Google Ventures invests in sectors including life sciences, consumer, enterprise, crypto, climate, and frontier technology. With Alphabet as its sole limited partner, Google Ventures focuses on long-term investments. Its operating partners assist startups in design, equity, diversity & inclusion, talent, and engineering and help them connect with Google for technology and expertise. Founded in 2009 as Google Ventures, Google Ventures manages over $8 billion in assets with 400 active portfolio companies in North America and Europe. Some notable investments include Uber, Nest, Slack, GitLab, and One Medical. Google Ventures is based in the San Francisco Bay Area with offices in Cambridge, New York, and London.

Google Ventures

Greylock Partners invests in entrepreneurs that focus on consumer and enterprise software companies. The firm invests in companies that define new markets, including Airbnb, AppDynamics, Apptio, Arista Networks (NYSE: ANET), Cloudera, Docker, Dropbox, Facebook (Nasdaq: FB), LinkedIn (NYSE: LNKD), Medium, Nextdoor, Palo Alto Networks (NYSE: PANW), Pandora (NYSE: P), Pure Storage, and Workday (NYSE: WDAY). It was founded in 1965 and headquartered in Menlo Park, California.

Greylock

Accel is an early and growth-stage venture capital firm that powers a global community of entrepreneurs. Accel backs entrepreneurs who have what it takes to build a business.  Accel’s vision for entrepreneurship and business enables it to identify and invest in the companies that will be responsible for the growth of next-generation industries. Accel-backed companies include Atlassian, Braintree, Cloudera, DJI, Dropbox, Dropcam, Etsy, Facebook, Flipkart, Lookout Security, MoPub, Qualtrics, Slack, Spotify, Supercell, Vox Media, and others.

Accel

IQT identifies and partners with companies developing advanced technologies. It evaluates emerging technologies and collaborates with entities that show potential for practical applications. IQT serves industries such as defense, cybersecurity, and telecommunications.

SV Angel is a service organization, investing in founders who share these values. They support entrepreneurs in building lasting companies by assisting at key inflection points and leveraging networks to help them propel their businesses forward.

SV Angel

Lightspeed Venture Partners is a venture capital firm that engages in consumer, enterprise, technology, and cleantech markets. It focuses on seed, early-stage, later-stage, expansion-stage, start-ups, growth companies, and incubation, and specializes in debt financing for start-ups and growth companies. Lightspeed Venture Partners invests in various sectors that include enterprise, consumer, big data, bitcoin, enterprise technology, cleantech, mobile, internet, financial technology, cloud solutions, e-commerce, storage, media, networking, energy, and software, software-as-a-service, information technology, biotechnology, and social.

Lightspeed Venture Partners

BlackRock is an investment management company that provides its services to a diverse range of clients, including institutions, intermediaries, foundations, and individual investors. The firm operates as a global asset manager, overseeing and advising on a wide array of investment portfolios. In addition to its role as an investment manager, BlackRock is also known for its technological innovations and solutions that support various aspects of the financial industry. The company's multifaceted approach encompasses investment management, financial technology, and serving a broad spectrum of clients in the financial ecosystem.

BlackRock

Nepenthe Capital

Boston Trust Walden Company is an independent, employee-owned firm providing investment management services to institutional investors and private wealth clients.

Boston Trust Walden Company

Addition is a venture capital firm that invests in early and growth-stage tech companies. The firm was founded in 2020 by Lee Fixel with a mission to support visionary entrepreneurs on their journey to build impactful and enduring businesses.

Addition

Walden International is unique among US venture firms through its focus on cross-border investments that leverage global markets and talent to grow industry-leading companies. For more than 30 years, their integrated team has brought extensive added value to help companies through capital, relationships and expertise. They look to partner with the best of the best – entrepreneurs with a strong appreciation for the benefits of leveraging talent and markets independent of geography to gain unfair advantage. Their team brings both extensive venture expertise together with in-depth operating experience to help you grow your company. They invest in early and expansion stage companies across sectors such as Semiconductors, Clean Tech, Internet & Digital Media and Software.

