GaiaNet Alternatives

Forethought will answer common, repetitive tickets automatically to reduce your agents' workload. Forethought analyzes sentiment to accurately predict and tag incoming cases and reduces manual work for your team. Don’t leave customers waiting in a queue. Forethought will connect customers to agents with the right skills to help them. Have incoming cases routed right away and free up more agents to help customers. Forethought recognizes and retrieves relevant previous tickets and articles to help agents. Get an up-to-date picture of how Forethought is helping your support team’s performance. ‍Create reports and dashboards that you can share with your team or organization. Meet SupportGPT™: the World’s First Generative AI Platform for Customer Support. SupportGPT™ leverages Large Language Models—the same technology behind OpenAI’s ChatGPT—and fine-tunes them on your customers’ conversation history.

Achieve structure, a consistent brand experience and a shorter time to market with Gaia. And use more media than ever before. With more media channels than ever, distributing the right content is essential to attract new customers. Gaia’s digital asset management solution enhances the ability to always find and use the right image. Gain insight into the possibilities with Artificial Intelligence and use more content than ever. Upload the highest resolution to Gaia, and we ensure that you always have the right format at your disposal. So no more overwritten files. Prefer a watermark? No problem, we do that with multiple photos at the same time. How’s that for your brand identity? A central location for access, management and distribution of brand assets. Find content faster through AI with our Magic Tags. Always the right dimensions at your disposal. Increase the (re)use of your digital content.

Dynamiq is a platform built for engineers and data scientists to build, deploy, test, monitor and fine-tune Large Language Models for any use case the enterprise wants to tackle. Key features: 🛠️ Workflows: Build GenAI workflows in a low-code interface to automate tasks at scale 🧠 Knowledge & RAG: Create custom RAG knowledge bases and deploy vector DBs in minutes 🤖 Agents Ops: Create custom LLM agents to solve complex task and connect them to your internal APIs 📈 Observability: Log all interactions, use large-scale LLM quality evaluations 🦺 Guardrails: Precise and reliable LLM outputs with pre-built validators, detection of sensitive content, and data leak prevention 📻 Fine-tuning: Fine-tune proprietary LLM models to make them your own

Experiment, and push the boundaries of individual alignment, artificial consciousness, open-source software, and decentralization, in ways that monolithic companies and governments are too afraid to try. Hermes 3 contains advanced long-term context retention and multi-turn conversation capability, complex roleplaying and internal monologue abilities, and enhanced agentic function-calling. Our training data aggressively encourages the model to follow the system and instruction prompts exactly and in an adaptive manner. Hermes 3 was created by fine-tuning Llama 3.1 8B, 70B, and 405B, and training on a dataset of primarily synthetically generated responses. The model boasts comparable and superior performance to Llama 3.1 while unlocking deeper capabilities in reasoning and creativity. Hermes 3 is a series of instruct and tool-use models with strong reasoning and creative abilities.

Arcane Office encrypts all your document and photos and then send them to a hub of your choice. The default storage provider is Gaia by Blockstack. It's decentralized storage that works by hosting data in one or more existing storage systems. Thanks to Blockstack, you have an option to choose your own storage provider if you want. There is no difference in what provider you are using; Arcane Office will encrypt all your data with the highest security standards. Make a spreadsheet and save it to Blockchain secured cloud storage. Collaborate with anyone on any devices. GDPR compliant. Decentralized and private. Load & save Microsoft Excel and Google Sheets.

AI/ML API: Your Gateway to 200+ AI Models Revolutionize Your Development with a Single API AI/ML API is transforming the landscape for developers and SaaS entrepreneurs worldwide. Access over 200 cutting-edge AI models through one intuitive, developer-friendly interface. 🚀 Key Features: Vast Model Library: From NLP to computer vision, including Mixtral AI, LLaMA, Stable Diffusion, and Realistic Vision. Serverless Inference: Focus on innovation, not infrastructure management. Simple Integration: RESTful APIs and SDKs for seamless incorporation into any tech stack. Customization Options: Fine-tune models to fit your specific use cases. OpenAI API Compatible: Easy transition for existing OpenAI users. 💡 Benefits: Accelerated Development: Deploy AI features in hours, not months. Cost-Effective: GPT-4 level accuracy at 80% less cost. Scalability: From prototypes to enterprise solutions, grow without limits. 24/7 AI Solution: Reliable, always-on service for global

