Best AI tools for< Optimize Networks >

Caffe is a deep learning framework developed by Berkeley AI Research (BAIR) and community contributors. It is designed for speed, modularity, and expressiveness, allowing users to define models and optimization through configuration without hard-coding. Caffe supports both CPU and GPU training, making it suitable for research experiments and industry deployment. The framework is extensible, actively developed, and tracks the state-of-the-art in code and models. Caffe is widely used in academic research, startup prototypes, and large-scale industrial applications in vision, speech, and multimedia.

Metal Networks is an AI-enabled B2B software platform that aims to transform B2B industrial supply chains by simplifying quoting processes through AI-enabled product taxonomy and catalog search. The platform addresses the challenges faced by both buyers and suppliers in the industrial material and commercial markets, such as product abbreviations, lack of taxonomy, manual data entry, and messy catalogs. By leveraging AI technology, Metal Networks streamlines RFQ processes, enhances digital experiences, and boosts operational efficiency for organizations. The platform caters to wholesalers, suppliers, distributors, producers, manufacturers, procurement buyers, traders, software providers, integrators, and various managerial roles by offering seamless digitization solutions.

Brand Networks (BN) is a leading provider of AI-driven social technologies that empower organizations to deliver unrivaled brand experiences. BN's Social Activation Engine includes three core solutions: Brand Advocate, Advertising Optimization, and Data Collaboration. Brand Advocate helps organizations harness the passion of their brand enthusiasts to create authentic, compelling, and brand-safe content at scale. Advertising Optimization leverages AI to optimize campaign performance and media spend across leading social channels. Data Collaboration enables brands to share and capitalize on valuable data sets, elevating consumer experiences and boosting social engagement. BN's advanced AI integrations, including content creation, brand compliance, and advertising optimization, provide organizations with the tools they need to power social transformation and achieve their business goals.

LatenceTech is a tech startup that specializes in network latency monitoring and analysis. The platform offers real-time monitoring, prediction, and in-depth analysis of network latency using AI software. It provides cloud-based network analytics, versatile network applications, and data science-driven network acceleration. LatenceTech focuses on customer satisfaction by providing full customer experience service and expert support. The platform helps businesses optimize network performance, minimize latency issues, and achieve faster network speed and better connectivity.

The Global Blockchain Show is an annual event that brings together experts and enthusiasts in the blockchain and AI industries. The event features a variety of speakers, workshops, and exhibitions, and provides a platform for attendees to learn about the latest developments in these fields. The 2024 Global Blockchain Show will be held in Dubai, UAE, from April 16-17. The event will feature a keynote address from Sophia, the world's most famous humanoid robot, as well as presentations from other leading experts in the blockchain and AI fields. Attendees will also have the opportunity to network with other professionals in the industry and learn about the latest products and services from leading companies. The Global Blockchain Show is a must-attend event for anyone interested in the latest developments in blockchain and AI.

Zoocial is an AI-powered social media marketing tool that offers a comprehensive solution for businesses to enhance their online presence and engage with customers effectively. It provides features such as AI-powered chatbots for Facebook Messenger and Instagram, social media management tools, e-commerce platform integration, and marketing automation capabilities. Zoocial helps businesses optimize their social media strategies, automate tasks, and convert followers into customers, ultimately boosting sales and brand visibility.

Anycores is an AI tool designed to optimize the performance of deep neural networks and reduce the cost of running AI models in the cloud. It offers a platform that provides automated solutions for tuning and inference consultation, optimized networks zoo, and platform for reducing AI model cost. Anycores focuses on faster execution, reducing inference time over 10x times, and footprint reduction during model deployment. It is device agnostic, supporting Nvidia, AMD GPUs, Intel, ARM, AMD CPUs, servers, and edge devices. The tool aims to provide highly optimized, low footprint networks tailored to specific deployment scenarios.

EnterpriseAI is an advanced computing platform that focuses on the intersection of high-performance computing (HPC) and artificial intelligence (AI). The platform provides in-depth coverage of the latest developments, trends, and innovations in the AI-enabled computing landscape. EnterpriseAI offers insights into various sectors such as financial services, government, healthcare, life sciences, energy, manufacturing, retail, and academia. The platform covers a wide range of topics including AI applications, security, data storage, networking, and edge/IoT technologies.

