Alternatives to Spark NLP

Haystack’s pipeline architecture allows you to apply the latest NLP technologies to your data. Implement production-ready semantic searching, question answering and document ranking. Evaluate components and fine tune models. Haystack's pipelines allow you to ask questions in natural language, and find answers in your documents with the latest QA models. Perform semantic search to retrieve documents ranked according to meaning and not just keywords. Use and compare the most recent transformer-based language models, such as OpenAI's GPT-3 and BERT, RoBERTa and DPR. Build applications for semantic search and question answering that can scale up to millions of documents. Building blocks for the complete product development cycle, including file converters, indexing, models, labeling, domain adaptation modules and REST API.

Machine learning can provide insightful text analysis that extracts, analyses, and stores text. AutoML allows you to create high-quality custom machine learning models without writing a single line. Natural Language API allows you to apply natural language understanding (NLU). To identify and label fields in a document, such as emails and chats, use entity analysis. Next, perform sentiment analysis to understand customer opinions and find UX and product insights. Natural Language with speech to text API extracts insights form audio. Vision API provides optical character recognition (OCR), which can be used to scan scanned documents. Translation API can understand sentiments in multiple languages. You can use custom entity extraction to identify domain-specific entities in documents. Many of these entities don't appear within standard language models. This allows you to save time and money by not having to do manual analysis. You can create your own machine learning custom models that can classify, extract and detect sentiment.

ChatGPT is an OpenAI language model. It can generate human-like responses to a variety prompts, and has been trained on a wide range of internet texts. ChatGPT can be used to perform natural language processing tasks such as conversation, question answering, and text generation. ChatGPT is a pretrained language model that uses deep-learning algorithms to generate text. It was trained using large amounts of text data. This allows it to respond to a wide variety of prompts with human-like ease. It has a transformer architecture that has been proven to be efficient in many NLP tasks. ChatGPT can generate text in addition to answering questions, text classification and language translation. This allows developers to create powerful NLP applications that can do specific tasks more accurately. ChatGPT can also process code and generate it.

Azure AI Language is an Azure managed service that allows you to develop applications for natural language processing. You can identify key terms and phrases, analyze emotion, summarize text and build conversational interfaces. Use Language to annotate AI models, train them, evaluate them, and deploy them with minimal machine learning expertise. Out-of-the-box capabilities, such as predefined entity categories for each business or text analytics for healthcare domains can help you get up and running quickly. You can also customize and optimize them when necessary. To train your machine-learning model, provide a few labeled example sentences. Multilingual models can be created in one language, and then used for many other languages. Language Studio allows you to scan your content and quickly suggest labels using advanced language models powered by GPT. Text can be categorized and labelled to extract vital information.

ToothFairyAI is a Software-as-a-Service (SaaS) that provides access to powerful Natural Language Processing (NLP) and Natural Language Generation (NLG) APIs. ToothFairyAI allows users to easily configure and customize a variety of transformer models through the ToothFairyAI application. ToothFairyAI was designed to make creating natural language applications easier with minimal effort. It comes with a large library of pre-trained model that can be used to create customized solutions. ToothFairyAI also allows users to easily customize and configure these models via an intuitive user interface. This allows you to quickly create powerful NLP and NLG applications.

InstructGPT is an open source framework that trains language models to generate natural language instruction from visual input. It uses a generative, pre-trained transformer model (GPT) and the state of the art object detector Mask R-CNN to detect objects in images. Natural language sentences are then generated that describe the image. InstructGPT has been designed to be useful in all domains including robotics, gaming, and education. It can help robots navigate complex tasks using natural language instructions or it can help students learn by giving descriptive explanations of events or processes.

Conversational language understanding is an AI feature that allows you to build applications with conversational language. It understands natural language and can extract key information about the user's goals from phrases. Create multilingual, customizable intent classification and entity extraction models across 96 languages for your domain-specific keyword or phrase. Train in a natural language, and use it in multiple languages without retraining. Create intents and entities quickly and label your own utterances. Add prebuilt components of a variety of commonly used types. Evaluation with quantitative measurements such as precision and recall. The intuitive and user-friendly Language Studio has a simple dashboard for managing model deployments. Use seamlessly with Azure AI Language and Azure Bot Service to create a conversational solution. Conversational language understanding (CLU) is the next-generation of Language Understanding.

