Best AI tools for< Ai Inference Specialist >

FuriosaAI is an AI application that offers Hardware RNGD for LLM and Multimodality, as well as WARBOY for Computer Vision. It provides a comprehensive developer experience through the Furiosa SDK, Model Zoo, and Dev Support. The application focuses on efficient AI inference, high-performance LLM and multimodal deployment capabilities, and sustainable mass adoption of AI. FuriosaAI features the Tensor Contraction Processor architecture, software for streamlined LLM deployment, and a robust ecosystem support. It aims to deliver powerful and efficient deep learning acceleration while ensuring future-proof programmability and efficiency.

Wallaroo.AI is an AI inference platform that offers production-grade AI inference microservices optimized on OpenVINO for cloud and Edge AI application deployments on CPUs and GPUs. It provides hassle-free AI inferencing for any model, any hardware, anywhere, with ultrafast turnkey inference microservices. The platform enables users to deploy, manage, observe, and scale AI models effortlessly, reducing deployment costs and time-to-value significantly.

NeuReality is an AI-centric solution designed to democratize AI adoption by providing purpose-built tools for deploying and scaling inference workflows. Their innovative AI-centric architecture combines hardware and software components to optimize performance and scalability. The platform offers a one-stop shop for AI inference, addressing barriers to AI adoption and streamlining computational processes. NeuReality's tools enable users to deploy, afford, use, and manage AI more efficiently, making AI easy and accessible for a wide range of applications.

VeroCloud is a platform offering tailored solutions for AI, HPC, and scalable growth. It provides cost-effective cloud solutions with guaranteed uptime, performance efficiency, and cost-saving models. Users can deploy HPC workloads seamlessly, configure environments as needed, and access optimized environments for GPU Cloud, HPC Compute, and Tally on Cloud. VeroCloud supports globally distributed endpoints, public and private image repos, and deployment of containers on secure cloud. The platform also allows users to create and customize templates for seamless deployment across computing resources.

Cerebras is a leading AI tool and application provider that offers cutting-edge AI supercomputers, model services, and cloud solutions for various industries. The platform specializes in high-performance computing, large language models, and AI model training, catering to sectors such as health, energy, government, and financial services. Cerebras empowers developers and researchers with access to advanced AI models, open-source resources, and innovative hardware and software development kits.

Luxonis is an AI application that offers Visual AI solutions engineered for precision edge inference. The application provides stereo depth cameras with unique features and quality, enabling users to perform advanced vision tasks on-device, reducing latency and bandwidth demands. With open-source DepthAI API, users can create and deploy custom vision solutions that scale with their needs. Luxonis also offers real-world training data for self-improving vision intelligence and operates flawlessly through vibrations, temperature shifts, and extended use. The application integrates advanced sensing capabilities with up to 48MP cameras, wide field of view, IMUs, microphones, ToF, thermal, IR illumination, and active stereo for unparalleled perception.

Rebellions is an AI technology company specializing in AI chips and systems-on-chip for various applications. They focus on energy-efficient solutions and have secured significant investments to drive innovation in the field of Generative AI. Rebellions aims to reshape the future by providing versatile and efficient AI computing solutions.

The pplx-api is an AI tool designed to provide documentation and examples for blazingly fast LLM inference. It offers a reference for developers to integrate AI capabilities into their applications efficiently. The tool focuses on enhancing natural language processing tasks by leveraging advanced models and algorithms. Users can access detailed guides, API references, changelogs, and engage in discussions related to AI technologies.

Cambricon is an AI technology company that specializes in developing intelligent acceleration cards and systems. They offer a range of products including cloud AI acceleration cards, edge AI chips, and intelligent processing units. Cambricon's advanced chiplet technology and MLUarch03 architecture provide high-performance AI solutions for training and inference tasks. The company is dedicated to advancing the AI industry through innovative hardware and software platforms.

Viral Magic is an AI-powered influencer agency that leverages advanced algorithms to match brands with the most suitable influencers for their marketing campaigns. The platform streamlines the influencer marketing process by providing data-driven insights and analytics to optimize campaign performance. With a vast network of influencers across various industries, Viral Magic helps brands reach their target audience effectively and efficiently.