Klu.ai is a Generative AI platform that simplifies the process of designing, deploying, and optimizing AI applications. Klu integrates with your preferred Large Language Models, incorporating data from varied sources, giving your applications unique context. Klu accelerates building applications using language models like Anthropic Claude, Azure OpenAI, GPT-4, and over 15 other models, allowing rapid prompt/model experimentation, data gathering and user feedback, and model fine-tuning while cost-effectively optimizing performance. Ship prompt generations, chat experiences, workflows, and autonomous workers in minutes. Klu provides SDKs and an API-first approach for all capabilities to enable developer productivity. Klu automatically provides abstractions for common LLM/GenAI use cases, including: LLM connectors, vector storage and retrieval, prompt templates, observability, and evaluation/testing tooling.

ChatGPT is a language model developed by OpenAI. It has been trained on a diverse range of internet text, allowing it to generate human-like responses to a variety of prompts. ChatGPT can be used for various natural language processing tasks, such as question answering, conversation, and text generation. ChatGPT is a pre-trained language model that uses deep learning algorithms to generate text. It was trained on a large corpus of text data, allowing it to generate human-like responses to a wide range of prompts. The model has a transformer architecture, which has been shown to be effective in many NLP tasks. In addition to generating text, ChatGPT can also be fine-tuned for specific NLP tasks such as question answering, text classification, and language translation. This allows developers to build powerful NLP applications that can perform specific tasks more accurately. ChatGPT can also process and generate code.

OpenPipe provides fine-tuning for developers. Keep your datasets, models, and evaluations all in one place. Train new models with the click of a button. Automatically record LLM requests and responses. Create datasets from your captured data. Train multiple base models on the same dataset. We serve your model on our managed endpoints that scale to millions of requests. Write evaluations and compare model outputs side by side. Change a couple of lines of code, and you're good to go. Simply replace your Python or Javascript OpenAI SDK and add an OpenPipe API key. Make your data searchable with custom tags. Small specialized models cost much less to run than large multipurpose LLMs. Replace prompts with models in minutes, not weeks. Fine-tuned Mistral and Llama 2 models consistently outperform GPT-4-1106-Turbo, at a fraction of the cost. We're open-source, and so are many of the base models we use. Own your own weights when you fine-tune Mistral and Llama 2, and download them at any time.

Vicuna-13B is an open-source chatbot trained by fine-tuning LLaMA on user-shared conversations collected from ShareGPT. Preliminary evaluation using GPT-4 as a judge shows Vicuna-13B achieves more than 90%* quality of OpenAI ChatGPT and Google Bard while outperforming other models like LLaMA and Stanford Alpaca in more than 90%* of cases. The cost of training Vicuna-13B is around $300. The code and weights, along with an online demo, are publicly available for non-commercial use.

StableVicuna is the first large-scale open source chatbot trained via reinforced learning from human feedback (RHLF). StableVicuna is a further instruction fine tuned and RLHF trained version of Vicuna v0 13b, which is an instruction fine tuned LLaMA 13b model. In order to achieve StableVicuna’s strong performance, we utilize Vicuna as the base model and follow the typical three-stage RLHF pipeline outlined by Steinnon et al. and Ouyang et al. Concretely, we further train the base Vicuna model with supervised finetuning (SFT) using a mixture of three datasets: OpenAssistant Conversations Dataset (OASST1), a human-generated, human-annotated assistant-style conversation corpus comprising 161,443 messages distributed across 66,497 conversation trees, in 35 different languages; GPT4All Prompt Generations, a dataset of 437,605 prompts and responses generated by GPT-3.5 Turbo; And Alpaca, a dataset of 52,000 instructions and demonstrations generated by OpenAI's text-davinci-003.