GPT-4 (Generative Pretrained Transformer 4) a large-scale, unsupervised language model that is yet to be released. GPT-4, which is the successor of GPT-3, is part of the GPT -n series of natural-language processing models. It was trained using a dataset of 45TB text to produce text generation and understanding abilities that are human-like. GPT-4 is not dependent on additional training data, unlike other NLP models. It can generate text and answer questions using its own context. GPT-4 has been demonstrated to be capable of performing a wide range of tasks without any task-specific training data, such as translation, summarization and sentiment analysis.

Natural language processing (NLP), which is a natural way to extract insights from unstructured text, is a great way to gain insight. To understand common topics and trends, identify key phrases and entities, such as people, places, or organizations. Pretrained models that are domain-specific can be used to classify medical terminology. Sentiment analysis allows you to gain a deeper understanding of customer opinions. You can evaluate text in many languages. Broad entity extraction Identify key concepts in text, including key words and named entities, such as people, places and organizations. Sentiment analysis that is powerful: Find out what customers think about your brand and how sentiment is around certain topics. Robust language detection: Assess text input in a variety of languages. Flexible deployment: Text Analytics can be run anywhere: on-premises, in the cloud, or at the edge with containers.

NLP software libraries and text analytics for on-premise integration or deployment. Integrate Salience in your enterprise business intelligence architecture, or white label it within your data analytics product. Salience can process 200 tweets per seconds while scaling from one process core to entire data centers with small memory footprint. For higher levels of ease, you can use Java, Python, C#, or the native C/C++ interface. You have full access to the technology. You can tune every text analytics function and NLP feature. This includes tokenization and part-of-speech tagging, sentiment scoring, categorization and theme analysis. Based on a pipeline model that includes NLP rules and machine-learning models. Identify where issues are occurring in the pipeline. You can adjust specific features without affecting the entire system. Salience runs entirely on your servers, but you can also offload sensitive data to the cloud servers.

You can use advanced language models and coding to solve a variety of problems. To build cutting-edge applications, leverage large-scale, generative AI models that have deep understandings of code and language to allow for new reasoning and comprehension. These coding and language models can be applied to a variety use cases, including writing assistance, code generation, reasoning over data, and code generation. Access enterprise-grade Azure security and detect and mitigate harmful use. Access generative models that have been pretrained with trillions upon trillions of words. You can use them to create new scenarios, including code, reasoning, inferencing and comprehension. A simple REST API allows you to customize generative models with labeled information for your particular scenario. To improve the accuracy of your outputs, fine-tune the hyperparameters of your model. You can use the API's few-shot learning capability for more relevant results and to provide examples.

The Moveworks AI platform combines conversational-AI, machine learning, and natural language understanding (NLU) with deep integrations in enterprise systems to automate the resolution of IT support problems. Our system is pre-trained so it can understand common IT support issues and enterprise language. It starts to deliver right away and keeps getting smarter over time.

With just a few lines, you can integrate natural language understanding and generation into the product. The Cohere API allows you to access models that can read billions upon billions of pages and learn the meaning, sentiment, intent, and intent of every word we use. You can use the Cohere API for human-like text. Simply fill in a prompt or complete blanks. You can create code, write copy, summarize text, and much more. Calculate the likelihood of text, and retrieve representations from your model. You can filter text using the likelihood API based on selected criteria or categories. You can create your own downstream models for a variety of domain-specific natural languages tasks by using representations. The Cohere API is able to compute the similarity of pieces of text and make categorical predictions based on the likelihood of different text options. The model can see ideas through multiple lenses so it can identify abstract similarities between concepts as distinct from DNA and computers.

spaCy is designed for real work, real products and real insights. The library respects your time, and tries not to waste it. It is easy to install and the API is simple and efficient. spaCy excels in large-scale information extraction tasks. It is written in Cython, which is carefully managed for memory. SpaCy is the library to use if your application requires to process large web dumps. spaCy was released in 2015 and has been a industry standard with a large ecosystem. You can choose from a wide range of plugins and integrate them with your machine-learning stack to create custom components and workflows. You can use these components to recognize named entities, part-of speech tagging, dependency parsing and sentence segmentation. Easy extensible with custom components or attributes Model packaging, deployment, workflow management made easy.