Cisco offers a range of Artificial Intelligence (AI) solutions to help organizations leverage the power of AI in various aspects of their operations. From infrastructure scaling to data insights and AI-powered software, Cisco provides a comprehensive suite of services to accelerate the adoption and implementation of AI technologies. The company also invests in AI innovation and collaborates with industry leaders like NVIDIA to shape the future of AI infrastructure. With a focus on responsible AI, Cisco aims to deliver cutting-edge solutions that drive productivity and security while ensuring inclusivity and transparency in the AI ecosystem.

Rick's Cloud is an AI-powered platform that offers a wide range of services related to cloud computing, artificial intelligence, machine learning, and security. The platform provides insights and trends in the IT industry, with a focus on AI and its impact on various sectors. Rick's Cloud aims to help businesses thrive by leveraging AI technologies and staying ahead of industry trends.

Poker Bot AI+ is an advanced poker AI application that offers fully automated poker bots powered by neural networks and machine learning. The application provides a suite of products to enhance poker gameplay, including automated online poker bots, AI advisor PokerX, Poker Ecology service, poker skill development with AI-guided tips, and Android-based poker farms on emulators. It supports various poker games and rooms, ensuring optimal decision-making for players. The software guarantees secure gameplay by emulating human behavior and safeguarding user identity. Before purchasing, the effectiveness of the poker bot is demonstrated privately. Poker Bot AI+ aims to revolutionize the poker industry with cutting-edge AI technology.

Skai is an omnichannel marketing platform that leverages AI-powered capabilities to help clients take their campaigns to the next level. It offers a suite of full-funnel capabilities for commerce media advertisers, enabling effective and efficient activation of media programs across various channels. Skai brings together 100+ publishers and retail media networks into one platform for complete visibility across paid media programs. With AI technology, users can identify investment opportunities, make confident decisions, and maximize engagement across search, social, retail media, and app stores.

Newor Media is a programmatic ad management company that provides publishers with a full suite of ad monetization solutions to maximize their earnings using the industry’s most advanced AI-driven tech stack. With algorithmic real-time bidding, machine-learning, and a team of Ad Ops experts, Newor Media helps publishers increase their ad revenue while balancing user experience. The company has partnerships with all major networks and agencies, ensuring that publishers have access to the most diverse and quality-driven demand in the market.

Vectorizer.AI is an online tool that allows users to convert PNG and JPG images to SVG vectors quickly and easily using artificial intelligence. The application utilizes deep learning networks and classical algorithms to analyze, process, and convert images from pixels to geometric shapes. It offers a full-featured deep vector engine, clean corners, high performance, symmetry modeling, and adaptive simplification, among other advanced features. Vectorizer.AI supports various input and output formats, including SVG, PDF, EPS, DXF, and PNG, making it a versatile tool for creating scalable vector graphics.

Functionize is an AI Agentic Automation Platform for Enterprises that offers expert AI agents to handle business processes autonomously. The platform utilizes deep learning neural networks to deliver unparalleled performance across various enterprise applications. Functionize's AI agents run autonomously, self-heal workflows, and redefine efficiency and reliability in automation. The platform provides immediate value with pretrained automation, evolves with operational environments, and ensures seamless adaptability and precision in every task. Functionize helps mitigate risks, unlock gains, and support digital transformation for enterprises.

AdIntelli is an AI tool that helps users earn revenue from their AI Agent by integrating in-chat ads. It offers a seamless way to monetize AI applications by tapping into global ad networks and optimizing ad placements with advanced AI-driven technology. AdIntelli simplifies the process of earning revenue from AI Agents, making it accessible and profitable for users without the need for coding skills.

DLabs.AI is an AI software development company that specializes in harnessing the power of artificial intelligence to help businesses grow and operate more efficiently. They offer a range of AI solutions tailored to various industries, such as marketing, sales, customer service, retail, healthcare, education, finance, and manufacturing. With expertise in data science, machine learning, natural language processing, and neural networks, DLabs.AI provides unique AI applications that optimize workflows, automate processes, and enhance decision-making. Their focus on data security, personalized solutions, and continuous support sets them apart as a trusted partner in the AI industry.

