV) cache to retrieval heads and a lightweight, constant-length KV cache to streaming heads, DuoAttention achieves significant reductions in memory usage and decoding time for LLMs. The framework uses an optimization-based algorithm with synthetic data to accurately identify retrieval heads, enabling efficient inference with minimal accuracy loss compared to full attention. DuoAttention also supports quantization techniques for further memory optimization, allowing for decoding of up to 3.3 million tokens on a single GPU.

NoLabs is an open-source biolab that provides easy access to state-of-the-art models for bio research. It supports various tasks, including drug discovery, protein analysis, and small molecule design. NoLabs aims to accelerate bio research by making inference models accessible to everyone.

Accelerate web app development with Material Tailwind GPT's components - 10x faster.

Accelerates the learning of key phrases and cultural norms for travelers in various languages.

Expert in tailored accelerator search for startups.

The Go-To Coach for Aspiring Digital Entrepreneurs, Innovators, & Startups. Learn More at UnderdogInnovationInc.com.

Niche-focused startup guide, humorous, strategic, simplifying ideas.

Drop in any requirements or any text ; I'll help you create an MVP with insights.

A guide for developing university-focused digital startup accelerator programs.