Graphlogic Conversational AI Platform consists of: Robotic Process Automation for Enterprises (RPA), Conversational AI, and Natural Language Understanding technology to create advanced chatbots and voicebots. It also includes Automatic Speech Recognition (ASR), Text-to-Speech solutions (TTS), and Retrieval Augmented Generation pipelines (RAGs) with Large Language Models. Key components: Conversational AI Platform - Natural Language understanding - Retrieval and augmented generation pipeline or RAG pipeline - Speech to Text Engine - Text-to-Speech Engine - Channels connectivity API Builder Visual Flow Builder Pro-active outreach conversations Conversational Analytics - Deploy anywhere (SaaS, Private Cloud, On-Premises). - Single-tenancy / multi-tenancy - Multiple language AI

Machine teaching that is highly efficient An annotation tool powered with active learning. Prodigy is a scriptable tool that allows data scientists to do annotations themselves. This allows for a new level in rapid iteration. Transfer learning technologies allow you to train production-quality models using very few examples. Prodigy allows you to take full advantage modern machine learning by using a more agile approach for data collection. You'll be more productive, more independent, and deliver more successful projects. Prodigy combines state-of-the art insights from machine learning with user experience. You are only required to annotate examples that the model doesn't already know. The web application is flexible, powerful, and follows modern UX principles. It's simple to understand: it's designed for you to focus on one decision at the time and keep you clicking, much like Tinder for data.

OptiSol offers AI-powered solutions for document analysis. OptiSol transforms data into insights by using a variety technologies, such as natural language processing and Machine Learning. They offer a range of services including document comprehension and visual comprehension. OptiSol is easily integrated into existing applications, and can be used across a wide range of industries.

Clarifai is a leading AI platform for modeling image, video, text and audio data at scale. Our platform combines computer vision, natural language processing and audio recognition as building blocks for building better, faster and stronger AI. We help enterprises and public sector organizations transform their data into actionable insights. Our technology is used across many industries including Defense, Retail, Manufacturing, Media and Entertainment, and more. We help our customers create innovative AI solutions for visual search, content moderation, aerial surveillance, visual inspection, intelligent document analysis, and more. Founded in 2013 by Matt Zeiler, Ph.D., Clarifai has been a market leader in computer vision AI since winning the top five places in image classification at the 2013 ImageNet Challenge. Clarifai is headquartered in Delaware

AI21 Studio provides API access to Jurassic-1 large-language-models. Our models are used to generate text and provide comprehension features in thousands upon thousands of applications. You can tackle any language task. Our Jurassic-1 models can follow natural language instructions and only need a few examples to adapt for new tasks. Our APIs are perfect for common tasks such as paraphrasing, summarization, and more. Superior results at a lower price without having to reinvent the wheel Do you need to fine-tune your custom model? Just 3 clicks away. Training is quick, affordable, and models can be deployed immediately. Embed an AI co-writer into your app to give your users superpowers. Features like paraphrasing, long-form draft generation, repurposing, and custom auto-complete can increase user engagement and help you to achieve success.

Integrate our text analytics APIs into your product, platform, and application to add world-leading NLP. This is the most complete NLP feature stack available. It has been 19 years in development and is constantly improving with new configurations, models, and libraries. You can determine whether a piece is positive, neutral, or negative. Sort and organize documents into configurable groups. Determine the intended purpose of customers and reviewers. Locate people, places and dates. Find companies, products, jobs, titles and more. Our text analytics and NLP systems can be deployed on any combination of public, private, hybrid, or on-premise cloud infrastructures. Our core text analytics and natural-language processing software libraries are available to you. This product is ideal for data scientists and architects who need to have full access to the underlying technology, or for on-premise deployment security or privacy reasons.