Tailwind is an AI-enhanced social media and email marketing tool that leverages advanced AI technology to help businesses grow their online presence and engage with their target audience effectively. The tool offers a wide range of features such as AI-generated marketing content, social design creation, scheduling and distribution across multiple networks, hashtag finder, personalized post times, and more. Tailwind is designed to simplify the marketing process for businesses by providing tailored marketing plans, personalized designs, and automated optimization, ultimately saving time and effort for users.

Atomwise is an AI-powered drug discovery company that uses machine learning to identify new small molecule medicines. The company's platform combines the power of convolutional neural networks with massive chemical libraries to discover new drug candidates. Atomwise has a portfolio of wholly owned and co-developed pipeline assets, and is backed by prominent investors.

Fedica (Formerly Tweepsmap) is an AI-driven social media analytics and publishing platform that helps users build a thriving social media community. It offers tools for publishing, analyzing, listening, and engaging across various social networks. With advanced scheduling capabilities, AI-driven analytics, community analysis, and social listening features, Fedica empowers users to optimize their social media presence and grow their followers strategically.

cl-waffe2 is an experimental deep learning framework in Common Lisp, providing fast, systematic, and customizable matrix operations, reverse mode tape-based Automatic Differentiation, and neural network model building and training features accelerated by a JIT Compiler. It offers abstraction layers, extensibility, inlining, graph-level optimization, visualization, debugging, systematic nodes, and symbolic differentiation. Users can easily write extensions and optimize their networks without overheads. The framework is designed to eliminate barriers between users and developers, allowing for easy customization and extension.

MNN is a highly efficient and lightweight deep learning framework that supports inference and training of deep learning models. It has industry-leading performance for on-device inference and training. MNN has been integrated into various Alibaba Inc. apps and is used in scenarios like live broadcast, short video capture, search recommendation, and product searching by image. It is also utilized on embedded devices such as IoT. MNN-LLM and MNN-Diffusion are specific runtime solutions developed based on the MNN engine for deploying language models and diffusion models locally on different platforms. The framework is optimized for devices, supports various neural networks, and offers high performance with optimized assembly code and GPU support. MNN is versatile, easy to use, and supports hybrid computing on multiple devices.

DeepLearning-Interview-Awesome-2024 is a repository that covers various topics related to deep learning, computer vision, big models (LLMs), autonomous driving, smart healthcare, and more. It provides a collection of interview questions with detailed explanations sourced from recent academic papers and industry developments. The repository is aimed at assisting individuals in academic research, work innovation, and job interviews. It includes six major modules covering topics such as large language models (LLMs), computer vision models, common problems in computer vision and perception algorithms, deep learning basics and frameworks, as well as specific tasks like 3D object detection, medical image segmentation, and more.

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

Stake-auto-bot is a tool designed for automated staking in the cryptocurrency space. It allows users to set up automated processes for staking their digital assets, providing a convenient way to earn rewards and secure networks. The tool simplifies the staking process by automating the necessary steps, such as selecting validators, delegating tokens, and monitoring rewards. With Stake-auto-bot, users can optimize their staking strategies and maximize their returns with minimal effort.

Neural Network Compression Framework (NNCF) provides a suite of post-training and training-time algorithms for optimizing inference of neural networks in OpenVINO™ with a minimal accuracy drop. It is designed to work with models from PyTorch, TorchFX, TensorFlow, ONNX, and OpenVINO™. NNCF offers samples demonstrating compression algorithms for various use cases and models, with the ability to add different compression algorithms easily. It supports GPU-accelerated layers, distributed training, and seamless combination of pruning, sparsity, and quantization algorithms. NNCF allows exporting compressed models to ONNX or TensorFlow formats for use with OpenVINO™ toolkit, and supports Accuracy-Aware model training pipelines via Adaptive Compression Level Training and Early Exit Training.

SharpNEAT is a complete implementation of NEAT written in C# and targeting .NET 9. It provides an implementation of an Evolutionary Algorithm (EA) with the specific goal of evolving a population of neural networks towards solving some goal problem task. The framework facilitates research into evolutionary computation and specifically evolution of neural networks, allowing for modular experimentation with genetic coding and evolutionary algorithms.