Query and compare a large selection of open-source and proprietary models at once. Replace costly APIs with cheap custom AI models. Customize foundational models on your private data to adapt them to your particular use case. Small fine-tuned models can perform on par with GPT-4 and are up to 90% cheaper. Airtrain’s LLM-assisted scoring simplifies model grading using your task descriptions. Serve your custom models from the Airtrain API in the cloud or within your secure infrastructure. Evaluate and compare open-source and proprietary models across your entire dataset with custom properties. Airtrain’s powerful AI evaluators let you score models along arbitrary properties for a fully customized evaluation. Find out what model generates outputs compliant with the JSON schema required by your agents and applications. Your dataset gets scored across models with standalone metrics such as length, compression, coverage.

Instruction-following models such as GPT-3.5 (text-DaVinci-003), ChatGPT, Claude, and Bing Chat have become increasingly powerful. Many users now interact with these models regularly and even use them for work. However, despite their widespread deployment, instruction-following models still have many deficiencies: they can generate false information, propagate social stereotypes, and produce toxic language. To make maximum progress on addressing these pressing problems, it is important for the academic community to engage. Unfortunately, doing research on instruction-following models in academia has been difficult, as there is no easily accessible model that comes close in capabilities to closed-source models such as OpenAI’s text-DaVinci-003. We are releasing our findings about an instruction-following language model, dubbed Alpaca, which is fine-tuned from Meta’s LLaMA 7B model.

poolside is building next-generation AI for software engineering. A model built specifically for the challenges of modern software engineering. Fine-tune our model on how your business writes software, using your practices, libraries, APIs, and knowledge bases. Your proprietary model continuously learns how your developers write code. You become an AI company. We're building foundation models, an API, and an assistant to bring the power of generative AI to your developers. The poolside stack can be deployed to your own infrastructure. No data or code ever leaves your security boundary. Ideal for highly regulated industries like financial services, defense, and technology as well as retail, tech, and systems integrators. Your model ingests your codebases, documentation & knowledge bases to create a model that is uniquely suited to your dev teams & business. poolside is deployed in your environment which allows you to securely and privately connect it to your data.

Apply the latest NLP technology to your own data with the use of Haystack's pipeline architecture. Implement production-ready semantic search, question answering, summarization and document ranking for a wide range of NLP applications. Evaluate components and fine-tune models. Ask questions in natural language and find granular answers in your documents using the latest QA models with the help of Haystack pipelines. Perform semantic search and retrieve ranked documents according to meaning, not just keywords! Make use of and compare the latest pre-trained transformer-based languages models like OpenAI’s GPT-3, BERT, RoBERTa, DPR, and more. Build semantic search and question-answering applications that can scale to millions of documents. Building blocks for the entire product development cycle such as file converters, indexing functions, models, labeling tools, domain adaptation modules, and REST API.

Build and optimize text and image AI for your needs, train, fine-tune, and generate from your data. We use best-in-class open source models for image and language generation and can train them in minutes thanks to LoRA fine-tuning. Click the share button to create a link to your session, or create a bot. Optionally deploy to your own fully private infrastructure. You can start chatting with open source language models and generating images with Stable Diffusion XL by creating a free account right now. Fine-tuning your model on your own text or image data is as simple as drag’n’drop, and takes 3-10 minutes. You can then chat with and generate images from those fine-tuned models straight away, all using a familiar chat interface.

Intuitive experience to search for a narrative in human terms and stories, as well as leverage context and your team’s knowledge to better enable our proprietary machine learning models. Our Narrative Engine links your input to billions of pieces of content to filter and bring together the ones that match the subtleties of what you are looking for into Narratives you can analyze and track. Flexible workflow to fine-tune which creators of content and narrative amplifiers you are interested in. Select and fine-tune from a rich library, learn how naturally creators cluster or start with a set you follow and find others like them using our Community Machine Learning models. Easily track and analyze your Pendulum intelligence, going from top-level summaries to individual pieces of content to quickly spot trends and potential drivers of risk. Easily export charts and data to produce high-quality intelligence reports.

