Best AI tools for< Adopt Names >

NameBridge is an AI-powered tool that generates connotative Chinese names based on English names. The tool ensures the generated names sound great and have deep meanings. It is designed to help individuals create culturally appropriate Chinese names for various purposes such as business, writing, art, travel, and personal interests. NameBridge uses AI algorithms to instantly generate unique and meaningful Chinese names that are culturally significant and can be used in various contexts.

Arya.ai is an AI tool designed for Banks, Insurers, and Financial Services to deploy safe, responsible, and auditable AI applications. It offers a range of AI Apps, ML Observability Tools, and a Decisioning Platform. Arya.ai provides curated APIs, ML explainability, monitoring, and audit capabilities. The platform includes task-specific AI models for autonomous underwriting, claims processing, fraud monitoring, and more. Arya.ai aims to facilitate the rapid deployment and scaling of AI applications while ensuring institution-wide adoption of responsible AI practices.

Team-GPT is an enterprise AI software designed for teams ranging from 2 to 5,000 members. It provides a shared workspace where teams can organize knowledge, collaborate, and master AI. The platform offers features such as folders and subfolders for organizing chats, a prompt library with ready-to-use templates, and adoption reports to measure AI adoption rates. Team-GPT aims to make ChatGPT more accessible and cost-effective for teams by providing pay-per-use pricing and priority access to the OpenAI API.

Weam is an AI adoption platform designed for digital agencies to supercharge their operations with collaborative AI. It offers a comprehensive suite of tools for simplifying AI implementation, including project management, resource allocation, training modules, and ongoing support to ensure successful AI integration. Weam enables teams to interact and collaborate over their preferred LLMs, facilitating scalability, time-saving, and widespread AI adoption across the organization.

Scratchpad is an AI-powered workspace designed for sales teams to streamline their sales processes and enhance productivity. It offers features such as AI Sales Assistant, Pipeline Management, Slack Deal Rooms, Automations & Enablement, Deal Inspection, and Sales Forecasting. With Scratchpad, sales teams can automate collaboration, improve Salesforce hygiene, track deal progress, and gain insights into deal movement and pipeline changes. The application aims to simplify sales workflows, provide real-time notes and call summaries, and enhance team collaboration for better performance and efficiency.

Scratchpad is an AI-powered workspace designed for sales teams to streamline their sales processes and enhance productivity. It offers a range of features such as AI Sales Assistant, Pipeline Management, Deal Rooms, Automations & Enablement, and Deal Inspection. With Scratchpad, sales teams can benefit from real-time notes, call summaries, and transcripts, as well as AI prompts for sales processes. The application aims to simplify sales execution, improve CRM hygiene, and provide better deal control through automation and in-line coaching.

Matrix AI Consulting Services is an expert AI consultancy firm based in New Zealand, offering bespoke AI consulting services to empower businesses and government entities to embrace responsible AI. With over 24 years of experience in transformative technology, the consultancy provides services ranging from AI business strategy development to seamless integration, change management, training workshops, and governance frameworks. Matrix AI Consulting Services aims to help organizations unlock the full potential of AI, enhance productivity, streamline operations, and gain a competitive edge through the strategic implementation of AI technologies.

The Data & Trust Alliance is a group of industry-leading enterprises focusing on the responsible use of data and intelligent systems. They develop practices to enhance trust in data and AI models, ensuring transparency and reliability in the deployment processes. The alliance works on projects like Data Provenance Standards and Assessing third-party model trustworthiness to promote innovation and trust in AI applications. Through technology and innovation adoption, they aim to leverage expertise and influence for practical solutions and broad adoption across industries.

Rebecca Bultsma is a trusted and experienced AI educator who aims to make AI simple and ethical for everyday use. She provides resources, speaking engagements, and consulting services to help individuals and organizations understand and integrate AI into their workflows. Rebecca empowers people to work in harmony with AI, leveraging its capabilities to tackle challenges, spark creative ideas, and make a lasting impact. She focuses on making AI easy to understand and promoting ethical adoption strategies.

MetaPals is an AI-powered application that focuses on crafting digital experiences to form genuine emotional bonds with users. It leverages advanced AI technologies and partnerships with institutions like Nanyang Technological University and industry giants like Google AI and Firebase to redefine the way users interact with technology. MetaPals aims to solve the disconnect in the digital age by providing meaningful digital experiences and introducing unique digital companions through collaborations with renowned brands and IPs. The application allows users to adopt digital companions, dive into immersive adventures, and explore the intersection of technology and companionship, setting new standards of gameplay.