Walden International

Stonebridge Ventures

Snorkel AI

Snorkel AI is an AI development platform that enables enterprises to build production AI applications using programmatic data labeling and curation. Developed at Stanford AI Lab, it leverages weak supervision and other techniques to accelerate data preparation, making AI development faster and more efficient. Trusted by leading organizations, Snorkel AI helps create specialized, high-quality AI models by transforming proprietary data into AI-ready datasets.

Snorkel AI provides a data-centric AI platform called Snorkel Flow for automated data labeling, along with integrated model training, analysis, and guided iteration within a single workflow. Developers can choose between different training data sets, model architectures from its library, or use the Python SDK to train custom models. The platform also has an AutoML feature that selects the best algorithm and hyper-parameters for the problem automatically and includes guided iteration tools to provide insights on how to improve both data and models to reach model performance targets.

The toolkit to build machine learning applications at scale

Machine Learning Infrastructure

Snorkel AI offers a suite of solutions for the development of foundational model data and AI applications consisting of three main products: Snorkel Flow, Snorkel GenFlow, and Snorkel Foundry.

Empowering Tomorrow's Innovations with Generative AI Infrastructure

Generative AI Infrastructure

Snorkel AI Signs Agreement with BNY to Accelerate the Development of Predictive AI Models

Google Cloud

To make the Snorkel Flow platform available on Google Cloud Marketplace and to integrate it with Google's Vertex Generative AI Studio to allow Google Cloud customers develop and fine-tune ML models and generative AI applications using its own proprietary data.

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

Azure

To complement Azure AI services and the Azure Machine Learning platform with Snorkel AI's data labeling capability to generate high-quality data training sets, and automatically train and deploy custom ML models into production.

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

Snorkel AI provides a data-centric AI platform called Snorkel Flow for automated data labeling, along with integrated model training, analysis, and guided iteration within a single workflow. Developers can choose between different training data sets, model architectures from its library, or use the Python SDK to train custom models. The platform also has an AutoML feature that selects the best algorithm and hyper-parameters for the problem automatically and includes guided iteration tools to provide insights on how to improve both data and models to reach model performance targets.Snorkel AI also supports collaboration between developers and domain experts as well as integration with foundation models (FM) to build tailored ML models. Companies can use their proprietary data to build their custom FM or large language models (LLMs), or improve the accuracy of commercially available or open-source models for domain-specific generative AI and predictive AI applications. Moreover, Snorkel AI has integrations with a variety of ML infrastructure platforms that allows users to choose between a private cloud and a public cloud deployment architecture.Key customers and partnershipsIts key customers include five of the top 10 US banks, a number of government agencies, and Fortune 500 companies such as Apple, Intel, Chubb, and Google.The company <a href="https://sp-edge.com/updates/17515">partnered with Microsoft </a>to integrate Snorkel Flow with Azure AI services to aid data science and ML teams in developing AI/ML models tailored to their proprietary data. It also <a href="https://sp-edge.com/updates/20931">collaborated with Google Cloud </a>to make available the Snorkel Flow platform on Google Cloud Marketplace and to integrate it with Google's Vertex Generative AI Studio to develop and fine-tune ML models.Funding and financialsIn August 2021, Snorkel AI raised USD 85 million in Series C funding at a valuation of USD 1 billion. The round was co-led by Addition and funds and accounts managed by BlackRock. It planned to use the funds to scale its engineering and go-to-market teams to improve product 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 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