PyTorch Forecasting is a PyTorch-based package for time series forecasting with state-of-the-art network architectures. It offers a high-level API for training networks on pandas data frames and utilizes PyTorch Lightning for scalable training on GPUs and CPUs. The package aims to simplify time series forecasting with neural networks by providing a flexible API for professionals and default settings for beginners. It includes a timeseries dataset class, base model class, multiple neural network architectures, multi-horizon timeseries metrics, and hyperparameter tuning with optuna. PyTorch Forecasting is built on pytorch-lightning for easy training on various hardware configurations.

The Fire-Flyer File System (3FS) is a high-performance distributed file system designed for AI training and inference workloads. It leverages modern SSDs and RDMA networks to provide a shared storage layer that simplifies development of distributed applications. Key features include performance, disaggregated architecture, strong consistency, file interfaces, data preparation, dataloaders, checkpointing, and KVCache for inference. The system is well-documented with design notes, setup guide, USRBIO API reference, and P specifications. Performance metrics include peak throughput, GraySort benchmark results, and KVCache optimization. The source code is available on GitHub for cloning and installation of dependencies. Users can build 3FS and run test clusters following the provided instructions. Issues can be reported on the GitHub repository.

Zeta is a tool designed to build state-of-the-art AI models faster by providing modular, high-performance, and scalable building blocks. It addresses the common issues faced while working with neural nets, such as chaotic codebases, lack of modularity, and low performance modules. Zeta emphasizes usability, modularity, and performance, and is currently used in hundreds of models across various GitHub repositories. It enables users to prototype, train, optimize, and deploy the latest SOTA neural nets into production. The tool offers various modules like FlashAttention, SwiGLUStacked, RelativePositionBias, FeedForward, BitLinear, PalmE, Unet, VisionEmbeddings, niva, FusedDenseGELUDense, FusedDropoutLayerNorm, MambaBlock, Film, hyper_optimize, DPO, and ZetaCloud for different tasks in AI model development.

Deeppowers is a powerful Python library for deep learning applications. It provides a wide range of tools and utilities to simplify the process of building and training deep neural networks. With Deeppowers, users can easily create complex neural network architectures, perform efficient training and optimization, and deploy models for various tasks. The library is designed to be user-friendly and flexible, making it suitable for both beginners and experienced deep learning practitioners.

AI-Drug-Discovery-Design is a repository focused on Artificial Intelligence-assisted Drug Discovery and Design. It explores the use of AI technology to accelerate and optimize the drug development process. The advantages of AI in drug design include speeding up research cycles, improving accuracy through data-driven models, reducing costs by minimizing experimental redundancies, and enabling personalized drug design for specific patients or disease characteristics.

This repository contains a hand-curated list of great machine (deep) learning resources for Natural Language Processing (NLP) with a focus on Generative Pre-trained Transformer (GPT), Bidirectional Encoder Representations from Transformers (BERT), attention mechanism, Transformer architectures/networks, Chatbot, and transfer learning in NLP.

The LLM course is divided into three parts: 1. 🧩 **LLM Fundamentals** covers essential knowledge about mathematics, Python, and neural networks. 2. 🧑‍🔬 **The LLM Scientist** focuses on building the best possible LLMs using the latest techniques. 3. 👷 **The LLM Engineer** focuses on creating LLM-based applications and deploying them. For an interactive version of this course, I created two **LLM assistants** that will answer questions and test your knowledge in a personalized way: * 🤗 **HuggingChat Assistant**: Free version using Mixtral-8x7B. * 🤖 **ChatGPT Assistant**: Requires a premium account. ## 📝 Notebooks A list of notebooks and articles related to large language models. ### Tools | Notebook | Description | Notebook | |----------|-------------|----------| | 🧐 LLM AutoEval | Automatically evaluate your LLMs using RunPod |  | | 🥱 LazyMergekit | Easily merge models using MergeKit in one click. |  | | 🦎 LazyAxolotl | Fine-tune models in the cloud using Axolotl in one click. |  | | ⚡ AutoQuant | Quantize LLMs in GGUF, GPTQ, EXL2, AWQ, and HQQ formats in one click. |  | | 🌳 Model Family Tree | Visualize the family tree of merged models. |  | | 🚀 ZeroSpace | Automatically create a Gradio chat interface using a free ZeroGPU. |  |

LLMLight is a novel framework that employs Large Language Models (LLMs) as decision-making agents for Traffic Signal Control (TSC). The framework leverages the advanced generalization capabilities of LLMs to engage in a reasoning and decision-making process akin to human intuition for effective traffic control. LLMLight has been demonstrated to be remarkably effective, generalizable, and interpretable against various transportation-based and RL-based baselines on nine real-world and synthetic datasets.