Language Understanding (LUIS), a machine learning-based service that builds natural language into apps and bots. Rapidly create custom models that are enterprise-ready and can be continuously improved. Natural language can be added to your apps. LUIS is a language model that interprets conversations to find valuable information. It extracts information from sentences (entities) and interprets user intentions (goals). LUIS is seamlessly integrated with the Azure Bot Service, making creating sophisticated bots easy. You can quickly create and deploy a solution faster by combining powerful developer tools with pre-built apps and entity dictionary, such as Music, Calendar, and Devices. The collective knowledge of the internet is used to create dictionaries. This allows your model to identify valuable information from user conversations. Active learning is used for continuous improvement of the quality of the models.

swivl simplifies AI training Data scientists spend about 80% of their time on tasks that are not value-added, such as cleaning, cleaning, and annotation data. Our SaaS platform that doesn't require code allows teams to outsource data annotation tasks to a network of data annotators. This helps close the feedback loop cost-effectively. This includes the training, testing, deployment, and monitoring of machine learning models, with an emphasis on audio and natural language processing.

Pangeanic is the world's first deep adaptive machine translator offering 90% human parity for auto publication, automatic document classification, and a full NLP ecosystem to anonymize, summarize, name-entity recognition, data for AI services, and data for eDiscovery. Pangeanic is used by international and cross-national organizations, multinationals, government agencies, and other language companies around the globe. Our quality service philosophy is supported by the most up-to-date computer applications and state of-the-art language testing technology. Our entire package is designed to reduce translation and localization costs in any language.

OpenText™, Unstructured Data Analytics Products use AI and machine learning in order to help organizations discover and leverage key insights that are hidden deep within unstructured data such as text, audio, videos, and images. Organizations can connect their data at scale to understand the context and content locked in high-growth, unstructured content. Unified text, speech and video analytics support over 1,500 data formats to help you uncover insights within all types media. Use OCR, natural language processing and other AI models to track and understand the meaning of unstructured data. Use the latest innovations in deep neural networks and machine learning to understand spoken and written language in data. This will reveal greater insights.

Watson Natural Language Understanding, a cloud native product, uses deep learning to extract metadata such as entities, keywords and categories, sentiments, emotions, relations, and syntax. Text analysis can be used to uncover the topics in your data. It extracts keywords, concepts and categories. Unstructured data can be analyzed in more than 13 languages. Machine learning models for text mining are available that can be used outside-of-the box to provide high accuracy across your content. Watson Natural Language Understanding can be deployed behind your firewall or on any other cloud. Watson Knowledge Studio allows you to train Watson to understand your business language and extract custom insights. You can keep control of your data and have the assurance that it is safe and secure. IBM will not store or collect your data. Our advanced natural language processing service (NLP), gives developers the tools to extract valuable insights from unstructured information.

Rinalogy Classification API can integrate with your application and run in a customized environment. Rinalogy Classification API is a cloud-based machine learning API that runs in an environment you cannot control and requires you to transfer all your data. Instead, Rinalogy Classification API can easily be deployed in your IT infrastructure and close to your data. Rinalogy Classification API performs Exhaustive Sequential Classification, applying models to all documents in a collection. The models can be saved and improved with additional training data, or used to predict new documents later. You can adjust the number workers according to your workload with its scalable cluster deployment. The Rinalogy API allows you to add text classification, search, recommendation capabilities to client applications.

LaMDA, our most recent research breakthrough, adds pieces of the most intriguing piece of that puzzle: Conversation. Although conversations are more focused on specific topics, they can also be open-ended and lead to completely new areas. Talking to a friend about a TV program could turn into a conversation about the country in which the show was shot. Then, the conversation could lead to a debate about the best regional cuisine in that country. Modern chatbots, also known as chatbots, can be a bit stumped by this wandering quality. They tend to follow pre-determined paths and narrow conversations. LaMDA, which stands for "Language Model for Dialog Applications", can engage in a free-flowing manner about seemingly endless topics. This ability could open up new ways to interact with technology and help you find more useful applications.

SentioAI uses machine learning, natural language processing and predictive analytics to identify the most important documents from a given document population with unprecedented speed and accuracy. SentioAI solves Big Data's classification problem in a unique, proprietary way. The technology is able to work when other technologies fail and delivers faster results and costs less than other technologies. SentioAI provides a ranked list of documents, ranging from the most likely to be relevant to the most likely to be. The software allows users to review and tag a portion of the data set. This data is used to train SentioAI prediction engine so documents are ordered according to their relevancy. The system gets more accurate with each new document. SentioAI determines when a predictive engine has been trained and then runs the models on the complete data set to generate the results.

