Plug and Play is a seed and early-stage investor focused on great teams leading emerging growth companies.  Plug and Play runs 12 industry-specific accelerator programs twice a year, that acts as a platform for major corporations and high quality startups to connect and collaborate.  Located in the heart of Silicon Valley, Plug and Play participates in Seed, Angel and Series A funding where they often co-invest with their strategic partners. Through years of experience and as part of their network, Plug and Play has put together a world-class network of serial entrepreneurs, strategic investors, and industry leaders who actively assist the firm with its successful and growing investment portfolio.  SEED ROUND. Plug and Play participates in seed round investing through a program called Startup Camp. Startup Camp is a 10-week program based in Silicon Valley for top-notch entrepreneurs to work intensively on building out their business model. Select startups will refine their business models and prototypes with help from a combination of structured workshops, speaker series and mentorship sessions, as well as active coaching from their investment team. At the culmination of Startup Camp, founders will have crystalized their business plans and pitched their company to the venture capital community at EXPO Demo Day.''  ANGEL ROUND Plug and Play makes angel round investments throughout the year, sourced from their monthly Plug and Play Angels (PAPA) sessions. They are partnered with local angel investors in Silicon Valley who participate in PAPA to find the most promising startups and best new technologies.  SERIES A. Series A typical Series A round is in the range of $2 million to $10 million, and is intended to provide operating capital for the company for six months to two years. This round capitalizes the company as it develops its products, performs initial marketing and branding, acquires talent, and conducts other early-stage business operations. It is in this stage that Plug and Play will co-invest with over 180 venture capital partners.  Plug and Play has helped grow market leaders such as PayPal, Danger, Google, DropBox, LendingClub, Zoosk, SoundHound, CreditSesame, Skytree, and has over 400 more early-stage startups in its portfolio.

Plug and Play

We're Acequia Capital, a team and partnership with roots in Albuquerque. We're knowledge workers and systems thinkers who love to keep good company in most fields.

Acequia Capital (AceCap)

Founded in 2014, AC Ventures is a Southeast Asian venture capital firm that invests in early-stage startups focused on Indonesia and ASEAN, with over US$500 million in assets under management across five funds. The firm’s areas of investment focus on a variety of industries, including digital enablement, financial technologies, agriculture technologies, logistics, e-commerce, consumer technology, MSME solutions, waste management, renewable energy, and sustainability solutions.

AC Ventures

MiraclePlus invests in and accelerates early-stage startups. MiraclePlus assists startups in developing products that are good enough to succeed in the market. MiraclePlus' acceleration program works with the founders to get each team in top shape so that they can present to thousands of investors on Demo Day.

MiraclePlus

SilverStone Investment is an investment firm.

SilverStone Investment

Notable Capital is named for the founders we invest with, the ideas they pursue, the causes they champion, and the remarkable companies they build. Notable is a U.S.-based venture capital firm focused on early-to-growth stage companies in cloud infrastructure and business and consumer applications across the U.S., Israel, Europe, Latin America, and select go-global opportunities. Notable portfolio companies include Affirm, Airbnb, Block, Brightwheel, Drata, Handshake, HashiCorp, Ibotta, Orca Security, Quince, Slack, Slice, StockX, Stori, Vercel, Zendesk, and more.

Notable Capital

Camford Capital is a venture capital firm that invests in Enterprise, Consumer, FinTech, and Healthcare companies.

Camford Capital

LDV Partners they provide services for securitization of data and algorithms, robotics and artificial intelligence, precision health, and more.

LDV Partners

AimTop Ventures focuses on seed or early stage investments on technology application companies that can transform industries.

Aimtop Ventures

FEDML

FEDML Nexus AI® (https://nexus.fedml.ai) is a next-generation cloud platform that enables developers and enterprises to easily, economically, and securely build, deploy, and monetize their large language models (LLMs) and other generative AI models. It provides holistic support with a large-scale distributed GPU cloud (multi-cloud and multi-provider), high-performance ML libraries, user-friendly AIOps, and LLM and AI Agent studios.