Diffblue Cover is an autonomous AI-powered unit test writing tool for Java development teams. It uses next-generation autonomous AI to automate unit testing, freeing up developers to focus on more creative work. Diffblue Cover can write a complete and correct Java unit test every 2 seconds, and it is directly integrated into CI pipelines, unlike AI-powered code suggestions that require developers to check the code for bugs. Diffblue Cover is trusted by the world's leading organizations, including Goldman Sachs, and has been proven to improve quality, lower developer effort, help with code understanding, reduce risk, and increase deployment frequency.

Teraflow.ai is an AI-enablement company that specializes in helping businesses adopt and scale their artificial intelligence models. They offer services in data engineering, ML engineering, AI/UX, and cloud architecture. Teraflow.ai assists clients in fixing data issues, boosting ML model performance, and integrating AI into legacy customer journeys. Their team of experts deploys solutions quickly and efficiently, using modern practices and hyper scaler technology. The company focuses on making AI work by providing fixed pricing solutions, building team capabilities, and utilizing agile-scrum structures for innovation. Teraflow.ai also offers certifications in GCP and AWS, and partners with leading tech companies like HashiCorp, AWS, and Microsoft Azure.

StoryFile is a Conversational Video AI SaaS Technology platform designed for both educational and business solutions. It offers an interactive medium called a storyfile, making AI more human by enabling videos that can talk back. The platform helps businesses adopt artificial intelligence to enhance user engagement and provide personalized experiences.

Zest AI is an AI-driven credit underwriting software that offers a complete solution for AI-driven lending. It enables users to build custom machine learning risk models, adopt model assessment and regulatory compliance, and operate performance management and model monitoring. Zest AI helps increase approvals, manage risk, control loss, drive operational efficiency, automate credit decisioning, and improve borrower experience while ensuring fair lending practices. The software is designed to provide fair and transparent credit for everyone, making lending more accessible and inclusive.

Credo AI is a leading provider of AI governance, risk management, and compliance software. Our platform helps organizations to adopt AI safely and responsibly, while ensuring compliance with regulations and standards. With Credo AI, you can track and prioritize AI projects, assess AI vendor models for risk and compliance, create artifacts for audit, and more.

Capably is an AI Management Platform that helps companies roll out AI employees across their organizations. It provides tools to easily adopt AI, create and onboard AI employees, and monitor AI activity. Capably is designed for business users with no AI expertise and integrates seamlessly with existing workflows and software tools.

Zest AI is an AI-driven credit underwriting software that offers a complete solution for AI-driven lending. It enables users to build custom machine learning risk models, adopt model assessment and regulatory compliance, and operate performance management and model monitoring. Zest AI helps increase approvals, manage risk, control loss, drive operational efficiency, automate credit decisioning, and improve borrower experience while ensuring fair lending practices. The software is designed to provide powerful AI for better lending outcomes by accelerating loan growth and expanding credit access through accurate risk prediction and faster credit decisions.

McKinsey & Company is a global management consulting firm that provides a wide range of services to help businesses improve their performance. The company's website provides information on its services, insights, and thought leadership on a variety of topics, including artificial intelligence (AI). McKinsey & Company has a strong focus on AI and has developed a number of tools and resources to help businesses adopt and implement AI technologies. The company's website includes a section on AI that provides information on the latest AI trends, case studies, and white papers.

Nuanced is an AI tool that detects AI-generated images to protect the integrity and authenticity of online services. It helps platforms combat fraud, deepfakes, and inauthentic content by distinguishing between genuine human-authored artifacts and AI-generated content. Nuanced's algorithms stay ahead of the accelerating changes in AI content generation, providing a privacy-first solution that is simple to adopt and integrate. With Nuanced, businesses can focus on their core operations while ensuring the authenticity of their content.

TitanML is a platform that provides tools and services for deploying and scaling Generative AI applications. Their flagship product, the Titan Takeoff Inference Server, helps machine learning engineers build, deploy, and run Generative AI models in secure environments. TitanML's platform is designed to make it easy for businesses to adopt and use Generative AI, without having to worry about the underlying infrastructure. With TitanML, businesses can focus on building great products and solving real business problems.

VLMEvalKit is an open-source evaluation toolkit of large vision-language models (LVLMs). It enables one-command evaluation of LVLMs on various benchmarks, without the heavy workload of data preparation under multiple repositories. In VLMEvalKit, we adopt generation-based evaluation for all LVLMs, and provide the evaluation results obtained with both exact matching and LLM-based answer extraction.

xFasterTransformer is an optimized solution for Large Language Models (LLMs) on the X86 platform, providing high performance and scalability for inference on mainstream LLM models. It offers C++ and Python APIs for easy integration, along with example codes and benchmark scripts. Users can prepare models in a different format, convert them, and use the APIs for tasks like encoding input prompts, generating token ids, and serving inference requests. The tool supports various data types and models, and can run in single or multi-rank modes using MPI. A web demo based on Gradio is available for popular LLM models like ChatGLM and Llama2. Benchmark scripts help evaluate model inference performance quickly, and MLServer enables serving with REST and gRPC interfaces.

