Y Combinator is a startup accelerator that invests in a large number of startups twice a year. It created a new model for funding startups. Twice a year, the company invests a small amount of money ($150k) in a large number of startups. The startup accelerator works intensively with the companies for three months, to get them into the best possible shape and refine their pitch to investors. Each cycle culminates in Demo Day when the startups present their companies to a carefully selected, invite-only audience.

Y Combinator

Sequoia Scout is an investment firm operating in stealth mode.

Sequoia Scout

VentureSouq (VSQ) is a MENA-based venture capital fund manager with a global portfolio. VSQ manages thematic funds, with a current focus on FinTech and ClimateTech.

VentureSouq

Duke Angel Network leverages the Duke network to help investors find innovative early-stage companies with great teams, and their entrepreneurs find access to smart capital to fuel their growth. Their mission is to support the global Duke entrepreneurial community with an angel investing platform and co-investment fund (the Duke Innovation Fund) that engages and leverages the power of the Duke alumni network. The Duke Angel Network operational team and investment platform exist within the Duke Innovation and Entrepreneurship Initiative. The Duke Angel Network actively engages and matches Duke alumni network expertise with portfolio companies to support growth and success. The global Duke community offers a uniquely powerful opportunity for networking and guidance from industry experts and successful entrepreneurial leaders. Duke Angel Network members work actively to connect their portfolio companies with the Duke network to foster collaboration and further success.

Duke Angel Network

kt investment is a new technology business finance company established in 2015. It is an investment company that represents KT Group . kt investment seeks to contribute to social contribution and maximize investment return through win-win cooperation with promising SMEs and venture companies . kt investment seeks to achieve long-term returns by looking at the market from a global perspective and looking for value investment opportunities in the long term.

KT investment

Murex Partners is a VC firm specializing in thesis-driven investing.

Murex Partners

Pegasus Tech Ventures is a Silicon Valley-based venture capital firm working with emerging technology companies across the world, and specialize in helping entrepreneurs achieve global expansion into North America, Asia, and Europe. Our 100+ person team operates out of offices across 7 different countries and offers a wide range of domain expertise. Pegasus Tech Ventures currently has several multi-million dollar funds under management. We seek to work with world-class management and technical teams that are targeting disruptive opportunities in IT, Health IT, Artificial Intelligence, IoT, Robotics, Big Data, Virtual Reality, Augmented Reality, Quantum Computing, FinTech, and Next Generation Technologies.

Pegasus Tech Ventures

Atinum Partners is a venture capital firm that invests in the growth stage startups in the IT, biotech, and healthcare sectors.

Atinum Partners

Stonebridge Ventures

Premier Partners (프리미어 파트너스) is a Korean domestic funds management company. It provides investment services for individuals and businesses. Premier Partners was established in September 2005 in Seoul, Korea.

Premier Partners

The Korea Development Bank (KDB) provides long-term financing for projects designed to assist Koreaâ€:tm:s economic growth and development. It offers equipment capital loans and working capital loans to Korean private enterprises that undertake major industrial projects. The bank also extends guarantees to its clients to facilitate their other borrowings and to finance major industrial projects. KDB guarantees Won-denominated corporate debentures, local currency loans, and other Won liabilities and foreign currency loans from domestic and overseas Korean financial institutions and from foreign institutions. The bankâ€:tm:s other activities include engagement in a range of industrial development activities, including conducting economic and industrial research; performing engineering surveys; providing business analyses and managerial assistance; and offering trust services. As of June 30, 2007, KDB had 40 local branches, 6 overseas branches, and 2 overseas offices. The bank was founded in 1954 and is headquartered in Seoul, South Korea.

Korea Development Bank

Duke University is a private research university in Durham, North Carolina. Home of the Blue Devils, Duke University has about 15,000 undergraduate and graduate students and a world-class faculty helping to expand the frontiers of knowledge. The university has a strong commitment to applying knowledge in service to society, both near its North Carolina campus and around the world.

Duke University

KT&G is the leading tobacco company in South Korea with annual sales of over $4 billion USD. KT&G was originally a government-owned monopoly but was privatized and today is publicly traded, competing for market share with other international tobacco firms such as Philip Morris International, British American Tobacco, and Japan Tobacco. KT&G's sales volume share was 62% of the Korean market in 2009. KT&G produces popular Korean cigarette brands such as The One, Indigo, Arirang, This, This Plus, Zest, Esse, Raison, and Lo Crux. It has been expanded outside Korea, especially through its superslims brand Esse in Russia and other eastern European markets. KT&G also owns significant subsidiaries such as Korea Ginseng Corporation, Yungjin Pharm (a pharmaceuticals company), and several bio ventures. Its headquarters are in Daejeon.