StarCoder and StarCoderBase are Large Language Models for Code (Code LLMs) trained on permissively licensed data from GitHub, including from 80+ programming languages, Git commits, GitHub issues, and Jupyter notebooks. Similar to LLaMA, we trained a ~15B parameter model for 1 trillion tokens. We fine-tuned StarCoderBase model for 35B Python tokens, resulting in a new model that we call StarCoder. We found that StarCoderBase outperforms existing open Code LLMs on popular programming benchmarks and matches or surpasses closed models such as code-cushman-001 from OpenAI (the original Codex model that powered early versions of GitHub Copilot). With a context length of over 8,000 tokens, the StarCoder models can process more input than any other open LLM, enabling a wide range of interesting applications. For example, by prompting the StarCoder models with a series of dialogues, we enabled them to act as a technical assistant.

Gaia Carbon Accounting empowers organisations to accurately measure, manage, and report their carbon footprint, aligning with global sustainability standards. As businesses face increasing pressure to reduce greenhouse gas emissions, our software offers a comprehensive solution that integrates seamlessly with existing systems, such as Xero, NetSuite and Quickbooks. By adopting Gaia Carbon Accounting, organisations can enhance transparency, improve environmental performance, and strengthen their position in a competitive market where sustainability is key. This can be demonstrated through out of the box regulatory reporting, including SECR and CSRD.

Generative AI may be new, but we've been building for this day for the past 5 years. Deep Lake thus combines the power of both data lakes and vector databases to build and fine-tune enterprise-grade, LLM-based solutions, and iteratively improve them over time. Vector search does not resolve retrieval. To solve it, you need a serverless query for multi-modal data, including embeddings or metadata. Filter, search, & more from the cloud or your laptop. Visualize and understand your data, as well as the embeddings. Track & compare versions over time to improve your data & your model. Competitive businesses are not built on OpenAI APIs. Fine-tune your LLMs on your data. Efficiently stream data from remote storage to the GPUs as models are trained. Deep Lake datasets are visualized right in your browser or Jupyter Notebook. Instantly retrieve different versions of your data, materialize new datasets via queries on the fly, and stream them to PyTorch or TensorFlow.

Metal is your production-ready, fully-managed, ML retrieval platform. Use Metal to find meaning in your unstructured data with embeddings. Metal is a managed service that allows you to build AI products without the hassle of managing infrastructure. Integrations with OpenAI, CLIP, and more. Easily process & chunk your documents. Take advantage of our system in production. Easily plug into the MetalRetriever. Simple /search endpoint for running ANN queries. Get started with a free account. Metal API Keys to use our API & SDKs. With your API Key, you can use authenticate by populating the headers. Learn how to use our Typescript SDK to implement Metal into your application. Although we love TypeScript, you can of course utilize this library in JavaScript. Mechanism to fine-tune your spp programmatically. Indexed vector database of your embeddings. Resources that represent your specific ML use-case.

Fine-tune and deploy AI models with Simplismart's fastest inference engine. Integrate with AWS/Azure/GCP and many more cloud providers for simple, scalable, cost-effective deployment. Import open source models from popular online repositories or deploy your own custom model. Leverage your own cloud resources or let Simplismart host your model. With Simplismart, you can go far beyond AI model deployment. You can train, deploy, and observe any ML model and realize increased inference speeds at lower costs. Import any dataset and fine-tune open-source or custom models rapidly. Run multiple training experiments in parallel efficiently to speed up your workflow. Deploy any model on our endpoints or your own VPC/premise and see greater performance at lower costs. Streamlined and intuitive deployment is now a reality. Monitor GPU utilization and all your node clusters in one dashboard. Detect any resource constraints and model inefficiencies on the go.

Action-based orchestration to build complex backend agents with multiple steps. Working for all LLMs, build fully customized UI for your agent without writing a single line of code, serving on your domain. Track every step of your agent, literally every step, to deal with the nondeterministic nature of LLMs. Build fine-grain access control over your application, data, and agent. Specialized fine-tuned model for accelerating software development. Automatically handle concurrency, rate limiting, and more.

Lumora's intelligent AI can improve any AI prompt, but ideally, we suggest utilizing the pre-existing AI options as their efficacy has been demonstrated. Organize, categorize, and manage your prompts effortlessly with Lumora’s streamlined management interface, designed for teams. Optimize your prompts for OpenAI, MidJourney, Stability, and more, ensuring they deliver peak performance across all platforms. Our playground offers a comprehensive space to experiment with prompts, allowing for diverse testing and fine-tuning. Tokens are used to generate AI requests. This feature is only available for premium users. Lumora employs feedback from users and AI to develop a leading industry tool for enhancing prompts, demonstrating a measurable impact on outcomes from its early adopters. Organize, categorize, and manage your prompts effortlessly with Lumora’s streamlined management interface, designed for teams.