FedML offers a distributed MLOps platform and software tools for developers to train, deploy, customize, and monitor ML models at scale across edge and cloud nodes. Additionally, it has created open-source libraries for federated (collaborative) learning, which solves the challenge of training ML models on sensitive and regulated data. This approach allows ML models to be trained at the edge using private or siloed data, without the need to share or relocate such data. FedML's libraries support machine learning on edge devices, distributed computing, as well as single-machine simulation.

The toolkit to build machine learning applications at scale

Machine Learning Infrastructure

<div>FedML specializes in developing tools and platforms for custom AI model development. The company's offerings include a MLOps platform that simplifies the training, serving, and monitoring of GenAI models and LLMs. Its key products include FedML Nexus AI and FedLLM.</div>

Empowering Tomorrow's Innovations with Generative AI Infrastructure

Generative AI Infrastructure

FedML

FEDML Empowers On-Premise AI Innovation at DENSO

Konica Minolta

To enable collaborative and privacy-preserving training, serving, and monitoring of ML models for medical imaging and radiomics across decentralized data silos, leveraging FedML's decentralized and collaborative AI platform.

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.

FedML offers a distributed MLOps platform and software tools for developers to train, deploy, customize, and monitor ML models at scale across edge and cloud nodes. Additionally, it has created open-source libraries for federated (collaborative) learning, which solves the challenge of training ML models on sensitive and regulated data. This approach allows ML models to be trained at the edge using private or siloed data, without the need to share or relocate such data. FedML's libraries support machine learning on edge devices, distributed computing, as well as single-machine simulation.FedML also offers a model serving platform to deploy trained ML models via geo-distributed cloud computing resources, as well as a model monitoring platform for continually monitoring and improving the model in real time.Key customers and partnershipsAs of July 2023, FedML had over 10 enterprise customers from the healthcare, financial services, logistics, retail, smart city, generative AI, and web3 industries. It also reported having over 3,000 developers using its platform, handling 8,500 training jobs across 10,000 edge devices.The company partnered with Theta Labs (in <a href="https://sp-edge.com/updates/20521">July 2023 </a>), a Web3 blockchain infrastructure provider for video, media, and entertainment, to launch a decentralized supercluster for generative AI and content recommendation. Through the partnership, FedML will allow Theta Edge Network community members to offer their individual computing resources for training and deploying AI models, catering to personalized content recommendations for Theta.tv viewers.Funding and financialsFedML raised <a href="https://sp-edge.com/updates/20264">USD 11.5 million in a seed funding round </a>led by Camford Capital, at a valuation of USD 56.5 million. The round was divided into two tranches, with the first tranche of USD 4.3 million closing in March 2023, followed by the second tranche of USD 7.2 million closing July 2023. The company was to use the fresh funds to expand the development and adoption of its platform.

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.

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

<div>
 
 FedML specializes in developing tools and platforms for custom AI model development. The company's offerings include a MLOps platform that simplifies the training, serving, and monitoring of GenAI models and LLMs. Its key products include FedML Nexus AI and FedLLM.
 
 
 Launched in 
 <a href="https://sp-edge.com/updates">
 October 2023
 </a>
 , FedML Nexus AI is a cloud service featuring a GPU marketplace, a unified ML job scheduler, a no-code LLM studio for GenAI model development, and optimized MLOps solutions for streamlined distributed model training, with a focus on simplifying complex workflows for developers.
 
 
 FedLLM is a training pipeline for developing domain-specific LLMs similar to OpenAI's GPT-4, using proprietary data. It stands out for its compatibility with popular LLM libraries like Hugging Face and DeepSpeed, designed to enhance the efficiency, security, and privacy of custom AI development.&nbsp;
 
 
 FedML stands out as it supports custom and open-source AI models and provides comprehensive capabilities in training, deploying, monitoring, and enhancing ML models across different environments. It also offers a collaborative AI platform enabling companies and developers to collaborate on AI tasks by sharing data, models, and computational resources.&nbsp;
 
 
 As of July 2023, FedML has completed over 8,500 AI training tasks on 10,000 Edge devices, and its open-source federated machine-learning library has become the industry's most widely used, surpassing Google's TensorFlow Federated in popularity.
 
 
 The platform is offered through a SaaS subscription model, which includes a free Starter package, Advanced package for USD 199 per month, and custom pricing for enterprises (March 2024).
 