KT&G Corporation

HL Holdings provides mobility parts, infotainment, tuning, and fleet management of mobility services. They provide auto parts and module service of logistics services. They give freezing and refrigeration of cold chain services.

HL Holdings

Superb AI

Superb AI is an end-to-end training data platform that automates data preparation at scale and makes building and iterating on datasets quick, systematic, and repeatable. Launched in 2018 by data scientists, academics, and ML engineers, Superb AI is reinventing how teams of all sizes label, manage, curate, and deliver training data. Fueled by decades of experience and academic research in computer vision and deep learning, including 25+ publications, 7,300+ citations, and 100+ patents, Superb AI empowers companies at all stages to build and deploy computer vision applications faster than ever before. For more information or to get started for free, go to superb-ai.com.

Superb AI offers an end-to-end MLOps platform. It allows ML developers to curate and label data with AI assistance and automatically train custom AI models using no-code deep learning model training. The platform also facilitates one-click live deployment and monitoring of ML models to the cloud and access via API endpoints, without the need for extensive coding.

The toolkit to build machine learning applications at scale

Machine Learning Infrastructure

Superb AI participates in AI EXPO and introduces ‘Industrial Field Vision AI’

Superb AI offers an end-to-end MLOps platform. It allows ML developers to curate and label data with AI assistance and automatically train custom AI models using no-code deep learning model training. The platform also facilitates one-click live deployment and monitoring of ML models to the cloud and access via API endpoints, without the need for extensive coding.In addition, Superb AI offers fully managed services with AI/ML models built on open-source datasets and provides training data including images and videos to developers. The company also provides access to productivity apps that allow developers to automate workflows, migrate data, and convert data formats, which was in beta as of April 2024.Superb AI provides its platform and services through flexible packages based on customer requirements.Key customers and partnershipsIts notable customers include Hyundai, Toyota, Samsung, Rowbot, and LG.Funding and financialsIn September 2022, the company raised USD 16 million in a Series B funding round led by Korea Development Bank. It had planned to use the funds to expand its team and improve its technology.

Datagen provides a self-service synthetic data platform that generates visual synthetic data of humans for computer vision applications. The platform allows users to write their own code to generate labeled synthetic data for faces, full body, and humans in motion in the form of images and videos to test and train AI models while retaining complete control over the data. The data covers a range of computer vision tasks including face landmark detection, face and hair segmentation, facial recognition and identification, full body pose estimation, full body segmentation, and behavior detection.Key customers and partnershipsThe company serves three of the top five global technology companies and Fortune 500 companies across the automotive, smart fitness, AR/VR/metaverse, smart office, and home security industries. Its notable customers include Google, Toyota, NVIDIA, IBM, and Intel.Funding and financialsIn March 2022, the company raised USD 50 million in a Series B funding round led by Scale Venture Partners. The funds were utilized to bolster its position in the market.Datagen reported to have recorded 8x growth in revenue in 2022.

Datagen

Weights &amp; Biases offers a platform that allows users to build models with experiment tracking, data set and model versioning, data visualization, hyperparameter optimization, and model management. The platform enables users to automatically retrain and re-evaluate models and centrally manage all model versions through every lifecycle stage—from development to staging to production. It also helps to visualize comparisons between model versions to evaluate performance and identify regressions before model deployment. It also offers toolkits such as <a href="https://sp-edge.com/updates/19172">W&amp;B Weave and W&amp;B Production Monitoring </a>to build and monitor data- and ML-powered applications, respectively, through interactive visualizations.The company also offers a <a href="https://sp-edge.com/updates/17880">suite of tools (W&amp;B Prompts) </a>to support large language model operations (LLMOps). W&amp;B Prompts includes tools and features for experiment tracking, debugging, and collaboration, as well as a one-click method to evaluate and score prompts through the OpenAI Eval’s framework.The company provides the platform through a free tier and under a subscription model for up to USD 50 per user per month.Key customers and partnershipsWeights &amp; Biases served more than 700,000 ML practitioners as of August 2023. Its notable include NVIDIA, Toyota, BMW Group, Samsung, Fujifilm, Truebill, and Clear Capital.The company has <a href="https://sp-edge.com/updates/18663">partnered with Lambda </a>, a GPU cloud computing provider, to offer its MLOps platform integrated with the infrastructure services of the latter, catering to enterprises dealing with AI and deep-learning workloads.Funding and financialsIn August 2023, the company raised <a href="https://sp-edge.com/updates/20874">USD 50 million in a strategic investment </a>round at a valuation of USD 1.25 billion, led by Daniel Gross and Nat Friedman. The round also saw participation from Sapphire Ventures, Coatue, Insight Partners, and other investors. The company aimed to utilize the fresh funds to further develop its ML tools, including the launch of W&amp;B Prompts.