Snorkel AI offers a suite of solutions for the development of foundational model data and AI applications consisting of three main products: Snorkel Flow, Snorkel GenFlow, and Snorkel Foundry.Snorkel Flow enables the rapid construction, management, and deployment of predictive AI applications, such as classification and information extraction, utilizing techniques like programmatic labeling, fine-tuning, and distillation. This empowers enterprises to achieve high accuracy in production-grade applications, including tasks like financial document analysis, clinical trial analytics, and KYC compliance.&nbsp;Snorkel GenFlow facilitates the swift creation, management, and deployment of GenAI applications, such as summarization, question-answering, and chatbots. It achieves this by programmatically curating, scoring, filtering, and sampling instructions and responses for instruction tuning, incorporating methods like reinforcement learning with human feedback (RLHF). Enterprises can enhance task-specific performance and reliability by leveraging their proprietary data with this tool.Lastly, Snorkel Foundry provides a solution for creating custom foundational models or LLMs by programmatically processing and enhancing proprietary data. This enables enterprises to leverage their unique data for specialized domain-specific models that serve as the basis for all internal AI applications.The company claims its solutions help users accelerate AI development by 10x–100x and save up to 90% of labeling costs.In&nbsp;<a href="https://sp-edge.com/updates/34606">October 2024</a>, Snorkel AI launched new capabilities for the Snorkel Flow platform to accelerate the specialization of AI/ML models in enterprise settingsKey customers and partnershipsSnorkel AI’s customer base includes Apple, five of the top ten US banks, Memorial Sloan Kettering, BNY Mellon, Wayfair, US government agencies, and Pixability.Snorkel AI has a notable&nbsp;<a href="https://sp-edge.com/updates/17515">partnership with Microsoft</a> to empower Azure AI customers to customize and refine machine-learning models with their proprietary data. It also collaborated with<a href="https://sp-edge.com/updates/20931"> Google Cloud</a> to make the Snorkel Flow platform available on the Google Cloud Marketplace and integrate with Google's Vertex Generative AI Studio.&nbsp;

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’ 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 capabilities2. NR1-M™ 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 architectureThe 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 partnershipsIn 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.

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.&nbsp;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.&nbsp;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. In&nbsp;<a href="https://sp-edge.com/updates/28436">April 2024</a>, Databricks introduced its Data Intelligence platform for energy to use AI technology to process large data for energy companies. Following this, the company added synthetic data capabilities for AI agent evaluation in&nbsp;<a href="https://sp-edge.com/updates/37008">December 2024</a>.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).&nbsp; Key customers and partnershipsAs of November 2024, Databricks served a global customer base of more than 10,000 organisations, including Comcast, Conde, DuPont, Honeywell, Rolls-Royce, Shell, and Tata Steel.Databricks collaborates with over 1,200 global cloud, ISV, and consulting partners to deliver data, analytics, and AI solutions, supporting customers in scaling their projects.Notable partnerships include collaboration with AWS in&nbsp;<a href="https://sp-edge.com/updates/34884">October 2024</a> to leverage AWS Trainium chips as the preferred AI chip to power Databricks' Mosaic AI model training and serving capabilities.&nbsp;Databricks also partnered with Karini AI in&nbsp;<a href="https://sp-edge.com/updates/33687">September 2024</a> to accelerate GenAI deployment for enterprises.&nbsp;

Databricks

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’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 budgets2) 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 partnershipsThe 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%–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.&nbsp;

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.

ANALYST_QUICK_TAKE

PROMINENT_CATEGORY

<div>
 AI data firm Snorkel AI has added new features to its Snorkel Flow platform. These innovations are aimed at speeding up the tailoring of AI/ML models for use in enterprise situations.
 Among the new features are GenAI evaluation tools for case-specific benchmarks, efficient LLM fine-tuning workflows, RAG tuning workflows, simple annotation and feedback, Sequence tagging analysis tools, AI ecosystem integration, and enhanced named entity recognition (NER) for PDFs.&nbsp;
 These enhancements of Snorkel Flow improve domain-specific evaluation, boost retrieval accuracy through superior chunking, and simplify the extraction of information from PDFs. With such upgrades, Snorkel Flow aims to cut down on development time and enhance the accuracy of AI models, thus placing itself as the sole platform that supports the full lifecycle of AI data development.
 
</div> Analyst QuickTake: 
 Snorkel AI is actively working on improving its platform to make enterprise AI data development more programmatic and accessible and enhance its user experience.This recent launch is followed by Snorkel AI unveiling new data management capabilities in <a href="https: 
//sp-edge.com/updates/28894"> April 2024 </a> .

Snorkel AI

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