Entry Point AI is the modern AI optimization platform for proprietary and open source language models. Manage prompts, fine-tunes, and evals all in one place. When you reach the limits of prompt engineering, it’s time to fine-tune a model, and we make it easy. Fine-tuning is showing a model how to behave, not telling. It works together with prompt engineering and retrieval-augmented generation (RAG) to leverage the full potential of AI models. Fine-tuning can help you to get better quality from your prompts. Think of it like an upgrade to few-shot learning that bakes the examples into the model itself. For simpler tasks, you can train a lighter model to perform at or above the level of a higher-quality model, greatly reducing latency and cost. Train your model not to respond in certain ways to users, for safety, to protect your brand, and to get the formatting right. Cover edge cases and steer model behavior by adding examples to your dataset.

Built on cutting-edge modern technologies, and with a highly scalable architecture, Fullscreen Retail Analytics transforms the raw location data into beautiful and meaningful insights. Using Wi-Fi infrastructure, indoor location, and device detection to create real-time analytics Fullscreen Retail Analytics allows you to count, track and understand visitors’ behavior and shopper patterns. The platform is delivered in a SaaS model, cloud-based or, deployable in the client’s infrastructure, using a decentralized architecture, based on one central hub that distributes the data, and independent and scalable nodes, one for each location. Implementation of integrated web and mobile platforms, starting from shopping and loyalty mobile applications that smooth omnichannel in-store and online experiences, continuing with B2B sales and distribution platforms, and finalizing with retail analytics technologies that deliver complex analysis and valuable reports.

GaiaLens is an AI-powered sustainability platform for institutional investors and financial services companies. Our platform acts as an automated ESG analyst team that can support investors throughout the whole ESG investment lifecycle and save them a significant amount of time. Choose your universe and screen on financial criteria and ESG factors at the same time. Research over 200 ESG factors for over 20,000 public companies and go right down to the raw values. GaiaLens is an automated ESG analyst team at your fingertips. Access the latest and highest quality ESG data available. We aim to simplify sustainable investing using technology. The GaiaLens platform is comprised of a suite of tools to help investors fulfill their ESG needs including portfolio reporting, investment screening, and deep-dive research capabilities. Investors can upload a portfolio in seconds and start comparing its ESG performance against a chosen benchmark.

TrueFoundry is a Cloud-native Machine Learning Training and Deployment PaaS on top of Kubernetes that enables Machine learning teams to train and Deploy models at the speed of Big Tech with 100% reliability and scalability - allowing them to save cost and release Models to production faster. We abstract out the Kubernetes for Data Scientists and enable them to operate in a way they are comfortable. It also allows teams to deploy and fine-tune large language models seamlessly with full security and cost optimization. TrueFoundry is open-ended, API Driven and integrates with the internal systems, deploys on a company's internal infrastructure and ensures complete Data Privacy and DevSecOps practices.

Solving Web3 reliability and performance issues by efficiently employing the resources of hundreds of third-party node providers combined with a state-of-the-art decentralized blockchain API platform and an improved user experience. Start building on the most relevant blockchain projects in the Web3 world. Aiming at providing one of the most resilient decentralized infrastructure services and the fastest response times in the industry, Blast is making use of clustering mechanisms and third-party node geographical distribution in order to help Web3 developers in getting their infrastructure needs covered easily and allow them to focus solely on the development of their applications. Scaling is simply done by allowing more Node providers into our network. Good node behavior is enforced within our protocol by performing periodic checks and applying coercive measures for nodes that underperform, like slashing staked tokens or exclusion from the network.