We have been pioneers in the development of clinical NLP platforms and their applications for over 15 years. This has resulted in high precision and accuracy. Our core competency is to interpret unstructured notes accurately and at scale. Tested on billions of real clinical notes and documents. AI that can explain with context, reasoning, and evidence for output. NLP with medical knowledge infused with 4M+ entities and 50M+ relationships. Innovative Machine Learning (ML), & Deep Learning(DL) models were used to build this NLP. Use a foundation of rich ontologies and clinician-specific terminologies. We can understand, interpret, and extract context & significance from the inconsistent, inconsistent, and non-standard data contained in medical documents. Our clinical domain experts continually infuse knowledge graphs to our NLP by mapping all clinical entities and their relationship between them. We have more than 4,000,000 entities and 50,000,000 relationships.

Comprehensive IP data of high quality for patent analytics. 136 million patents in 100+ countries. Brands and organizations of every size trust us. XLSCOUT combined data with the best-in class artificial intelligence technologies to create the most accurate, comprehensive and intelligent patent & publication database. Using Natural Language Processing (NLP), Machine Learning (ML), and innovation/scientific principles, XLSCOUT gives you more time and reliable insights to confidently make data-driven strategic decisions. Drafting LLM, a cutting edge platform for drafting patent applications, uses Large Language Models (LLMs), & Generative AI to draft top-tier preliminary drafts. Novelty Checker LLM quickly scans patent and non-patent literature to deliver a comprehensive list with ranked prior art references, along with a report on key features.

A new category of AI. Most AI solutions today are designed using a mathematical and statistical lens. We took a different approach. Intelligent Artifacts' team has created a new type of AI based on information theory. It is a true AGI that eliminates the current shortcomings in machine intelligence. Our framework separates the intelligence layer from the data and application layers, allowing it to learn in real time and allowing it to make predictions down to the root cause. A truly integrated platform is required for AGI. Intelligent Artifacts will allow you to model information, not data. Predictions and decisions can be made across multiple domains without the need for rewriting code. Our dynamic platform and specialized AI consultants will provide you with a tailored solution that quickly provides deep insights and better outcomes from your data.

SparkCognition, an industrial AI company, has created a natural language processing solution that automates the workflows of unstructured data within companies so that humans can concentrate on high-value business decisions. DeepNLP uses machine learning to automate the retrieval, classification, and analysis of information. DeepNLP integrates with existing workflows to allow organizations to respond more quickly to changes in their businesses and get quick answers to specific queries.

The AI language platform that drives significant revenue increase. The Persado Motivation AI Platform combines a vast language database, advanced AI, machine learning and a decisioning algorithm to deliver the precise language to motivate every individual to act and engage, resulting in unprecedented revenue growth. The Persado Motivation AI Platform translates the intent of a given message, using AI and machine-learning models. Together with an unmatched decision engine, it generates the exact language that motivates every individual to engage and take action. Leveraging patented algorithms, the platform learns consumer response patterns and continues to refine language, delivering hyper-personalization at scale for elevated performance.

BERT is a large language model that can be used to pre-train language representations. Pre-training refers the process by which BERT is trained on large text sources such as Wikipedia. The training results can then be applied to other Natural Language Processing tasks (NLP), such as sentiment analysis and question answering. You can train many NLP models with AI Platform Training and BERT in just 30 minutes.

You can choose from our library and fine-tune or create your own capabilities to analyze, process, and present text, audio, and video at large scale. Incorporate advanced NLP in your app or workflow. You can choose from the existing library or create your own. With just one API call, you can summarize, tag, and analyze language using stackable, composable NLP blocks. These blocks are built on state of the art models. Our powerful Custom-Skill engine allows you to create and fine-tune custom Language skills from your data. Only 5% of the world’s population can speak English as their first language. One AI's capabilities can be used in multiple languages. You can build a podcast platform, CRM or content publishing tool using One AI's multilingual capabilities.

