Best AI tools for< Optimize Biomarker Scoring >

Nucleai is an AI-driven spatial biomarker analysis tool that leverages military intelligence-grade geospatial AI methods to analyze complex cellular interactions in a patient's biopsy. The platform offers a first-of-its-kind multimodal solution by ingesting images from various modalities and delivering actionable insights to optimize biomarker scoring, predict response to therapy, and revolutionize disease diagnosis and treatment.

Paige is a leading AI company revolutionizing pathology with next-generation technology. They provide diagnostic and biomarker AI, predictive analytics technology, and AI-assisted applications to support cancer detection, subtyping, and molecular biomarker discovery from tissue samples. Paige offers a range of AI suites for prostate, breast, colon, and PanCancer, as well as the innovative Paige Alba™ multi-modal co-pilot. Their advanced AI technology and services help streamline AI development, optimize existing applications, and drive groundbreaking advancements in cancer care.

Beacon Biosignals provides an EEG neurobiomarker platform that is designed to accelerate clinical trials and enable new treatments for patients with neurological and psychiatric diseases. Their platform is powered by machine learning and a world-class clinico-EEG database, which allows them to analyze existing EEG data for insights into mechanisms, PK/PD, and patient stratification. This information can be used to guide further development efforts, optimize clinical trials, and enhance understanding of treatment efficacy.

Qualtrics XM is a leading Experience Management Software that helps businesses optimize customer experiences, employee engagement, and market research. The platform leverages specialized AI to uncover insights from data, prioritize actions, and empower users to enhance customer and employee experience outcomes. Qualtrics XM offers solutions for Customer Experience, Employee Experience, Strategy & Research, and more, enabling organizations to drive growth and improve performance.

The Shopify App Store is a platform that offers a wide variety of applications to enhance and customize Shopify stores. With over 8,000 apps available, users can find tools for sales channels, product sourcing, marketing, store design, order management, and more. These apps are designed to help merchants optimize their online stores, improve customer experience, and boost sales.

Cloudflare is a platform that offers a range of products and services to help users build, secure, and optimize their websites and applications. It provides solutions for web analytics, troubleshooting errors, domain registration, content delivery, and more. Cloudflare also offers developer products like Workers and AI products like AI Vectorize and AI Gateway. Additionally, Cloudflare provides Zero Trust Access, Tunnel Gateway, and Browser Isolation services to enhance security and performance. The platform aims to simplify the process of managing online assets and improving user experience.

Jobscan is a comprehensive job search tool that helps job seekers optimize their resumes, cover letters, and LinkedIn profiles to increase their chances of getting interviews. It uses artificial intelligence and machine learning technology to analyze job descriptions and identify the skills and keywords that recruiters are looking for. Jobscan then provides personalized suggestions on how to tailor your application materials to each specific job you apply for. In addition to its resume and cover letter optimization tools, Jobscan also offers a job tracker, a LinkedIn optimization tool, and a career change tool. With its powerful suite of features, Jobscan is an essential tool for any job seeker who wants to land their dream job.

TestMarket is an AI-powered sales optimization platform for online marketplace sellers. It offers a range of services to help sellers increase their visibility, boost sales, and improve their overall performance on marketplaces such as Amazon, Etsy, and Walmart. TestMarket's services include product promotion, keyword analysis, Google Ads and SEO optimization, and advertising optimization.

VWO is a comprehensive experimentation platform that enables businesses to optimize their digital experiences and maximize conversions. With a suite of products designed for the entire optimization program, VWO empowers users to understand user behavior, validate optimization hypotheses, personalize experiences, and deliver tailored content and experiences to specific audience segments. VWO's platform is designed to be enterprise-ready and scalable, with top-notch features, strong security, easy accessibility, and excellent performance. Trusted by thousands of leading brands, VWO has helped businesses achieve impressive growth through experimentation loops that shape customer experience in a positive direction.

Botify AI is an AI-powered tool designed to assist users in optimizing their website's performance and search engine rankings. By leveraging advanced algorithms and machine learning capabilities, Botify AI provides valuable insights and recommendations to improve website visibility and drive organic traffic. Users can analyze various aspects of their website, such as content quality, site structure, and keyword optimization, to enhance overall SEO strategies. With Botify AI, users can make data-driven decisions to enhance their online presence and achieve better search engine results.