 
 Key customers and partnerships
 
 
 As of July 2023, FedML is utilized by over 3,000 developers worldwide and 10 enterprise clients spanning various industries such as healthcare, retail, financial services, smart home and city, and mobility.
 
 
 In 
 <a href="https://sp-edge.com/updates/20521">
 July 2023
 </a>
 , FedML announced its collaboration with Theta Labs, a Web3 blockchain infrastructure specializing in video, media, and entertainment, with the aim of introducing a decentralized supercluster dedicated to GenAI and content suggestion.
 
 
 Funding and financials
 
 
 In 
 <a href="https://sp-edge.com/updates/20264">
 July 2023
 </a>
 , the firm raised USD 11.5 million in seed funding. The company noted the funds would be allocated for platform development.
 
</div>

<div>
 
 Founded in Israel, NeuReality specializes in providing hardware infrastructure to streamline computation processes to accelerate the development of AI applications. Its technology assists AI inferencing deployment by offering a comprehensive system solution that seamlessly supports a vast array of deep learning models.
 
 
 NeuRealitys&rsquo; infrastructure includes an architecture called the Network Addressable Processing Unit (NAPU) to maximize the capabilities of Deep Learning Accelerators (DLAs). This design facilitates inference through purpose-built NAPUs that are specifically crafted for AI inference tasks, enhancing performance and efficiency.
 
 
 The NR1 AI Inference Solution by NeuReality is a comprehensive system comprising architecture, hardware, and software platforms. Launched in November 2023, it intends to simplify the installation, utilization, and management of AI, making it accessible and manageable for users.
 
 
 The hardware offerings of the solution include,
 
 
 1. 
 NR1 Network Addressable Processing Unit
 : A network addressable inference Server-on-a-Chip with an embedded Neural Network Engine, which is a workflow-optimized hardware device with specialized processing units, native network capabilities, and virtualization capabilities
 
 
 2. 
 NR1-M&trade; AI Inference Module
 : A full-height, double-wide PCIe card containing one NR1 Network Addressable Processing Unit (NAPU) system-on-chip and a network addressable Inference Server that can connect to an external Deep Learning Accelerator (DLA)
 
 
 3. 
 NR1-S AI Inference Appliance
 : An optimized design for an inference server that contains NR1-M modules with the NR1 NAPU, which enables disaggregated AI service in a scalable and efficient architecture
 
 
 The software component of the solution is designed to be compatible with any trained model from any development environment. It includes tools that handle the entire AI pipeline and enable seamless connection of AI workflows to any environment.
 
 
 NeuReality differs from traditional AI chip connectivity in replacing CPU-centric support with an AI-centric platform. This allows components to communicate directly with AI accelerators, eliminating the need for commands to pass through a central processing unit. Additionally, the technology enables AI accelerators to connect with each other, enhancing efficiency and performance in AI applications. It also claims its AI-centric approach reduces complexity, cost, and power usage. The firm claims it can reduce inference costs by 90%.
 
 
 Key customers and partnerships
 
 
 In November 2021, NeuReality teamed up with IBM to develop advanced AI inference technology by enhancing its NR1 chip and system for use in IBM's Hybrid Cloud.
 
 
 In September 2021, the company partnered with Xilinx to develop AI-centric platforms that improve real-world AI applications. This collaboration was intended to focus on NeuReality's AI-centric inference platform NR1-P and address existing issues with AI deployment including cost and complexity.
 
 
 Funding and financials
 
 
 In 
 <a href="https://sp-edge.com/updates/27745">
 March 2024
 </a>
 , NeuReality secured USD 20 million in funding led by The European Innovation Council (EIC) Fund. The funds were intended to accelerate the deployment of NeuReality&rsquo;s NR1AI Inference Solution.
 
 
 In December 2022, it secured USD 35 million in a Series A funding round led by Samsung Ventures, with Cardumen Capital, Varana Capital, OurCrowd, XT Hi-Tech, and others as participants. The funding was used to launch its flagship AI inferencing solution.
 