Folio3 has a dedicated team of Data Scientists and Consultants who have completed end-to-end projects in machine learning, natural language processing and computer vision. Companies can now use highly customized solutions with advanced Machine Learning capabilities thanks to Artificial Intelligence and Machine Learning algorithms. Computer vision technology has revolutionized the way companies use visual content. It has also made it easier to analyze visual data and introduced new functions that are image-based. Folio3's predictive analytics solutions produce fast and effective results that allow you to identify anomalies and opportunities in your business processes.

Natural Language Processing is Artificial Intelligence. It allows computers to understand and analyze human language. Pryon's AI can read, organize, and search in ways that were previously impossible for humans. This powerful ability is used in every interaction to both understand a request as well as to retrieve the correct response. The sophistication of the underlying natural languages technologies is directly related to the success of any NLP project. Your content can be used in chatbots, search engines, automations, and other ways. It must be broken down into pieces so that a user can find the exact answer, result, or snippet they are looking for. This can be done manually or by a specialist who breaks down information into intents or entities. Pryon automatically creates a dynamic model from your content to attach rich metadata to each piece. This model can be regenerated in a click when you add, modify or remove content.

Azure AI Content Understanding transforms unstructured, multimodal data into valuable insights. From text, audio, video, and images, you can derive meaningful insights. AI-based methods, such as scheme extraction or grounding, can be used to produce high-quality and precise data for downstream applications. Streamline and unify data pipelines from different data types to create a single workflow, reducing costs and speeding up time to value. Learn how businesses and call centers can use call recordings to generate valuable insights to track KPIs and enhance product experiences and respond to customer queries more quickly and accurately. Azure AI offers a variety of AI models that can transform data from a variety of input modalities such as images, audio or video into a structured output which can be processed and analyzed easily by downstream applications.

Abacus.AI is the first global end-to-end autonomous AI platform. It enables real-time deep-learning at scale for common enterprise use cases. Our innovative neural architecture search methods allow you to create custom deep learning models and then deploy them on our end-to-end DLOps platform. Our AI engine will increase user engagement by at least 30% through personalized recommendations. Our recommendations are tailored to each user's preferences, which leads to more interaction and conversions. Don't waste your time dealing with data issues. We will automatically set up your data pipelines and retrain the models. To generate recommendations, we use generative modeling. This means that even if you have very little information about a user/item, you won't have a cold start.

Create a natural language interface to your data. NLP is the heart of modern enterprise data processing. We provide developers the tools they need to quickly and efficiently build NLP systems that are ready for production. Our open-source framework allows for API-driven, scalable NLP application architectures. We believe in sharing. Our software is open-source. We value our community and make modern NLP accessible, practical, scalable, and easy to use. Natural language processing (NLP), a branch in AI, allows machines to interpret and process human language. Companies can use human language to interact and communicate with data and computers by implementing NLP. NLP is used in areas such as semantic search, question answering (QA), conversational A (chatbots), text summarization and question generation. It also includes text mining, machine translation, speech recognition, and text mining.

Amazon Comprehend is a HIPAA-eligible, natural language processing (NLP), service that uses machine-learning to extract health data form medical text. No machine learning experience is necessary. Today, a lot of health data is found in free-form medical texts like doctor's notes, clinical trials reports, and patient records. Manually extracting data can be time-consuming and automated rule-based attempts at extracting data won't capture the whole story because they don't take context into consideration. The data is not usable for large-scale analytics that will help improve the healthcare and life sciences industry, patient outcomes, and increase efficiencies.

Deep Talk is the fastest way for text to be transformed from chats, emails and surveys into real business intelligence. Our AI platform makes it easy to understand what's going on inside customer communications. Unsupervised deep learning models for unstructured text data analysis Deepers are pre-trained deep learning models that can detect custom patterns in your data. The "Deepers API" allows you to analyze text in real-time and tag text or conversations. Reach out to the people who are in need of a product, ask for a new feature, or complain. Deep Talk offers cloud-based deeplearning models as a service. To extract all the insights and data from WhatsApp, chat conversation, emails, surveys, or social networks, you just need to upload the data or integrate one the support services

Production-ready AI models that are fast and accurate. High-availability inference API that leverages the most advanced NVIDIA GPUs. We have selected the most popular open-source natural language processing models (NLP) and deployed them for the community. You can fine-tune your models (including GPT-J) or upload your custom models. Then, deploy them to production. Upload your AI models, including GPT-J, to your dashboard and immediately use them in production.