Siteimprove is an AI-powered platform that offers a comprehensive suite of digital governance, analytics, and SEO tools to help businesses optimize their online presence. It provides solutions for digital accessibility, quality assurance, content analytics, search engine marketing, and cross-channel advertising. With features like AI-powered insights, automated analysis, and machine learning capabilities, Siteimprove empowers users to enhance their website's reach, reputation, revenue, and returns. The platform transcends traditional boundaries by addressing a wide range of digital requirements and impact-drivers, making it a valuable tool for businesses looking to improve their online performance.

SiteSpect is an AI-driven platform that offers A/B testing, personalization, and optimization solutions for businesses. It provides capabilities such as analytics, visual editor, mobile support, and AI-driven product recommendations. SiteSpect helps businesses validate ideas, deliver personalized experiences, manage feature rollouts, and make data-driven decisions. With a focus on conversion and revenue success, SiteSpect caters to marketers, product managers, developers, network operations, retailers, and media & entertainment companies. The platform ensures faster site performance, better data accuracy, scalability, and expert support for secure and certified optimization.

EverSQL is an AI-powered tool designed for SQL query optimization, database observability, and cost reduction for PostgreSQL and MySQL databases. It automatically optimizes SQL queries using smart AI-based algorithms, provides ongoing performance insights, and helps reduce monthly database costs by offering optimization recommendations. With over 100,000 professionals trusting EverSQL, it aims to save time, improve database performance, and enhance cost-efficiency without accessing sensitive data.

Attention Insight is an AI-driven pre-launch analytics tool that provides crucial insights into consumer engagement with designs before the launch. By using predictive attention heatmaps and AI-generated attention analytics, users can optimize their concepts for better performance, validate designs, and improve user experience. The tool offers accurate data based on psychological research, helping users make informed decisions and save time and resources. Attention Insight is suitable for various types of analysis, including desktop, marketing material, mobile, posters, packaging, and shelves.

Competera is an AI-powered pricing platform designed for online and omnichannel retailers. It offers a unified workplace with an easy-to-use interface, real-time market data, and AI-powered product matching. Competera focuses on demand-based pricing, customer-centric pricing, and balancing price elasticity with competitive pricing. It provides granular pricing at the SKU level and offers a seamless adoption and onboarding process. The platform helps retailers optimize pricing strategies, increase margins, and save time on repricing.

Inventoro is a smart inventory forecasting and replenishment tool that helps businesses optimize their inventory management processes. By analyzing past sales data, the tool predicts future sales, recommends order quantities, reduces inventory size, identifies profitable inventory items, and ensures customer satisfaction by avoiding stockouts. Inventoro offers features such as sales forecasting, product segmentation, replenishment, system integration, and forecast automations. The tool is designed to help businesses decrease inventory, increase revenue, save time, and improve product availability. It is suitable for businesses of all sizes and industries looking to streamline their inventory management operations.

Vic.ai is an AI-powered accounting software designed to streamline invoice processing, purchase order matching, approval flows, payments, analytics, and insights. The platform offers autonomous finance solutions that optimize accounts payable processes, achieve lasting ROI, and enable informed decision-making. Vic.ai leverages AI technology to enhance productivity, accuracy, and efficiency in accounting workflows, reducing manual tasks and improving overall financial operations.

Paro is a professional business finance and accounting solutions platform that matches businesses and accounting firms with skilled finance experts. It offers a wide range of services including accounting, bookkeeping, financial planning, budgeting, business analysis, data visualization, strategic advisory, growth strategy consulting, startup and fundraising consulting, transaction advisory, tax and compliance services, AI consulting services, and more. Paro aims to help businesses optimize faster by providing expert solutions to bridge gaps in finance and accounting operations. The platform also offers staff augmentation services, talent acquisition, and custom solutions to enhance operational efficiency and maximize ROI.

Seventh Sense is an AI software designed to optimize email delivery times using artificial intelligence for HubSpot and Marketo users. It helps email marketers improve engagement and conversions by personalizing email delivery times based on individual recipient behavior. The tool aims to address the challenges of email marketing in today's competitive digital landscape by leveraging AI to increase deliverability, engagement, and conversions. Seventh Sense has been successful in helping hundreds of companies enhance their email marketing performance and stand out in crowded inboxes.