</div>

NeuReality

<div>
 
 Accubits is an AI and BLOCKCHAIN focused development and solutions company based in Washington DC with its development offices in India and Dubai. Pioneering as a custom Blockchain solutions provider delivering solutions ever since 2012, Accubits is one of the oldest and experienced Blockchain dev house in the market and is featured as one among the top 13 Blockchain companies in India by INC42. We are a big family of engineers, innovators, inventors and many others continually working to help our customers in leveraging their business and adding value to their lives. Over the past 6 years, We have delivered more than 600 projects, for over 200 clients worldwide. Several of Fortune 500 companies in sectors from Retail to Health are being powered by our solutions to streamline and leverage their growth.Our portfolio for AI solutions includes intelligent conversational tools, RPAs, CRMs, SIPs, real-time video and image analytics systems, state of the art ALPR systems and many more being used enterprises, startups across North America, Canada, Middle East, Hong Kong, Singapore, Indonesia, India &amp; Sweden. Our portfolio of Blockchain development includes custom DApps and smart contracts, crypto token and exchange development, integrated blockchain services and ICO platforms.
 
</div>

Accubits

<div>
 
 LeewayHertz is a leading software development company delivering tailor-made digital solutions to businesses worldwide. Our team of 250+ full-stack developers, designers and innovators has designed and developed 100+ digital solutions across industry verticals. As a close-knit team of AI and web3 experts, designers and full-stack developers, we undertake collaborative research and development to create next-gen applications and solutions perfectly suited to the evolving tech space. As a technology pioneer with deep knowledge and expertise in AI, blockchain and other advanced technologies like IoT, LeewayHertz believes in helping companies overcome their most complex tech challenges and drive business growth. Our motto, &lsquo;You Dream It: We Build It,&rsquo; reflects our business philosophy. From putting flesh on your idea to delivering the expected end product, we do whatever it takes to make your project successful. Having worked with 30+ top fortune 500 companies and created various on-demand solutions, we boast an impressive work portfolio demonstrating our expertise.
 
</div>

LeewayHertz

Databricks, a data and AI company established by the original developers behind prominent Big Data solutions such as Delta Lake, Apache Spark, and MLflow, and provides organizations with AI and data analytics tools for efficient management of their data.Databricks' primary product is the Databricks Lakehouse platform, a unified data intelligence platform that merges a data warehouse and data lake to provide developers with efficient access to data and enables enterprise customers to create their AI models—similar to a ChatGPT-style AI system—using only their internal data.Databricks Unity Catalog, part of the Databricks Lakehouse Platform, provides unified governance for structured and unstructured data, machine-learning models, notebooks, dashboards, and files across various environments, offering automated monitoring, proactive alerts, and seamless data sharing through Delta Sharing integration. Furthermore, Databricks offers an open architecture that streamlines the AI development process, allowing the integration of various LLMs such as Llama 2, Azure OpenAI, and Anthropic, enabling customization with enterprise data for tailored model creation.Notably, Lakehouse leverages NVIDIA technology for accelerated data processing and AI model generation. Databricks also offers industry-specific solutions like Databricks Lakehouse for Healthcare, Financial Services, Retail, and Manufacturing.Databricks has expanded its offerings through multiple acquisitions, including MosaicML ( <a href="https://sp-edge.com/updates/19683">July 2023 </a>), Arcion ( <a href="https://sp-edge.com/updates/23041">October 2023 </a>), Okera ( <a href="https://sp-edge.com/updates/18197">May 2023 </a>), and Datajoy (October 2022). Key customers and partnershipsAs of July 2023, Databricks served a global customer base of approximately 10,000, including notable customers such as Comcast, DuPont, Honeywell, Rolls-Royce, Shell, and Tata Steel.Notable partnerships include collaboration with NVIDIA to incorporate NVIDIA TensorRT-LLM into its inference service and a partnership with Hevo-Data to automate data integration into the lakehouse for mutual customers (October 2022).Databricks also partnered with Karini AI to accelerate GenAI deployment for enterprises (<a href="https://sp-edge.com/updates/33687">September 2024</a>)Databricks also provides an LLM Mesh partner program; it has partnered with firms such as <a href="https://sp-edge.com/updates/24218">Dataiku </a>where an emphasis is placed on comprehensive data access, enabling tight integration of GenAI applications with enterprise data.