Weights & Biases

BentoML offers an open-source platform called Bento Cloud, for the deployment and scaling of AI applications. It is a fully managed platform that handles the complexities of AI infrastructure, providing serverless autoscaling as required during the development and production stages. The platform helps to ship models to production with advanced deployment options including online and shadow A/B testing, while also providing visibility through model performance monitoring. The platform integrates with an organization’s existing data stack and enables users to continuously deploy and improve models in production. The company offers its platform through a combination of subscription and usage-based model.In addition, BentoML also provides the following open-source platforms: 1) Yatai, for model deployment on Kubernetes and 2) bentoctl, for model deployment on any cloud platform.Key customers and partnershipsAs of January 2024, BentoML reported that over 1,000 organizations, comprising more than 3,000 members, use its platform. Its notable customers include Koo, Open Layer, Line, and Naver.The company entered into a strategic partnership with TomTom, a developer of location technology, to help integrate with various models as well as in LLM deployments.Funding and financialsThe company raised <a href="https://sp-edge.com/updates/19684">USD 9 million in seed funding </a>in June 2023 led by DCM Ventures, with participation from Bow Capital. It aimed to channel the newly acquired funds to enhance its platform and offer developers a range of tools for building, deploying, and scaling AI applications efficiently.

BentoML

Iguazio provides a serverless platform based on its open-source Nuclio framework that helps users to develop, deploy, and manage real-time AI applications without requiring them to manually manage underlying infrastructures such as servers and storage. The platform creates real-time intelligence for applications located at the edge, public cloud, and on-premise data centers and reduces bandwidth constraints by consolidating data into a repository and making it available for applications as required. The platform can ingest and transform data from any source, which is then used to train, evaluate, deploy, and monitor models in production.The company leverages Big Data and ML software such as Apache Spark, TensorFlow, and Kubernetes to manage software containers that enable applications to run across different computing environments.Key customers and partnershipsIguazio serves customers in the financial services, telecommunications, smart mobility, manufacturing, retail, AdTech, gaming, healthcare, energy, and utilities sectors. Notable customers include Samsung, Microsoft, NVIDIA, AWS, Google, and Intel.Funding and financialsIn January 2020, the company raised USD 24 million in a funding round led by INCapital Ventures. The funds were utilized to accelerate its growth, expand its reach into new global markets, grow sales, and facilitate new sales channels that include companies such as Dell Technologies

Iguazio

Cogito Tech provides image and video annotation to generate computer vision training data sets for ML &amp; deep learning (DL). The video annotation solution leverages AI-powered tools to convert video into a sequence of images and generates training data sets for ML-based AI models, including self-driving cars and drones. The AI model understands and derives insights from visual data to detect, identify, classify, and track objects in an image or video. Cogito also provides virtual assistants and chatbots to help users in the process of training ML algorithms. Cogito Tech also provides high-quality, ethically sourced datasets that are compliant and reliable to train ML models.In addition, the company provides services to fine-tune LLMs and GenAI applications through reinforcement learning techniques as well as stress test models through red teaming.Key customers and partnershipsAs of December 2022, the company served more than 150 customers across 25 countries in the retail, medical, automotive, agriculture, robotics, smart cities, security, and manufacturing industries. Notable customers includes Verizon Media, The University of Sydney, National Geographic, Tumblr, and Vimeo.

Cogito Tech

Platforms and frameworks that help developers build and train ML models.

Platforms that deploy and host the trained and tested models in production and integrate them into applications through APIs.

Platforms that generate artificial data that mimics the characteristics of real data, which is then used to train ML models at scale.

Platforms that help monitor and manage ML models in training and deployment to track performance, conduct variance analysis, and optimize performance.

Makers of hardware such as CPUs, GPUs, and other application-specific hardware required to train and run ML workloads.

Integrated solutions that handle the end-to-end processes of developing, training, deploying, and monitoring ML models.

Data exchange providers and platforms that offer data labeling services via manual and/or software methods, which are used as input to train ML models.

Includes companies that provide infrastructure to build AI/ML applications

Provides tools to build, monitor, and deploy GenAI applications

Industry is focused on offering platforms for other businesses to build AI-/ML-powered apps

Superb AI

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