The next generation of our open source large language model. This release includes model weights and starting code for pretrained and fine-tuned Llama language models — ranging from 7B to 70B parameters. Llama 2 pretrained models are trained on 2 trillion tokens, and have double the context length than Llama 1. Its fine-tuned models have been trained on over 1 million human annotations. Llama 2 outperforms other open source language models on many external benchmarks, including reasoning, coding, proficiency, and knowledge tests. Llama 2 was pretrained on publicly available online data sources. The fine-tuned model, Llama-2-chat, leverages publicly available instruction datasets and over 1 million human annotations. We have a broad range of supporters around the world who believe in our open approach to today’s AI — companies that have given early feedback and are excited to build with Llama 2.

Don't let slow and inaccurate transcription tools slow you down: transcribe audio in seconds. Transkribieren.xyz is here to change the game, offering a fresh take on transcriptions that's faster, more accurate, and more versatile than others. Our web-based platform delivers top-notch transcriptions at lightning speed. Upload your audio and let Transkribieren.xyz do the magic. Our AI-driven transcription engine powered by OpenAI delivers exceptional quality, so you can trust your content will be spot on. Our intuitive browser-based editor makes it easy to fine-tune your content in real time.

Exelysis Contact Center is a contemporary telecom framework providing advanced features, improving the reliability of communication. Exelysis, through group based routing, allows the intelligent distribution of calls and the optimal utilization of agent resources. With Exelysis Contact Center, each call can be multiply tagged based on its characteristics, allowing for fine grained handling. An agent group acts like the bonding agent between calls and handling agents. Groups can abstract skills, departments and campaigns, providing great flexibility when modelling the call routing scenarios. Groups can be bundled in sets, allowing more complex scenarios to be implemented. Queueing of calls is performed dynamically, based on the call’s characteristics. Priorities allow for delicate tuning of call handling order, and advanced features like priority levels allow assigning important calls to agents concurrently with their streamlined workload.

CodeGen is an open-source model for program synthesis. Trained on TPU-v4. Competitive with OpenAI Codex.

The open source AI model you can fine-tune, distill and deploy anywhere. Our latest instruction-tuned model is available in 8B, 70B and 405B versions. Using our open ecosystem, build faster with a selection of differentiated product offerings to support your use cases. Choose from real-time inference or batch inference services. Download model weights to further optimize cost per token. Adapt for your application, improve with synthetic data and deploy on-prem or in the cloud. Use Llama system components and extend the model using zero shot tool use and RAG to build agentic behaviors. Leverage 405B high quality data to improve specialized models for specific use cases.

Capture production data, evaluate outputs collaboratively, and fine-tune your LLM's performance. Know exactly what goes on in production with an in-depth log overview. Collaborate with product managers, domain experts and engineers to build reliable model outputs. Track AI metrics such as speed, quality scores, and token usage. Copilot automates evaluations and model improvements for your use case. Create, manage, and optimize prompts to achieve precise and relevant interactions between users and AI models. Compare foundation models, and fine-tuned versions to improve prompt performance and save tokens. Collaborate with your team to build a proprietary fine-tuning dataset for your AI models. Build custom fine-tuning datasets to optimize model performance for specific use cases.

Ask anything about fitness, code generation, marketing, copywriting advice, etc. Gasby gives instant responses, using OpenAI latest models. Bring your OpenAI API Key to use, no login required

Fine-tune and get completions on private LLMs with a simple web API. No infrastructure is needed. Build private, SOC2-compliant AI applications instantly. Personalize models to your use case easily with our developer platform. Simply define the data you want to teach it and pick the base model - we take care of the rest. Put private LLMs into applications with a single API call, no more dealing with deployment, orchestration, or infrastructure hassles. The most powerful OSS model available—highly generalized capabilities with amazing narrative and reasoning capabilities. Harness a fully unlocked LLM to build the highest quality internal automation systems for your company.

Powerful language models a click away. Join over 8,000 developers building the next wave of world-changing applications. Fine-tune and deploy GPT-J, GPT-NeoX, Codegen, and FLAN-T5. Multiple models, each with different capabilities and price points. GPT-J is the fastest model, while GPT-NeoX is the most powerful—and more are on the way. Use these models for classification, entity extraction, code generation, chatbots, content generation, summarization, paraphrasing, sentiment analysis, and much more. These models have been pre-trained on a vast amount of text from the open internet. Fine-tuning improves upon this for specific tasks by training on many more examples than can fit in a prompt, letting you achieve better results on a wide number of tasks.