Databricks

<div>
 
 Labelbox offers a data-centric AI platform for enterprises, enabling them to develop, optimize, and use AI to solve complex problems and power new products and services.&nbsp;&nbsp;
 
 
 Labelbox&rsquo;s platform offers capabilities for building, optimizing, training, fine-tuning LLMs, and AI-enabled data labeling automation.&nbsp;
 
 
 Its products include&nbsp;
 
 
 1) Catalog: A platform for building AI applications with features such as advanced search capabilities and optimizing data for labeling budgets
 
 
 2) Annotate: A data labeling solution designed to streamline and accelerate labeling operations using automation tools and pre-labeling techniques
 
 
 (3) Model: Offers tools for data enrichment, model-assisted labeling, and custom Foundry Apps to automate data management tasks and improve AI model performance&nbsp;&nbsp;
 
 
 (4) Boost: Offers fully managed tailored solutions such as on-demand data labeling services to enhance AI development speed and efficiency.&nbsp;
 
 
 As such, Labelbox enables companies to streamline the fine-tuning and alignment of LLMs and enables the validation of outputs through techniques such as reinforcement learning with human feedback (RLHF), reinforcement learning from AI feedback (RELIEF), and evaluation. This incorporation of human expertise ensures more accurate, contextually relevant, trustworthy, and secure results from LLM systems.
 
 
 The platform is offered through a SaaS subscription model with packages ranging from free subscriptions with limited usage and custom pricing for enterprises.
 
 
 Key customers and partnerships
 
 
 The firm's solutions have use cases across diverse industries, including retail, consumer internet, healthcare, manufacturing, and financial services. Labelbox has a large portfolio of customers, including NASA's Jet Propulsion Laboratory and Blue River Technology, a smart AgriTech company that used Labelbox's model-assisted labeling suite to enhance its See &amp; Spray technology in smart agriculture, resulting in herbicide cost savings of 70%&ndash;80. Labelbox's customers also include several Fortune 500 companies, such as Walmart, P&amp;G, Audi Adobe, Airbnb, Bayer, and Bosch.
 
 
 Key partnerships include a long-term collaboration with 
 <a href="https://sp-edge.com/updates/21770">
 Google Cloud
 </a>
 to facilitate digital transformations in retail, consumer internet, financial services, and manufacturing and logistics.
 
 
 Funding and financials
 
 
 In January 2022, the firm raised USD 110 million in Series D funding led by SoftBank's Vision Fund 2. The company planned to utilize the funds to finance company expansion.
 
 
 
</div>

Labelbox

Integrated solutions that handle various processes such as model training, fine-tuning, model deployment, monitoring, and maintenance in working with and deploying LLMs

Platforms that provide hardware such as high-performance CPUs, GPUs, or TPUs, including cloud-based solutions that are commonly used to train and run GenAI models efficiently

Platforms that assist with fine-tuning pre-trained GenAI models or custom models tailored to specific use cases. Includes services that train models from scratch or use existing models

Platforms that store and retrieve training data in vector databases for access during the model training phase

Services to deploy GenAI models (on-premises or cloud-based) into production environments and integration tools to support existing systems and workflows

Ongoing monitoring of GenAI models to ensure performance. Includes regular model retraining, performance optimization, and troubleshooting

Platforms that assist in designing and refining prompts or instructions to GenAI models to get the desired responses or outcomes

Platforms that enable safe, responsible, and ethical GenAI deployment, ensuring compliance with regulations and/or protection against GenAI-based cybersecurity threats.

All services offered by these companies provide support to AI/ML

NLP is a key component of generative AI which is the core focus of this hub.

All companies within this space are offering infrastructure for generative AI

Generative AI infrastructure hub covers companies that deploy and run these foundation models.

DISRUPTOR_PRESENT

PROMINENT_CATEGORY

The given HTML code contains a <div> element that wraps around a <ul> element. Inside the <ul> element, there are two <li> elements. Each <li> element contains a element. The content of the first element announces the launch of FedML Nexus AI, a cloud service for developing large language models and GenAI. The content of the second element mentions the features provided by the platform, such as a GPU marketplace, a ML job scheduler, a LLM studio, and optimized MLOps solutions for distributed model training. The platform aims to save developers time and effort by simplifying their workflows.

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