CEREBRUMX is an AI-powered platform that offers preventive car maintenance telematics solutions for various industries such as fleet management, vehicle service contracts, electric vehicles, smart cities, and media. The platform provides data insights and features like driver safety, EV charging, predictive maintenance, roadside assistance, and traffic flow management. CEREBRUMX aims to optimize fleet operations, enhance efficiency, and deliver high-value impact to customers through real-time connected vehicle data insights.

KG-LLM-Papers is a repository that collects papers integrating knowledge graphs (KGs) and large language models (LLMs). It serves as a comprehensive resource for research on the role of KGs in the era of LLMs, covering surveys, methods, and resources related to this integration.

SurveyX is an advanced academic survey automation system that leverages Large Language Models (LLMs) to generate high-quality, domain-specific academic papers and surveys. Users can request comprehensive academic papers or surveys tailored to specific topics by providing a paper title and keywords for literature retrieval. The system streamlines academic research by automating paper creation, saving users time and effort in compiling research content.

Slideflow is a deep learning library for digital pathology, offering a user-friendly interface for model development. It is designed for medical researchers and AI enthusiasts, providing an accessible platform for developing state-of-the-art pathology models. Slideflow offers customizable training pipelines, robust slide processing and stain normalization toolkit, support for weakly-supervised or strongly-supervised labels, built-in foundation models, multiple-instance learning, self-supervised learning, generative adversarial networks, explainability tools, layer activation analysis tools, uncertainty quantification, interactive user interface for model deployment, and more. It supports both PyTorch and Tensorflow, with optional support for Libvips for slide reading. Slideflow can be installed via pip, Docker container, or from source, and includes non-commercial add-ons for additional tools and pretrained models. It allows users to create projects, extract tiles from slides, train models, and provides evaluation tools like heatmaps and mosaic maps.

LitData is a tool designed for blazingly fast, distributed streaming of training data from any cloud storage. It allows users to transform and optimize data in cloud storage environments efficiently and intuitively, supporting various data types like images, text, video, audio, geo-spatial, and multimodal data. LitData integrates smoothly with frameworks such as LitGPT and PyTorch, enabling seamless streaming of data to multiple machines. Key features include multi-GPU/multi-node support, easy data mixing, pause & resume functionality, support for profiling, memory footprint reduction, cache size configuration, and on-prem optimizations. The tool also provides benchmarks for measuring streaming speed and conversion efficiency, along with runnable templates for different data types. LitData enables infinite cloud data processing by utilizing the Lightning.ai platform to scale data processing with optimized machines.

Party Builder for Genshin Impact is an AI-assisted team creation tool that helps players assemble well-rounded teams by analyzing characters' attributes, constellation levels, weapon types, elemental reactions, roles, and community scores. It allows users to optimize their team compositions for better gameplay experiences. The tool provides a user-friendly interface for easy team customization and strategy planning, enhancing the overall gaming experience for Genshin Impact players.

Laravel Slower is a powerful package designed for Laravel developers to optimize the performance of their applications by identifying slow database queries and providing AI-driven suggestions for optimal indexing strategies and performance improvements. It offers actionable insights for debugging and monitoring database interactions, enhancing efficiency and scalability.

This repository documents how to optimize common algorithms based on CUDA. It includes subdirectories with code implementations for specific optimizations. The optimizations cover topics such as compiling PyTorch from source, NVIDIA's reduce optimization, OneFlow's elementwise template, fast atomic add for half data types, upsample nearest2d optimization in OneFlow, optimized indexing in PyTorch, OneFlow's softmax kernel, linear attention optimization, and more. The repository also includes learning resources related to deep learning frameworks, compilers, and optimization techniques.

llm-analysis is a tool designed for Latency and Memory Analysis of Transformer Models for Training and Inference. It automates the calculation of training or inference latency and memory usage for Large Language Models (LLMs) or Transformers based on specified model, GPU, data type, and parallelism configurations. The tool helps users to experiment with different setups theoretically, understand system performance, and optimize training/inference scenarios. It supports various parallelism schemes, communication methods, activation recomputation options, data types, and fine-tuning strategies. Users can integrate llm-analysis in their code using the `LLMAnalysis` class or use the provided entry point functions for command line interface. The tool provides lower-bound estimations of memory usage and latency, and aims to assist in achieving feasible and optimal setups for training or inference.