BladeRunner is a browser plug-in that highlights AI-generated text directly on web pages. It helps users detect AI-generated content in various contexts such as social media, news, education, e-commerce, and government communications. The tool aims to assist individuals in distinguishing between human-generated and AI-generated text, especially in the age of advanced language models and increasing AI influence on digital content.

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

vHub.ai is an AI-powered Influencer Marketing SaaS Platform that offers a comprehensive suite of tools to streamline influencer marketing campaigns. With features like in-depth influencer insights, authenticity assurance, instant campaign analytics, effortless influencer coordination, and tailor-made campaign strategies, vHub.ai aims to revolutionize the way brands collaborate with influencers. The platform boasts a database of 5 million influencers and 100's of influencer marketing agencies, providing users with the perfect influencer at optimal pricing. By leveraging AI search engine capabilities and VQS (vHub Quality Score), vHub.ai ensures genuine connections and successful influencer partnerships. Users can track campaign performance in real-time, manage all types of campaigns, and customize strategies with precision. With a focus on data-driven influencer discovery, authentic campaigns, custom success campaigns, ROI-driven marketing, and streamlined campaign management, vHub.ai empowers brands to maximize their influencer marketing ROI and reach.

Impulze.ai is an Influencer Analytics Platform designed to help users discover and manage influencers from a vast global database covering Instagram, TikTok, and YouTube. The platform offers AI algorithms that effectively identify the right influencers, allowing users to effortlessly filter influencers based on various criteria such as engagement rate, follower count, location, age, and gender. Additionally, Impulze.ai provides audience analytics, fraud detection, and data-driven matching to help users find the perfect match for their brand. With features like real-time performance metrics, audience filters, and campaign tracking, Impulze.ai streamlines influencer marketing strategies for agencies and marketers, saving time and enhancing brand awareness.

Lamini is an enterprise-level LLM platform that offers precise recall with Memory Tuning, enabling teams to achieve over 95% accuracy even with large amounts of specific data. It guarantees JSON output and delivers massive throughput for inference. Lamini is designed to be deployed anywhere, including air-gapped environments, and supports training and inference on Nvidia or AMD GPUs. The platform is known for its factual LLMs and reengineered decoder that ensures 100% schema accuracy in the JSON output.

MySocial.ai is an AI-powered tool designed to help users optimize their digital brand on LinkedIn. It offers features such as curated content suggestions, AI copywriting assistance, post scheduling, and personalized content recommendations. By leveraging AI technology, MySocial.ai aims to assist users in expanding their reach, maximizing influence, and enhancing engagement on the platform.

integrate.ai is a platform that enables data and analytics providers to collaborate easily with enterprise data science teams without moving data. Powered by federated learning technology, the platform allows for efficient proof of concepts, data experimentation, infrastructure agnostic evaluations, collaborative data evaluations, and data governance controls. It supports various data science jobs such as match rate analysis, exploratory data analysis, correlation analysis, model performance analysis, feature importance & data influence, and model validation. The platform integrates with popular data science tools like Azure, Jupyter, Databricks, AWS, GCP, Snowflake, Pandas, PyTorch, MLflow, and scikit-learn.

Cision is an end-to-end communications and media intelligence platform that provides a suite of tools and services to help public relations and communications professionals understand, influence, and amplify their stories. Cision's platform includes PR Newswire, CisionOne, and Cision Insights, which offer a range of capabilities such as PR distribution, media monitoring, media analytics, and influencer outreach. Cision's solutions are used by a wide range of organizations, including Fortune 500 companies, government agencies, and non-profit organizations.

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.

Spikes Studio is an AI-powered video editing tool that specializes in transforming long videos into viral clips for platforms like YouTube, Twitch, TikTok, and Reels. The platform offers advanced editing features, such as auto-captions, AI-generated B-Roll, audio enhancements, GIFs, and social media scheduling. With a focus on boosting viewer retention and engagement, Spikes Studio provides a fast and efficient solution for content creators to repurpose their videos effortlessly.

BMF (Babit Multimedia Framework) is a cross-platform, multi-language, customizable multimedia processing framework developed by ByteDance. It offers native compatibility with Linux, Windows, and macOS, Python, Go, and C++ APIs, and high performance with strong GPU acceleration. BMF allows developers to enhance its features independently and provides efficient data conversion across popular frameworks and hardware devices. BMFLite is a client-side lightweight framework used in apps like Douyin/Xigua, serving over one billion users daily. BMF is widely used in video streaming, live transcoding, cloud editing, and mobile pre/post processing scenarios.