An AI engine that uses the Chaos Box algorithm to analyze real-time player inputs and dynamically generate NPC responses and new storylines based on Deep Reinforcement Learning. It can support massively emergent behaviors for AIs and NPCs in games without even a single script. Different from DeepMind and OpenAI, we are exploring more in the multi-agent and multi-objective scenario as for Reinforcement Learning. In this scenario, the behavior patterns for each different agent should coordinate and connect with each other to generate reasonable and dramatic story experience, helping the game production team significantly enhance every, no matter simple or complicated, statistics that can measure the user conversion rate in these experience-driven scenarios. Furthermore, based on the structure of game cloud service with client SDK, the game production teams can integrate our service during any stage of the game project with less effort, giving them a better user experience.

Chain Cloud is a decentralized infrastructure protocol designed for developers to access blockchain networks on-demand. Permissionless infrastructure is designed for you to retain control of your funds and keys. Designed to deploy your requested blockchain node without any technical knowledge. Join a network of computing resources for Chain Protocol and earn XCN. Using Chain Cloud, developers can access public blockchain networks to easily build their applications and projects with RPC API endpoints and complete automated nodes. Focus on shipping and scaling your product instead of building and maintaining ledger infrastructure. Ledgers do not require code changes, even if you add new features, transaction types, and even products to your ledger. Architected for the enterprise, Chain scales as your business does. Get unmatched insights into your business with fine-grain tracking and powerful analytics with Archive Node capabilities.

The OpenAI Realtime API is a newly introduced API, announced in 2024, that allows developers to create applications that facilitate real-time, low-latency interactions, such as speech-to-speech conversations. This API is designed for use cases like customer support agents, AI voice assistants, and language learning apps. Unlike previous implementations that required multiple models for speech recognition and text-to-speech conversion, the Realtime API handles these processes seamlessly in one call, enabling applications to handle voice interactions much faster and with more natural flow.

Spheron is a web3 infrastructure platform that provides tools and services to decentralize cloud storage and computing, allowing audited data centers to join the Spheron marketplace. The decentralized and governed nature of the infrastructure, overseen by Spheron, ensures permissionless access and heightened security for all users. Spheron Compute offers a feature-rich alternative to traditional cloud services at only one-third of the cost. Spheron offers a Compute Marketplace, which allows users to set up valuable tools quickly and easily, whether they want to deploy databases, nodes, tools, or AI. With Spheron, you don't have to worry about the technical stuff, and you can focus on deploying your Node with ease. Spheron Network has also partnered with organizations like Shardeum, Avail, Elixir, Filecoin, Arbitrum, etc, to redefine access to it and promote a more decentralized, inclusive, and community-centric ecosystem.

Lamini makes it possible for enterprises to turn proprietary data into the next generation of LLM capabilities, by offering a platform for in-house software teams to uplevel to OpenAI-level AI teams and to build within the security of their existing infrastructure. Guaranteed structured output with optimized JSON decoding. Photographic memory through retrieval-augmented fine-tuning. Improve accuracy, and dramatically reduce hallucinations. Highly parallelized inference for large batch inference. Parameter-efficient finetuning that scales to millions of production adapters. Lamini is the only company that enables enterprise companies to safely and quickly develop and control their own LLMs anywhere. It brings several of the latest technologies and research to bear that was able to make ChatGPT from GPT-3, as well as Github Copilot from Codex. These include, among others, fine-tuning, RLHF, retrieval-augmented training, data augmentation, and GPU optimization.

Run your dApps in a decentralized modular cloud built for real-world needs and configured for your requirements. SKALE Networks's modular protocol is one of the first of its kind to allow developers to easily provision highly configurable blockchains, which provide the benefits of decentralization without compromising on computation, storage, or security. Elastic blockchains are highly performant, decentralized, configurable, Ethereum compatible, and use the latest breakthroughs in modern cryptography to provide provable security. The standard for security in distributed systems, BFT guarantees that the network can reach consensus even when up to one third of participants are malicious. Following the same model as the Internet, this protocol recognizes latencies of nodes and the network, allowing messages to take an indefinite period of time to deliver. BLS Threshold Signatures enable efficient interchain communication and support randomness in node allocation.