This GitHub repository contains examples of fine-tuning open source large language models. It showcases the process of fine-tuning and quantizing large language models using efficient techniques like Lora and QLora. The repository serves as a practical guide for individuals looking to optimize the performance of language models through fine-tuning.

Safeguards Shield is a security and alignment toolkit designed to detect unwanted inputs and LLM outputs. It provides tools to optimize RAG pipelines for accuracy and ensure trustworthy AI needs are met. The SDK aims to make LLMs accurate and secure, unlocking value faster by unifying a set of tools.

DeGPT is a tool designed to optimize decompiler output using Large Language Models (LLM). It requires manual installation of specific packages and setting up API key for OpenAI. The tool provides functionality to perform optimization on decompiler output by running specific scripts.

GLake is an acceleration library and utilities designed to optimize GPU memory management and IO transmission for AI large model training and inference. It addresses challenges such as GPU memory bottleneck and IO transmission bottleneck by providing efficient memory pooling, sharing, and tiering, as well as multi-path acceleration for CPU-GPU transmission. GLake is easy to use, open for extension, and focuses on improving training throughput, saving inference memory, and accelerating IO transmission. It offers features like memory fragmentation reduction, memory deduplication, and built-in security mechanisms for troubleshooting GPU memory issues.

Sarathi-Serve is the official OSDI'24 artifact submission for paper #444, focusing on 'Taming Throughput-Latency Tradeoff in LLM Inference'. It is a research prototype built on top of CUDA 12.1, designed to optimize throughput-latency tradeoff in Large Language Models (LLM) inference. The tool provides a Python environment for users to install and reproduce results from the associated experiments. Users can refer to specific folders for individual figures and are encouraged to cite the paper if they use the tool in their work.

Trace is a new AutoDiff-like tool for training AI systems end-to-end with general feedback. It generalizes the back-propagation algorithm by capturing and propagating an AI system's execution trace. Implemented as a PyTorch-like Python library, users can write Python code directly and use Trace primitives to optimize certain parts, similar to training neural networks.

Cursor Lens is an open-source tool that acts as a proxy between Cursor and various AI providers, logging interactions and providing detailed analytics to help developers optimize their use of AI in their coding workflow. It supports multiple AI providers, captures and logs all requests, provides visual analytics on AI usage, allows users to set up and switch between different AI configurations, offers real-time monitoring of AI interactions, tracks token usage, estimates costs based on token usage and model pricing. Built with Next.js, React, PostgreSQL, Prisma ORM, Vercel AI SDK, Tailwind CSS, and shadcn/ui components.

Awesome-AI-SEO is a curated list of powerful AI tools and platforms designed to transform your SEO strategy. This repository gathers the most effective tools that leverage machine learning and artificial intelligence to automate and enhance key aspects of search engine optimization. Whether you are an SEO professional, digital marketer, or website owner, these tools can help you optimize your site, improve your search rankings, and increase organic traffic with greater precision and efficiency. The list features AI tools covering on-page and off-page optimization, competitor analysis, rank tracking, and advanced SEO analytics. By utilizing cutting-edge technologies, businesses can stay ahead of the competition by uncovering hidden keyword opportunities, optimizing content for better visibility, and automating time-consuming SEO tasks. With frequent updates, Awesome-AI-SEO is your go-to resource for discovering the latest AI-driven innovations in the SEO space.

NanoFlow is a throughput-oriented high-performance serving framework for Large Language Models (LLMs) that consistently delivers superior throughput compared to other frameworks by utilizing key techniques such as intra-device parallelism, asynchronous CPU scheduling, and SSD offloading. The framework proposes nano-batching to schedule compute-, memory-, and network-bound operations for simultaneous execution, leading to increased resource utilization. NanoFlow also adopts an asynchronous control flow to optimize CPU overhead and eagerly offloads KV-Cache to SSDs for multi-round conversations. The open-source codebase integrates state-of-the-art kernel libraries and provides necessary scripts for environment setup and experiment reproduction.

Embedded inference of Deep Learning models is quite challenging due to high compute requirements. TI’s Edge AI software product helps optimize and accelerate inference on TI’s embedded devices. It supports heterogeneous execution of DNNs across cortex-A based MPUs, TI’s latest generation C7x DSP, and DNN accelerator (MMA). The solution simplifies the product life cycle of DNN development and deployment by providing a rich set of tools and optimized libraries.

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.

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