Code Atlas is a lightweight interpreter developed in C++ that supports the execution of multi-language code snippets and partial Markdown rendering. It consumes significantly lower resources compared to similar tools, making it suitable for resource-limited devices. It leverages llama.cpp for local large-model inference and supports cloud-based large-model APIs. The tool provides features for code execution, Markdown rendering, local AI inference, and resource efficiency.

Awesome-LLMOps is a curated list of the best LLMOps tools, providing a comprehensive collection of frameworks and tools for building, deploying, and managing large language models (LLMs) and AI agents. The repository includes a wide range of tools for tasks such as building multimodal AI agents, fine-tuning models, orchestrating applications, evaluating models, and serving models for inference. It covers various aspects of the machine learning operations (MLOps) lifecycle, from training to deployment and observability. The tools listed in this repository cater to the needs of developers, data scientists, and machine learning engineers working with large language models and AI applications.

ReductStore is a high-performance time series database designed for storing and managing large amounts of unstructured blob data. It offers features such as real-time querying, batching data, and HTTP(S) API for edge computing, computer vision, and IoT applications. The database ensures data integrity, implements retention policies, and provides efficient data access, making it a cost-effective solution for applications requiring unstructured data storage and access at specific time intervals.

InternLM is a powerful language model series with features such as 200K context window for long-context tasks, outstanding comprehensive performance in reasoning, math, code, chat experience, instruction following, and creative writing, code interpreter & data analysis capabilities, and stronger tool utilization capabilities. It offers models in sizes of 7B and 20B, suitable for research and complex scenarios. The models are recommended for various applications and exhibit better performance than previous generations. InternLM models may match or surpass other open-source models like ChatGPT. The tool has been evaluated on various datasets and has shown superior performance in multiple tasks. It requires Python >= 3.8, PyTorch >= 1.12.0, and Transformers >= 4.34 for usage. InternLM can be used for tasks like chat, agent applications, fine-tuning, deployment, and long-context inference.

A curated list of open source repositories for AI Engineers. The repository provides a comprehensive collection of tools and frameworks for various AI-related tasks such as AI Gateway, AI Workload Manager, Copilot Development, Dataset Engineering, Evaluation, Fine Tuning, Function Calling, Graph RAG, Guardrails, Local Model Inference, LLM Agent Framework, Model Serving, Observability, Pre Training, Prompt Engineering, RAG Framework, Security, Structured Extraction, Structured Generation, Vector DB, and Voice Agent.

This repository showcases how to deploy generative AI models from Amazon SageMaker JumpStart using the AWS CDK. Generative AI is a type of AI that can create new content and ideas, such as conversations, stories, images, videos, and music. The repository provides a detailed guide on deploying image and text generative AI models, utilizing pre-trained models from SageMaker JumpStart. The web application is built on Streamlit and hosted on Amazon ECS with Fargate. It interacts with the SageMaker model endpoints through Lambda functions and Amazon API Gateway. The repository also includes instructions on setting up the AWS CDK application, deploying the stacks, using the models, and viewing the deployed resources on the AWS Management Console.

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

AI-resources is a repository containing links to various resources for learning Artificial Intelligence. It includes video lectures, courses, tutorials, and open-source libraries related to deep learning, reinforcement learning, machine learning, and more. The repository categorizes resources for beginners, average users, and advanced users/researchers, providing a comprehensive collection of materials to enhance knowledge and skills in AI.

SambaNova AI Starter Kits is a collection of open-source examples and guides designed to facilitate the deployment of AI-driven use cases for developers and enterprises. The kits cover various categories such as Data Ingestion & Preparation, Model Development & Optimization, Intelligent Information Retrieval, and Advanced AI Capabilities. Users can obtain a free API key using SambaNova Cloud or deploy models using SambaStudio. Most examples are written in Python but can be applied to any programming language. The kits provide resources for tasks like text extraction, fine-tuning embeddings, prompt engineering, question-answering, image search, post-call analysis, and more.

This repository is a work in progress that contains first-principle implementations of groundbreaking AI algorithms using various deep learning frameworks. Each implementation is accompanied by supporting research papers, aiming to provide comprehensive educational resources for understanding and implementing foundational AI algorithms from scratch.