GPT-3.5 is the next evolution to GPT 3 large language model, OpenAI. GPT-3.5 models are able to understand and generate natural languages. There are four main models available with different power levels that can be used for different tasks. The main GPT-3.5 models can be used with the text completion endpoint. There are models that can be used with other endpoints. Davinci is the most versatile model family. It can perform all tasks that other models can do, often with less instruction. Davinci is the best choice for applications that require a deep understanding of the content. This includes summarizations for specific audiences and creative content generation. These higher capabilities mean that Davinci is more expensive per API call and takes longer to process than other models.

The open-source ML observability Platform. From validation to production, evaluate, test, and track ML models. From tabular data up to NLP and LLM. Built for data scientists and ML Engineers. All you need to run ML systems reliably in production. Start with simple ad-hoc checks. Scale up to the full monitoring platform. All in one tool with consistent APIs and metrics. Useful, beautiful and shareable. Explore and debug a comprehensive view on data and ML models. Start in a matter of seconds. Test before shipping, validate in production, and run checks with every model update. By generating test conditions based on a reference dataset, you can skip the manual setup. Monitor all aspects of your data, models and test results. Proactively identify and resolve production model problems, ensure optimal performance and continually improve it.

Sparrow is a research model that serves as a proof of concept. It was created with the goal to train dialogue agents to be more helpful and correct. Sparrow helps us understand how to train agents to be more helpful and safer, and ultimately to help create safer and more useful artificial intelligence (AGI). Sparrow is currently not available for public use. Because it is difficult to determine what makes a conversation successful, training conversational AI can be a challenging problem. We use reinforcement learning (RL) to address this problem. This is a form that uses people's feedback and the preference feedback of study participants to train a model about how useful an answer is. We show participants multiple models of the same question, and ask them which one they prefer.

Nuance Virtual Assistant combines AI, deep neural networks and machine learning to create conversational, personalized interactions across all digital channels. You can provide customers with fast, frictionless and effective self-service to answer their questions. This will increase customer satisfaction and reduce contact center costs. Customers can be transferred to a live agent and the entire conversation can be passed to the agent with the appropriate skillset. This reduces customer effort and speeds up resolution. With Nuance Essentials Virtual Assistant, you can have a chatbot up and running in just three weeks. Nuance Virtual Assistant allows you to better serve customers, reduce the number cases that are transferred directly to agents, and simplify your AI to support customer service transformation.

Use NeuralSpace's enterprise-grade APIs for speech & text AI in 100+ languages. Intelligent Document Processing can reduce manual tasks by 50%. Data can be extracted, understood, and categorised from any document, regardless of its quality, layout, file type, or format. Free your team from manual work so they can focus on what's important. Advanced speech and text AI can make your products accessible to all users. NeuralSpace allows you to train and deploy large language models. Our low-code, user-friendly APIs make integration easy. We provide the tools, you bring your vision to reality.

Machine learning models can transform your knowledge into text-based workflows that are scaleable and human-level. You can either create your own models, retrain our models for your task, or purchase Primer models off the shelf. Primer Automate is available to anyone in your company. No coding or technical skills are required. You can add a structured layer to your data and create an scalable, self-curating knowledgebase that can quickly scan through billions of documents. Quickly find answers to critical questions, track updates in real-time, and generate easy-to-read reports automatically. To find the most important information, process all your documents, emails and social media. Primer Extract makes it easy to quickly and efficiently explore your data using cutting-edge machine learning techniques. Extract offers more than keyword search. It also provides OCR, translation, and image recognition capabilities.

SoapBox was created for children. Our mission is to transform learning and play for children all over the world using voice technology. Our low-code, scalable platform has been licensed by education and consumer businesses worldwide to provide world-class voice experiences for literacy, English language tools, smart toys and games, apps, robots, and other market products. Our proprietary technology is independent and reliable. It can be used by children of all ages, from 2-12 years. It can also be used to recognize different dialects and accents around the world and has been independently verified not to have any racial bias. Privacy-by-design is the approach used to build the SoapBox platform. Our work and philosophy are based on protecting children's fundamental right to privacy.