Mooncake is a serving platform for Kimi, a leading LLM service provided by Moonshot AI. It features a KVCache-centric disaggregated architecture that separates prefill and decoding clusters, leveraging underutilized CPU, DRAM, and SSD resources of the GPU cluster. Mooncake's scheduler balances throughput and latency-related SLOs, with a prediction-based early rejection policy for highly overloaded scenarios. It excels in long-context scenarios, achieving up to a 525% increase in throughput while handling 75% more requests under real workloads.

AgentKit is a framework for creating and orchestrating AI Agents, enabling developers to build, test, and deploy reliable AI applications at scale. It allows for creating networked agents with separate tasks and instructions to solve specific tasks, as well as simple agents for tasks like writing content. The framework requires the Inngest TypeScript SDK as a dependency and provides documentation on agents, tools, network, state, and routing. Example projects showcase AgentKit in action, such as the Test Writing Network demo using Workflow Kit, Supabase, and OpenAI.

PyTorch Forecasting is a PyTorch-based package designed for state-of-the-art timeseries forecasting using deep learning architectures. It offers a high-level API and leverages PyTorch Lightning for efficient training on GPU or CPU with automatic logging. The package aims to simplify timeseries forecasting tasks by providing a flexible API for professionals and user-friendly defaults for beginners. It includes features such as a timeseries dataset class for handling data transformations, missing values, and subsampling, various neural network architectures optimized for real-world deployment, multi-horizon timeseries metrics, and hyperparameter tuning with optuna. Built on pytorch-lightning, it supports training on CPUs, single GPUs, and multiple GPUs out-of-the-box.

uTensor is an extremely light-weight machine learning inference framework built on Tensorflow and optimized for Arm targets. It consists of a runtime library and an offline tool that handles most of the model translation work. The core runtime is only ~2KB. The workflow involves constructing and training a model in Tensorflow, then using uTensor to produce C++ code for inferencing. The runtime ensures system safety, guarantees RAM usage, and focuses on clear, concise, and debuggable code. The high-level API simplifies tensor handling and operator execution for embedded systems.

LLM4Opt is a collection of references and papers focusing on applying Large Language Models (LLMs) for diverse optimization tasks. The repository includes research papers, tutorials, workshops, competitions, and related collections related to LLMs in optimization. It covers a wide range of topics such as algorithm search, code generation, machine learning, science, industry, and more. The goal is to provide a comprehensive resource for researchers and practitioners interested in leveraging LLMs for optimization tasks.

Optimizes cloud-based networks for efficient organizational operations.

Expert in data encoding schemes

Analyse & visualise semantic networks entities and attributes for content creation.

Expert in physics-informed neural networks for practitioners

Friendly guide on home networks, making tech easy to grasp

A WiFi expert discussing technology, networks, and troubleshooting.

Explore our expert for LinkedIn Advertising, designed for impactful B2B marketing. It smartly navigates professional networks, tailoring ad strategies, refining targeting, and analyzing engagement, to connect your brand with key industry players and decision-makers on LinkedIn.

Advises on wireless communication technologies to enhance organizational efficiency.

Neural Network Master V2.0

Especialista em redes, direto e objetivo.

I'm Back Propagation, here to help you understand and apply back propagation techniques to your AI models.

Guides organization in telecommunications systems implementation and optimization.

Aids in RF system analysis and antenna optimization.

A friendly and insightful guide to mastering PyTorch.

The most comprehensive guide to ML theory and applications.

Adapts explanations to user's TensorFlow skill level

Expert in PyTorch, adept at simplifying complex concepts.

Designs and optimizes organization's network architecture to ensure seamless operations.

Premier 5G Network Expertise, Endorsed by OpenAI

A technical encyclopedia for network operations, offering detailed solutions and advice.