Fast, lightweight, portable, rust-powered, and OpenAI compatible. We work with cloud providers, especially edge cloud/CDN compute providers, to support microservices for web apps. Use cases include AI inference, database access, CRM, ecommerce, workflow management, and server-side rendering. We work with streaming frameworks and databases to support embedded serverless functions for data filtering and analytics. The serverless functions could be database UDFs. They could also be embedded in data ingest or query result streams. Take full advantage of the GPUs, write once, and run anywhere. Get started with the Llama 2 series of models on your own device in 5 minutes. Retrieval-argumented generation (RAG) is a very popular approach to building AI agents with external knowledge bases. Create an HTTP microservice for image classification. It runs YOLO and Mediapipe models at native GPU speed.

Mindset Al's agent talks to users, determine exactly what they're looking for, and serves up easy-to-digest slices of content. Mindset Al's agent instantly delivers accurate, personalized, specific answers directly from your content library. When users ask a question, the Al agent will engage in conversation to determine exactly what they're looking for, so they'll always get the best-fit answer. Capabilities allow our AI to interact like a human coach, offering different responses based on user's needs and preferences. Mindset automatically updates to keep your knowledge in sync. Choose which parts of your knowledge base Mindset can access. Fine-tune your agent to fit exactly what you need and give it access to any LLM. Mindset connects to all your workplace applications. See how employees are engaging with your content. Track agent bias, monitor performance, and run tests at scale before giving your team access.

Open Architecture for Building and Running Load Tests. Need to quickly load test a home page, a single URL within your site, or even a mobile API endpoint. We allow you to compose simple tests and then scale them to tens of thousands of users within a few minutes. Apache JMeter, Gatling, Selenium, and WebDriver are more than just open source tools we enable in cloud load testing, they are vibrant communities with deep knowledge and products built on what real users need. Open load tests give you the flexibility of writing load tests in languages and utilities you use every day. You can write custom tests in Python, PHP or Node.js. We provide an open, easy, and cheap way for load testing. We achieve this with an open architecture which provides tuning and control to setting up the cloud load agents.

ChatGLM-6B is an open-source, Chinese-English bilingual dialogue language model based on the General Language Model (GLM) architecture with 6.2 billion parameters. Combined with model quantization technology, users can deploy locally on consumer-grade graphics cards (only 6GB of video memory is required at the INT4 quantization level). ChatGLM-6B uses technology similar to ChatGPT, optimized for Chinese Q&A and dialogue. After about 1T identifiers of Chinese and English bilingual training, supplemented by supervision and fine-tuning, feedback self-help, human feedback reinforcement learning and other technologies, ChatGLM-6B with 6.2 billion parameters has been able to generate answers that are quite in line with human preferences.

Our open source research efforts are focused both on the new "ware" ("middleware" and "software" that will wrap and integrate LLMs), as well as building high-quality, automation-focused enterprise models available in Hugging Face. LLMWare also provides a coherent, high-quality, integrated, and organized framework for development in an open system that provides the foundation for building LLM-applications for AI Agent workflows, Retrieval Augmented Generation (RAG), and other use cases, which include many of the core objects for developers to get started instantly. Our LLM framework is built from the ground up to handle the complex needs of data-sensitive enterprise use cases. Use our pre-built specialized LLMs for your industry or we can customize and fine-tune an LLM for specific use cases and domains. From a robust, integrated AI framework to specialized models and implementation, we provide an end-to-end solution.

The quickest way to get started with our illustration generator is to use pre-made models. If you want to depict a style or an object that is not available in the premade models you can train your own fine tune by uploading 5-15 illustrations. there are no limits to fine-tuning you can use it for illustrations icons or any assets you need. Read more about fine-tuning. Illustrations are exportable in PNG and SVG formats. Fine-tuning allows you to train the stable-diffusion AI model, on a particular object or style, and create a new model that generates images of those objects or styles. The fine-tuning will be only as good as the data you provide. Around 5-15 images are recommended for fine-tuning. Images can be of any unique object or style. Images should contain only the subject itself, without background noise or other objects. Images must not include any gradients or shadows if you want to export it as SVG later. PNG export still works fine with gradients and shadows.