SheetCopilot is an assistant agent that manipulates spreadsheets by following user commands. It leverages Large Language Models (LLMs) to interact with spreadsheets like a human expert, enabling non-expert users to complete tasks on complex software such as Google Sheets and Excel via a language interface. The tool observes spreadsheet states, polishes generated solutions based on external action documents and error feedback, and aims to improve success rate and efficiency. SheetCopilot offers a dataset with diverse task categories and operations, supporting operations like entry & manipulation, management, formatting, charts, and pivot tables. Users can interact with SheetCopilot in Excel or Google Sheets, executing tasks like calculating revenue, creating pivot tables, and plotting charts. The tool's evaluation includes performance comparisons with leading LLMs and VBA-based methods on specific datasets, showcasing its capabilities in controlling various aspects of a spreadsheet.

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.

NNStreamer is a set of Gstreamer plugins that allow Gstreamer developers to adopt neural network models easily and efficiently and neural network developers to manage neural network pipelines and their filters easily and efficiently.

JavaScript tokenizer for LLaMA 3 designed for client-side use in the browser and Node, with TypeScript support. It accurately calculates token count, has 0 dependencies, optimized running time, and somewhat optimized bundle size. Compatible with most LLaMA 3 models. Can encode and decode text, but training is not supported. Pollutes global namespace with `llama3Tokenizer` in the browser. Mostly compatible with LLaMA 3 models released by Facebook in April 2024. Can be adapted for incompatible models by passing custom vocab and merge data. Handles special tokens and fine tunes. Developed by belladore.ai with contributions from xenova, blaze2004, imoneoi, and ConProgramming.

This simple package can be used to fix an invalid json string. To know all cases in which this package will work, check out the unit test. Inspired by https://github.com/josdejong/jsonrepair Motivation Some LLMs are a bit iffy when it comes to returning well formed JSON data, sometimes they skip a parentheses and sometimes they add some words in it, because that's what an LLM does. Luckily, the mistakes LLMs make are simple enough to be fixed without destroying the content. I searched for a lightweight python package that was able to reliably fix this problem but couldn't find any. So I wrote one How to use from json_repair import repair_json good_json_string = repair_json(bad_json_string) # If the string was super broken this will return an empty string You can use this library to completely replace `json.loads()`: import json_repair decoded_object = json_repair.loads(json_string) or just import json_repair decoded_object = json_repair.repair_json(json_string, return_objects=True) Read json from a file or file descriptor JSON repair provides also a drop-in replacement for `json.load()`: import json_repair try: file_descriptor = open(fname, 'rb') except OSError: ... with file_descriptor: decoded_object = json_repair.load(file_descriptor) and another method to read from a file: import json_repair try: decoded_object = json_repair.from_file(json_file) except OSError: ... except IOError: ... Keep in mind that the library will not catch any IO-related exception and those will need to be managed by you Performance considerations If you find this library too slow because is using `json.loads()` you can skip that by passing `skip_json_loads=True` to `repair_json`. Like: from json_repair import repair_json good_json_string = repair_json(bad_json_string, skip_json_loads=True) I made a choice of not using any fast json library to avoid having any external dependency, so that anybody can use it regardless of their stack. Some rules of thumb to use: - Setting `return_objects=True` will always be faster because the parser returns an object already and it doesn't have serialize that object to JSON - `skip_json_loads` is faster only if you 100% know that the string is not a valid JSON - If you are having issues with escaping pass the string as **raw** string like: `r"string with escaping\"" Adding to requirements Please pin this library only on the major version! We use TDD and strict semantic versioning, there will be frequent updates and no breaking changes in minor and patch versions. To ensure that you only pin the major version of this library in your `requirements.txt`, specify the package name followed by the major version and a wildcard for minor and patch versions. For example: json_repair==0.* In this example, any version that starts with `0.` will be acceptable, allowing for updates on minor and patch versions. How it works This module will parse the JSON file following the BNF definition: ::= | ::= | | ; Where: ; is a valid real number expressed in one of a number of given formats ; is a string of valid characters enclosed in quotes ; is one of the literal strings 'true', 'false', or 'null' (unquoted) ::=