Awesome-Embodied-AI is a curated list of papers on Embodied AI and related resources, tracking and summarizing research and industrial progress in the field. It includes surveys, workshops, tutorials, talks, blogs, and papers covering various aspects of Embodied AI, such as vision-language navigation, large language model-based agents, robotics, and more. The repository welcomes contributions and aims to provide a comprehensive overview of the advancements in Embodied AI.

The Intel Gaudi Tutorials repository contains source files for tutorials on using PyTorch and PyTorch Lightning on the Intel Gaudi AI Processor. The tutorials cater to users from beginner to advanced levels and cover various tasks such as fine-tuning models, running inference, and setting up DeepSpeed for training large language models. Users need access to an Intel Gaudi 2 Accelerator card or node, run the Intel Gaudi PyTorch Docker image, clone the tutorial repository, install Jupyterlab, and run the Jupyterlab server to follow along with the tutorials.

Responsible AI Toolbox is a suite of tools providing model and data exploration and assessment interfaces and libraries for understanding AI systems. It empowers developers and stakeholders to develop and monitor AI responsibly, enabling better data-driven actions. The toolbox includes visualization widgets for model assessment, error analysis, interpretability, fairness assessment, and mitigations library. It also offers a JupyterLab extension for managing machine learning experiments and a library for measuring gender bias in NLP datasets.

README-AI is a developer tool that auto-generates README.md files using a combination of data extraction and generative AI. It streamlines documentation creation and maintenance, enhancing developer productivity. This project aims to enable all skill levels, across all domains, to better understand, use, and contribute to open-source software. It offers flexible README generation, supports multiple large language models (LLMs), provides customizable output options, works with various programming languages and project types, and includes an offline mode for generating boilerplate README files without external API calls.

llm-resource is a comprehensive collection of high-quality resources for Large Language Models (LLM). It covers various aspects of LLM including algorithms, training, fine-tuning, alignment, inference, data engineering, compression, evaluation, prompt engineering, AI frameworks, AI basics, AI infrastructure, AI compilers, LLM application development, LLM operations, AI systems, and practical implementations. The repository aims to gather and share valuable resources related to LLM for the community to benefit from.

The End-to-End LLM Bootcamp is a comprehensive training program that covers the entire process of developing and deploying large language models. Participants learn to preprocess datasets, train models, optimize performance using NVIDIA technologies, understand guardrail prompts, and deploy AI pipelines using Triton Inference Server. The bootcamp includes labs, challenges, and practical applications, with a total duration of approximately 7.5 hours. It is designed for individuals interested in working with advanced language models and AI technologies.

A repository that lists papers related to Large Language Model (LLM) based agents. The repository covers various topics including survey, planning, feedback & reflection, memory mechanism, role playing, game playing, tool usage & human-agent interaction, benchmark & evaluation, environment & platform, agent framework, multi-agent system, and agent fine-tuning. It provides a comprehensive collection of research papers on LLM-based agents, exploring different aspects of AI agent architectures and applications.

The Together Cookbook is a collection of code and guides designed to help developers build with open source models using Together AI. The recipes provide examples on how to chain multiple LLM calls, create agents that route tasks to specialized models, run multiple LLMs in parallel, break down tasks into parallel subtasks, build agents that iteratively improve responses, perform LoRA fine-tuning and inference, fine-tune LLMs for repetition, improve summarization capabilities, fine-tune LLMs on multi-step conversations, implement retrieval-augmented generation, conduct multimodal search and conditional image generation, visualize vector embeddings, improve search results with rerankers, implement vector search with embedding models, extract structured text from images, summarize and evaluate outputs with LLMs, generate podcasts from PDF content, and get LLMs to generate knowledge graphs.

Ling is a MoE LLM provided and open-sourced by InclusionAI. It includes two different sizes, Ling-Lite with 16.8 billion parameters and Ling-Plus with 290 billion parameters. These models show impressive performance and scalability for various tasks, from natural language processing to complex problem-solving. The open-source nature of Ling encourages collaboration and innovation within the AI community, leading to rapid advancements and improvements. Users can download the models from Hugging Face and ModelScope for different use cases. Ling also supports offline batched inference and online API services for deployment. Additionally, users can fine-tune Ling models using Llama-Factory for tasks like SFT and DPO.

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